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Cloud Computing: a Novel Approach for Improving Service Capability of Wireless Mesh Networks
Ran Li, Ziyi Lu, Xiaobo Wang, Baoqiang Kana
Nanjing Telecommunication Technology Research Institute of CESEC, 211107 Nanjing, China
aemail: Ryanlee730@163.com
Keywords: cloud computing; wireless mesh networks; service capability
Abstract. With the number of applications increased in wireless mesh networks (WMNs), insufficient service capability is becoming a main obstacle. Meanwhile, cloud computing is an effective approach for organizing computing resource which can improve service capability remarkably. In this paper, framework of WMNs with cloud computing is proposed. Service capability of WMNs with cloud computing is judged and scored from 6 dimensions to make a composite comparison, which is shown cloud computing will be a promising approach for improving service capability in WMNs.
Introduction
With explosive increase of Internet services and Websites, technique of more efficient and effective information retrieval or data computing is on urgent need. Cloud computing [1] has already been proved an effective approach for organizing computing resource, which provides users compute capability, storage space and software service on demand.
There are many frameworks supporting for cloud computing application construction. Google’s MapReduce [2] is a programming framework applied by Google’s search engine which is already implemented by open source application such as Hadoop. Dryad [3] is a cloud computing framework proposed by Microsoft. Also, Amazon’s elastic computing cloud (EC2) and simple storage services (S3) [4] provide cloud computing and cloud storage service. Based on the provided service, cloud computing service can be categorized into 3 types: Infrastructure as a Service (IaaS), such as Amazon EC2 and S3; Platform as a Service (PaaS), such as Google App Engine and Microsoft Windows Azure [6]; Software as a Service (SaaS), such as Rackspace.
Wireless mesh networks (WMNs) [5,6] is a wireless multihop networks with much more flexibility and network coverage. WMNs is developing based on mobile ad hoc network. In WMNs, some mesh routers are separated from normal nodes which are responsible for routing and providing various services. Some nodes are organized as an ad hoc network connected to external network through a neighbor mesh router.
In WMNs, there is no uniform node for whole network’s management and control, which may bring weakness for network security; there are much more data redundancy and garbage decreasing transfer efficiency; also the types of application and service is too limited to achieve user’s requirement. Cloud computing, as a newly developing technique, not only can be deployed according to requirement, but also more reliable and extensible for various applications. Import cloud computing in WMNs can provide various thin terminal strong network service and promote service level and capability. In this paper, we propose a framework of WMNs with cloud computing and analysis service capability of WMNs with cloud computing from 6 dimensions to make a composite judgment.
Wireless mesh networks with cloud computing
Fig. 1 is flow of data transfer in a normal WMNs, nodes are organized as several ad hoc networks, some node are considered as mesh router and is responsible for gathering data from an ad hoc network. Mesh router communicate each other for sharing information throughout the whole network and distribute information to every node belong to. However, there are some drawbacks of traditional communication mode of WMNs:
Advanced Materials Research Vols. 765-767 (2013) pp 1142-1145Online available since 2013/Sep/04 at www.scientific.net© (2013) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMR.765-767.1142
All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP,www.ttp.net. (ID: 130.207.50.37, Georgia Tech Library, Atlanta, USA-14/11/14,12:24:02)
Data redundancy: continuous transferred data may have correlation to each other, which will bring lots of redundancy and cost valuable network bandwidth.
Data garbage: data transferred periodically in WMNs may bring network congestion. Data without timeliness become data garbage, which will lose its worthiness even the communication is over.
Complicated communication process: as in Fig. 1, data upload and distribute process cross multi levels and servers, the whole communication process contain 3 phases: data collection, forward, fusion and processing, which make the communication and information sharing process much more complicated.
Obscure application categorization: data transferred in WMNs does not categorized by its application requirement, which make it difficult to provide relevant service quality.
ad hoc 2
ad hoc 3ad hoc 1
mesh router
mesh router
mesh router
mesh router
node
node
node
node
nodenode
node
nodenode
node
node
node
Fig.1. Flow of data transfer in WMNs
Data
collection
Fusion and
processing
Data center
nodenode
nodenode
node node
nodenode
node
upload distribute
Fig 2. Framework and flow of data transfer in WMNs with cloud computing
Fig. 2 is framework and flow of data transfer in WMNs with cloud computing. Data collected from nodes are uploaded to data center straightly. In data center, all data are fused and processed, then distribute to every node for data sharing throughout the whole WMNs. Compared to traditional communication mode, WMNs with cloud computing shows several obvious advantage:
Data center with much higher efficient and effective data processing capability can fusion and distribute data on high speed, which makes real-time data sharing throughout whole WMNs possible.
Data center take the place of mesh routers of each level in traditional communication mode, which not only decrease data upload and distribute process, but also decrease data redundancy and garbage to improve efficiency.
Data center with strong computing power can define more intelligent strategy according different application requirement. Meanwhile, data center can monitor load of each data link, which realize data distributing on demand.
Advanced Materials Research Vols. 765-767 1143
Key techniques
There are some key techniques must be considered when import cloud computing in the area of WMNs.
A. Security of cloud
For security of cloud, a series of mechanism is constructed including multi-levels from low to high. The security architecture contains low-level cloud security infrastructure, security monitoring, risk control and emergency response, as shown in Fig. 3.
Risk control
and
emergency
response
security
monitoring
cloud security
infrastructure
application
data
data center
hardware platform
access control
data security
storage security
network security
physical security
Fig 3. Cloud security architecture of WMNs
Cloud security infrastructure provides secure storage and computing service for high-level applications, which is the base of cloud security. There are different security technique for different levels: physical media security should be considered for hardware platform; storage and network security are considered at data center level, including integrality, reliability, transfer confidentiality of static data; data level contains data access control, data access authorization, et al; user certification, user access control, program integrality inspection and flaw management is considered at application level.
For cloud computing platform may suffer threats from many sources, a complete risk control and emergency response mechanism should be constructed. Risk control will analyze and judge risk at a time in order to manage security of the whole platform and get rid of accidents. Emergency response will make quick response for security accidents and recover them as soon as possible.
Security monitoring realizes verifying, alarming and defending for attack against cloud computing platform as well as prevent fatal secure accident.
B. Bandwidth of communication Cloud computing is based on network infrastructure, which asks for well bandwidth condition,
however, there are also a certain number of narrow band nodes applied in WMNs. Therefore, adaptation of WMNs for narrow band communication must be considered for importing cloud computing. There are several approaches for adaptation: one way is decrease data amount for transport in order to cut down bandwidth occupied, such as compressed encoding, agent software when communicate across multi subnet, improve efficiency and reliability of narrow band communication through request agent, multi address transmitting, data caching and filtering, et al.
C. Consistency of service provision Particular application of WMNs will inevitably bring service interrupt issue, therefore, a series
of mechanism should be constructed for consistency of service. One approach is preventing service from interrupting; the other is recovering service interrupt as soon as possible.
For preventing interrupting, optimized scheduling algorithm, as well as self-adapting encoding modulation, multicast and secure access authentication can be defined in data center.
For service interrupt recovering, redundancy service can be applied. It stores a copy in data center for each service, a secure routing will be made once service interruption occurs, and the copy will re-transport to ensure service recovery as soon as possible.
Service capability analysis of WMNs with cloud computing
In order to judging service capability of WMNs with cloud computing, according the idea of service-oriented, 6 dimensions of service will be judged as diversity, extensibility, quality, security, infrastructure adaptability and future outlook. Comparison results are shown in table 1.
Table 1 Comparison of WMNs with and without cloud computing WMNs without cloud computing WMNs with cloud computing
diversity small amount and limited kinds of data transfer
large amount of data transfer; remote computing and storage; data fusion and sharing on-line; decision support; et al.
extensibility restricted by low level infrastructure, less of service extensibility
extensible for various applications, client terminal join in dynamically; new application can be deployed at any time
1144 Advanced Information and Computer Technology in Engineering andManufacturing, Environmental Engineering
quality lack of QoS mechanism QoS mechanism can be uniformly deployed in data center
security no central node, lack of infrastructure for secure key management and safety routing
security architecture includes different levels can be constructed in data center to ensure infrastructure and data security.
infrastructure adaptability
tolerable to current infrastructure, no more reconstruction
large amount of data transfer ask for more communication bandwidth
futrue outlook limited kinds of service cannot reach to development of users’ requirements
bottleneck will be break with developing of bandwidth condition of WMNs, more widely future outlook
Fig. 4 is the quantification radar chart constructed according to comparison results in table 1. Each dimension is scored by capability analyzed and full mark of each dimension is 10. According to the radar chart, WMNs with cloud computing ask for stronger infrastructure, however, it remarkably improves service capability and level, which has more widely prospect and more widely future application area.
diversityextensibility
qualitysecurity
Infrastructure
adaptability
Future
outlook
WMNs without
cloud computing
WMNs with
cloud computing
10
10
10
10
10
10
3
6
4
8
3
6
7
43
8
3
6
Fig 4. Quantification radar chart for WMNs with and without cloud computing
Conclusions
With number of applications increased in WMNs, there is urgent need for improving service capability. In this paper, framework of cloud computing applied in WMNs and relevant key technique should be considered is proposed and explained. Finally, a composite service capability analysis from 6 dimensions is made, which is shown cloud computing will be a promising approach for improving service capability in WMNs.
References
[1] Q. Zhang, L. Cheng and R. Boutaba. Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, (2010), 1(1): 7-18. [2] J. Dean and S. Ghemawat. Mapreduce: simplified data processing on large clusters. Communications of the ACM (2008), 51(1): pp. 1-13. [3] M. Isard and Y. Yu. Distributed data-parallel computing using a high-level programming language. In: Proceedings of the 35th SIGMOD international conference on management of data. (2009): 987-994. [4] Amazon.com. Amazon Web Services (AWS), Online at http://aws.amazon.com, 2008. [5] R.C. Carrano, L.C.S. Magalhaes, D.C.M. Saade, et al. IEEE 802.11s multihop MAC: a turorial. IEEE Communications Surveys & Tutorials. 2011, 13(1):52-67. [6] I.F. Akyildiz, X. D. Wang, W. L. Wang. Wireless mesh networks: a survey. Computer Networks, 2005, 47(4):445-487.
Advanced Materials Research Vols. 765-767 1145
Advanced Information and Computer Technology in Engineering and Manufacturing, Environmental
Engineering 10.4028/www.scientific.net/AMR.765-767 Cloud Computing: A Novel Approach for Improving Service Capability of Wireless Mesh Networks 10.4028/www.scientific.net/AMR.765-767.1142
DOI References
[6] I.F. Akyildiz, X. D. Wang, W. L. Wang. Wireless mesh networks: a survey. Computer Networks, 2005,
47(4): 445-487.
http://dx.doi.org/10.1016/j.comnet.2004.12.001
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