Channel Assignment In Wireless Mesh Networks Research Articles

A hybrid framework for routing and channel assignment in WMN’s

Wireless mesh network (WMNs) can replace the physical existence of wired network; nevertheless, to solve the problem of traffic and congestion, they must carefully arrange radio resource assignment. In this paper, we focus on the major issues while transferring the data over the network and optimization of resources. WMN mainly suffers from congestion problem when numbers of channel transfer data at a same time which indirectly leads to overlapping channels and sometime data cannot be mitigated to destination. To overcome this problem and provide optimal solution we proposed hybrid channel assignment technique which offers four phase solution technique, in this technique firstly by mitigating the traffic than assigning the optimal path based on greedy and BFS. The purpose of this congestion control hybrid ant based greedy-BFS-load balancing (CCHAGBL) technique is to diminish the number of used slots, which is directly related to the overall resource assignment. We also provide optimal solution using Ant colony optimization technique with hybrid algorithm to achieve the network efficiency and resource utilization with randomly generated traffic. With the help of hybrid ant based greedy-BFS-load balancing (GBL) channel assignment algorithm throughput and packet delivery ratio is upgraded and delay is reduced to minimum.

A Particle Swarm and Clonal Selection Algorithm based Channel Assignment Algorithm in MRMC Wireless Mesh Network

Channel Assignment (CA) in MRMC Wireless Mesh Network (WMN) is an efficient device that exploits numerous non-intersecting channels to reduce the interference and augment the capability of WMN. However, CA could diminish the complete network interference; its consequences might cause certain design issues that impact the efficiency of the network. A good CA in wireless mesh networks could minimize numerous interference co-channels and enhance the throughput. The clonal selection approach is simulated using the rudimentary notion of adaptive immune reply to virus stimulus. The PSO is inspired using the social behaviors of swarms. Motivated by these two optimization methodologies, in this paper, a hybridized particle swarm aided clonal selection approach is introduced for resolving channel assignment issue, i.e., evaluating a lower-interference channel assignment depending on gathered data. Conflict Vector in Conflict Graph known as antigens in clonal selection algorithm having fewer affinity values are improved using the particle swarm optimization update operation. Then the clonal selection and mutation operation is employed iteratively to generate the optimum conflict vectors. The experimental results are carried out using NS2. From the outcomes, it is clearly shown that the suggested approach has better energy efficiency, packet delivery ratio, and less network delay, packet drop compared to existing algorithms.

SeCA: A framework for Secure Channel Assignment in wireless mesh networks

To maximize the available throughput in multi-channel multi-radio wireless mesh networks (WMNs), it is a critical issue to design a channel assignment scheme efficiently utilizing orthogonal channels. However, most channel assignment schemes are vulnerable to the misbehaviors of nodes participating in channel assignment, and existing secure channel assignment schemes do not address all of the vulnerabilities. In this paper, we address the threats to channel assignment in WMNs resulting from node misbehaviors and present a generic verification framework to detect such misbehaviors. We develop a concrete verification scheme based on this framework and an existing distributed channel assignment scheme. We validate our approach by implementing the verification scheme and evaluating it through simulation. The results show that our approach improves misbehavior detection with minimum performance overhead.