73 research outputs found

    Investigation of fitness function weight-coefficients for optimization in WMN-PSO simulation system

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    (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.With the fast development of wireless technologies, Wireless Mesh Networks (WMNs) are becoming an important networking infrastructure due to their low cost and increased high speed wireless Internet connectivity. In our previous work, we implemented a simulation system based on Particle Swam Optimization for solving node placement problem in wireless mesh networks, called WMN-PSO. In this paper, we use Size of Giant Component (SGC) and Number of Covered Mesh Clients (NCMC) as metrics for optimization. Then, we analyze effects of weight-coefficients for SGC and NCMC. From the simulation results, we found that the best values of the weight-coefficients for SGC and NCMC are 0.7 and 0.3, respectively.Peer ReviewedPostprint (author's final draft

    An annealing approach to router nodes placement problem in wireless mesh networks

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    Mesh router nodes placement is a central problem to Wireless Mesh Networks (WMNs). An efficient placement of mesh router nodes is indispensable for achieving network performance in terms of both network connectivity and user coverage. Unfortunately the problem is computationally hard to solve to optimality even for small deployment areas and a small number of mesh router nodes. As WMNs are becoming an important networking infrastructure for providing cost-efficient broadband wireless connectivity, researchers are paying attention to the resolution of the mesh router placement problem through heuristic approaches in order to achieve near optimal, yet high quality solutions in reasonable time. In this work we propose and evaluate a Simulated Annealing (SA) approach to placement of mesh router nodes in WMNs. The optimization model uses two maximization objectives, namely, the size of the giant component in the network and user coverage. Both objectives are important to deployment of WMNs; the former is crucial to achieve network connectivity while the later is an indicator of the QoS in WMNs. The SA approach distinguishes for its simplicity yet its policy of neighborhood exploration allows to reach promising areas of the solution space where quality solutions could be found. We have experimentally evaluated the SA algorithm through a benchmark of generated instances, varying from small to large size, and capturing different characteristics of WMNs such as topological placements of mesh clients. The experimental results showed the efficiency of the annealing approach for the placement of mesh router nodes in WMNs.Peer ReviewedPostprint (published version

    Efficient and robust routing of highly variable traffic

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006.Includes bibliographical references (p. 316-324).Many emerging applications for the Internet are characterized by highly variable traffic behavior over time that is difficult to predict. Classical approaches to network design rely on a model in which a single traffic matrix is estimated. When actual traffic does not conform to such assumptions, desired bandwidth guarantees cannot be provided to the carried traffic. Currently, Internet Service Providers (ISPs) use gross capacity over-provisioning and manual routing adaptation to avoid network congestion caused by unpredictable traffic. These lead to increased network equipment and operational costs. Development of routing infrastructures that optimize network resources while accommodating extreme traffic unpredictability in a robust and efficient manner will be one of the defining themes in the next phase of expansion of the Internet. This thesis proposes two-phase routing as a capacity efficient and robust strategy for handling highly variable traffic. The scheme allows preconfiguration of the network such that all traffic patterns permissible within the network's natural ingress-egress capacity constraints can be routed with bandwidth guarantees without requiring detection of traffic changes in real-time or reconfiguring the network in response to it.(cont.) The scheme routes traffic in two phases -- traffic entering the network is sent from the source to a set of intermediate nodes in predetermined split ratios that depend on the intermediate nodes, and then from the intermediate nodes to the final destination. The scheme has the desirable properties of supporting static optical layer provisioning in IP-over-Optical networks and indirection in specialized service overlay models unlike previous approaches -- like direct source-destination path routing - for handling variable traffic. This thesis represents the first comprehensive study, problem formulation, and algorithm design for many aspects of two-phase routing. Our contributions can be grouped into three broad parts. First, we consider the problems of minimum cost network design and maximum throughput network routing for the scheme. We give a simple solution for minimum cost network design. For maximum throughput network routing. we design linear program.ling based and combinatorial algorithms. We show how the algorithms can handle a total cost constraint for maximum throughput two-phase routing. This can be used to solve the link capacitate version of minimum cost two-phase routing.(cont.) We establish theoretical bounds on the resource requirements of two-phase routing under throughput and cost models with respect to the optimal scheme that is allowed to make the routing dynamically dependent on the current traffic matrix. We also generalize the traffic split ratios to depend not only on the intermediate nodes but also on source and destination of traffic and solve the corresponding optimization problems. Second, we consider making two-phase routing resilient to network failures. Two-phase routing in IP-over-Optical networks can be protected against router node failures through redistribution of traffic split ratio for the failed router node to other intermediate nodes. We propose two different schemes for provisioning the optical layer to handle router node failures. We develop linear programming formulations for both schemes and a fast combinatorial algorithm for the second scheme so as to maximize network throughput. Two-phase routing can be made resilient against link failures by protecting the first and second phase paths using pre-provisioned restoration mechanisms. We consider three such restoration mechanisms - local (link/span) restoration, K-route path restoration, and shared backup path restoration.(cont.) We provide linear programming formulations and combinatorial algorithms for maximum throughput two-phase routing with local restoration and K-route path restoration. We show that the problem of maximum throughput two-phase routing with shared backup path restoration is JVP-hard. Assuming an approximation oracle for a certain disjoint paths problem (which we also show to be AP-hard), we design a combinatorial algorithm with provable guarantees. Third, we consider the application of two-phase routing to multi-hop Wireless Mesh Networks (WMNs). These networks have recently been of much research interest due to their lowered need for wired infrastructure support and due to envisaged new applications like community wireless networks. We extend our optimization framework for maximum throughput two-phase routing in wired networks to handle routing and scheduling constraints that are peculiar to WMNs and arise from the requirement to handle radio transmit/receive diversity and the phenomenon of wireless link interference. We evaluate various aspects of two-phase routing on actual ISP topologies using the developed algorithms. For the WMN application, we use randomly generated WMN topologies for the evaluations.by Sudipta Sengupta.Ph.D
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