A Novel Routing Algorithm Based-on Ant Colony in Mobile Ad hoc Networks

Sanaz Asadinia Department of Computer

Engineering, Islamic Azad University Arak Branch,

Arak, Iran sanaz asadinia@yahoo.com

Marjan kuchaki Rafsanjani Department of Computer

Shahid Bahonar University of Kerman,

Kerman, Iran kuchaki. m@Srbiau.ac.ir

Arsham Borumand Saeid Department of Mathematics, Shahid Bahonar University

of Kerman, Kerman, Iran

arsham@mail.uk.ac.ir

Abstract A Mobile Ad hoc Network (MANET) is made up of

mobile nodes that communicate through wireless connections, without any existing infrastructure or central administrator. Topology of the network is not fIXed. Hence, routing in dynamic network is a new challenge. Nature-inspired algorithms (swarm intelligence) such as Ant Colony Optimization algorithms have shown to be a good method for expanding routing algorithms for MANETs. Swarm Intelligence (SI) is the local interaction of many simple agents to accede a global goal. SI is based on collective behavior of social insect colonies for solving different types of problems. In this paper, we propose a new routing algorithm for MANETs, which combines the idea of ant colony optimization with zone based hierarchical link state (ZHLS) protocol. The algorithm is based on ants jump from one zone to the next zones which contains of the proactive routing within a zone and reactive routing between the zones. The proposed algorithm will improved the performance of the network such as delay and packet delivery ratio than traditional routing algorithms.

1. Introduction

Mobile ad hoc network (MANET) is an infrastructure­less multi-hop network where each node communicates with other nodes directly or indirectly through intermediate nodes. Thus, all nodes in a MANET basically function as mobile routers participating in some routing protocol required for deciding and maintaining the routes. Since MANETs are infrastructure-less, self­organizing, rapidly deployable wireless networks, they are highly suitable for applications communications in regions with no wireless infrastructure, emergencies and natural disasters, and military operations [1, 2]. Another application is Bluetooth which is designed for personal use and enables printers, scanners, mobile phones and music players to be connected wireless to a personal area

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network this creates a tremendous flexibility because it enables devices to move freely between different networks [3]. Routing is one of the key issues in MANETs due to their highly dynamic and distributed nature. Numerous ad hoc routing algorithms exist to allow networking under various conditions. They can be separated into three groups, proactive, reactive and hybrid algorithms. In proactive routing algorithms maintain continuously updated state of the network and the existing routes; however, in some cases it may generate an unnecessary overhead to maintain the routing tables and then may be better to create routes only on demand, the case of reactive routing algorithms. In reactive routing algorithms require time-consuming route creations that may delay the actual transmission of the data when sources have no path towards their destination and then, in this case may be better to use a proactive routing algorithm. In hybrid protocols try to profit the advantages of both reactive and proactive protocols and combine their basic properties into one. These protocols have the potential to provide higher scalability than pure reactive or proactive protocols thanks to the collaboration between nodes with close proximity to work together and therefore reduce the route discovery overhead [4].

Recently, a new family of algorithms emerged inspired by swarm-intelligence, which provides a novel approach to distributed optimization problems. The expression "Swarm Intelligence" defines any attempts to design algorithms inspired by the collective behavior of social insect colonies and other animal societies. Ant colonies, bird flocking, animal herding and fish schooling are examples in nature that use swarm intelligence. Several algorithms which are based on ant colony were introduced in recent years to solve the routing problem in mobile ad hoc networks.

This paper provides the description of a hybrid routing scheme based on both an Ant Colony Optimization (ACO) and a zone based hierarchical link state (ZHLS)

protocol, that 'pretends' to profit the advantages of both reactive and proactive algorithms. Ant Colony Optimization (ACO) is a family of optimization algorithms based on real ants' behaviour in finding a route to food nest. It has been observed available routes, ants find shortest route to food nest. To achieve this, ants communicate through deposition of a chemical substance called pheromone along the route. Shortest path has highest concentration leading to more and more ants using this route [5]. There are some successful ant-based algorithms to network that we will introduce them in next section.

2. Related work

Routing in MANETs has traditionally used the knowledge of the connectivity of the network with emphasis on the state of the links. To overcome the problems associated with the link-state and distance vector algorithms, numerous routing

protocols have been proposed The routing protocols proposed for MANETs are generally categorized into three groups: table driven (also called proactive) and on­demand (also called reactive) and hybrid protocols which are both proactive and reactive in nature [4].

2.1. Routing in mobile ad hoc networks

In Proactive Routing Protocols, each node continuously maintains up-to-date routes to every other node in the network. Routing information is periodically transmitted throughout the network in order to maintain routing table. Thus, if a route has already existed before traffic arrives, transmission occurs without delay. Otherwise, traffic packets should wait in queue until the node receives routing information corresponding to its destination. However, for highly dynamic network topology, the proactive schemes require a significant amount of resources to keep routing information up-to­date and reliable. Proactive protocols suffer the disadvantage of additional control traffic that is needed to continually update stale route entries. Since the network topology is dynamic, when a link goes down, all paths that use that link are broken and have to be repaired. This protocol is appropriate for a network with low mobility. Certain proactive routing protocols are Destination­Sequenced Distance Vector (DSDV) [6], Wireless Routing Protocol (WRP) [7] and so on. The main differences among them are the number of used tables, the information that is kept and the forward packet police to maintain the tables updated.

Reactive Routing Protocols in contrast to proactive approach, a node initiates a route discovery throughout the network, only when it wants to send packets to its

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destination. For this purpose, a node initiates a route discovery process through the network. This process is completed once a route is determined or once a route has been established, it is maintained by a route maintenance process until either the destination becomes inaccessible along every path from the source or until the route is no longer desired. In reactive schemes, nodes maintain the routes to active destinations. A route search is needed for every unknown destination. Therefore, theoretically the communication overhead is reduced at expense of delay due to route research. Furthermore, the rapidly changing topology may break an active route and cause subsequent route searches. Reactive strategies are suitable for networks with high mobility and relatively small number of flows. Some reactive protocols are Ad hoc On-Demand Distance Vector (AODV) [8], Dynamic Source Routing (DSR) [9], Temporally Ordered Routing Algorithm (TORA) [10] and Associativity-Based Routing (ABR) [11].

A hybrid Protocol combines the advantages of both proactive and reactive protocols [12].

In hybrid algorithm each node maintains both the topology information within its zone and the information regarding neighboring zones that means proactive behavior within a zone and reactive behavior among zones. Thus, a route to each destination within a zone is established without delay, while a route discovery and a route maintenance procedure is required for destinations that are in other zones [12]. The zone routing protocol (ZRP) [13], zone-based hierarchical link state (ZHLS) [14] routing protocol and distributed dynamic routing algorithm (DDR) [15] are three hybrid routing protocols. The hybrid protocols can provide a better trade-off between communication overhead and delay, but this trade-off is subjected to the size of a zone and the dynamics of a zone. The hybrid approach is an appropriate candidate for routing in a large network. Joa-Ng et al. [14] proposed a hybrid routing protocol is called Zone-based Hierarchical Link State Routing Protocol in the effort to combine the features of proactive and reactive protocols. In Zone-based Hierarchical Link State Routing Protocol (ZHLS), the network is divided into non-overlapping zones. Unlike other hierarchical protocols, there is no zone-head. ZHLS defines two levels of topologies - node level and zone level. A node level topology tells how nodes of a zone are connected to each other physically. A virtual link between two zones exists if at least one node of a zone is physically connected to some node of the other zone. Zone level topology tells how zones are connected together. There are two types of Link State Packets (LSP) as well - node LSP and zone LSP. A node LSP of a node contains its neighbor node information and is propagated with the zone where as a zone LSP contains the zone information and is propagated globally. So, each node has

full node connectivity knowledge about the nodes in its zone and only zone connectivity infonnation about other zones in the network. So given the zone id and the node id of a destination, the packet is routed based on the zone id till it reaches the correct zone. Then in that zone, it is routed based on node id. A <zone id, node id> of the destination is sufficient for routing so it is adaptable to changing topologies. In ZHLS, Zone LSPs are flooded throughout the network so that all nodes know both zone level and node level topologies of the network. This simplifies the routing but introduces communication overhead [14].

2.2 Ant-based routing algorithms for MANETs

There exist some successful ant-based algorithms to network control, being the most prominent AntNet [16], and Ant-based Control (ABC) [17], which have a number of properties desirable in MANETs. AntNet and ABC use two ants, forward and backward ants to find the shortest route from the source to the destination.

AntNet [16] is a proactive ACO routing algorithm for packet switch networks. In this algorithm, a forward ant is launched from the source node at regular intervals. A forward ant at each intermediate node selects the next hop using the information stored in the routing table of that node. The next node is selected with a probability proportional to the goodness of that node which is measured by the amount of pheromone deposited on the link to that node. When a forward ant reaches the destination, it generates a backward ant which takes the same path as the corresponding forward ant but in opposite direction. The backward ant updates pheromone values as it moves on its way to the source node.

ARA (Ant colony based Routing Algorithm) proposed by Gunes et al. [18, 21] is a reactive ACO routing algorithm for mobile ad hoc networks. ARA has two phases: route discovery, and route maintenance. In route discovery phase, the sender broadcasts a forward ant. The ant is relayed by each intermediate node until reaches the destination. After receiving a forward ant in the destination, the ant is destroyed and a backward ant is sent back to the sender. The backward ant increases the pheromone value corresponding to the destination in each intermediary node until it reaches the sender. When the sender receives a backward ant, the route maintenance phase starts by sending data packets. Since the pheromone track is already established by the forward and backward ants, subsequent data packets will perform the route maintenance by adjusting the pheromone values.

ARAMA (Ant Routing Algorithm for Mobile Ad hoc networks) proposed by Hossein and Saadawi [19, 21] is a proactive routing algorithm. The main task of the forward ant as in other ACO algorithms for MANETs is to collect path information. However, in ARAMA, the forward ant takes into account not only the hop count factor, as most

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protocols do, but also the links local heuristic along the route such as the node's battery power and queue delay. ARAMA defines a value called grade. This value is calculated by each backward ant, which is a function of the path information stored in the forward ant. At each node, the backward ant updates the pheromone amount of the node's routing table, using the grade value. The protocol uses the same grade to update pheromone value of all links. The authors claim that the route discovery and maintenance overheads are reduced by controlling the forward ant's generation rate. However, they do not clarify how to control the generation rate in a dynamic environment.

AntHocNet is a hybrid ant based routing protocol proposed by Di Caro [20, 21] in the effort to combine the advantages from both AntNet and ARA. AntHocNet reactively finds a route to the destination on demand, and proactively maintains and improves the existing routes or explore better paths. In AntHocN et, ant maintains a list of nodes it has visited to detect cycles. The source node sends out forward ants and when it receives all the backward ants, one generation is completed. Each node i keeps the identity of the forward ants, the path computation, number of hops, number of the ant from the source to node i, and the time the ant visited node i. Note that more than one ant may have reached node i and therefore the identity of the ant is important. When an ant arrives at a node, the node checks the ant's path computation and the time it reached node i. If the path computation and time are within a certain limit of those produced by another ant of the same generation then the ant is forwarded. Otherwise, the ant is discarded. In case of a link failure at a node and no alternative paths are available, the node sends a reactive forward ant to repair the route locally and to determine an altemative path. If a backward ant is received for the reactive forward ant, the data packets are sent along the newly found path and all its neighbors are notified about the change in route. Otherwise, the node sends a notification to all its neighbors of the lost destination paths which in tum initiate forward ants from the neighbors. In the next section, we present the main ideas of our algorithm.

3. The Proposed Routing Scheme

Our algorithm uses the ZHLS protocol which consists of the proactive routing within a zone and reactive routing between the zones. The network is divided into zones which are the node's local neighborhood. The network divides into non-overlapping zones; a node is only within a zone. The zone size depend on node mobility, network density, transnnSSlon power and propagation characteristics. Each node knows its physical location by geo-location techniques such as Global Positioning

System (GPS). The nodes can be categorized as interior and gateway nodes.

In Figure 1 for node S, nodes C, D, and E are gateway nodes, and nodes A, B are interior nodes. All other nodes are exterior nodes (outside the zone). To determining gateway and interior nodes, a node needs to lrnow its local neighbors. This is achieved by a detection process based on replies to hello messages transmitted by each node. Each node only lrnows the connectivity within its zone and the zone connectivity of the whole network.

I I ZoneS

I /\!::.F I : fp\ -@- - �� I /

I - - - �::.; - - - i @@���.� - -iJ -� --- --L --

(U-l_ �

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I : --� ?,::\- r- -I : \0 ® I : Zone I

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Figure 1.Example of our scheme structure

3.1. Routing table

The algorithm has two routing tables, Intrazone Routing Table (lntraRT) and Interzone Routing Table (lnterRT). IntraRT is a routing table maintained proactively. A node can determine a path to any node within its zone immediately. InterRT is a routing table for storing routes to a destination out of its zone. The gateway nodes of the zone are used to find routes between zones.

3.2. ANTs

The defined ants in our scheme are same with HOPNET algorithm [22] that classified in 5 types: internal forward ant, external forward ant, backward ant, notification ant and error ant. The internal forward ant is the responsible for maintaining the proactive routing table continuously within its zone. The external forward ant performs the reactive routing to nodes beyond its zone. When an external forward ant is received at the destination, it is converted to a backward ant and sent back along the discovered route. If a new route is

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reactively discovered, then a notification ant will be sent to source node and to all nodes on the route to update their reactive routing table. The error ant is utilized to warn some changes in the network topology and to restart a new search by the destination if the source still needs a route.

3.3. Route discovery

We use ACO algorithm for fmding the shortest route between two nodes (Vi, Vj) in network. Each communication link has two values, cp(Vi, Vj)represents pheromone value per link and w(Vi, Vj) represents time which the links may be in connection. The pheromone value gets updated by the ants as they move the links. The ants change the concentration of the pheromone value on their path to the destination and on their route back to the source. Route discovery occurs by Intrazone and Interzone routing. The IntraR T basic structure is a matrix whose rows are its neighbors and the colmnns are all identified nodes within its zone. In route discovery within a zone (lntrazone routing), each node periodically sends internal forward ants to its neighbors to maintain the Intrazone routing table updated. When the source node wants to transmit a data packet to a node within its zone, it first searches the colmnns of its IntraRT to see if the destination exists in its zone. If it finds the destination in its IntraRT, then Route discovery phase is done. At the current node, the ant verifies the pheromone amount for each neighbor which has a route to destination. The neighbor which has the biggest pheromone amount is chosen to next hop. After selecting a node as next hop increase pheromone concentration selected link and along all other links the pheromone is decremented. Pheromone concentration on a link (Vi,Vj) along consists considering the path from current node Vi to source node Vs, the pheromone value on link (Vi,Vs) in Vj's routing table is reinforced. The amount of pheromone on a link (Vi,Vs) is increased by following equation[22]:

E cp(Vi, Vs) = cp(Vi, Vs) + T(Vs, vi) + w(Vi, Vj) (1) That E has to be chosen appropriately to avoid fast or

slow evaporation and T (Vs,Vi) represents the total time required to traverse from Vs to Vi. The pheromone concentration on all other entries not equal to Vi in the same colunm Vs in Vj's routing table is decremented using the evaporation equation below:

cp(Vl, Vs) = (1 - E)cp(Vl, Vs) 'Vl"* i (2) Where E is the evaporation coefficient provided by the user [22].

On its path back to the source, an ant again updates the pheromone concentration. The pheromone concentration update for entry (Vb, Vd) is [22]:

c cp(Vb, Vd) = cp(Vb, Vd) + T(Vs, Vd) _ T(Vs, Vk) (3) If not found the destination in its IntraRT, then Route discovery between zones is done.

In route discovery between zones (Interzone routing), When a node wants to send a data packet to a destination node, it verifies the Interzone routing table to discover an existent route. If the route exists and has not expired, then the node transmits the data packet. Otherwise, the node starts a search process to find a new path to destination. When a source node will to transmit a data packet to a node thither its zone, the node sends external forward ants to search a path to the destination. The external forward ants are first sent by the node to its gateway nodes. The gateway nodes check to see if the destination is within its zone. If the destination is not within its zone and the path has expired, the ants jump between the border zones via the other gateway nodes until an ant localizes a zone with the destination. This ant propagation through the border zones is called bordercast. At the destination, forward ant is converted to a backward ant and is sent to the source. Then, the data packet is transmitted. Use bordercast and routing tables process reduces the delay, because intraRT proactively maintains all the routes within its zone and interRT stores the path to the destination that the ants recently visited. These tables contribute to fast end to end packet transmission since the paths are readily accessible. An example of the route discovery between zones is given below using Figure 1. Assume the source I want a route to the destination L. Since L does not belong to I's zone, node I will send external forward ants to gateway nodes its neighbor zones, namely F and H. Nodes H, F looks through the IntraRT table to check if L is within its zones. In this example, L will not be in the tables. Therefore, H will send the ant to its gateway node, G. G will send external forward ants to gateway nodes of its neighbor zones, D and K. D cannot find L in its zone. Therefore, Node D sends the ant to its gateway nodes. K finds the destination node L within their zone. K then send forward ants with their attached addresses to node L via the path indicated in IntraRT table. The backward ant traverses in the reverse direction, for example, <L, K, G, H, I> to source I from destination T.

3.4. Route maintenance

In mobile ad-hoc network, the flexible mobility and communication interference will lead to the invalidation of some route. There are two reasons which an intermediate node will not be able to deliver packets: i)

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the pheromone concentration along the neighboring links is zero, in the case the ants cannot select any links to travel if all their links, up and down are zero and the data packet is failed at that node, ii) damaged route. If the damaged route is within a zone, it will recover after a period because the IntraRT is proactively maintained. If the damaged route is between zones, the up node of the broken link will conduct a local repair process and then search an alternative path to the destination while buffering all the packets it receives. If the node finds a new path to the destination, it will send all the buffered packets to the destination, then a notification ant will be sent to the source to allow the source node know the change of route. If a new path cannot be found instead failed path, an error ant will be sent to the source node. Hence increases packet delivery ratio [22].

4. Conclusion and future work

Routing in MANETs is 'a hard work' and actually it is an interesting research area that has been growing in recent years. Its difficulty is mainly generated because of the constant changes in the network. There exist some traditional solutions such as proactive protocols and reactive protocols, each one with their advantages and disadvantages. In spite of this, these solutions have to improve to offer better performance. In fact, there is a new generation of hybrid routing protocols that have 'the potential' to provide higher scalability than pure reactive or proactive protocols, and moreover to maintain routing information much longer because of the collaboration between nodes.

In this paper, we have proposed a new routing algorithm for MANETs, which combines the idea of ant colony optimization (ACO) with zone-based hierarchical link state (ZHLS) protocol. The algorithm contains of the proactive routing within a zone and reactive routing between the zones. The algorithm is efficient for end to end delay and packets delivery ratio. We will simulate our proposed algorithm with one of network simulators and we compare the scheme performance with other routing algorithms.

5. References

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