A Survey of Search Algorithms for Peer-to-Peer File

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A Survey of Search Algorithms forPeer-to-Peer File Sharing Applications inMobile Computing InfrastructureAjay Arunachalam1, Vinayakumar Ravi21Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro, Sweden (e-mail: [email protected])2Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia. (e-mail: [email protected])

Ajay Arunachalam (e-mail: [email protected]).

ABSTRACT Peer-to-Peer (P2P) Networking have a lot of practical applicability’s over the years. Filestorage and resource sharing are few key areas among the others where such peered network architectureis widely successful. The common building block for P2P networking is to store or locate an identifiableresource, for which there are basically 3 approaches namely (1) local storage/broadcast search (2) globalstorage/local search (3) distributed storage/distributed search. With the development of mobile hardwareand wireless technology, it further became feasible to use mobile devices in these P2P networks. Thiscomputing architecture is widely used in Mobile Ad-hoc Network (MANET) for building content sharingapplications. Search algorithm and file transfer schemes are the basic components of such content sharingsystems. In this article, we provide a brief overview of the resource discovery approaches for peer-to-peerfile sharing applications over MANET. We analyze and classify the search techniques into 4 broad schemes,mainly the flooding-based schemes, Distributed Hash Table (DHT) based schemes, advertisement-basedschemes, and social network-based schemes. The pros and cons of each technique is summarized. Further,a one-to-one comparison is done across the classes for quick interpretation. We also outline the variousissues, and complications that should be taken into consideration while designing any resource discoveryalgorithm. Further, we briefly discuss the security threats, and present state-of-the-art countermeasures for it.Also, we highlight some important guidelines that need to be focused while designing efficient file sharingapplications and services in Mobile Edge Computing (MEC) enabled networks. Comprehensive and in-depth assessments of the related approaches are presented providing clear insights for the future researchdirections.

INDEX TERMS File sharing, Peer-to-peer, MANET, Resource discovery, Social network, Mobile edgecomputing, Ad-hoc, P2P, search, Security, Privacy, Content discovery, Mobile Computing, lookup, Searchalgorithm, structured, unstructured, P2P MANET, Wireless Network, Routing, Network Infrastructure,Architecture, Mobile Ad-hoc Network, Service discovery.

I. INTRODUCTION

PEER-TO-PEER (P2P) network gained a lot of attentionover the years, and file sharing constitutes majority of

the internet traffic due to its distributed architecture [40] [41].File sharing applications over the internet is one of the in-demand services based on the P2P design paradigm. Over thepast decades, the most popular examples were the Napsterand Gnutella systems. With the rapid progress of mobilewireless communication, it is feasible to build an ad-hoc net-work instantly. Mobile Ad-hoc Network (MANET) has beena popular research area due to the rapid development trends.MANETs are characterized by wireless nodes, and multi-

hop communications building a dynamic infrastructure-lessnetwork. Due to these special characteristics, it is widelyused in various practical platforms like military battlefieldsystems, disaster recovery systems, electronic device com-munications, internet of things, response systems, etc. Adetailed study of the fundamental properties and servicesof MANETs is done in [42]. P2P network and MANETshare many common features such as both are decentralized,self-organizing, self-scaling and self-healing networks, andtherefore their combination can be an ideal choice, where aP2P overlay network can run over the underlying MANET.But, then both of these networks have one major challenge,

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i.e., maintaining continuous connectivity. Therefore, simplyadopting P2P overlay protocol over MANET is ineffective.Further, due to lack of sync between these networks, resourcediscovery protocols perform poorly [1]. P2P or overlay net-works are self-scaling and low barrier communication net-works maintaining higher layer logical connections betweenpeers to form an overlay network that is independent ofthe underlying network topology. Different overlay networkscan be formed by peers of an application running over theMANET. Fig. 1. depicts overlays formed by the communica-tion of peers, where each virtual link of the overlay networkis supported by a path in the underlying physical network.

The combination of these networks also poses potentialchallenges due to the differences in the layers of operation,transmission mechanisms, and continuous node mobility. Toovercome the challenges imposed by mobile environment onsuch peer-to-peer networks that include resource constraints,wireless network characteristics, heterogeneity of nodes, etc.,many studies have been carried out in the area of routing, net-work architecture, query dissemination, group management,etc. Migration of such peer-to-peer file sharing systems froma wired network layout to multi-hop wireless communicationarchitecture attracted the research community to explore so-lutions to enable content sharing in such dynamic scenario ofP2P MANETs. This type of network became popular with thewidespread of distributed applications, such as file sharing,social networks, service discovery, etc.

In this paper, we review the various search mechanisms inP2P file-sharing deployment over MANET. The performanceof each search method is studied, and a detailed summaryis presented in terms of search strategy, overlay structure,routing algorithm, and the underlay architecture. Further, wehighlight their advantages and disadvantages.

A. COMPARISON OF P2P ARCHITECTURESA P2P network can be classified based on the structural andbehavioral characteristics as purely decentralized architec-ture (which can be structured or unstructured) and hybridarchitecture (that can be centralized indexing or decentralizedindexing). In structured P2P systems the arrangement of thepeers are based on strict well organized rule, while in theunstructured P2P systems the peers connect to each otherin an random fashion. The hybrid architecture is mixture ofpeer-to-peer and client-server model. The centralized indexedhybrid P2P systems maintain a central index server, whereinthe files and user information are stored in directory basedorder. Each peer maintains a connection to the index server.In the decentralized indexed hybrid P2P systems there is nocentralized index server, but here some nodes are given moreimportant role than the others called the super nodes, whichmaintain the indexes for the information shared by theirlocal connections. The super nodes themselves are connectedthrough a pure P2P network.

We compare the different architectures of peer-to-peer sys-tems based on features like scalability, flexibility, robustness,and manageability. We provide a schematic analysis as shown

TABLE 1. P2P architecture comparison.

UnstructuredP2P

StructuredP2P

Centralizedhybrid

P2P

Decentralizedhybrid

P2PScalable N Y N YFlexible Y N N YRobust Y Y N YManageable N Y Y Y

in Table 1. The unstructured pure P2P system where the blindsearch techniques are used is not scalable, due to the over-whelming message exchanges. While, in structured system,one can overcome the scalability limitation with intelligentDHT-based search strategies. The other important feature inpure P2P system is the joining and leaving of the peers, i.e.,the flexibility. The unstructured systems lack manageabilityas each peer is its own controller. But, then such systems arerobust, since failure of any particular node doesn’t impact theoverall system.

From the above comparison, it is noticed that the decen-tralized hybrid P2P architecture has the best overall perfor-mance. In the following section, we highlight few real-timeapplication services based on the peer-to-peer principle.

B. P2P APPLICATION SCENARIOS IN MANETApart from the content sharing application many other ap-plications were also proposed for MANETs based on peer-to-peer architecture. Some, related areas where P2P designparadigm are applied in MANETs are listed below:-

• Location services [43 - 45]• Service discovery [46]• Name services [47 - 49]• Multimedia services [50 - 51]• Overlay-based multicast services [52 - 53]• Dissemination services [54]In the above section, we briefly discuss on MANETs, and

the various P2P architectures along with their applicabilityover the years. The rest of the paper is organized as fol-lows: Section II provides an overview of the P2P file shar-ing scenarios in MANET. It further introduces the varioustechniques grouped by their search principles. Section IIIprovides assessment of the related works highlighting theiradvantages and disadvantages. In Section IV, we describefew important parameters that need to be considered whendesigning a resource discovery system. Further, we also briefthe security threats observed in such resultant network. Openresearch issues are discussed in Section V. Finally, SectionVI concludes the study with important observations.

II. P2P FILE SHARING OVER MANETSIn this section, we study the deployment strategies to enablefile sharing over MANETs. P2P file sharing is widely usedin the Internet. Usually, such system consists of file transferand search protocol. The file transfer process is responsiblefor transferring of the files, while the search protocol is

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FIGURE 1. P2P Overlay in MANET.

responsible for locating the resources/objects. Content shar-ing is one of the core application area of MANETs. Theexchange of resources within MANET uses P2P services. Insuch deployment, one of the major challenges is to quicklyand efficiently locate objects in spite of high mobility, batterypower constraints, limited memory and bandwidth restric-tions. Many related works are proposed over the years toenable P2P file sharing over mobile ad-hoc networks.

[2], studied existing protocols and proposed five routingapproaches, i.e., Broadcast over Broadcast, Broadcast, Dis-tributed Hash Table (DHT) over Broadcast, DHT over DHT,and the traditional DHT scheme to integrate the P2P filesearch protocol and MANET routing protocol for enablingcontent sharing over MANETs. A simple approach is todirectly apply the broadcast based P2P lookup protocol overthe on-demand MANET routing protocol, i.e., Broadcastover Broadcast, where the query is broadcasted to everyvirtual neighbor peer in the overlay. While, in the broadcastapproach, the neighbors in the P2P overlay layer are directlymapped to neighbors in the underlying physical layer. Re-garding the DHT over Broadcast approach, a DHT-basedpeer-to-peer protocol is applied over MANET. To improvethe scalability, further the DHT-based lookup protocol areintegrated with the DHT-based MANET routing protocols,i.e., the single DHT approach where the lookup protocol is

combined with the network route request to reduce imple-mentation complexity.

The proposed methods follow the integrated or the cross-layered design paradigm. In the integrated approach theapplication layer file search is integrated with the networklayer, whereas in the cross-layer design the peer-to-peerprotocols at the application layer and routing protocols atthe network layer are coordinated in sync with other layersto improve the overall performance. A graphical summarygiven in Fig. 3. explains the different approaches to integratethe application and network layer protocols to enable efficientP2P file sharing over MANETs. Also, the advantages anddisadvantages of each routing approach is listed. The studyhighlights that the cross-layer approach performs better thandirectly overlaying P2P protocol on MANET. We study theresource searching algorithms in such implementation.

A. RESOURCE DISCOVERY (RD) IN P2P FILE SHARINGAPPLICATIONS OVER MANET

One of the important applications of the peer-to-peer net-works includes the file sharing systems. Generally, a P2Pfile sharing system includes file get, file send, file caching,file search, and indexing methods as a part of the system.Search algorithms are an integral part of such system. Ingeneral, the basic meaning of resource discovery in a stan-

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FIGURE 2. Approaches to enable P2P file sharing in MANET.

dard P2P system is to discover the address of the node inthe network, which actually hold the requested resource. So,from the resource reply which will be sent by a resourcecontaining node, the querying node will resolve the addressof the resource provider. Issues of resource discovery in P2PMANETs are discussed in [3][4]. From their preliminarystudy, it is observed that in such dynamic network, it iscritical to consider the underlay topology to design an ef-ficient search protocol [5]. The major goals of any searchmechanism is not only to successfully locate the resource,but also to incur low routing overhead, minimize query delay,and consume low battery power especially with the natureof mobile nodes [6][7][39]. Based on the search mechanismused in such P2P file-sharing applications over MANET,they can be categorized as flooding based, DHT based, con-tent advertisement based and social community-based searchschemes. We discuss each category briefly in the followingsub-sections.

B. FLOODING BASED SEARCH SCHEMESIn this scheme, the search query is flooded throughout thenetwork. When a node wants to locate an object, it broad-casts the message to its neighbors. Based on the reply, thequery is resolved. We examine several related approachesin this category. Orion [8] provides a keyword-based filesearch scheme for MANET. It combines the Gnutella-likeflooding technique with the Ad-hoc On-demand Distance

Vector (AODV) routing protocol, wherein the query requestis distributed by the link layer flooding. It maintains tworouting tables, i.e., response routing table and file table atthe network and application layers respectively. The responserouting table contains the node information for the next hopto traverse the target route.

7DS [9] provides a data sharing platform based on peer-to-peer characteristics to enable web browsing without direct in-ternet connection. It uses a broadcast mechanism that enablespeers to share and access documents amongst each other.It’s the first effort to port peer-to-peer technology in mobileenvironment. The web contents are disseminated among theneighboring peers within their geographic area.

Gruber et al. [10] proposed a P2P file sharing applicationfor MANET, using the cross-layer communication ideology.In their system, the file search is a combination of the flood-ing, and the Dynamic Source Routing (DSR) technique. Thestructure of the Mobile Peer-to-Peer (MPP) protocol stack isgiven in Fig. 3. To carry user data, it uses HTTP over theTCP protocol. The communication between the applicationlayer and the network layer is managed by the Mobile PeerControl Protocol (MPCP), which allows the P2P applicationto register itself in the Enhanced Dynamic Source Routing(EDSR) layer, which is a modified version of DSR protocol.

To lower the broadcast overhead, [11] introduces the con-cept of zoning in P2P (ZP2P), i.e., local zones are determinedby a fixed hop-count. The main idea in ZP2P is to set up

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FIGURE 3. MPP protocol structure (Adapted from [10]).

a zone for each node, where within the zone it employsa proactive routing scheme, while outside the zone it usesreactive routing. To locate the object, the node first checks itslocal cache to verify whether any of the local zone memberscan provide the information for the requested object. If theobject is not available within the local nodes, then the requestis forwarded to other zone members that are k-hops awaythrough its border nodes. This process continues until thewhole network is searched or until some predefined TTLvalue.

In the traditional Gnutella-like (GIA) search protocol, arandom nature of query forwarding incurs load on mobilepeers due to frequent re-routing of the query message. Toeffectively use the network and mobile resources, Linh et al.[12] proposed a file sharing application for cellular networksbased on the GIA architecture, where the super nodes areused to supplement the routing, thereby reducing the load onmobile peers. In their protocol, the lookup scheme is basedon biased random walk method. A resource search schemefor mobile file sharing application based on P2P paradigmis proposed in [13]. Here, the search service uses a localbroadcasting mechanism along with an indexing technique tostore content indices on the nodes along the query reply path.The caching of results helps the query search process, but atthe same time the local broadcasting is not always effective.For stable peer-to-peer data sharing over MANETs, a reliablecommunication prototype is proposed in [14]. They introducetwo schemes, i.e., configuration and routing schemes. Therouting scheme is used to find an emergency path in case ofdisconnection. It is composed of reconnection algorithms thatare used for finding such emergency routes.

A Bluetooth based P2P file sharing application forMANET is proposed in [15]. They modify the Gnutella pro-tocol to include the provision of Bluetooth. The application

works in dual mode. The initial mode mirrors P2P interactiondesigned for the internet which facilitates user-based search-ing, and the succeeding mode includes automatic search tosuit the mobile network. To improve ORION, an adaptivefile based search methods are proposed in [16]. In the firstmethod, the query message filtering is done via gossip insteadof flooding the whole network. While, in the second method,an adaptive hop based searching is carried out using localbroadcasting. Generally, in the flooding based schemes, ahigh volume of traffic is generated, which causes networkoverhead. Further, with limitations of TTL it also doesn’tguarantee successful search, but then these techniques areeasy to implement and offers suitable flexibility.

C. DHT BASED SEARCH SCHEMESThe search techniques in this category are based on Dis-tributed Hash Table (DHT) which is used to map the resourceobjects to their respective nodes by hashing, where each nodemaintains a DHT index. The information of a resource isstored in its corresponding nodes according to strict rulesto abide the well-organized structure. The schemes in thiscategory rely on DHT to store and maintain the resourceinformation of the neighbors. During a search request, theinformation is obtained from the hash table. Several searchproposals are based on DHT as the query search is moreefficient, but certainly these schemes have limitations inmobile environment.

Li et al. [17] propose a DHT based peer-to-peer file sharingprotocol for MANET. The search technique in their protocolis based on structured indexing. This scheme suffers fromhigh maintenance overhead in a frequently changing topol-ogy. Zahn et al. [18] take into account the physical node loca-tion. Their scheme integrates the pastry P2P overlay protocolwith the AODV reactive routing protocol. The basic idea isto have a good synchronization between the overlay and thephysical network. To achieve this, it forms a physical clusterof peers whose identifiers are near to the predetermined key,i.e., the landmark key which is an overlay ID. In [19], ChordP2P overlay protocol is applied to a mesh network. Duringlookup, the client forwards the message to its reference meshrouter within the transmission range, which in turn forwardsthe request message to DHT overlay, where it then followsthe chord lookup mechanism. MeshChord [19] uses thelocation-based awareness concept, and one-hop broadcastingwith overhearing capacity to improve the lookup process. Atransparent layered DHT is mapped directly to the existingad-hoc routing protocol in [20]. A virtual network is formedin the application layer that represents the overlay network,while the underlying physical network is managed by theAODV routing protocol. Several protocols based on the in-tegrated approach are also proposed, where the P2P architec-ture is directly implemented at the routing layer itself, like theVirtual Ring Routing (VRR) [21], Scalable Source Routing(SSR) [22], CrossRoad [23], HashLine [24], and DynamicP2P Source Routing (DPSR) [25]. In DHT based searchtechniques, the mapping of objects to their corresponding

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nodes becomes tedious (i.e., the control message overheadcreated by the DHT), and further requires high maintenancedue to rapid mobility. Further, these schemes might not befeasible for a frequently changing topology.

D. ADVERTISEMENT BASED SEARCH SCHEMESIn this approach, nodes regularly broadcast the advertisementmessage to inform the surrounding nodes about its contentsto be shared.

In [26], a push-pull based P2P file sharing system overMANET is proposed. Their method is based on SwarmIntelligence. Further, they use bloom filter to maintain alist of shared files. Their protocol is a two-process scheme,consisting of pull and push phase. In the advertisement(pull) phase the file holder node broadcasts an advertisementmessage to inform nearby nodes about the files that are to beshared. While, the discovery (push) phase is responsible forlocating the file, and then leaving traces of pheromone to helpthe search process to benefit in the future.

In [27], a clustered architecture based file transfer schemeis proposed. Here, the nodes needing the same file aregrouped into a common cluster. On receipt of a query request,the node forwards the request to other nodes in the clustervia broadcast. During file transfer, the leader of the clusterperiodically transmits data packets to the entire cluster. Shahet al. [28] propose a method to construct an unstructuredP2P overlay over MANET using the underlying cluster-basedrouting protocol. In their resource discovery process, thequery request is published to all immediate neighbors whofirstly check their local repositories, and respond accordingly.But, if there is no match, then the query request is forwardedto other connected neighbor nodes within the transmissionrange. If the resource requesting node doesn’t receive anyresponse within a fixed time period, then the query requestis rebroadcasted, until the threshold value is reached. In[29], they proposed a robust mobile peer-to-peer architecturebased on super node that enables efficient resource sharingand service provisioning. A super node selection algorithmconsiders the node’s capabilities and its context. Further, theypropose a scheme that enables nodes to exchange their re-sponsibilities to other powerful nodes that are already presentor that may join the network. Certain protocols consider thenodes physical locations to provide efficient service in awireless ad-hoc network. One such scheme is proposed by[30]. They suggest integrating content location based servicealong the geographical region. In their method, each clientfinds the nearby server with the knowledge of geographicaldistance metric. The nodes make use of this informationto advertise the contents periodically to the other nodes indifferent regions.

Repantis et al. [31] proposed a file sharing service, whereinthe nodes use the bloom filter data structure to build the con-tent synopsis of their available resources, and further spreadthis information adaptively to other relevant nodes. Dhurand-her et al. [32] proposed a P2P Bee Algorithm (P2PBA) forP2P file search in mobile ad-hoc network using the swarm

intelligence theory. They use the bee algorithm that depictsthe honeybee behavior during the food searching processas seen in natural habitat. Their protocol scans through asizeable area, and selectively move towards the promisingnodes after several routines, thereby optimizing the searchprocess. The advertisement based search schemes are mostlysuitable for stably connected MANETs. But, in a dynamictopology, it increases the overhead drastically, and is lessefficient, as routes expire due to abrupt disconnection. Thecontent publishing search schemes overall reduce the over-head, but still the advertisement process itself causes the nodeoverhead. And, also such methods may lead to false positiveerrors in case the node fails, or route expires due to frequentmobility.

E. SOCIAL NETWORK BASED SEARCH SCHEMESSearch algorithms under this category use the social net-work and community based ideology. Many principles ofsocial network are followed, e.g., the interest based grouping,meeting frequency, movement pattern of the nodes, etc. Thesearch schemes are devised based on the social networkcharacteristics that focus on frequency of meeting, and theirprobabilities. In this search strategy, a forwarding node isselected as the node that has high probability of efficient andsuccessful transmission. Several such schemes are reviewedhere.

A social-network based peer-to-peer file sharing systemover MANET (SPOON) is proposed in [33]. It considers thenode’s interest and moving pattern to compliment the service.Node interests are extracted from the files it holds. Based onthe common interests, a community is build using the com-munity construction algorithm. Further, every communityelects a coordinator, and an ambassador using the node roleassignment algorithm, where the coordinator guides the intra-community searching, while the ambassador guides the inter-community searching. Qureshi et al. [34] proposed a peer-to-peer content driven communication strategy for mobilesocial networks suitable for disconnected scenario, i.e., forcases when the end-to-end connectivity is not feasible. Theirscheme considers the node’s interest, storing and forward-ing capability along with the node’s mobility information.The protocol is defined as three-layered architecture, wherethe top layer handles the user interface and works as anapplication layer, the middle layer deals with the contentdriven data dissemination, and the bottom layer handles thedata forwarding mechanism in a multi-hop communicationfashion.

A context driven data dissemination approach is proposedin [35]. To establish a social relationship between differentcommunities, parameters like time spent by members withinthe community, interests of the members, and knowledgeof data spread within the community, etc. are used. Thisinformation is used by each node to calculate the utilityvalue for every encountered object, and then reordered in theincreasing order of utility value to improve the disseminationand searching process. An extension of [33] is carried in

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[36] that focuses mainly on the disconnected mobile ad-hocnetwork. They proposed a social community based peer-to-peer file sharing application for low end-to-end connectivityenvironment. From their previous work, they include addi-tional schemes for file pre-fetching, query completion andloop prevention, while also considering the node churn.

For effective file sharing in an infrastructure less and fre-quent disconnecting environment such as MANETs, Palazziet al. [37] propose an asynchronous communication modelthat uses special peers to delegate the tasks. They proposeda system that is based on application layer overlay networkwith Delay/Disruption Tolerant Networks (DTN) feature formobile environment. They use node mobility to disseminatedata in such disconnected network. Li et al. [38] proposeda location based file sharing deployment over MANET withsocial network characteristics. A social relationship is estab-lished by considering the similarities among different nodeswhich is measured while taking into account the currentphysical locations of the nodes, and their common interests.Based on the study, we observe that social network features,like the node movement, social relationship, community con-text, node interest, frequency of meeting, etc., are consideredin devising the file sharing systems over MANET. We pro-vide a tabular classification to understand the different socialnetwork characteristics used in the assessed approaches inTable 2.

The search techniques in this category help lower theoverhead, and ease the search process, but then it involvescomplex procedures, and also consumes more energy. Theother challenge is the construction of the community whichis hindered by the frequent node mobility, and abrupt dis-connection. From our study, we notice that for the imple-mentation of these schemes one needs to specially take intoaccount the overlay, and the underlay topology structure aspeer-to-peer network focus on search protocol at the appli-cation layer, while mobile ad-hoc network refer to routingfunctionality at the network layer. It is also observed thatflooding or broadcasting is necessary in both networks tomaintain connectivity due to the frequent changing topology,in comparison to the wired architecture. To complimentMANETs, the cross-layered approach will be more suitablerather than just adopting the P2P protocol directly. Theideology of the social-based methods looks promising, as thesearch scheme takes into account the social relationship thatcan help to adhere the dynamic topology of ad-hoc networks.But, then it also increases complexity, and further consumesextra resources.

III. ANALYSISIn this section, a tabular summarization of the various searchschemes in peer-to-peer deployment over mobile ad-hoc net-work is given. We compare the different systems categori-cally by discussing their search strategies, underlay and over-lay characteristics, along with their deployment approachesgiven in Table 3 to Table 6. Further, the strengths and weak-nesses of each system are discussed given in Table 7 to Table

10. For user readability, we further summarize the discussedsearch schemes extracting few key performance indicatorsgiven as in Table 11. We compare them in terms of scala-bility (i.e., bad, good, excellent), implementation complexity(i.e., low, medium, high), maintenance complexity (i.e., low,medium, high), search efficiency (i.e., low, medium, high),energy efficiency (i.e., low, medium, high), transmission cost(i.e., low, medium, high), best applicable network size (i.e.,small, medium, large), and the cross-layer property (i.e.,yes or no). The implementation complexity & maintenancecomplexity are based on the algorithmic overhead with re-spect to the consumed resources and the generated messages.The scalability categorization was based on the number ofnodes, and capability of the search algorithm to scale uptowithout largely hampering the overall performance. In gen-eral terms, the lower value denotes the better achievementof the performance measure for implementation complexity,maintenance complexity, and the transmission cost, while thehigher value signifies best for search and energy efficiency.The rest indicators are self-explanatory. And, finally, wesummarize the broad search schemes in a nutshell by doinga direct comparison across each class for highlighting keycomparable characteristics as given in Table 12. We focus onunderstanding the factors like ease of implementation (i.e.,easy, complex), candidature type for large networks (i.e.,applicable, suitable), suitability for highly dynamic scenario(i.e., yes or no), feasibility for real-time systems (i.e., bestfit, medium fit, worst fit), robustness to churn (i.e., yes orno), significance of node failure (i.e., low, medium, high),lower resource constraints (i.e., yes or no), and providesshortest path (i.e., yes or no). An ideal scheme should beeasy to implement, compliment large networks, suit wellfor highly dynamic environment, adapt to churn, have lowimpact in case of node failure, lower power and bandwidthconsumption, use shortest path to reach the destination, andshould be practically applicable in real-time scenarios. Fromour study, we notice that the flooding based search schemesimpose loose restriction between the overlay network topol-ogy and the resource location, thereby feasible for highlydynamic mobile networks. Further, largely the systems werebased on cross-layer communication pattern, that performbetter than the direct deployment of P2P overlay protocolsover MANET, but then it still have certain open issues likethe layer synchronization, effectiveness to growing networksize and increasing query request rate, redundancy in com-munication at different layers, security issues, etc. Also, itis noticeable that hit rate has been always a concern insuch evolving environment, bearing the tradeoff with batterypower consumption.

IV. CHALLENGES AND COMPLICATIONSIn this section, we describe a few common challenges thathamper the search performance and possible complications.The design of the resource discovery technique in suchdynamic environment is not a trivial task. Apart from thebasic search mechanism and content publishing technique,

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TABLE 2. Social network features used in the studied methods.

Ref. MeetingFrequency

CommunityContext

NodeMovement

Pattern

NodeInterest

Publish/Subscribe

UtilityFunction

SocialRelationship

34 * * * * *35 * *36 * * * *37 * * * * *38 *39 * *

one needs to deal with several issues such as churn, boot-strapping, security, load balancing, efficient resource man-agement, formulating effective re-ranking strategy, etc. Fromthe study, it is noticed that the decentralized hybrid P2Parchitecture is ideal for such highly dynamic scenario. But,then such large scaled decentralized systems also sufferfrom problems such as topology mismatch, collaborationissues, flash crowds, free riders and fault-tolerance issues.Further, both of these overlay and underlay network haveone common problem, i.e., maintaining continuous nodeconnectivity. Also, many standard decentralized systems onlysupport keyword or indexed search, but do not focus onsophisticated multiple queries. Thus, there is a need forspecialized schemes to enable complex and scalable queries.

A. CHALLENGES: FROM A SECURITY PERSPECTIVESuch evolving resultant networks are susceptible to bothMANET and P2P attacks as challenges of both architecturesare present as shown in Fig. 4.

FIGURE 4. Major challenges in P2P MANETs.

Due to the nature of these networks, the attacks lead tomore severe effects in totality decreasing the overall per-formance of the lookup process. The malicious nodes aresufficient to affect the routing process with high probability.Such nodes may misuse peer-to-peer mechanism to increasethe traffic populating the routing table, and thereby posesa threat to resource consumption in MANET. On the otherhand, sybil attacks may occur on both layers, wherein mul-tiple virtual identities are generated, thereby increasing theimpact of other attacks, and directly increasing the resourceconsumption. Similarly, the blackhole attacks can also affect

the P2P services by redirecting routes to only specific nodesto deny resource sharing.

Due to limited resource constraints, the security algorithmsneed to be framed within the limitation of the bandwidthcapacity. Further, due to decentralized nature, the availabilityof authority cannot be pre-assumed. Thereby, the trust factorbecomes necessity in such mobile environment, but withinsider attacks it leads to denial of cooperation. Trust is oneof the major concerns as the routing algorithm has to purelyrely on the cooperation of the nodes.

1) MEC Enabled P2P file sharing applications – SecurityIssuesMEC-assisted P2P communication system are prone to sev-eral challenges from security perspective. We enlist fewattacks that is concern in such setup. With computationaloffloading to edge nodes makes it vulnerable to maliciousattacks. Also, as edge nodes allocate some portion of itsresources with other devices even if their identity is unknownmakes it vulnerable to DDoS attacks [56]. Further, such MECenabled file sharing scenarios involves unsecure end devicesleading to injection attacks.

2) Peer-to-Peer SIP over MANETs – Security IssuesP2P streaming/messaging applications use Session Initial-ization Protocol (SIP) to establish a communication. [55]discusses the existing deployment of SIP over MANETsand the security issues in such dynamic environment. Theyhighlight two key factors, i.e., scalability security havingtradeoff in such evolving systems. Streaming media applica-tions over MANET are exposed to several attacks like Sybil,data integrity, service denial, data storage retrieval attacks,etc [57], [58], [59], [60].

B. COUNTERMEASURES: TO DEAL WITH SECURITYTHREATSWe suggest some countermeasures for routing attacks in suchresultant evolving systems, and brief security measures forsuch highly dynamic environment. Our study suggests thatcross-layering can improve the robustness of peer-to-peersystems in MANET. While, most of the security mechanismsproposed for mobile ad-hoc networks are still applicable incontext of Mobile Peer-to-Peer (MP2P) systems, but then itcan be further improved by harnessing cross-layer informa-tion. So, one has to improve the security measures at both

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TABLE 3. Side-by-side comparison of Flooding based search schemes.

System Search StrategyP2POverlayProtocol

RoutingProtocol

Deploymentapproachwith Underlay

8

Orion uses one-hop broadcast flooding for searching, and maintainsa file-based routing table that stores the next hop information to reachthe destination. When a node wants to locate an object, it issues aquery message that is broadcasted throughout the network. On receivingthe query message, each node sets up a reverse route to the queryinitiator, and then retransmits to its physical neighbors.

Gnutella-like AODV Integrated

9

7DS uses a local broadcasting mechanism for document sharing amongpeers. Here, the system can operate in different modes for appropriatepeer cooperation and querying mechanism like the data sharing,forwarding, active and passive modes. During the active mode, thesystem checks for any requests in the queue and broadcasts them.While in the passive mode, an advertisement triggers the query process.For better synchronization among the peers the system is driven by twostrategies, i.e., data sharing and forwarding. In data sharing mode whena peer receives the query, it checks its local cache and only broadcaststhe query further if the cache is hit. And, in forwarding mode on receivingthe data or query the peers just forwards them to other peers, i.e.,rebroadcasts it.

N/A N/A N/A

10

To locate a file, the request is flooded throughout the MANET using theenhanced version of Dynamic Source Routing protocol for node-to-nodecommunication. When a node receives the request message, itcommunicates with the application layer using the MPP stack to checkfor the match. Every intermediate node adds its own node address tothe message to create a DSR style route, and then rebroadcasts therequest message to its physical neighbors.

Gnutella-like DSR Cross-Layered

11

To locate a file, the requesting node verifies its cache first to check if thenode’s local zone has the resource. If the resource information is notavailable, then the node broadcasts the request to other zones via theedge nodes.

Gnutella-like AODV Cross-Layered

12Uses super nodes to augment the lookup process. GIA search protocoluses a biased random walk rather than randomly choosing the neighbor,where it selects high capacity nodes to forward the query.

Gnutella-like N/A Layered

13Proposes a distributed file searching protocol that uses local broadcastingtechnique for resource search. Along the reply path, caching of the queryresult is done by storing the content index.

Gnutella-like Custom N/A

14

Proposes a configuration and routing scheme. In the configuration phasethe MANET nodes are allocated IP’s dynamically. While in the routingphase the query is routed to the destination node. The nodes maintaina scanning table and lookup table. The scanning table contains theinformation of all the directly connectable nodes, while the lookuptable contains information about the location of the target data.

Gnutella-like AODV Integrated

15

Searching takes place in two modes, i.e., manual and automatic.The manual query search is carried out by the user, while theautomatic query search is carried out by the peer’s agent.To search a file, the peer floods a query request to other peerson the network similar to the Gnutella protocol. The agent oneach peer builds a user-profile based on the user’s interestsrepresented by a set of keywords. To facilitate an automaticsearch, two new packets are defined, i.e., RecRequest andRecResponse. The RecRequest packet contains the profileinformation that is sent to agents of the connected peers.Upon receiving the RecRequest packet, the remote agentuses this profile information to get the recommendationfrom its repository. The RecResponse packet contains thisrecommended files information that are returned back tothe agent.

Gnutella-like Custom Layered

16

Proposes two search schemes with message filtering andadaptive features. In the first scheme, a node floods a queryrequest message with the requested file identifier distributedvia a link layer flooding. Information of all the intermediatenodes along the reply path is maintained in the response routingtable. While in the second scheme, the query is forwarded to atmost limited number of hops using a local broadcast transmission.


VOLUME 4, 2016 9

TABLE 4. Side-by-side comparison of DHT based search schemes.


RoutingProtocol


17

M-Chord is based on a hierarchical architecture with super nodes and ordinary nodes.The ordinary nodes are registered to their corresponding super nodes. They modifythe chord protocol to suit the MP2P environment. During a file request, the sourcenode calculates the ID of the file based on its content and title using hash function.Then, this ID is forwarded as a request to their corresponding source super node.On receiving the request, the source super node lookup its finger table and generatesrouting information successively along the route until the destination super nodewhose ID space covers the requested file ID is reached. The destination super nodeproceeds with a local lookup. The chord routing mechanism is used along the ring.

Chord Custom Cross-Layered

18

Nodes whose identifiers are close to overlay ID are grouped as one physical cluster.MADPastry integrates the overlay and physical routing. It tries to identify the nodethat is numerically closer to the key than the current node. If a physical route to anoverlay hop is unavailable, then it simply broadcasts the overlay packet within its owncluster. Along with the idea of proximity awareness using random land marking,physical clusters of nodes are formed that share common overlay ID.

Pastry AODV Integrated

19

During a lookup, the request message is forwarded to a router within its transmissionrange. The reference router then forwards the resource request message in the DHToverlay using the chord indexing mechanism. MeshChord utilizes the location awarenessand overhearing strategies to lower the routing overhead.

Chord DSR Integrated

20

Bamboo uses a proactive overlay adaptation scheme to maintain the network structure.Every node generates a neighbor ping to reach its 1-hop neighbors. The node alsoperforms leafset update by periodic random node selection from the leafset andexecutes push-pull operation. Every file name and peer is hashed to a key. The peersmaintain a routing table which contains entries that direct to an intermediate closerpeer to the requested key. The peer closest to the requested key knows the addressof the actual peer storing the requested file.

Bamboo AODV Layered

21

It integrates P2P concepts at the network layer. In VRR, the nodes are organized as avirtual ring ordered by their identifiers which are fixed, unique. VRR hashes the node

IP addresses to obtain the identifiers. Every node maintains routing path informationabout its neighbors in the ring. Each node also maintains a virtual neighbor set (vset)and a physical neighbor set (pset). The vset nodes hold the predecessor and successornode information, while the pset nodes hold the nodes that can directly communicatewith each other at the link layer. In VRR, a node routes packet to a destination byforwarding them to nodes whose identifiers are numerically closer to the destinationidentifier.

Custom AODV Integrated

22

It combines the Dynamic Source Routing (DSR) protocol in the physical networkalong with the Chord protocol in the virtual ring formed by the address spaces.By maintaining a route cache, each node contains source routes to all its neighborsin the virtual ring. During routing, the node chooses the intermediate nodes fromits cache which is physically close to itself and virtually close to the destination node.

Chord DSR Integrated

23

To lower the overhead that is observed with direct deployment of pastry over MANET,a cross-layered architecture is proposed to optimize the overlay. Every node runningthe CrossROAD piggybacks advertises its presence in the overlay. Each node in theoverlay maintains a routing table. The sender of the message identifies the closestdestination to the key, and delivers it through the routing protocol directly at thenetwork layer.

Pastry OSLR Integrated

24

Their scheme integrates the P2P search functionality with the network layer.A one-dimensional space, (i.e., a line) is used into which the keys and node IDsare mapped using a hash function (hashline). The system is partitioned intosegments, where each node is responsible from one segment. The values of keysin one segment are maintained by the corresponding node responsible for thatsegment. During lookup, the node forwards a query request to one of its children, ifthe file with key coincides with the hashline segment of its children. Otherwise, therequest is forwarded to the parent, and finally the node responsible for the hashlinesegment receives the query. A tree-based routing mechanism is used.

CAN Custom Integrated

25

Their technique integrates pastry P2P overlay protocol, and DSR routing protocol atthe network layer. It implements DHT in MANETs, to map objects to their correspondingnodes using a hash function. The routing in DPSR is similar to Pastry where key isgenerated by hashing the destination IP address, and further the message is routedto the node whose node ID is numerically closest to the key.

Pastry DSR Integrated

10 VOLUME 4, 2016

TABLE 5. Side-by-side comparison of Advertisement based search schemes.


RoutingProtocol


[26]

The requesting node first searches its cache for the desiredinformation, and then the query is forwarded to the intermediatenodes based on their pheromone table which stores each neighborlink’s pheromone intensity, i.e., the probability value ofrouting message along that neighbor, judged by the number oftraversed hops of an reply message in the process.

Gnutella-like ARA Cross-Layered

[27]

They focus on the file transfer process. Nodes downloading the samefile are grouped into multiple clusters where each cluster has arequest agent and a provider. Upon receiving the file request, anode transmits the request to other nodes in the cluster via alink layer broadcast. In the data transmission phase, theprovider periodically sends data packets to whole cluster.

N/A N/A Cross-Layered

[28]

A keyword-based search mechanism is used to locate a file. Duringthe file lookup, a File-lookup Request message (FRQST) ispublished to all neighbors. On receiving the message, the nodechecks its local repository. If there is a match, then a FileReply message (FRPLY) is sent to the querying node. Otherwise,the FRQST message is forwarded to its directly connected neighbornodes excluding itself. If no FRPLY is received, and the numberof retries is less than the threshold value then the FRQST isagain reinitiated.

Gnutella-like CBRP Integrated

[29]

The network is divided into regions. Each region signifies a groupthat contains nodes that are physically positioned within theregion boundary. Each group has a super node that handles thequeries, and publishes within their respective group. The supernode holds the records of active peers, available resources,services offered to resolve the queries efficiently within thatgroup.

N/A N/A N/A

[30]

They proposed a geographic location-based protocol that uses physicalnode location information to provide effective service in anad-hoc network. The content server periodically advertises thecontents containing information to all nodes along severalgeographical locations. The contents are disseminated along withthe requests in several directions to ensure their meeting.

N/A N/A N/A

[31]

Each node maintains a summary information of their respective data aswell as information about the remote peers, and then adaptivelydisseminates this content synopsis to the most promising peer. Anode uses bloom filter to build the snapshot of their data. Basedon this local and global information, the nodes can route thequery efficiently.

Gnutella-like Custom Integrated

[32]

Uses swarm intelligence based patterns to locate files. The searchprocess proceeds by selectively traversing to more promisingsource while scanning through a sizeable area of the network.Within the area, the file request message is broadcasted acrossthe network for searching. While during scanning of the area, ifthe file response message is generated, then the nodes in theroute store the message in the PatchInfo table.

Gnutella-like Custom Cross-Layered

layers individually for a cross-layered architecture. Anotherapproach is to constantly monitor the intermediate overlaynodes only. To prevent sybil attacks, node reputation valuecan also be used, where the Sybil nodes can improve theirown reputation. To prevent blackhole attacks, unique requestIDs, TTL, and timestamps can also be used.

V. FUTURE RESEARCH PROSPECTS

This section provides some open problems that haven’t beenstudied thoroughly in the development of resource discov-ery techniques for P2P systems over MANET. From thediscussion, and analysis of the state of the art techniques,it is observed that there is no independent technique thataddresses all issues involved in resource discovery, especially

in terms of having good hit rate, lowering resource consump-tion (battery power and network bandwidth), minimizingmessage overhead, reducing search latency, etc. At large,most of the search schemes ignore the scalability, and loadbalancing issues which are very important considering themagnitude of large-scaled P2P systems. Further, most of thediscussed techniques use simulation based analysis. Mathe-matical modeling and formal validation of these models areinteresting directions for further research. The peer-to-peerdeployment over mobile ad-hoc network uses real-time com-munication to efficiently share information among peers in anad-hoc fashion. However, in these networks, node mobilityincurs several challenges such as frequent disconnection,signal attenuation, re-route discovery, etc. Peer discovery is

VOLUME 4, 2016 11

TABLE 6. Side-by-side comparison of Social network-based search schemes.


RoutingProtocol


[33]

Here, the node interest and moving pattern of the node is considered.First, the nodes with common interest and high frequency ofmeeting form the community. Then, the inter-community meetingfrequency of the nodes is considered. To forward a query, thenode that is frequent visitor to other community is chosen, sothat the desired file can be located at the earliest.

N/A N/A N/A

[34]

Their protocol considers the user’s interest. When a user makes asearch, his personal interests are matched with the database,and accordingly the query results are returned. Further, theuser send’s an invitation to number of interested users. Onreceipt of the invitation, if a user is interested, he responds,and then both of them become friends. Among friends, theresources can be viewed and shared. The user announces hisavailable resources to the friends who can then request theresources.


[35]

Based on the social community based theory. A social relationship isdeduced by maintaining a utility value among the communities.Each node calculates a utility value for every encountered datawith respect to its connected community knowledge, datadestination information, and then accordingly it caches the datawith highest utility value. Further, the peer decides which datato fetch from other peers to maximize the utility value in itsown buffer.

N/A N/A N/A

[36]

Propose an interest oriented file searching scheme, that selects nodesto forward the query based on similarity to the interests of thenodes. The file search takes place in two phases, i.e., withinthe community and across the communities. On a file request froma node within the community, the neighbors within single hopcount are searched. If the file is not found, then the requestis forwarded to the community coordinator which checks thecommunity file index. If the file is still not found, then thecoordinator forwards the request to the ambassador nodes whichin turn forward the request to other communities matching thequeried file. A file reply is sent back to the requesting nodevia the ambassador nodes of the community.

N/A N/A N/A

[37]

Their search technique uses the local indexing strategy, where thefiles and indices are maintained locally. The query model usesthe keyword based scheme. The index information are stored usingthe inverted index list.


[38]

Their system uses user’s profile and node location information tobuild a location based social network over MANETs. A socialrelation is established considering the similarities among them.The content search is managed by using social relationships,where the contents are only shared among interested users. Byconsidering the node position and interests the similarity ismeasured.

N/A N/A N/A

still an open research problem in this domain. Designinga buffering or cache optimizing technique to improve theperformance of resource discovery scheme is another areathat can be focused on.

Also, an interesting point for future research study is ex-tending and configuring the structured P2P protocols to suitand work well under such highly dynamic network scenario.Further, investigating the variation of search query behaviorsover time will help to devise an effective implementation ofresource discovery technique. Most of the discussed searchschemes haven’t considered the security aspect, which is achallenging research subject in such volatile environment.In MANETs, a malicious node attack is very frequent, butisn’t mentioned in most of the techniques. Furthermore, nodereputation, trust, authentication and authorization can also be

considered for enhancing the security of the search protocols.Another direction for further study is to focus on a cross-layered search architecture design to compliment large scalednetwork, while minimizing overhead. As a next step, onecan also focus on providing collaborative filtering schemesfor P2P file sharing applications explicitly designed forMANETs that can be tested in real-time scenarios. Perhaps,one should also consider the relationship between topology,and the search algorithm for designing an effective strategy.Another, interesting area of research is the Mobile EdgeComputing (MEC) technology, wherein file sharing applica-tions and services could further evolve with an optimum levelof resource utilization. Typically, the peer-to-peer systemsreside on the edge of the Internet or in ad-hoc network.They connect together instantly in an ad-hoc manner or use

12 VOLUME 4, 2016

TABLE 7. Advantages and Disadvantages of the Flooding based resource discovery techniques.

References Pros Cons

[8]Eliminates redundant routing paths. Offers noticeable search efficiency andquery delay. Suitable for small networks. Offers suitable dynamicityand flexibility.

Only supports keyword based queries. Can’t lower the signalingoverhead. Offers low scalability. High capacity nodes required.Less secured. High energy and bandwidth consumption. Causes highnode overhead.

[9]Suitable for small geographical area. Cache manager helps improve thequery search process. Offers suitable robustness. Suitable forhighly dynamic mobile network scenarios. Uses minimum bandwidth.

Practical implementation is not feasible. Hardware dependent. Built forkeyword search. Complex design.

[10]

Can handle link failures and mobility. Provides location awareservices. Reduces search overhead. Offers noticeablescalability. Decreases signaling overhead. Increases querysuccess rate.

Dependent on MPCP protocol for cross-layer synchronization. Not suitablefor increasing query request rate. Causes network wide broadcast ofsearch query request. High battery power and bandwidth consumption.Node overhead.

[11]

Network wide broadcast is limited marginally. Local cache helps improvesearch efficiency. Suitable for small sized network. Reducesoverhead in certain scenarios as compared to broadcast byflooding.

Performance depends on factors like zone radius, and node density within thelocal zone. Generates additional traffic as number of zones increases.Low security. Doesn’t guarantee to find an object within the local zone.Offers low scalability. Mobile and network resource consumption is high.

[12]Supports any type of queries. Offers suitable load-balancing anddynamicity. Includes topology adaptation algorithm. Improvessearch efficiency and reduces query delay.

Offers low security. Suffers from redundancy where the content indices arereplicated. Suffers from single points of failure and bottlenecks.

[13]Restricts query flooding throughout the network. Reduces communicationcost. Local broadcast along with caching technique help improvesuccess rate. Reduces query response time.

Only handles popular queries efficiently. Local broadcasting mechanismcan’t always guarantee to locate the file. Low security. Supports onlysimple queries. Content index maintenance for each node is tedious.

[14]Offers suitable fault-tolerance and robustness. Removes bottleneck andsingle point of failure .Offers dynamic IP address allocation tonodes. Offers noticeable load balancing.

Not suitable for highly mobile and large scaled networks. Involvescomplex procedures. Battery power and bandwidth consumptions arehigh. Offers low security.

[15]Uses software agents to improvise the search process. Supportsdynamic and opportunistic information exchange. Providesrecommendation based retrieval. Improves hit rate. Reduces lookup time.

A set of keywords is used to describe interests of a user. Increasesnetwork traffic in both manual and automatic search modes.Involves complex procedures. High maintenance overhead.Requires high bandwidth and consumes more energy.

[16]Supports query filtering to limit broadcasting. Lowers forwarding of thequery messages. Reduces transmission overhead. Offers noticeablescalability. Mobile and network resources are used effectively.

Maintenance of the response routing table becomes tedious when the networksize grows and mobility increases. Low fault-tolerant and is less robust.Not suitable for a highly dynamic network. Offers low security.

TABLE 8. Advantages and Disadvantages of the DHT based resource discovery techniques.


[17]To manage resource effectively, they use registering mechanism as inM-CAN. Offers suitable load-balancing. Offers good robustness.Offers suitable efficiency. Minimizes query response time.

Lookup fails if wrong nodes reply among the participating set of nodes.Complex procedures involved. Suffers from single point offailure, and bottleneck. High maintenance overhead. Rely on highcapacity nodes. Maximum battery power consumption.

[18]Reduces the lookup delay. Minimizes routing overhead by integratingoverlay and physical routing. Offers suitable scalability anddynamicity.

Doesn’t support multiple services. Minimum priority is given to popularservices. Maximum contributing peers are not given any priority.Complex design. Accuracy of the pastry table and the leaf settable depends on the number of packets that the MADPastry nodesreceive or overhear.

[19]Reduces message overhead with the use of location awareness andoverhearing strategies. Minimizes routing stretch. Lowers queryresponse time.

Heavily dependent on the Mesh router. High capacity nodes required withGPS enabled functionality. High battery power consumption. Nodeoverhead is high.

[20] Doesn’t require any change to the routing or overlay layer. Offerssuitable flexibility. Easy implementation and manageable.

Overhead increases with the increase in number of nodes. Proactivemanagement increases network traffic, high congestion. Offers lowscalability. Energy efficiency is low. Network load increaseswhile the success ratio decreases.

[21]Keys can also identify application objects instead of just VRR nodes.Avoids flooding throughout the network. Offers suitableload-balancing.

Complex procedures involved. Causes node overhead. Offers lowscalability. Introduces complexity in implementation.

[22] Reduces average request path length. Offers noticeable load balancing.Incur less maintenance overhead.

To maintain consistency, predecessor and successor nodes have to beperiodically managed. Effectiveness of source route is based onthe cache entry. Frequent cache update is required.

[23]Supports topology aware functionality. Reduces communication overhead.Guarantees message delivery through shortest path. Suitable forsmall networks.

External data sharing module is required for cross-layer communication.Incurs additional cost at OSLR layer. Not suitable for highlydynamic mobile network. Periodic advertisement of message causeshigh maintenance overhead. Suffers from low scalability anddynamicity.

[24]

Integrates query search and routing strategy. Can respond to location basedqueries. Offers suitable query routing strategy. Maintainlocation awareness via the tree formation holding information ofparent and child relationship.

Routing table entries grow with the increase in number of physicalneighbors. Incurs high node overhead. Membership management costis high. Suitable for low mobility and dynamicity. Maintenanceoverhead is high.

[25]Message delivery is guaranteed, if the destination node is within thetransmission range. Discovery and rediscovery processes arelimited in DPSR. Offers suitable scalability.

Routing in DPSR takes multiple hops in the namespace. Routing delay ishigh. Less secured.

telecom operator’s mobile network to connect to the P2Papplication. But, with the uptrend of mobile device users inthese systems, it further incurs resource challenges, and alsoresults in poor user experience, thereby bearing additionalcost to the network operators. Research studies indicate thatthis overload hugely affects the network latency. To handlethis extra traffic posed in mobile network, the MEC technol-ogy is used which enables the operators to better adapt the

traffic, thereby helping in improving the content delivery, andrapid deployment of applications overall providing flexibilityto the end users. Considering the booming MEC technology,the peer-to-peer file sharing applications over ad-hoc net-work, can incorporate these characteristics to improve servicequality and network efficiency in such evolving network. Toleverage this on-the-fly service, cooperative caching can alsobe an additional area of study in such MEC enabled file

VOLUME 4, 2016 13

TABLE 9. Advantages and Disadvantages of the Advertisement based resource discovery techniques.


[26]Avoids redundant overhead. Bloom filter is used to maintain a list ofshared resources to lower message size and communicationoverhead. Offers suitable robustness.

Suffers from false positive error. Periodic advertisement generatesadditional traffic. Causes node overhead. Increases searchlatency.

[27] Increases downloading speed. Lowers power consumption. Offers suitabledynamicity. Reduces signaling overhead. Offers noticeable scalability.

Performance solely depends on the cluster size and density. Generatesadditional traffic from broadcasting as the number of clustersincreases. Suffers from failures of request agents. Lowsecurity. Management of clusters is difficult. Cluster formationincreases complexity.

[28]

Minimizes average path stretch. File retrieval is feasible via a shorterpath in the underlying physical network. Reduces search delay.Lowers routing overhead. Offers suitable load balancing andscalability.

Focuses on keyword based search. High capacity nodes required. Complexprocedures involved. Calculating and maintaining distancesbecomes tedious. Less robust. Offers low security. Suffers fromsingle point of failure and bottleneck. Consumes extra bandwidthand battery power.

[29]Effective hit rate within the group. Offers suitable load-balancing andscalability. Offers suitable dynamicity. Lowers network traffic.Improves success ratio. Lowers response time.

Involves complex procedures for super-peer selection. Provides lowsecurity. High capacity nodes required. Causes high nodeoverhead. Suffers from bottleneck and single point of failure.

[30]Reduces query cost. Lowers message overhead. Offers suitablescalability. Improves search efficiency. Offers suitabledynamicity and flexibility.

Their algorithm assumes that every node knows the physical locationinformation of the nearby nodes. Maintaining distance metricsbecomes tedious. The scheme suffers from bottlenecks. Requireshigh capacity nodes with GPS enabled functionality.

[31] Improves search efficiency. Offers suitable scalability and dynamicity.Lowers query delay.

Suffers from false positive error. Generates high overhead todisseminate information. Node overhead.

[32] Improves network coverage. Gets optimized over time. Improves searchefficiency. Offers noticeable dynamicity and flexibility.

Incurs high overheads due to its iterative nature. Suffers from lowscalability. Low security. High battery power and bandwidthconsumptions.

TABLE 10. Advantages and Disadvantages of the Social network based resource discovery techniques.


[33]Similarity based grouping helps improve search efficiency. Lowerstransmission cost. Offers suitable load balancing. Reduces querydelay.

Involves complex algorithms. Suffers from bottlenecks and single pointsof failure. High maintenance overhead. Causes node overhead.

[34]

Suitable for both connected and disconnected MANET communications.Supports content-based routing, where the messages are routedbased on their available contents rather than the classicalrouting which is just based on destination address. Offerssuitable scalability. Offers faster dissemination.

Frequent announcement and invitation leads to overhead. A user has tomaintain a document list and document repository which istedious. Supports only keyword based search. Offers low security.

[35]

Network and mobile resources are used effectively compared to theflooding technique. Offers suitable dynamicity and flexibility.Caching improves hit ratio. Offers suitable success rate andquery response time.

High capacity nodes required. Involves complex procedures. Predictionmay lead to deception. Frequent caching of data becomes tedious.Incurs high node overhead. Less secured.

[36]Lowers communication cost. Improves success rate. Lowers query delay.Offers suitable dynamicity and load balancing. Offers suitablescalability.

Maintenance overhead is high. Involves complex procedures. It suffers frombottleneck and single point of failure.

[37]Indexing reduces the search latency. Suitable for both connected anddisconnected MANETs. Reduces communication overhead. Improvessuccess ratio.

Causes node overhead. High capacity nodes are required to store fileinformation and their indexes. Overhead in index maintenance.Supports only keyword based queries.

[38]Removes bottlenecks and single points of failure. Offers noticeablesuccess rate and query response time. Suitable for small sizenetworks.

Suffers from low security. Requires high capacity nodes with GPSfunctionality. Involves complex procedures.

TABLE 11. Key performance indicators evaluation - Part A.

Characteristics [8] [9] [10] [11] [12] [13] [14] [15] [16] [17]Scalability Bad Bad Good Bad Good Good Bad Bad Good BadImplementationComplexity Medium High Medium Medium Low Medium High High Medium High

MaintenanceComplexity High High High High High High High High High High

SearchEfficiency Medium Low Medium Medium Medium Medium Medium Medium Medium Medium

EnergyEfficiency Low Low Low Low Medium Medium Low Low Medium Low

TransmissionCost High Medium High High Medium Low High High Medium Low

Cross-layerproperty No No Yes Yes No No No No Yes Yes

BestApplicableNetworkSize

Small Small Medium Small Medium Medium Small Small Small Small

sharing scenario. The other research direction along similarlines could be the peer offloading techniques that may helpto optimize the network resource utilization. Let us imagine,

we have a P2P streaming application. Now with the mobilephone constraints, say editing an audio/video clips requires alarge amount of energy and computation which is provided

14 VOLUME 4, 2016

TABLE 12. Key performance indicators evaluation - Part B.

Characteristics [18] [19] [20] [21] [22] [23] [24] [25] [26] [27]Scalability Good Bad Bad Bad Bad Bad Bad Good Bad GoodImplementationComplexity High High Low High High High High Medium High High

MaintenanceComplexity High High High High Medium High High High High High

SearchEfficiency Medium Medium Low Low Low Low Medium Low Low Low

EnergyEfficiency Low Low Low Low Low Low Low Low Low Medium

TransmissionCost Medium Medium High High Medium High Medium Medium Medium Medium

Cross-layerproperty No No No No No Yes No No Yes Yes


Small Small Small Small Small Small Small Small Small Small

TABLE 13. Key performance indicators evaluation - Part C.

Characteristics [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38]Scalability Good Good Good Good Bad Bad Good Bad Good Good BadImplementationComplexity Medium Medium Medium High High High High High High High High

MaintenanceComplexity High High High High High High High High High High High

SearchEfficiency Medium Medium Medium Medium Medium Medium Low Medium Medium Medium Medium

EnergyEfficiency Low Medium Medium Low Low Medium Low Low Medium Medium Medium

TransmissionCost High Low Medium High High Low High Medium Low Medium Medium

Cross-layerproperty No No No No Yes No Yes No No Yes No


Small Small Small Small Small Small Medium Small Small Small Small

TABLE 14. Summarization of schemes.

Criteria Flooding basedschemes

DHT basedschemes

Advertisement basedschemes

Social network basedschemes

Ease of Implementation Easy Complex Complex ComplexCandidature type for largenetworks Applicable Applicable Applicable Applicable

Suitable for highly dynamicscenario Yes No No Yes

Feasible for real-time systems Best fit Worst fit Worst fit Medium fitRobust to churn Yes No No YesSignificance of node failure Low High High HighLower resource constraints No No No YesProvide shortest path Yes No Yes No

with some limitations as compared to PC or laptop. To dealwith such resource constraint situation, focusing on the com-putational offloading aspect to the resource-rich platformsmight help to improve the performance of such applicationsin the upcoming 5G communication era.

VI. CONCLUDING REMARKS

Peer-to-Peer (P2P) networking is used in Mobile Ad-hocNetwork (MANET) to deploy content sharing applications.

Resource searching algorithms in such deployment have at-tracted a lot of attention over the years. In this article, westudy how resource discovery is carried out in such P2P filesharing applications over MANET. We review and comparestate of the art search algorithms to provide some interestinglines for future researches. We have investigated the searchschemes in four different categories, i.e., flooding basedtechniques, distributed hash table based techniques, contentadvertisement based techniques and the social network based

VOLUME 4, 2016 15

techniques. For each of these classes, we have comprehen-sively reviewed and compared several existing works cate-gorically by discussing their search mechanisms, underlayand overlay characteristics, and their deployment strategies.Further, each method is assessed and presented along withits strengths and weaknesses. We also compare each schemeevaluating few key performance indicators. To conclude aconsolidated comparison is done among the categories forquick summarization in terms of factors such as ease ofimplementation, candidature type, suitability for highly dy-namic scenario, feasibility for real-time systems, robustnessto churn, impact of node failure, whether it lower resourceconstraints, and provides shortest path or not. We also givean overview of the common challenges and complicationsobserved in such resultant systems. Further, we also shredlimelight on the file sharing scenarios in MEC enabled ad-hocnetwork, and its application domains highlighting few openresearch questions. From the study, we notice that most ofthe search schemes are based on the flooding technique thathas a wide and practical scope of applicability. Many systemslacked the fault tolerance and robustness capabilities. Also,almost all the reviewed systems are vulnerable to securityattacks. This critical aspect should be focused more. Ourstudy concludes that the resource searching algorithms incross-layered implementations can handle link mismatch,and failures better than the other prototypes.

REFERENCES[1] M. C. Castro, A. J. Kassler, C.-F. Chiasserini, C. Casetti, and I. Korpeoglu,

“Peer-to-Peer Overlay in Mobile Ad-hoc Networks,” in in Handbook ofPeer-to-Peer Networking, Springer, 2010, pp. 1045–1080.

[2] G. Ding and B. Bhargava, “Peer-to-peer File-sharing over Mobile Ad hocNetworks,” in Second IEEE Annual Conference on Pervasive Computingand Communications Workshops, 2004, pp. 1–5.

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AJAY ARUNACHALAM is a post-doctoral re-searcher (Artificial Intelligence) at the Centre forApplied Autonomous Sensor Systems (AASS),School of Science and Technology, Örebro Uni-versity, Örebro, Sweden, to which he contributeswith research on Autonomous Precision Agricul-ture Robot. Prior to his present role, he was work-ing as a Data Scientist at True Corporation PublicCompany Limited, an Communications Conglom-erate, working with Petabytes of data, and build-

ing & deploying models in production. He received the Ph.D. degree inComputer Science and Information Systems (CSIS) from National Instituteof Development Administration (NIDA), Thailand. And, his Master’s inComputer Science & Engg. from Anna University, Chennai, India, andthe Bachelor in Computer Engineering from Savitribai Phule Pune Uni-versity, Pune, India. His research interests include Distributed Systems,Wireless and Mobile Networking, Algorithmic Trading, Big Data, AppliedMachine Learning/Deep Learning, Opacity in AI systems, Optimization,FOSS related to e-learning/m-learning/e-governance. More details availableat https://sites.google.com/site/ajayarunachalamprofile/.

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VINAYAKUMAR RAVI received the Ph.D. de-gree in computer science from ComputationalEngineering & Networking, Amrita Schoolof Engineering, Coimbatore, Amrita VishwaVidyapeetham, India. He is currently AssistantResearch Professor at Center for Artificial Intel-ligence, Prince Mohammad Bin Fahd University,Khobar, Saudi Arabia. Prior to that, he was aPostdoctoral research fellow in developing andimplementing novel computational and machine

learning algorithms and applications for big data integration and data miningwith Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA.He has received MCA from Amrita Vishwa Vidyapeetham, Mysore in2014 and BCA from JSS College of Arts, Commerce and Sciences, Ootyroad, Mysore in 2011. His Ph.D. work centers on Application of Machinelearning (some times Deep learning) for Cyber Security and discusses theimportance of Natural language processing, Image processing and Big dataanalytics for Cyber Security. He has more than 50 research publications inreputed IEEE conferences, IEEE Transactions and Journals. His publicationsinclude prestigious conferences in the area of Cyber Security, like IEEES&P and IEEE Infocom. He has given many invited talks on deep learningapplications in IEEE conferences and Industry workshops in 2018. Hehas got a full scholarship to attend Machine Learning Summer School(MLSS) 2019, London. Dr. Ravi has served as a Technical ProgramCommittee (TPC) member at international conferences including SSCCSymposium, IEEE TrustCom-2020, and IEEE SmartData-2020. He is aneditorial board member for Journal of the Institute of Electronics andComputer (JIEC), International Journal of Digital Crime and Forensics(IJDCF), and he has organized a shared task on detecting malicious domainnames (DMD 2018) as part of SSCC’18 and ICACCI’18. His researchinterests include application of data mining, machine learning (includingdeep learning), natural language processing and image processing for CyberSecurity, big security data analytics, disease gene discovery/prioritization,computational drug discovery and drug repositioning. More details availableat https://vinayakumarr.github.io/.

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Documents

A Survey of Search Algorithms for Peer-to-Peer File