Joint Routing and Scheduling in Wireless Mesh Networks based on Traffic Prediction Using ARIMA

This paper considers the channel-assignment and scheduling in wireless mesh networks that employ multiple radios and multiple channels. In contrast to the various algorithms available in the literature, we explicitly model the delay overhead that is incurred during channel switching, and use that delay in the design of algorithms. We prove that the well known Greedy Maximal Scheduling (GMS) algorithm does not have any provable efficiency ratio when the switching overhead is considered. We present a centralized algorithm (CGSSO), and a dynamic algorithm (DMSSO), both of which consider switching overhead. Simulation results show that the proposed algorithms significantly outperform other algorithms in packet throughput and average packet delay metrics. Results also show that the improvements in performance become more pronounced as the switching delay increases.

Wireless mesh networks (WMN) is an budding technology that provides affluent assortment of applications that engross in future generation networking technologies. WMN is promising network habitually considered for its architecture due to its adaptability of its node. A node in WMN acts as a client and as well as a server processing hop by hop transmission. We minimize delay using Tabu search optimization and followed by traffic scheduling enhancing the quality of services in WMN. The simulation results prove our proposed work achieved in many quality of services.

Wireless technology is emerging as a key technology for the future networks. Wireless mesh networks (WMNs) have emerged as an indispensable technology for deployment of wireless services for various applications in personal, enterprise, and metropolitan areas. Researchers are working actively in different fields of WMNs for providing better services. Routing protocols play a vital role in WMNs to provide reliable configuration and maintenance of topology of the network. Designing a suitable cost metric for routing protocols to provide quality links for data transmission is the backbone of WMNs. Many cost metrics have been proposed for WMNs and is still an active research topic as new performance metrics need to be discovered due to the dynamics of this field. This paper considers the genetic algorithm-based routing technique for WMN.We have studied the existing cost metrics and proposed a genetic algorithm technique for routing in WMN. To evaluate the genetic algorithm, and to determine the relative performance of the genetic algorithm in the context of routing in WMN, we carry out experiments on two test systems. We have evaluated the quality of the results produced by our algorithm with the traditional hop count metric results. Our results show that routing in WMN using genetic algorithm produces better results as compared to traditional hop count metric results. Finally, we carry out a detailed analysis of results, which help us in gaining an insight into the suitability of genetic algorithm for routing in WMN.

In this paper, we address the problem of computing the transport capacity of Wireless Mesh Networks dedicated to Internet access. Routing and transmission scheduling have a major impact on the capacity provided to the clients. A cross-layer optimization of these problems allows the routing to take into account contentions due to radio interferences. We develop exact linear programs and provide an efficient column generation process computing a relaxation of the problem. It allows to work around the combinatoric of simultaneously achievable transmissions, hence computing solutions on large networks. Our approach is validated through extensive simulations. Evolution of the capacity of a mesh network with its parameters, as well as the algorithmic complexity are then discussed. We conjecture that the problem can be solved in polynomial time and that the gateway placement problem is only subject to localized constraints.

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.

Optimising multi-rate link scheduling for wireless mesh 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.

We consider the problem of centralized multihop scheduling in wireless mesh networks for solutions to realize intelligent transportation systems. A scheduling tree construction strategy is investigated, which could use any predetermined selection metrics, while avoiding primary and secondary interferences to a great extent. Two centralized multihop scheduling algorithms are presented to schedule nodes on the constructed scheduling tree. In contrast with FIFO algorithm, the fair algorithm has the property that it guarantees fairness among downlink relay queues of each relay node, while making an efficient utilization of free mini-slots. The feasibility of scheduling tree construction strategy with both minimal hop count and maximal signal strength metrics for a mesh cell is studied through experiment. Simulation results of network throughput and average active link number show that the Fair algorithm utilizes network resources more efficiently than the FIFO algorithm

Cognitive radio (CR) technology has been attracted as a solution for the frequency scarcity problem in the wireless mesh network which operates on multiple frequency bands (or channels). In this paper, we consider the channel assignment and routing in CR-based wireless mesh networks (CRWMNs). In the CRWMN, CR nodes access the channels without disturbing primary users (PUs) which have a privilege to access the channels. When a PU is activated on one of the operating channels of the CRWMN, the network should update the channel assignment and routing to protect the transmission of the PU. This update, called joint channel assignment and routing update (JCAR-update), causes large signaling overhead in the CRWMN. To reduce such signaling overhead, we propose a two-step JCAR-update scheme. In the first step, each CR node tries to perform a simple recovery algorithm in a distributed way. The recovery algorithm is to reassign channels to affected links without exchanging control information. In the second step, only if the recovery fails, the CRWMN re-optimizes the channel assignment and routing. Simulation results show that the proposed scheme reduces the signaling overhead and supports stable operation in CRWMNs.

Joint routing and scheduling in multi-Tx/Rx wireless mesh networks with random demands

This paper introduces danger theory in artificial immune system as a method of responding to danger in wireless mesh networks. It identifies the challenges in deploying Wireless Mesh networks (WMNs) and focus on secure routing as one of the key challenges in deploying WMNs. In order to implement a secure routing system, various Artificial Immune System (AIS) models were analysed. These models have been used in Intrusion Detection System (IDS) and computer security in the literature. In this paper, the authors propose to use Danger models to secure routing in WMNs. The first step in secure routing process is to identify and classify the network dangers and take necessary actions to overcome those dangers. For the classification task, we apply Self-organizing Maps (SOMs) as the classifier to classify the danger levels in WMNs. These identified danger conditions are further deployed as the warning signals for the design of secure routing protocol. The experimental results validate the proposal of applying the Danger Theory (DT) into security area and good performance is also reported by the use of Artificial Neural Network (ANN) classifier.

Voice over IP (VoIP) over a wireless mesh network (WMN) is a killer application candidate of the next generation services over wireless and mobile network infrastructure. Yet, the routing and transport efficiencies in consideration of specific attributes of WMNs have been little emphasized. Distinctively from conventional networks, the major traffic pattern of WMNs is anycast (one-to-one-of-many). To fully utilize the service aspects of WMNs, load balancing and scalability should simultaneously be supported. For VoIP, one challenge is to maintain the perceived quality depending on both loss and delay. In this paper, we assess autonomous load balancing anycast routing regarding VoIP supportability. The protocol is based on physics analogy and a distributed algorithm. We compare the protocol with shortest-path routing and back-pressure routing via simulations. Simulation results exhibit that autonomous load balancing of the protocol efficiently supports voice calls to guarantee the certain level of quality.

The ultimate goal of routing in wireless mesh networks (WMNs) is to find the “good” paths between the source and destination. Considering of the characteristics of this new networking paradigm, such as low mobility and less restriction from the energy effect, the focus is on the design and optimization of the technology to establish the path that can reflect this network feature. In this paper, an efficient routing algorithm is proposed based on decision-making sequence in WMNs, and the routing process is mapped into multi-stage decision process. We construct a mathematical model for it and present a multi-decision sequential routing method taking use of the idea of dynamic programming. In addition, a new metric (EEDT) for routing based on the information of MAC layer in WMNs is given, which optimized the two objectives- end to end delay and throughput. In the end, the multi-decision sequential routing algorithm (MDSR) is proposed that synthesized the suggesting method and new metric. The path selected by MDSR would be better based on the mathematical model, and it has lower delay of routing building. At the same time, EEDT can accurately capture the quality of the network links. Simulation results show that the proposed routing algorithm significantly improves the performance of the WMNs in terms of end-to-end delay and throughput.

Wireless mesh networks (WMN) possess characteristics such as self-healing, self-configuring and self-discovery. Due to this nature WMN has emerged as the most widely used popular network. Since these devices are operated using battery resources, several works have been carried out for minimizing energy consumption during routing process, thereby increasing network lifetime. WMNs are more vulnerable for attackers due to its wide usage. Many works can be found to detect the intruder during routing without considering energy as a metric. There exist possibilities of intruder to attack the battery resource thereby reducing network efficiency in energy-aware routing. Hence in this work we propose a novel approach to detect an intruder by self-monitoring mechanism of node considering metrics such as packet size, data rate, remaining energy and draining rate of a energy resources of a node. The proposed model consists of three modules, namely self-intrusion detector, monitor and evaluator. It detects and helps in making decisions to participate in the network transmission. The working of the model is analyzed and shows that the proposed model detects intruder effectively, thereby resulting in increase of WMN efficiency.

The problem of scheduling and tree routing in WiMAX/802.16 based mesh networks were not defined in the standard and are thus subject to extensive research. In this paper, we consider the problem of joint routing and scheduling in 802.16-based wireless mesh network, with the objective of determining a minimum length schedule that satisfies a given (uplink/downlink) end-to-end traffic demand. Minimizing the schedule length amounts to maximizing the spectrum spatial reuse by concurrently transmitting on as many links as possible, which we refer to as a transmission configuration (a group of links that can simultaneously transmit without violating the signal-to-interferenceplus- noise ratio (SINR) requirement). Our model is referred to as maximum spatial reuse (MSR). Since there is an overwhelming number of possible transmission configurations to be assigned to time slots, we adopt the column generation technique to construct our MSR model. We present two formulations for modeling MSR, namely the link-based column generation (CGLink) formulation and the path-based column generation (CGPath) formulation. These two formulations differ mainly in the number of routing decision variables. Our experimental results indicate that the path-based formulation needs much less computational (CPU) time than the link-based formulation in order to determine the (same) optimized solution with the same spatial reuse gain.