Identifying Design Requirements for Wireless Routing Link Metrics

In this paper, we identify and analyze the requirements to design a new routing link metric for wireless multihop networks. Considering these requirements, when a link metric is proposed, then both the design and implementation of the link metric with a routing protocol become easy. Secondly, the underlying network issues can easily be tackled. Thirdly, an appreciable performance of the network is guaranteed. Along with the existing implementation of three link metrics Expected Transmission Count (ETX), Minimum Delay (MD), and Minimum Loss (ML), we implement inverse ETX; invETX with Optimized Link State Routing (OLSR) using NS-2.34. The simulation results show that how the computational burden of a metric degrades the performance of the respective protocol and how a metric has to trade-off between different performance parameters

Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using simulated annealing

This is the post-print version of the article - Copyright @ 2008 Springer-VerlagThis paper proposes a simulated annealing (SA) algorithm based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. In the proposed SA multicast algorithm, the path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we anticipate the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the annealing process are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed SA based multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using tabu search

Copyright @ 2009 IEEE Computer SocietyThis paper proposes a tabu search (TS) based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the tabu search procedure are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed TS multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

A genetic-inspired joint multicast routing and channel assignment algorithm in wireless mesh networks

Copyright @ 2008 IEEEThis paper proposes a genetic algorithm (GA) based optimization approach to search a minimum-interference multicast tree which satis¯es the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented en- coding method is used and each chromosome is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. Crossover and mutation are well designed to adapt to the tree structure. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed GA based multicast algorithm achieves better performance in terms of both the total channel conflict and the tree cost than that of a well known algorithm

Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks

In this paper, we consider the joint opportunistic routing and channel assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks (CRNs) for improving aggregate throughput of the secondary users. We first present the nonlinear programming optimization model for this joint problem, taking into account the feature of CRNs-channel uncertainty. Then considering the queue state of a node, we propose a new scheme to select proper forwarding candidates for opportunistic routing. Furthermore, a new algorithm for calculating the forwarding probability of any packet at a node is proposed, which is used to calculate how many packets a forwarder should send, so that the duplicate transmission can be reduced compared with MAC-independent opportunistic routing & encoding (MORE) [11]. Our numerical results show that the proposed scheme performs significantly better that traditional routing and opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201

Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods

Copyright @ 2010 Elsevier B.V. All rights reserved.In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the channel assignment. Therefore they bear severe drawback, that is, channel assignment cannot work well with the determined multicast tree. In this paper, we integrate them together and solve it by intelligent computational methods. First, we develop a unified framework which consists of the problem formulation, the solution representation, the fitness function, and the channel assignment algorithm. Then, we propose three separate algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and tabu search). These three algorithms aim to search minimum-interference multicast trees which also satisfy the end-to-end delay constraint and optimize the usage of the scarce radio network resource in wireless mesh networks. To achieve this goal, the optimization techniques based on state of the art genetic algorithm and the techniques to control the annealing process and the tabu search procedure are well developed separately. Simulation results show that the proposed three intelligent computational methods based multicast algorithms all achieve better performance in terms of both the total channel conflict and the tree cost than those comparative references.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1