Performance Of Wireless Mesh Networks Research Articles

EVALUATING ROUTING ALGORITHMS ACROSS DIFFERENT WIRELESS MESH NETWORK TOPOLOGIES USING NS-3 SIMULATOR

Wireless Mesh Networks are gaining traction as a solution for delivering reliable connectivity without centralized infrastructure. They operate through wireless node interconnections, forming self-configuring networks ideal for scenarios where wired networks are impractical. Routing is crucial in Wireless Mesh Networks to ensure efficient communication among nodes. However, the suitability of routing algorithms for Wireless Mesh Network’s topology requires further investigation. This paper proposes an investigation into the effectiveness of routing algorithms like AODV, DSDV, and OLSR across various Wireless Mesh Networks topologies using NS-3 simulation. It also aims to determine the optimal number of nodes and protocols to maximize throughput and minimize packet loss within a limited area. Through rigorous NS-3 simulations, the study demonstrates that AODV, DSDV, and OLSR exhibit differing effectiveness across random, mesh grid, and Fruchterman-Reingold topologies. These results emphasize the importance of considering topology-specific factors when selecting and optimizing routing protocols for Wireless Mesh Networks. In summary, Wireless Mesh Networks offer decentralized connectivity, but the effectiveness of routing algorithms in different topologies remains understudied. This investigation addresses this gap by evaluating routing algorithms across various topologies, shedding light on their suitability and performance in Wireless Mesh Networks.

Sustainable optimizing WMN performance through meta-heuristic TDMA link scheduling and routing

Wireless mesh networks (WMNs) have become a popular solution for expanding internet service and communication in both urban and rural areas. However, the performance of WMNs depends on generating optimized time-division multiple access (TDMA) schedules, which distribute time into a list of slots called superframes. This study proposes novel meta-heuristic algorithms to generate TDMA link schedules in WMNs using two different interference/constraint models: multi-transmit-receive (MTR) and full-duplex (FD). The objectives of this study are to optimize the TDMA frame for packet transmission, satisfy the constraints, and minimize the end-to-end delay. The significant contributions of this study are: (1) proposing effective and efficient heuristic solutions to solve the NP-complete problem of generating optimal TDMA link schedules in WMNs; (2) investigating the new FD interference model to improve the network capacity above the physical layer. To achieve these objectives and contributions, the study uses two popular meta-heuristics, the artificial bee colony (ABC) and/or genetic algorithm (GA), to solve the known NP-complete problems of joint scheduling, power control, and rate control. The results of this study show that the proposed algorithms can generate optimized TDMA link schedules for both MTR and FD models. The joint routing and scheduling approach further minimizes end-to-end delay while maintaining the schedule's minimum length and/or maximum capacity. The proposed solution outperforms the existing solutions in terms of the number of active links, end-to-end delay, and network capacity. The research aims to improve the efficiency and effectiveness of WMNs in most applications that require high throughput and fast response time.

Analysis of multimedia network data security based on routing algorithm

In today’s society, the application of multimedia data is increasing, and the accompanying data security is also an important issue. This paper will analyze the data security of multimedia network based on routing algorithm. The advantages of wireless local area networks (WLAN) and ad hoc networks are combined in wireless mesh networks (WMNs), which have steadily grown to be a reliable method of wireless broadband access. The application of multi RF and multi-channel technology improves the performance of WMN. However, the limitation that includes the number of wireless network interface cards and channels in the network, results in the great challenges ofrouting and channel allocation in multi RF and multi-channel WMN. Based on AODV algorithm, this paper proposes a new cross layer routing algorithm which is JRCA-AODV algorithm. The simulation results demonstrate that the JRCA-AODValgorithm can successfully increase multiRF multi-channel WMN throughput while lowering packet loss rate and network delay. Take the packet rate of 8 Mbps as an example, the network throughput based on JRCA-AODV algorithm is 1.14 times that of MRMC-AODV algorithm, the packet loss rate based on JRCA-AODV algorithm is 14.06% lower than that of MRMC-AODV algorithm, and the network time delay based on JRCA-AODV algorithm is 14.27% lower than that of MRMC-AODV algorithm. At the same time, JRCA-AODV algorithm can effectively reduce the probability of data loss caused by the competitive and shared access mechanism of the channel, improve the success rate of data transmission, thus reduce the probability of data eavesdropping and tampering in the process of repeated transmission, and improve the security of multimedia network data.This will provide a new direction for promoting the idea of multimedia data security.

Energy Efficient Routing in Wireless Mesh Networks using Multi-Objective Dwarf Mongoose Optimization Algorithm

Wireless Mesh Networks (WMNs) are part of wireless technologies that are known for their flexibility and extended coverage. Wireless applications have reached their peak in applications related to various fields such as healthcare, image processing, and so on. However, delay and energy efficiency are considered the two aspects that diminish the performance of WMNs. To overcome the aforementioned issues, this research introduces an effective routing method using Multi-Objective Dwarf Mongoose Optimization Algorithm (MO-DMOA). The MO-DMOA performs routing by considering the multiple paths using an enriched population resource. The nomadic behaviour of MO-DMOA helps in detecting the optimal routing path with minimized over-exploitation. The proposed MO-DMOA is evaluated with different routing schemes such as Load Balance and Interference Avoid-Partially Overlapped Channels Assignment (LBIA-POCA) framework, and Multi-Objective Dyna Q-based Routing (MODQR). The outcomes obtained through the experimental analysis show that the proposed approach acquires a better throughput of 13.5×105kbps for 22 flows, whereas the existing LBIA-POCA achieves a throughput 60× 103 kbps

Energy Efficient Routing in Wireless Mesh Networks using Multi-Objective Dwarf Mongoose Optimization Algorithm

Wireless Mesh Networks (WMNs) are part of wireless technologies that are known for their flexibility and extended coverage. Wireless applications have reached their peak in applications related to various fields such as healthcare, image processing, and so on. However, delay and energy efficiency are considered the two aspects that diminish the performance of WMNs. To overcome the aforementioned issues, this research introduces an effective routing method using Multi-Objective Dwarf Mongoose Optimization Algorithm (MO-DMOA). The MO-DMOA performs routing by considering the multiple paths using an enriched population resource. The nomadic behaviour of MO-DMOA helps in detecting the optimal routing path with minimized over-exploitation. The proposed MO-DMOA is evaluated with different routing schemes such as Load Balance and Interference Avoid-Partially Overlapped Channels Assignment (LBIA-POCA) framework, and Multi-Objective Dyna Q-based Routing (MODQR). The outcomes obtained through the experimental analysis show that the proposed approach acquires a better throughput of 13.5×105kbps for 22 flows, whereas the existing LBIA-POCA achieves a throughput 60× 103 kbps

Enhanced TCP BBR Performance in wireless mesh networks (WMNs) and next-generation high-speed 5G networks

Enhanced TCP BBR Performance in wireless mesh networks (WMNs) and next-generation high-speed 5G networks

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.

Enhanced TCP BBR performance in wireless mesh networks (WMNs) and next-generation high-speed 5G networks

Enhanced TCP BBR performance in wireless mesh networks (WMNs) and next-generation high-speed 5G networks

Hybrid Harris Hawks With Sine Cosine for Optimal Node Placement and Congestion Reduction in an Industrial Wireless Mesh Network

The optimal performance of a wireless mesh network (WMN) can be greatly improved by strategically placing wireless mesh routers. As a result, it is crucial to optimally locate the WMN routers for better coverage and connectivity. Besides the optimal placement, the network congestion due to overlaying routers has to be taken into consideration. These issues have become a motivation for researchers to identify a variety of approaches to optimize WMN performance. Multiple metaheuristic algorithms have been employed for identifying the trade-offs between coverage and connectivity in WMN. Consequently, a novel hybrid Harris Hawks optimization with the sine cosine algorithm (HHOSCA) is presented in this work to tackle the aforementioned WMN optimization problems. The proposed HHOSCA seeks optimal router placement that leads to significantly increased network coverage and achieves full connectivity between the mesh routers. In addition, the proposed HHOSCA produces a cost-effective WMN by reducing the congestion in the network to the minimum number of routers whilst ensuring maximum coverage and connectivity. The superiority of the proposed HHOSCA in comparison to the other algorithm was validated by using 33 benchmark functions. It was compared against four well-known algorithms including Sine Cosine Algorithm (SCA), Harris Hawks optimization (HHO), Gray Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). These algorithms are statistically analyzed and compared to the simulated results of the proposed method. In addition, the performance of HHOSCA is compared to the state-of-the-art to highlight the efficacy of the proposed algorithm. The statistical analyses and simulation findings confirm that the HHOSCA outperforms the other algorithms in terms of network connectivity, coverage, network reduction, and convergence. The experimental results reveal that the proposed HHOSCA method achieves favourable optimization results compared with other relevant methods.

Multi-path QoE Routing Algorithm for wireless mesh network Based on Q-Learning

To address the problem of poor quality of experience(QoE) of wireless mesh network users in the current video streaming service, a wireless mesh network multi-path QoE algorithm based on Q-learning(QLMPQ) is proposed. The selection strategy is used to find the optimal master-slave path to improve the reliability of data transmission. Virtual simulation experiments are carried out under the conditions of different concurrent flows to verify the feasibility and accuracy of the algorithm. The experimental results show that compared with Q-Routing, QLAODV, and AODV algorithms, this algorithm can significantly improve the performance of wireless mesh networks.

Improved Multi-Channel Multi-Interface Routing Protocol for Wireless Mesh Networks

In recent years, Wireless Mesh Networks (WMN) are emerging as a potential technology to enhance the ability and availability of wireless networks. WMN consists of wireless mesh routers and terminals connected by wireless multi-hop communication. Besides, in WMN, each wireless node owns many interfaces, and each interface operates on many channels. However, effectively using multiple orthogonal channels and multiple interfaces to increase the performance of WMN and decrease the radio link transmission interference is of significant challenge. In this paper, we consider routing issues in WMN. Then, we proposed an on-demand routing protocol, adaptive multi-channel multi-interface operation, improved from the AODV protocol. This protocol is capable of effectively managing communication in the WMN and limited effects of co-channel interference. The simulation results on NS2 show that our proposed protocol improves throughput, delay and packet delivery rate compared to existing traditional protocols.

Coefficient of Restitution based Cross Layer Interference Aware Routing Protocol in Wireless Mesh Networks

In Multi-Radio Multi-Channel (MRMC) Wireless Mesh Networks (WMN), Partially Overlapped Channels (POC) has been used to increase the parallel transmission. But adjacent channel interference is very severe in MRMC environment; it decreases the network throughput very badly. In this paper, we propose a Coefficient of Restitution based cross layer interference aware routing protocol (CoRCiaR) to improve TCP performance in Wireless Mesh Networks. This approach comprises of two-steps: Initially, the interference detection algorithm is developed at MAC layer by enhancing the RTS/CTS method. Based on the channel interference, congestion is identified by Round Trip Time (RTT) measurements, and subsequently the route discovery module selects the alternative path to send the data packet. The packets are transmitted to the congestion free path seamlessly by the source. The performance of the proposed CoRCiaR protocol is measured by Coefficient of Restitution (COR) parameter. The impact of the rerouting is experienced on the network throughput performance. The simulation results show that the proposed cross layer interference aware dynamic routing enhances the TCP performance on WMN.

Internet Traffic based Channel Selection in Multi-Radio Multi-Channel Wireless Mesh Networks

Wireless Mesh Networks(WMNs) are the outstanding technology to facilitate wireless broadband Internet access to users. Routers in WMN have multiple radio interfaces to which multiple orthogonal/partially overlapping channels are assigned to improve the capacity of WMN. This paper is focused on channel selection problem in WMN since proper channel selection to radio interfaces of mesh router increases the performance of WMN. To access the Internet through WMN, the users have to associate with one of the mesh routers. Since most of the Internet Servers are still in wired networks, the major dominant traffic of Internet users is in downlink direction i.e. from the gateway of WMN to user. This paper proposes a new method of channel selection to improve the user performance in downlink direction of Internet traffic. The method is scalable and completely distributed solution to the problem of channel selection in WMN. The simulation results indicate the significant improvement in user performance.

Impact Of Load Balancing Interference Routing Metric On Multi Channel Multi Radio Wireless Mesh Network

Wireless Mesh Network (WMNs) is a promising technology that has been accepted favorably by the Internet Service Providers (ISPs). ISPs use it to provide last mile broadband Internet connectivity to the end users. This popularity arises from the fact, that it inter operates well with diverse wireless systems and provides robust fault tolerance with a high degree of redundancy and reliability. Routing metrics plays a crucial part in the performance of WMN. When routing protocols are implemented, the routing metric is assigned to different paths. It calculates the optimum path to predict the best routing path. These are integrated in routing protocols to improve WMNs efficiency in terms of reliability, latency, throughput, error rate and cost. This paper compares the impact of using load balancing interference aware routing metric (LBIARM) on the performance of Multi-Channel Multi Radio WMNs (MCMR WMNs). The performance of LBIARM was evaluated by comparing it with popular standard metrics weighted cumulative expected transmission time metric and Hop Count metric. OPNET Modeler 17.5 PL1 was used as a simulation tool for implementation. Simulation results show the effectiveness of using LBIARM metric on MCMR WMNs.

Optimal Coverage and Connectivity in Industrial Wireless Mesh Networks Based on Harris’ Hawk Optimization Algorithm

The placement of wireless mesh routers is a significant matter in enhancing the performance of a wireless mesh network. Therefore, it is essential that the mesh routers are optimally placed to guarantee strong connectivity and coverage for ensuring the best network accessibility. The importance of this issue has motivated the researchers to pursue more investigation on optimizing the networks’ performance. Various optimization algorithms have been developed in the literature to identify the trade-offs between network connectivity and client coverage. This work is aimed at implementing a novel application of Harris Hawk’s Optimization (HHO) algorithm to optimally place mesh routers in a wireless mesh network so as to improve connectivity and coverage. The HHO seeks optimal routers placement that leads to maximizing the connection between routers and increasing the number of covered clients. In this study, three network configurations are used with sizes of 40, 60, and 100 mesh routers. The simulation results are statistically analyzed and compared to other population-based algorithms such as Sine Cosine Algorithm (SCA), Gray Wolf’s Optimization (GWO), and Particle Swarm Optimization (PSO). Moreover, the performance of HHO is compared with the state-of-the-art to validate the effectiveness of the proposed approach. The simulation findings and statistical analysis confirm that the HHO outperforms the other algorithms in terms of network coverage and connectivity. The outcomes demonstrate that HHO can be considered an efficacious means to enhance the performance of wireless mesh networks (WMNs).

Solving the Mesh Router Nodes Placement in Wireless Mesh Networks Using Coyote Optimization Algorithm

Wireless Mesh Networks (WMNs) have rapid real developments during the last decade due to their simple implementation at low cost, easy network maintenance, and reliable service coverage. Despite these properties, the nodes placement of such networks imposes an important research issue for network operators and influences strongly the WMNs performance. This challenging issue is known to be an NP-hard problem, and solving it using approximate optimization algorithms (i.e. heuristic and meta-heuristic) is essential. This motivates our attempts to present an application of the Coyote Optimization Algorithm (COA) to solve the mesh routers placement problem in WMNs in this work. Experiments are conducted on several scenarios under different settings, taking into account two important metrics such as network connectivity and user coverage. Simulation results demonstrate the effectiveness and merits of COA in finding optimal mesh routers locations when compared to other optimization algorithms such as Firefly Algorithm (FA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Genetic Algorithm (GA), Bat Algorithm (BA), African Vulture Optimization Algorithm (AVOA), Aquila Optimizer (AO), Bald Eagle Search optimization (BES), Coronavirus herd immunity optimizer (CHIO), and Salp Swarm Algorithm (SSA).

A comparison study of chi-square and uniform distributions of mesh clients for different router replacement methods using WMN-PSODGA hybrid intelligent simulation system

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.

Adaptive DSR to mitigate packet dropping attacks in WMNs using cross layer metrics

Wireless Mesh network (WMN) is a form of Wireless Ad hoc network, where mesh topology is used to connect the radio nodes together and it is prone to vulnerabilities due to its open architecture. Packet loss is the major issue due to its open wireless physical media, frequent topological changes, scalability and power constraints. The most common blackhole and grayhole attacks besieged on network layer degrade the performance of WMN by dropping packets during transmission. In general, packet drops in WMN during transmission may happen due to mobility or buffer overflow or power depletion or malicious behavior of the intermediate nodes. This paper proposes an Adaptive Dynamic Source Routing protocol (ADSR) to detect the actual cause for packet drops, identify and isolate the misbehaving nodes using the cross layer metrics. It employs proactive, reactive mode of detection of packet dropping nodes and the packets are rerouted through alternate paths using packet salvaging technique. Bait-RREQ with virtual IP address is used to detect the blackhole nodes proactively and node behavior analysis is used to detect the packet dropping nodes reactively. The performance of ADSR is analyzed using a mathematical model by considering the characteristics of a node’s behavior. Using extensive simulations the performances are thoroughly analyzed, evaluated and compared with traditional DSR, WatchDog (WD), Bait-DSR (BDSR) protocols. Simulation results show that ADSR is better than other mentioned protocols with negligible increase in network overhead (less than 2%) which is due to the use of Bait-RREQ and packet salvaging technique. The proper identification of actual cause for packet drops significantly reduces the false positive rate of detection of malicious nodes with an increased packet delivery ratio (not lower than 95%) and throughput.

Deep Reinforcement Learning for Communication Flow Control in Wireless Mesh Networks

Wireless mesh network (WMN) is one of the most promising technologies for Internet of Things (IoT) applications because of its self-adaptive and self-organization nature. To meet different performance requirements on communications in WMNs, traditional approaches always have to program flow control strategies in an explicit way. In this case, the performance of WMNs will be significantly affected by the dynamic properties of underlying networks in real applications. With providing a more flexible solution in mind, in this article, for the first time, we present how we can apply emerging Deep Reinforcement Learning (DRL) on communication flow control in WMNs. Moreover, different from a general DRL based networking solution, in which the network properties are pre-defined, we leverage the adaptive nature of WMNs and propose a self-adaptive DRL approach. Specifically, our method can reconstruct a WMN during the training of a DRL model. In this way, the trained DRL model can capture more properties of WMNs and achieve better performance. As a proof of concept, we have implemented our method with a self-adap-tive Deep Q-learning Network (DQN) model. The evaluation results show that the presented solution can significantly improve the communication performance of data flows in WMNs, compared to a static benchmark solution.

Performance Evaluation of CANCAR Algorithm in Realistic Wireless Mesh Networks

Approaches for increasing the network throughput and thus enhancing the performance of wireless mesh networks are one of the key challenges. Network Coding (NC) offers a way to improve on the network performance, by sharing network resources. With the additional approaches, where routing decisions are made with the awareness of coding capabilities and opportunities, the performance of NC can be further improved. As shown in this paper, in the case of proposed proactive routing procedure CANCAR (Congestion-Avoidance Network Coding-Aware Routing), which takes into account the coding awareness along with the information of the measured traffic coding success, it can be efficiently used to support the congestion avoidance and enable more encoded packets, thus indirectly increasing the network throughput. Comprehensive evaluation of CANCAR in realistic simulation environments confirms that the performance in terms of network goodput is notably improved in comparison to COPE. In addition, we showed that the accurate use of measured coding success information for congestion-avoidance routing improves the network performance and has the potential to increase the number of encoded packets. Furthermore, the CANCAR also enables the fairer share of system resources according to the Jain’s fairness index.