Impact of interface constraint on channel assignment in wireless mesh networks

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.

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.

Wireless mesh networks (WMNs) have emerged as a promising technology for providing ubiquitous access to mobile users, and quick and easy extension of local area networks into a wide area. Channel assignment problem is proven to be an NP-complete problem in WMNs. This paper aims proposing a new method to solve channel assignment problem in multi-radio, multichannel wireless mesh networks for improving the quality of communications in the network. Here, a new hybrid state channel assignment method is employed. This paper proposes a Link-Layard Protocol and Learning Automata (LLLA) to achieve a smart method for suitable assignment. Simulation results show that the proposed algorithm has better results compared to AODV method. E.g., it reduces the packet drop considerably without degrading.

This paper addresses the throughput maximization problem in wireless mesh networks. For the case of cooperative access points, we present a negotiation-based throughput maximization algorithm which adjusts the operating channel and power level among access points automatically, from a game-theoretical perspective. We show that this algorithm converges to the optimal channel and power assignment which yields the maximum overall throughput with arbitrarily high probability. Moreover, we analyze the scenario where access points belong to different regulation entities and hence non-cooperative. The long- term behavior and corresponding performance are investigated and the analytical results are verified by simulations.

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.

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.

The wireless mesh network is a new emerging technology exploiting the advantages of multiple radios and multiple channels. In this paper we have studied the channel assignment problem which is to assign channels to links in the network, and aimed at minimizing the network interference so as to improve the network throughput. The channel assignment problem is proved to be NP-hard. In this paper, we have developed a new approach based on the particle swarm optimization (PSO) algorithm and a heuristic algorithm to solve channel assignment problem in multi-radio multi-channel wireless mesh networks. Meanwhile, the crossover operation is employed in the discrete particle swarm optimization (DPSO) algorithm to handle the discrete channel assignment problem. Experimental results have shown that the rate of interference in the DPSO algorithm descends by 67.67% compared with the Tabu-based algorithm when there are 12 channels and 5 radios. And the heuristic algorithm can also yield good solutions with good quality in both dense and sparse networks.

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.

Wireless Mesh Network (WMN) is a multi hop low cost, with easy maintenance robust network providing reliable service coverage. WMNs consist of mesh routers and mesh clients. In this architecture, while static mesh routers form the wireless backbone, mesh clients access the network through mesh routers as well as directly meshing with each other. Different from traditional wireless networks, WMN is dynamically self-organized and self-configured. In other words, the nodes in the mesh network automatically establish and maintain network connectivity. Over the years researchers have worked, to reduce the redundancy in broadcasting packet in the mesh network in the wireless domain for providing reliable service coverage, the source node deserves to broadcast or flood the control packets. The redundant control packet consumes the bandwidth of the wireless medium and significantly reduces the average throughput and consequently reduces the overall system performance. In this paper I study the optimization problem in Wireless Mesh Networks. We have proposed a novel approach to reduce the broadcast redundant packet in the wireless mesh network. Also we have shown, a novel procedure to forward the control packet to the destination nodes and efficiently minimize the transmitted control packet in the wireless mesh cloud , that covers the domain.

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]

In this paper we present a new cross-layer method for the routing problem in Wireless Mesh Networks taking into account the Quality of Service (QoS) with rate adaptation. Since different routing metrics play certain importance in the multihop routing, multiple objectives such as transmission delay, traffic load and bandwidth are incorporated to the routing metric. Meanwhile a new link-layer sensing technique enables the transmitter to acquire the current contention status with low overhead, and rate adaptation is considered in the routing discovery. Theoretical analysis and simulation results show that the proposed QoS-Aware HWMP has a better average end-to-end delay guarantees and bandwidth guarantees.

A key problem in wireless mesh networks is forwarding packets to/from one or more gateways with connectivity to the Internet. In this respect, a short link schedule, which determines the transmission time of links, is critical. To date, existing link schedulers do not consider routers that incorporate advances in multiple input multiple output communications, i.e., interference cancellation and spatial multiplexing. In particular, these routers are able to transmit or receive distinct packets on all their links concurrently as well as deliver multiple packets to a neighbor simultaneously. To this end, we consider the problem of deriving a time division multiple access schedule that forwards packets to their respective destination quickly. We first consider the personalized broadcast problem, which assumes a single gateway and present Algo-PB, a solution that produces a schedule that is within 34.5% of the lower bound, and is 45.5% shorter than those computed by the state-of-the-art algorithms. We then extend the problem to consider multiple gateways. This so-called forest construction problem is modeled as an integer linear program (ILP). We then outline Algo-FC, a novel heuristic that generates a balanced forest by repeatedly picking a node from the heaviest tree and migrating it to another tree if doing so reduces the overall load. Experiment results show that the resulting forest generated by Algo-FC is within 9.1% of the ILP solution.

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.

Channel assignment problems in multi-radio wireless mesh networks (WMNs) have been shown to be NP-hard in various scenarios in the literature. By far, most of research efforts have focused on developing efficient approximation algorithms that run reasonably fast and provide good quality channel assignment rather than the optimal one. However, from the practical network design and deployment standpoint, engineers care more about whether it is feasible to optimally assign channels in the simplest way (i.e., exhaustive search), as most of existing commercial WMNs are of small/medium scale. In this paper, we attempt to answer this practical question. We study the complexity of general channel assignment problems with certain basic and common properties. The results show that the complexity in terms of the number of different possible assignments is exponential in the number of wireless links. Furthermore, we estimate the theoretical runtime of determining the optimal channel assignment by exhaustive search and validate it through experiments. We show that, given certain computing power (e.g., an off-the-shelf notebook PC), it is feasible to optimally solve channel assignment problems in small-scale and medium-scale commercial multi-radio WMNs. In other words, approximation algorithms are not needed for most of current commercial WMNs.

Wireless Mesh Networks (WMNs) have many advantages such as low cost and increased high speed wireless Internet connectivity, therefore WMNs are becoming an important networking infrastructure. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on Simulated Annealing (SA) for solving node placement problem in WMNs, called WMN-SA. In this paper, we implement a hybrid simulation system based on PSO and SA, called WMN-PSOSA. We evaluate the performance of WMN-PSOSA by conducting computer simulations considering Exponential and Weibull distributions. Simulation results show that WMN-PSOSA performs better for Weibull distribution compared with the case of Exponential distribution.