Optimization In Wireless Mesh Networks Research Articles

A Delaunay Edges and Simulated Annealing-Based Integrated Approach for Mesh Router Placement Optimization in Wireless Mesh Networks.

Wireless Mesh Networks (WMNs) can build a communications infrastructure using only routers (called mesh routers), making it possible to form networks over a wide area at low cost. The mesh routers cover clients (called mesh clients), allowing mesh clients to communicate with different nodes. Since the communication performance of WMNs is affected by the position of mesh routers, the communication performance can be improved by optimizing the mesh router placement. In this paper, we present a Coverage Construction Method (CCM) that optimizes mesh router placement. In addition, we propose an integrated optimization approach that combine Simulated Annealing (SA) and Delaunay Edges (DE) in CCM to improve the performance of mesh router placement optimization. The proposed approach can build and provide a communication infrastructure by WMNs in disaster environments. We consider a real scenario for the placement of mesh clients in an evacuation area of Kurashiki City, Japan. From the simulation results, we found that the proposed approach can optimize the placement of mesh routers in order to cover all mesh clients in the evacuation area. Additionally, the DECCM-based SA approach covers more mesh clients than the CCM-based SA approach on average and can improve network connectivity of WMNs.

Multi-Objective Routing Optimization for 6G Communication Networks Using a Quantum Approximate Optimization Algorithm.

Sixth-generation wireless (6G) technology has been focused on in the wireless research community. Global coverage, massive spectrum usage, complex new applications, and strong security are among the new paradigms introduced by 6G. However, realizing such features may require computation capabilities transcending those of present (classical) computers. Large technology companies are already exploring quantum computers, which could be adopted as potential technological enablers for 6G. This is a promising avenue to explore because quantum computers exploit the properties of quantum states to perform certain computations significantly faster than classical computers. This paper focuses on routing optimization in wireless mesh networks using quantum computers, explicitly applying the quantum approximate optimization algorithm (QAOA). Single-objective and multi-objective examples are presented as robust candidates for the application of quantum machine learning. Moreover, a discussion about quantum supremacy estimation for this problem is provided.

SR-WMN: Online Network Throughput Optimization in Wireless Mesh Networks With Segment Routing

In this letter, we for the first time introduce segment routing (SR) to wireless mesh networks (WMNs) under the primary interference model, and try to obtain the upper bound of maximum network throughput from an online routing perspective. We first propose an SR-enabled WMN (SR-WMN) architecture. We then develop an online primal-dual algorithm with guaranteed worst case performance bound. We finally show via simulation that the proposed solution tends to be close to the optimum by configuring just over half of the wireless mesh routers (WMRs) to support SR.

Deployment optimization of wireless mesh networks in wind turbine condition monitoring system

This study aims to propose a deployment optimization method based on IEEE 802.11 heterogeneous wireless mesh networks (WMNs) for the condition monitoring system (CMS) of wind turbines. This method can provide a flexible, low-cost, and easy-to-implement network framework for wind farms in harsh environments, thereby avoiding interference of the newly installed CMS on the communication network of the SCADA system. The K-medoids clustering algorithm transforms the continuous space location problem into the discrete space location problem. Moreover, the mesh client (MC) coverage and backbone network connectivity issues are considered to ensure that the generated candidate point set can meet the coverage and connectivity requirements without generating numerous redundant nodes. Firstly, according to the characteristics of the model, the K-medoids clustering algorithm is used to obtain a set of candidate points of mesh routers (MRs) that meet the coverage rate. Secondly, a reasonable connection algorithm is proposed according to the constraints, and the optimal deployment is selected from the candidate points. Thirdly, taking the number of hops from MR to MG and the priority of MC as the weight. The path planning with the least number of MRs and load balancing is obtained by constructing a minimum spanning tree (MST) based on the improved Kruskal algorithm. Finally, Multi-channel inter-frequency networking technology is adopted to reduce interference between co-channels and between adjacent channels. The result shows that the method proposed can minimize network operating costs, meet the capacity requirements of MC, and reduce link losses.

On Demand Stable Routing with Channel Allocation and Backoff Countdown Optimization in Wireless Mesh Networks

The multi-channel and multi-interface wireless mesh networks (WMNs) allow multiple orthogonal channels simultaneously to facilitate increased broadband connectivity to the end-users. Many efforts have been devoted to allocate the channels to the interfaces in a multi-channel multi-interface setting. Recently, the hybrid channel allocation mechanism jointly optimizes the routing and channel assignment, by utilizing the queuing traffic. It is essential to map the optimization of traffic distribution on each channel along with channel switching in such an order that it adapts to the changing traffic. However, the contention in medium access and channel switching delay are the key issues in a multi-channel hidden terminal problem. The proposed optimized stable path- channel allocation and routing (OSCAR) protocol is a hybrid multi-channel protocol that reduces the communication delay without degrading the network performance. The proposed work, OSCAR determines a highly stable path that increases mesh routers to improve the routing efficiency. The channel allocation mechanism mainly promotes queue dynamics based probabilistic channel selection (QDPCS), and backoff countdown optimization (BCO). An essential component of the QDPCS scheme is the factor of queuing utilization, and this strategy selects a least congested channel. The BCO mechanism creates the logical order among contending nodes based on the remaining backoff value. It reduces the medium access delay and enables the feasibility of scheduled transmissions without degrading the network throughput. Finally, the performance evaluation results show that the OSCAR protocol outperforms the existing protocol over WMNs.

Threshold Accepting Heuristic for Fair Flow Optimization in Wireless Mesh Networks

Developing effective, fairness-preserving optimization algorithms is of considerable importance in systems which serve many users. In this paper we show the results of the threshold accepting procedure applied to extremely difficult problem of fair resource allocation in wireless mesh networks (WMN). The fairness is modeled by allowing preferences with regard to distribution of Internet traffic between network participants. As aggregation operator we utilize weighted ordered weighted averaging (WOWA). In the underlaying optimization problem, the physical medium properties cause strong interference among simultaneously operating node devices, leading to nonlinearities in the mixed-integer pricing subproblem. That is where the threshold accepting procedure is applied. We show that, the threshold accepting heuristic performs much better than the widely utilized simulated annealing algorithm.

Energy and Throughput Optimization of Wireless Mesh Networks With Continuous Power Control

Providing high data rates with minimum energy consumption is a crucial challenge for next generation wireless networks. There are few papers in the literature which combine these two issues. This paper focuses on multi-hop wireless mesh networks using a MAC layer based on Spatial Time Division Multiple Access (S-TDMA). We develop an optimization framework based on linear programming to study the relationship between throughput and energy consumption. Our contributions are two-fold. First, we formulate and solve, using column generation, a new MILP to compute offline energy-throughput tradeoff curve. We use a physical interference model where the nodes can perform continuous power control and can use a discrete set of data rates. Second, we highlight network engineering insights. We show, via numerical results, that power control and multi-rate functionalities allow optimal throughput to be reached, with lower energy consumption, using a mix of single hop and multi-hop routes.

On max–min fair flow optimization in wireless mesh networks

The paper is devoted to modeling wireless mesh networks (WMN) through mixed-integer programming (MIP) formulations that allow to precisely characterize the link data rate capacity and transmission scheduling using the notion of time slots. Such MIP models are formulated for several cases of the modulation and coding schemes (MCS) assignment. We present a general way of solving the max–min fairness (MMF) traffic objective for WMN using the formulated capacity models. Thus the paper combines WMN radio link modeling with a non-standard way of dealing with uncertain traffic, a combination that has not, to our knowledge, been treated so far by exact optimization models. We discuss several ways, including a method based on the so called compatible or independent sets, of solving the arising MIP problems. We also present an extensive numerical study that illustrates the running time efficiency of different solution approaches, and the influence of the MCS selection options and the number of time slots on traffic performance of a WMN. Exact joint optimization modeling of the WMN capacity and the MMF traffic objectives forms the main contribution of the paper.

Performance evaluation for on-demand routing protocols based on OPNET modules in wireless mesh networks

In wireless networks, users expect to get access to the network securely and seamlessly to share the data flow of access points anytime and anywhere. However, either point-to-point or point-to-multipoint methods in traditional wireless networks make the network bandwidth decrease rapidly, which cannot meet the requirements of users. Recently, a new wireless broadband access network, wireless mesh networks (WMNs), has emerged. As one of the key technologies in WMNs, wireless routing protocols plays an important role in performance optimization of WMNs. Therefore, in this paper, we address the on-demand routing protocols by focusing on dynamic source routing (DSR) protocol and ad hoc on-demand distance vector (AODV) routing protocol in WMNs. Then, we use the OPNET modules to establish the simulation models of DSR and AODV protocols in WMNs. Simulation and results show that, DSR protocol that is based on the dynamic source routing is not suitable for wireless transmission, while AODV routing protocol that is based on the purpose-driven routing is suitable for wireless transmission with rapid change of network topology.

Gateway Placement for Throughput Optimization in Wireless Mesh Networks

In this paper, we address the problem of gateway placement for throughput optimization in multi-hop wireless mesh networks. Assume that each mesh node in the mesh network has a traffic demand. Given the number of gateways to be deployed (denoted by k) and the interference model in the network, we study where to place exactly k gateways in the mesh network such that the total throughput is maximized while it also ensures a certain fairness among all mesh nodes. We propose a novel grid-based gateway deployment method using a cross-layer throughput optimization, and prove that the achieved throughput by our method is a constant times of the optimal. Simulation results demonstrate that our method can effectively exploit the available resources and perform much better than random and fixed deployment methods. In addition, the proposed method can also be extended to work with multi-channel and multi-radio mesh networks under different interference models.

Gateway Placement Optimization in Wireless Mesh Networks With QoS Constraints

In a wireless mesh network (WMN), the traffic is aggregated and forwarded towards the gateways. Strategically placing and connecting the gateways to the wired backbone is critical to the management and efficient operation of a WMN. In this paper, we address the problem of gateways placement, consisting in placing a minimum number of gateways such that quality-of-service (QoS) requirements are satisfied. We propose a polynomial time near-optimal algorithm which recursively computes minimum weighted Dominating Sets (DS), while consistently preserving QoS requirements across iterations. We evaluate the performance of our algorithm using both analysis and simulation, and show that it outperforms other alternative schemes by comparing the number of gateways placed in different scenarios