Backbone Wireless Mesh Networks Research Articles

A load-balanced algorithm for Internet Gateway placement in Backbone Wireless Mesh Networks

The placement of Internet Gateways (IGWs) is crucial in designing Backbone Wireless Mesh Networks (BWMNs) as it establishes the connection between the BWMN and the wired backbone. Efficient placement ensures high-bandwidth network coverage and utilization of the BWMN architecture. Despite considerable research efforts devoted to the IGW placement problem in WMNs, further research is still needed to tackle IGW reduction, improve Quality of Service (QoS), and achieve load balancing among IGWs and Wireless Mesh Routers (WMRs). In this paper, we propose a Load-balanced Algorithm for IGW placement in BWMN to achieve high-bandwidth network coverage while satisfying QoS constraints. The algorithm distributes WMRs among IGWs based on their location and computation degree, considering the load balance between IGWs and WMRs in each cluster. Experimental results demonstrate that our algorithm outperforms existing algorithms in terms of the number of IGWs placed in various scenarios. Our algorithm achieves an impressive reduction of more than 20% in the number of IGWs required in small typologies, and the improvement further escalates in larger topologies. To accomplish this, we utilize the innovative IGW Reallocation() algorithm, which accurately calculates the load ratio for each WMR within each cluster, facilitating the selection of the most suitable WMR to be designated as the new IGW. Additionally, our algorithm effectively addresses traffic load balancing for both IGWs and the entire network system by skillfully leveraging the relay links and delay hops present within WMRs forming the clusters. The outcomes of our research conclusively demonstrate that our Load-balanced Algorithm significantly enhances IGW placement efficiency, network coverage, and traffic load balancing, leading to improved performance, scalability, and a noteworthy contribution to the design and optimization of BWMNs.

An efficient mesh router nodes placement in wireless mesh networks based on moth‐flame optimization algorithm

SummaryOne of the most challenging tasks is deploying a wireless mesh network backbone to achieve optimum client coverage. Previous research proposed a bi‐objective function and used a hierarchical or aggregate weighted sum method to find the best mesh router placement. In this work, to avoid the fragmented network scenarios generated by previous formulations, we suggest and evaluate a new objective function to maximize client coverage while simultaneously optimizing and maximizing network connectivity for optimal efficiency without requiring knowledge of the aggregation coefficient. In addition, we compare the performance of several recent meta‐heuristic algorithms: Moth‐Flame Optimization (MFO), Marine Predators Algorithm (MPA), Multi‐Verse Optimizer (MVO), Improved Grey Wolf Optimizer (IGWO), Salp Swarm Algorithm (SSA), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Harris Hawks Optimization (HHO), Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), and Slime Mould Algorithm (SMA). We empirically examined the performance of the proposed function using different settings. The results show that our proposed function provides higher client coverage and optimal network connectivity with less computation power. Also, compared to other optimization algorithms, the MFO algorithm gives higher coverage to clients while maintaining a fully connected network.

A Deep Learning-Based Routing Approach for Wireless Mesh Backbone Networks

Optimal routing decisions are key in communication network environments to minimize bottlenecks such as traffic congestion and limited bandwidth. Routing in wireless mesh backbone networks is the focus of this study given that they are popular particularly for providing broadband connectivity to a huge number of users accessing and transmitting multimedia data hence are susceptible to communication-oriented bottlenecks. Existing routing solutions are mainly optimistic approaches. These mainly depend on link states, distance and hop counts which present a routing generalization bottleneck especially in huge wireless mesh networks because it is difficult to get the entire footprint of the network. Simply put, it is very difficult to determine an optimal route in a huge wireless mesh network (WMN) with dynamic network conditions. Since deep learning has a strong generalization ability. In this paper, a deep learning-based routing approach is proposed with the goal of ensuring a defined optimal quality of service (QoS) in a WMN. In order to achieve the study purpose, a wireless mesh network simulation environment is built and a network data feature set is orchestrated to generate a data set used to train a Long short Term Memory (LSTM)-based deep learning model that estimates the route with the optimal QoS. The generated data set is validated by training other learning models including the Multilayer Perceptron (MLP), Logistic Regression (LR) and Random Forest (RF). Our results show that the routes selected by the LSTM-based model provides the best packet delivery ratio (PDR) and throughput. Our results further show that the learning models (MLP, LR, RF) also provide better PDR and throughput compared to the traditional Ad-hoc On-demand Distance Vector (AODV) routing protocol.

Optimized Reinforcement Learning Based Multipath Transfer Protocol in Wireless Mesh Network

Multiple radios working on different channels are used in Wireless Mesh Networks (WMNs) to improve network performance and reduce Energy Consumption (EC). Effective routing in Backbone WMNs is where each cross-section switch is well-organized with multiple Radio Interfaces (RI), and a subset of hubs is occupied as a gateway to the Internet. Most routing methods decrease the forward overheads by evolving one dimension, <i><i>e.g</i>.</i>, hop count and traffic proportion. With that idea, while considering these dimensions together, the complexity of the routing issue increases drastically. Consequently, an effective EC routing method considers a few performances simultaneously, and the requirement of MRC around the gateways is also considered. In this paper, the proposed Reinforcement Learning (RL) method based routing selection on MPR communication directs the network traffic in WMNs. Here the radio routing path selects the channel depending on the optimized node where optimization is agreed by Particle Swarm Optimization (PSO) technique. This aims to reduce the EC by switching states and utilizing efficient routing with the reduction in traffic demand. Experimental results showed better performance of throughput and EC compared with existing work.

Router and gateway node placement in wireless mesh networks for emergency rescue scenarios

The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations. The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers, and are used in the generation of ad hoc Wireless Mesh Networks (WMN). Several fundamental problems are considered and algorithms are proposed to solve these problems. The Router Node Placement problem (RNP) and a generalization of it that takes into account additional constraints arising in actual field usage is considered first. The RNP problem tries to determine how to optimally place routers in a WMN. A new algorithm, the RRT-WMN algorithm, is proposed to solve this problem. It is based in part on a novel use of the Rapidly Exploring Random Trees (RRT) algorithm used in motion planning. A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and Particle Swarm Optimization (PSO), shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios. The Gateway Node Placement Problem (GNP) tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service (QoS) constraints.Two alternatives are proposed for solving the combined RNP-GNP problem. The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm. The second approach, WMNbyAreaDecomposition, proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions, thus creating a number of simpler RNP problems that are then solved concurrently. Both algorithms are evaluated on real-world GIS models of different size and complexity. WMNbyAreaDecomposition is shown to outperform existing algorithms using 73% to 92% fewer router nodes while at the same time satisfying all QoS requirements.

A Hexagonal Topology and Coordinate Based Routing for Wmns

Wireless mesh networks (WMNs) contain both i.e mesh router and clients, where backbone of WMNs is mesh router due to immaterial portability. They give orchestrate access to both work and customary clients. In a WMN, it is feasible to accomplish an IGW or any Mesh Routers via various paths. Anyway this may prompt an unwanted circumstance, in which the most ideal ways may degenerate on account of the disbalancing of burden, subsequently bringing about problematic execution. To avoid this problem, we propose coordinate based multi-way routing protocol, which knows about area of its neighbors for an Infrastructural WMN. The principal thought is on the examination of directing estimation with speedy route revelation, as possible least hopes, least delays, most outrageous information rates and least possible defect-rates. Reproduction outcome, demonstrate that our introduced method estimation is preferable than current lattice, ETX and ETT metric employed in directing.

Robust Channel Allocation with Heterogeneous Requirements for Wireless Mesh Backbone Networks

When multiple mobile sensors and actuators share a common wireless mesh backbone network of defence systems, the channel allocation mechanism must guarantee the heterogeneous link requirements under conditions of uncertainty. In this paper, a robust channel allocation mechanism is proposed by exploiting partially overlapped channels for directional multi-channel wireless mesh networks. The approach relies on a chance-constrained optimization problem, in which the objective is to minimize the spectrum usage of the network, and the constraints are the signal-to-interference-plus-noise ratio requirements of links with uncertainty. We convert the proposed integer non-linear optimization problem into a mixed-integer convex problem by using efficient transition and approximation. The optimal channel allocation is obtained by solving the proposed optimization problem which adapts to the heterogeneous link and robustness requirements. The simulation results show that the proposed method ensures the heterogeneous link requirements under uncertain conditions while minimizing the spectrum usage of the network.

Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT) and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low‐pass component of network traffic that describes the long‐range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low‐pass component. Otherwise, for the remaining high‐pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

Search-based routing in wireless mesh network

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.

Topology control based on the group mobility model for mobile wireless mesh backbone networks

Topology control based on the group mobility model for mobile wireless mesh backbone networks

Topology control based on the group mobility model for mobile wireless mesh backbone networks

In this paper, we study the characteristics and components of mobile wireless mesh backbone networks (MWMBNs). How to maintain the heterogeneous network connectivity in mobile scenarios is important. We propose a topology control algorithm based on the group mobility model for MWMBN to maintain network connectivity in mobile scenarios. It includes the following work: MWMBNs is classified into the mobile wireless backbone node group (MWBNG) and unit groups (UGs). the MWBNG is composed of all the MWBNs while the UG is composed of a MWBN and several TNs connect it. In the MWBNG, we propose the reference points assignment algorithm (RPAA) based on the RPGM model. In the UG, the TNs has different communication radius with the MWBNs', we propose the topology control algorithm based on tolerate zone using nomadic community mobility, the control algorithm does not need to use any control information to maintain topology control or to change the routing table. The TNs change the self-position to maintain the connectivity with the MWBN. The simulation results show the topology control algorithm based on the group mobility model for MWMBN to maintain the heterogeneous network connectivity when they move together.

Routing protocol for wireless quantum multi-hop mesh backbone network based on partially entangled GHZ state

Quantum multi-hop teleportation is important in the field of quantum communication. In this study, we propose a quantum multi-hop communication model and a quantum routing protocol with multihop teleportation for wireless mesh backbone networks. Based on an analysis of quantum multi-hop protocols, a partially entangled Greenberger–Horne–Zeilinger (GHZ) state is selected as the quantum channel for the proposed protocol. Both quantum and classical wireless channels exist between two neighboring nodes along the route. With the proposed routing protocol, quantum information can be transmitted hop by hop from the source node to the destination node. Based on multi-hop teleportation based on the partially entangled GHZ state, a quantum route established with the minimum number of hops. The difference between our routing protocol and the classical one is that in the former, the processes used to find a quantum route and establish quantum channel entanglement occur simultaneously. The Bell state measurement results of each hop are piggybacked to quantum route finding information. This method reduces the total number of packets and the magnitude of air interface delay. The deduction of the establishment of a quantum channel between source and destination is also presented here. The final success probability of quantum multi-hop teleportation in wireless mesh backbone networks was simulated and analyzed. Our research shows that quantum multi-hop teleportation in wireless mesh backbone networks through a partially entangled GHZ state is feasible.

Study of Topology Optimization Algorithm of Wireless Mesh Backbone Networks based on Directional Antenna

Study of Topology Optimization Algorithm of Wireless Mesh Backbone Networks based on Directional Antenna

Throughput improvement for delay-sensitive video broadcast in wireless mesh networks

In this paper, we address the problem of broadcast routing and scheduling of video streaming for delay-sensitive applications in backbone wireless mesh networks. Given a source node and a set of destinations, we aim to build a broadcast tree and compute an optimal schedule such that the throughput for the source to broadcast streaming data to all the destinations is maximized. We divide the whole period for video broadcast into identical time frames and prove that maximizing the throughput can be converted into minimizing the length of a time frame. We propose a three-step method as a solution. Firstly, we build the broadcast tree by defining a new routing metric to select relay nodes. Then we use local search method to adjust the tree structure. Last, we propose a greedy method to schedule concurrent transmissions. Simulations have demonstrated that our method can improve the performance significantly compared with existing methods.

Reinforcement learning based routing in wireless mesh networks

This paper addresses the problem of efficient routing in backbone wireless mesh networks (WMNs) where each mesh router is equipped with multiple radio interfaces and a subset of nodes serve as gate...

Zero-Degree algorithm for Internet GateWay placement in backbone wireless mesh networks

Internet GateWays (IGWs) are responsible for connecting the backbone wireless mesh networks (BWMNs) to the Internet/wired backbone. An IGW has more capabilities than a simple wireless mesh router (WMR) but is more expensive. Strategically placing the IGWs in a BWMN is critical to the Wireless Mesh Network (WMN) architecture. In order to solve the problem of IGWs placement in BWMNs, a novel algorithm is proposed in this paper. The new algorithm is involved in placing a minimum number of IGWs so that the Quality of Service (QoS) requirements are satisfied. Different from existing algorithms, this new algorithm incrementally identifies IGWs and prioritively assigns wireless mesh routers (WMRs) based on the computed degree of WMRs to identified IGWs. Performance evaluation results show that proposed algorithm outperforms other alternative algorithms by comparing the number of gateways placed in different scenarios. Furthermore, having control of the distribution of IGWs in order to locate them closest to available Internet/wired network connection points is an added advantage of this algorithm.

Remote Wireless Monitoring System for Heading Face of Coal Mine Based on WMN

t is necessary to establish a remote wireless monitoring system for the heading face of coal mine because of the risk of gas outburst and water inrush. This paper introduced a remote wireless monitoring system for heading face of coal mine based on wireless mesh network. The key technology is that the wireless backhaul link of this wireless communication system must remain high bandwidth and low latency after multi-hop in order to support video transmission because the laneway of coal mine is narrow and long. We used the technology of multi-interface multi-channel to design a 2-interface 3-channel backbone network for this wireless communication system. Each node of this backbone network is equipped with two interfaces, and three orthogonal channels of channel 1,6,11 provided by 802.11b/g are used. Compared to single interface single channel chain network, the 2-interface 3-channel wireless mesh backbone network has high throughput and low end to end delay while using appropriate channel allocation algorithm to make the channels of adjacent links non-interfered.

A Channel Splitting Strategy for Reducing Handoff Delay in Internet-Based Wireless Mesh Networks

Seamless intergateway handoff support is an essential issue to ensure continuous communications in Internet-based wireless mesh networks (WMNs). Due to the existence of multihop wireless links, traditional handoff schemes designed for single-hop wireless access networks can hardly guarantee the low handoff latency requirement in multihop WMNs. Existing solutions on reducing the handoff delay in WMNs ignore one important factor for the long handoff delay: the channel access delay of handoff signaling packets over the multihop wireless mesh backbone network. In this paper, we address the seamless intergateway handoff issue in Internet-based WMNs from a different perspective and propose a channel splitting strategy to reduce the channel access delay of handoff signaling packets over multihop wireless links. The handoff procedures of two scenarios when a mobile node has one or two transceivers are designed, and two transmission strategies for scheduling the delivery of handoff signaling packets are proposed. Simulation results show that by using the proposed channel splitting strategy, the handoff delay requirement in WMNs can be guaranteed, regardless of the background data traffic, and the average channel utilization can also be improved.

On the Partially Overlapped Channel Assignment on Wireless Mesh Network Backbone: A Game Theoretic Approach

The Wireless Mesh Network (WMN) has already been recognized as a promising broadband access network technology from both academic and commercial perspective. In order to improve the performance of WMNs, extensive research efforts have been dedicated towards finding means to increase the number of simultaneous transmissions in the network while avoiding signal interference among radios. In case of WMNs based on IEEE 802.11 b/g standards, most recent research works have relied upon the usage of orthogonal channels for solving the Channel Assignment (CA) problem. In this paper, we explore the possibility of exploiting Partially Overlapped Channels (POCs) by introducing a novel game theoretic distributed CA algorithm. Our proposed algorithm outperforms both the conventional orthogonal channel approach and the recent heuristic CA algorithms using POC. The proposed algorithm is shown to achieve near-optimal performance in the average case. In addition, the upper bound Price of Anarchy for Multi-Radio Multi-Channel (MRMC) networks is derived to evaluate the effectiveness of the proposed approach.

Link establishment and performance evaluation in IEEE 802.16 wireless mesh networks

Wireless mesh networks (WMNs) are one of the emerging technologies. Their capability for self-organization significantly reduces the complexity of network deployment and maintenance, and thus, requires minimal upfront investment. These networks consist of simple mesh routers and mesh clients, where mesh routers have minimal mobility and form the backbone of WMNs. They provide network access for both mesh and conventional clients. IEEE 802.16 standard (www.ieee 802.org/16) is a recent standard for broadband wireless access networks, which includes a mesh mode operation for distributed channel access of peering nodes. In accordance with the IEEE 802.16 MAC protocol, time is partitioned into frames of fixed duration, each one divided into two sub-frames, for control and data transmission, respectively. Slots in the control sub-frame are used by nodes to negotiate the schedule of transmissions in data sub-frames, and are accessed by means of a collision-free distributed procedure, namely the mesh election procedure. In this paper, we have analyzed the performance of the mesh election procedure by means of simulations, and identify the system configuration parameters that have the most impact on the performance of control message transmission using distributed scheduling algorithm.