Efficient Packet Forwarding in Mesh Network

Wireless mesh networks (WMNs) have emerged as a scalable, reliable, and agile wireless network that supports many types of innovative technologies such as the Internet of Things (IoT), Wireless Sensor Networks (WSN), and Internet of Vehicles (IoV). Due to the limited number of orthogonal channels, interference between channels adversely affects the fair distribution of bandwidth among mesh clients, causing node starvation in terms of insufficient bandwidth distribution, which impedes the adoption of WMN as an efficient access technology. Therefore, a fair channel assignment is crucial for the mesh clients to utilize the available resources. However, the node starvation problem due to unfair channel distribution has been vastly overlooked during channel assignment by the extant research. Instead, existing channel assignment algorithms equally distribute the interference reduction on the links to achieve fairness which neither guarantees a fair distribution of the network bandwidth nor eliminates node starvation. In addition, the metaheuristic-based solutions such as genetic algorithm, which is commonly used for WMN, use randomness in creating initial population and selecting the new generation usually leading the search to local minima. To this end, this study proposes a Fairness-Oriented Semichaotic Genetic Algorithm-Based Channel Assignment Technique (FA-SCGA-CAA) to solve node starvation problem in wireless mesh networks. FA-SCGA-CAA maximizes link fairness while minimizing link interference using a genetic algorithm (GA) with a novel nonlinear fairness-oriented fitness function. The primary chromosome with powerful genes is created based on multicriterion links ranking channel assignment algorithm. Such a chromosome was used with a proposed semichaotic technique to create a strong population that directs the search towards the global minima effectively and efficiently. The proposed semichaotic technique was also used during the mutation and parent selection of the new genes. Extensive experiments were conducted to evaluate the proposed algorithm. A comparison with related work shows that the proposed FA-SCGA-CAA reduced the potential node starvation by 22% and improved network capacity utilization by 23%. It can be concluded that the proposed FA-SCGA-CAA is reliable to maintain high node-level fairness while maximizing the utilization of the network resources, which is the ultimate goal of many wireless networks.

Wireless Mesh Networks (WMNs) are gaining a lot of attention from researchers due to their advantages such as easy maintenance, low upfront cost and high robustness. Connectivity and stability directly affect the performance of WMNs. However, WMNs have some problems such as node placement problem, hidden terminal problem and so on. In our previous work, we implemented a simulation system to solve the node placement problem in WMNs considering Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA), called WMN-PSODGA. In this paper, we compare chi-square and uniform distributions of mesh clients for different router replacement methods. The router replacement methods considered are Constriction Method (CM), Random Inertia Weight Method (RIWM), Linearly Decreasing Inertia Weight Method (LDIWM), Linearly Decreasing Vmax Method (LDVM) and Rational Decrement of Vmax Method (RDVM). The simulation results show that for chi-square distribution the mesh routers cover all mesh clients for all router replacement methods. In terms of load balancing, the method that achieves the best performance is RDVM. When using the uniform distribution, the mesh routers do not cover all mesh clients, but this distribution shows good load balancing for four router replacement methods, with RIWM showing the best performance. The only method that shows poor performance for this distribution is LDIWM. However, since not all mesh clients are covered when using uniform distribution, the best scenario is chi-square distribution of mesh clients with RDVM as a router replacement method.

Wireless Mesh Network (WMN) is recently emerged network having robustness. It supports clients to communicate with different types of networks, Internet etc which provides a better service to next generation. It consists of mesh routers and mesh clients. These mesh routers are minimal mobile and mesh clients are totally mobile. The protocols of Ad hoc network are used in WMN. These protocols assume that every node is mobile. But as the mesh routers are minimal mobile or not mobile, the protocols brings overhead for the mesh routers. Our task is to relieve mesh routers using ad hoc network protocol from the overhead and define a better protocol which will fit in WMN efficiently. To do so, we've found that the existing architecture of WMN is needed to be changed slightly. We have proposed a new architecture for Wireless Mesh Network. In our proposal WMN is relieved from overhead being caused by using ad hoc network protocol. Our architecture use unicasting technique in lieu of broadcasting technique for route discovery as well as route maintenance. We will first describe the overview of WMN, its existing architecture. Later we will go to our proposed architecture.

We consider the channel assignment problem in wireless mesh networks. Due to the limited number of radio interfaces that each node is equipped with, channel assignment must ensure that the interface constraint is obeyed, i.e., the number of different channels assigned to the links incident on a node must be no greater than the number of interfaces the node is equipped with. However, interface constraint may be one of the causes that hinder the performance of some of the existing heuristics. In this paper, we use simulated annealing to solve the channel assignment problem in wireless mesh networks. We propose two neighbor generating approaches that handle the interface constraint in different ways. The first approach starts with an infeasible random solution, and by using the penalty function technique the solution finally converges to a feasible one. The second approach, on the contrary, allows only feasible solutions to be generated during the simulated annealing process. Simulations are conducted that compare our proposed simulated annealing algorithms together with a tabu-based algorithm under different network traffic scenarios. The results show that our algorithms exhibit lower network interference than the tabu-based algorithm.

Wireless Mesh Networks (WMNs) have recently emerged as a technology for next-generation wireless networking. WMNs partially replace wired backbone networks, and it is therefore reasonable to plan carefully radio resource assignment to provide quality guarantees to traffic flows. Directional transmissions allow to reduce radio interference, thus exploiting spatial reuse. Therefore, as a main contribution, in this paper we study the joint routing and scheduling optimization problem in Wireless Mesh Networks where nodes are equipped with directional antennas. To this aim, we assume a Spatial reuse Time Division Multiple Access (STDMA) scheme, a dynamic power control able to vary the emitted power slot-by-slot, and a rate adaptation mechanism that sets transmission rates according to the Signal- to-Interference-and-Noise Ratio (SINR). We provide column generation-based heuristic approaches for the proposed models in a set of realistic-size instances and discuss the impact of different parameters on the network performance. The results show that our schemes increase considerably the total traffic accepted by the network, providing bounds to the achievable performance.

With the emergence of wireless networking paradigm, several optimization problems are appearing in such networks. Such problem are related to optimizing network connectivity, coverage and stability. The resolution of these problems turns out to be crucial for optimized network performance. In the case of Wireless Mesh Networks, such problems include computing placement of mesh router nodes so that network performance is optimized. However, as these optimization problems are known to be computationally hard to solve, Genetic Algorithms (GAs) have been recently investigated as effective resolution methods. Mutation operator is one of the GA ingredients. Unlike crossover operators, which achieve to transmit genetic information from parents to off springs, mutation operators usually make some small local perturbation of the individuals, having thus less impact on individuals. Moreover, crossover is "a must" operator in GA and is usually applied with high probability, while mutation operators when implemented, are applied with small probability. Due to this, mutation operator is usually considered as a secondary operator. However, many studies in the literature have shown that mutation when effectively combined with selection operators can improve the performance of GAs. In this work we present the results of an experimental study on the effect of mutation and selection operators in GA for mesh router nodes placement problem. The study aims to identify the mutation and selection types that work best for instances of different characteristics.

Over the past few years, wireless mesh networks (WMNs) have emerged to become a ubiquitous solution for providing wireless access at lower cost, greater flexibility, higher reliability and performance compared to conventional wireless local area network (WLANs). As the demand for delay sensitive real-time applications such as VOIP and streaming media grows, mobility management is becoming a critical function of WMN. Although Mobility management schemes designed for Mobile Ad Hoc Networks (MANETs) and traditional fixed networks might be useful for WMNs, mobility management in WMNs is still an active research issue because of the special properties of WMNs. This chapter focuses on the mobility management in wireless mesh networks, which takes into account the unreliability of wireless mesh links and other special properties of WMNs. The chapter began by discussing the special properties of WMNs and the general concepts of mobility management, and then gives an overview of the mobility management problems in wireless mesh networks (layer 2 handoff, vertical handoff and cross layer design, etc.) with some potential solutions.

Cognitive Radio (CR) technology constitutes a promising approach to increase the capacity of Wireless Mesh Networks (WMNs). Using this technology, Mesh Routers (MRs) and the attached Mesh Clients (MCs) are allowed to opportunis- tically transmit on the licensed band, but under the constraint not to interfere with the Primary Users (PUs) of the spectrum. Thus, the effective deployment of CR- WMNs require that each MR must be able to: sense the current spectrum, select an available PU-free channel and perform the spectrum handoff to a new channel in case of PU arrival on the current one. How to coordinate these actions in the optimal way which maximizes the performance of the CR-WMNs while minimizing the interference to the PUs constitutes an open research issue in CR systems. In this paper, we propose an adaptive spectrum scheduling and allocation scheme which allows a MR to identify the best schedule of (i) when to sense the current channel, (ii) when to transmit, (iii) when to perform a spectrum handoff. Due the large number of parameters involved, we propose Reinforcement Learning (RL) techniques to allow a MR to learn by itself the optimal balance between spectrum sensing-exploitation- exploration actions based on network feedbacks coming from the MCs. We perform extensive simulations which confirm the adaptivity and efficiency of our approach in terms of increased throughput when compared with non-learning based schemes for CR-WMNs.

A multi-radio Wireless Mesh Network (WMN) is a multi-hop network that consists of mesh routers and mesh clients, where mesh routers are equipped with multiple radio interfaces and form the backbone of the mesh network. To provide backbone support, it is necessary to reduce interference and balance load in Wireless Mesh Networks (WMNs). We propose load-aware routing metric (LARM), which captures the difference in transmission rates, packet loss ratio, intra/inter-flow interference and traffic load in multi-radio mesh networks. The LARM metric helps finding paths that are better in terms of balancing load and reducing the inter-flow and intra-flow interference in multi-radio networks. Simulation results show that LARM metric significantly outperforms several existing routing metrics in multi-radio wireless mesh networks.

Implementation of a Cuckoo Search intelligent simulation system for node placement problem in Wireless Mesh Networks: Performance evaluation for tuning hyperparameters [formula omitted] and [formula omitted]

An infrastructure wireless mesh network (WMN) is a hierarchical network consisting of mesh clients, mesh routers and gateways. Mesh routers constitute a wireless mesh backbone, to which mesh clients are connected as a star topology, and gateways are chosen among mesh routers providing Internet access. In this paper, the throughput capacity of infrastructure WMNs is studied. For such a network with Nc randomly distributed mesh clients, Nr regularly placed mesh routers and Ng gateways, assuming that each mesh router can transmit at W bits/s, the per-client throughput capacity has been derived as a function of Nc , Nr , Ng and W . The result illustrates that, in order to achieve high capacity performance, the number of mesh routers and the number of gateways must be properly chosen. It also reveals that an infrastructure WMN can achieve the same asymptotic throughput capacity as that of a hybrid ad hoc network by choosing only a small number of mesh routers as gateways. This property makes WMNs a very promising solution for future wireless networking.

QoS routing problem in wireless mesh networks is a NP-complete problem, and it is hard to get the global solution with the traditional algorithm. In this paper, we adopt a novel dynamic ant genetic hybrid algorithm to solve QoS unicast routing problem for wireless mesh network, whose innovation are using the best melting point evaluation strategy to control the calling of the two algorithms dynamically. Simulation results show that the novel algorithm is superior to the genetic algorithm and the static ant genetic hybrid algorithm in quality and efficiency for QoS routing in wireless mesh network.

The wireless mesh network is emerging as a promising technology in providing economical and scalable broadband Internet accesses to communities. The backbone of the wireless mesh network consists of mesh routers, which connect each other in an ad hoc manner via wireless links. The presence of backbone mesh routers and utilization of multiple channels and interfaces allow the wireless mesh network to have better capacity than that of the infrastructure-free ad hoc network formed by mesh clients directly. A special type of the mesh routers, referred to as gateway nodes, is capable of Internet connection, and other mesh routers and associated terminal clients have to access the Internet through the gateway nodes. In this paper, we present the analytically traceable stochastic models to characterize the average delay and throughput performance in wireless mesh networks. We model the forwarding mesh routers as an open queuing network. The analytical model takes into account the mesh router density, the random packet arrival process, the degree of locality of traffic and the collision avoidance mechanism of the IEEE802.11 DCF random access MAC. Our simulation results suggest that the analytical results are quite accurate, which can provide valuable insights in system performance and an effective guideline for the scalable design and optimization in wireless mesh networks.

Current works on the joint routing and channel assignment (JRC) problem in wireless mesh networks (WMNs) assume that all links operate at the base rate. In other words, they do not consider the presence of multiple bit-rates. However, in multi-rate WMNs, the achievable throughput of a link operating at higher rates could be much less than its bit-rate when it has to contend with low-rate links. This is also known as the multirate sharing problem. To address the problem, we first present a numerical formulation for estimating the dynamic link capacity, which can indicate the degree of the multi-rate sharing problem. Next, we propose an optimization model called MR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C, which solves the JRC problem by considering the dynamic link capacity in order to maximize the throughput in multi-rate, multi-radio, multi-channel WMNs. We then reformulate the primal problem as a Lagrangian dual problem, and apply the subgradient method to approach the dual. Finally, since each subproblem in the dual problem is also a non-linear problem, we design a polynomialtime algorithm to solve it. Our experiment results demonstrate that the proposed capacity formulation can approximate the actual link throughput. We compare MR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C with the base-rate JRC model via simulations. The results show that MR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C achieves throughput gains of 3-4 times and recover from network failure efficiently.

The paper presents an analysis of perceived quality of service (PQoS) as an objective function for network management. It provides a formulation of the problem a method for preserving PQoS wireless mesh network subscribers and suggests an algorithmic solution of the formulated problem in wireless mesh networks with centralized control.