Application of WMN-SA Simulation System for Node Placement in ...
International Journal of Mobile Computing and Multimedia Communications, 6(2), 13-21, April-June 2014 13
Application of WMNSA Simulation System for Node Placement in Wireless Mesh Networks:
A Case Study for a Realistic Scenario Shinji Sakamoto, Fukuoka Institute of Technology, Fukuoka, Japan Algenti Lala, Polytechnic University of Tirana, Tirana, Albania Tetsuya Oda, Fukuoka Institute of Technology, Fukuoka, Japan Vladi Kolici, Polytechnic University of Tirana, Tirana, Albania Leonard Barolli, Fukuoka Institute of Technology, Fukuoka, Japan Fatos Xhafa, Technical University of Catalonia, Barcelona, Spain
ABSTRACT One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. In WMNs, there are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, the authors consider the router node placement problem in WMNs. The objective is to find the optimal distribution of router nodes in order to provide the best network connectivity (the maximal number of connected routers) and coverage (maximal number of covered clients). The authors apply their proposed WMN-SA simulation system in a realistic scenario of the distribution of mesh clients considering Itoshima City, Fukuoka Prefecture, Japan. From simulation results, they found many insights that can be very important for real deployment of WMNs.
Keywords:
Connectivity, Coverage, Intelligent Algorithms, Simulated Annealing, WMNs
DOI: 10.4018/ijmcmc.2014040102 Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
14 International Journal of Mobile Computing and Multimedia Communications, 6(2), 13-21, April-June 2014
INTRODUCTION Wireless Mesh Networks (WMNs) (Akyildiz, Wang, & Wang, 2005; Nandiraju, Nandiraju, Santhanama, He, Wang, & Agrawal, 2007; Chen & Chekuri, 2007) are important network infrastructure for providing cost-efficient broadband wireless connectivity. They are showing their applicability in deployment of medical, transport and surveillance applications in urban areas, metropolitan, neighboring communities and municipal area networks. At the heart of WMNs are the issues of achieving network connectivity and stability as well as QoS in terms of user coverage. These issues are very closely related to the family of node placement problems in WMNs, such as mesh router nodes placement. Node placement problems have been long investigated in the optimization field due to numerous applications in location science (facility location, logistics, services, etc.) and classification (clustering). Facility location problems are thus showing their usefulness to communication networks, and more especially from WMNs field. WMNs are currently attracting a lot of attention from wireless research and technology community for providing cost-efficient broadband wireless connectivity. WMNs are based on mesh topology, in which every node (representing a server) is connected to one or more nodes, enabling thus the information transmission in more than one path (Durresi, Zhang, Durresi, & Barolli, 2010). The path redundancy is a robust feature of this kind of topology. Compared to other topologies, mesh topology needs not a central node, allowing networks based on such topology to be self-healing. These characteristics of networks with mesh topology make them very reliable and robust networks (Behera & Tripathy, 2014) to potential server node failures. In WMNs mesh routers provide network connectivity services to mesh client nodes. The good performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical deployment area to achieve network connectivity, stability
and user coverage. The objective is to find an optimal and robust topology of the mesh router nodes to support connectivity services to clients. For most formulations, node placement problems are shown to be computationally hard to solve to optimality (Garey & Johnson, 1979; Lim, Rodrigues, Wang & Xua, 2005; Amaldi, Capone, Cesana, Filippini, Malucelli, 2008; Wang, Xie, Cai & Agrawal, 2007), and therefore heuristic and meta-heuristic approaches are useful approaches to solve the problem for practical purposes. Several heuristic approaches are found in the literature for node placement problems in WMNs (Muthaiah & Rosenberg, 2008; Zhou, Manoj & Rao, 2007; M. Tang, 2009; Antony Franklin & Siva Ram Murthy, 2007; Vanhatupa, Hannikainen & Hamalainen, 2007). In our previous work (Xhafa, Sanchez, Barolli & Miho, 2010; Sakamoto, Kulla, Oda, Ikeda, Barolli & Xhafa, 2014), we implemented a simulation system using Simulated Annealing (SA) for WMNs. We call this simulation system WMN-SA. In this work, we applied our implemented WMN-SA system in a realistic scenario considering the distribution of mesh clients in Itoshima City, Fukuoka Prefecture, Japan. For simulations, we consider a realistic distributions of 108 mesh clients in Itoshima city. Then, we deployed 36 mesh routers and run WMN-SA simulation system to maximize the size of Giant Component (GC) and Number of Covered Mesh Clients (NCMC). The rest of the paper is organized as follows. In the next section, we present the definition of node placement problem. Then, we describe the proposed and implemented WMN-SA simulation system. After that, we present the simulation results. Finally, we give concluding remarks and future work.
NODE PLACEMENT PROBLEM IN WMNS In this problem, we are given a grid area arranged in cells where to distribute a number of mesh router nodes and a number of mesh
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This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Communications and Social Science. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2
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Application of WMNSA Simulation System for Node Placement in Wireless Mesh Networks:
A Case Study for a Realistic Scenario Shinji Sakamoto, Fukuoka Institute of Technology, Fukuoka, Japan Algenti Lala, Polytechnic University of Tirana, Tirana, Albania Tetsuya Oda, Fukuoka Institute of Technology, Fukuoka, Japan Vladi Kolici, Polytechnic University of Tirana, Tirana, Albania Leonard Barolli, Fukuoka Institute of Technology, Fukuoka, Japan Fatos Xhafa, Technical University of Catalonia, Barcelona, Spain
ABSTRACT One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. In WMNs, there are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, the authors consider the router node placement problem in WMNs. The objective is to find the optimal distribution of router nodes in order to provide the best network connectivity (the maximal number of connected routers) and coverage (maximal number of covered clients). The authors apply their proposed WMN-SA simulation system in a realistic scenario of the distribution of mesh clients considering Itoshima City, Fukuoka Prefecture, Japan. From simulation results, they found many insights that can be very important for real deployment of WMNs.
Keywords:
Connectivity, Coverage, Intelligent Algorithms, Simulated Annealing, WMNs
DOI: 10.4018/ijmcmc.2014040102 Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
14 International Journal of Mobile Computing and Multimedia Communications, 6(2), 13-21, April-June 2014
INTRODUCTION Wireless Mesh Networks (WMNs) (Akyildiz, Wang, & Wang, 2005; Nandiraju, Nandiraju, Santhanama, He, Wang, & Agrawal, 2007; Chen & Chekuri, 2007) are important network infrastructure for providing cost-efficient broadband wireless connectivity. They are showing their applicability in deployment of medical, transport and surveillance applications in urban areas, metropolitan, neighboring communities and municipal area networks. At the heart of WMNs are the issues of achieving network connectivity and stability as well as QoS in terms of user coverage. These issues are very closely related to the family of node placement problems in WMNs, such as mesh router nodes placement. Node placement problems have been long investigated in the optimization field due to numerous applications in location science (facility location, logistics, services, etc.) and classification (clustering). Facility location problems are thus showing their usefulness to communication networks, and more especially from WMNs field. WMNs are currently attracting a lot of attention from wireless research and technology community for providing cost-efficient broadband wireless connectivity. WMNs are based on mesh topology, in which every node (representing a server) is connected to one or more nodes, enabling thus the information transmission in more than one path (Durresi, Zhang, Durresi, & Barolli, 2010). The path redundancy is a robust feature of this kind of topology. Compared to other topologies, mesh topology needs not a central node, allowing networks based on such topology to be self-healing. These characteristics of networks with mesh topology make them very reliable and robust networks (Behera & Tripathy, 2014) to potential server node failures. In WMNs mesh routers provide network connectivity services to mesh client nodes. The good performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical deployment area to achieve network connectivity, stability
and user coverage. The objective is to find an optimal and robust topology of the mesh router nodes to support connectivity services to clients. For most formulations, node placement problems are shown to be computationally hard to solve to optimality (Garey & Johnson, 1979; Lim, Rodrigues, Wang & Xua, 2005; Amaldi, Capone, Cesana, Filippini, Malucelli, 2008; Wang, Xie, Cai & Agrawal, 2007), and therefore heuristic and meta-heuristic approaches are useful approaches to solve the problem for practical purposes. Several heuristic approaches are found in the literature for node placement problems in WMNs (Muthaiah & Rosenberg, 2008; Zhou, Manoj & Rao, 2007; M. Tang, 2009; Antony Franklin & Siva Ram Murthy, 2007; Vanhatupa, Hannikainen & Hamalainen, 2007). In our previous work (Xhafa, Sanchez, Barolli & Miho, 2010; Sakamoto, Kulla, Oda, Ikeda, Barolli & Xhafa, 2014), we implemented a simulation system using Simulated Annealing (SA) for WMNs. We call this simulation system WMN-SA. In this work, we applied our implemented WMN-SA system in a realistic scenario considering the distribution of mesh clients in Itoshima City, Fukuoka Prefecture, Japan. For simulations, we consider a realistic distributions of 108 mesh clients in Itoshima city. Then, we deployed 36 mesh routers and run WMN-SA simulation system to maximize the size of Giant Component (GC) and Number of Covered Mesh Clients (NCMC). The rest of the paper is organized as follows. In the next section, we present the definition of node placement problem. Then, we describe the proposed and implemented WMN-SA simulation system. After that, we present the simulation results. Finally, we give concluding remarks and future work.
NODE PLACEMENT PROBLEM IN WMNS In this problem, we are given a grid area arranged in cells where to distribute a number of mesh router nodes and a number of mesh
Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
7 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/article/application-of-wmn-sa-simulationsystem-for-node-placement-in-wireless-meshnetworks/128997?camid=4v1
This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Communications and Social Science. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2
Related Content Robust Algorithms for DOA Estimation and Adaptive Beamforming in Wireless Mobile Communications R.M. Shubair, K.O. AlMidfa, A. Al-Marri and M. Al-Nuaimi (2009). Mobile Computing: Concepts, Methodologies, Tools, and Applications (pp. 558-564).
www.igi-global.com/chapter/robust-algorithms-doa-estimationadaptive/26530?camid=4v1a Establishing A Personalized Information Security Culture Shuhaili Talib, Nathan L. Clarke and Steven M. Furnell (2011). International Journal of Mobile Computing and Multimedia Communications (pp. 63-79).
www.igi-global.com/article/establishing-personalized-information-securityculture/51662?camid=4v1a Primary Research on Arabic Visemes, Analysis in Space, and Frequency Domain Fatma Zohra Chelali and Amar Djeradi (2013). Contemporary Challenges and Solutions for Mobile and Multimedia Technologies (pp. 319-337).
www.igi-global.com/chapter/primary-research-arabic-visemesanalysis/70824?camid=4v1a
Towards Scalable Certificate Status Validation in Mobile Ad Hoc Networks Mohammad Masdari, Javad Pashaei Barbin and Moazam Bidaki (2013). International Journal of Mobile Computing and Multimedia Communications (pp. 35-48).
www.igi-global.com/article/towards-scalable-certificate-status-validation-inmobile-ad-hoc-networks/103968?camid=4v1a
