Energy coherence of angle based multicast routing algorithm in wireless mesh networks

Providing security and privacy to users are critical in wireless mesh networks (WMNs). In this paper, a distributed security architecture is introduced to manage the mesh clients and a secure routing scheme that preserves the privacy of the end-users is proposed. In order to maximize routing efficiency, key indexing is used and symmetric cipher is employed in most part of the proposed scheme to reduce computational complexity. Both single-hop mesh client to mesh router and multi-hop mesh client to mesh client secure anonymous routing are proposed and discussed. Security and anonymity analysis are conducted followed by a complete performance analysis of the proposed protocol focusing on the route establish time and the routing overhead. The results show a reasonable overhead that linearly increases with the number of intermediate nodes. It is also demonstrated that the proposed schemes perform well against a broad range of attacks.

Wireless mesh networks have attracted increasing attention and deployment as a high-performance and low-cost solution to last-mile broadband Internet access. Network routing plays a critical role in determining the performance of a wireless mesh network. To study the best mesh network routing strategy which can maximize the network throughput while satisfying the fairness constraints, existing research proposes to formulate the mesh network routing problem as an optimization problem. These works usually make ideal assumptions such as known static traffic input. Whether they could be applied for practical use under the highly dynamic and uncertain traffic in wireless mesh network is still an open issue. The main objective of this paper is to understand the effects of traffic uncertainty in wireless mesh networks and consider these effects in throughput maximization routing. It identifies the appropriate optimization framework that could integrate the statistical user traffic demand model into a tractable throughput maximization problem. The trace-driven simulation study demonstrates that our algorithm can effectively incorporate the traffic demand uncertainty in routing optimization, and outperform the throughput maximization routing which only considers static traffic demand.

Wireless technology has become an essential part of this era’s human life and has the capability of connecting virtually to any place within the universe. A mesh network is a self healing wireless network, built through a number of distributed and redundant nodes to support variety of applications and provide reliability. Similarly, anycasting is an important service that might be used for a variety of applications. In this paper we have studied anycast routing in the wireless mesh networks and the anycast traffic from the gateway to the mesh network having multiple anycast groups. We have also studied the geocast traffic in which the packets reach to the group head via unicast traffic and then are broadcasted inside the group. Moreover, we have studied the intergroup communication between different anycast groups. The review of the related literature shows that no one has considered anycasting and geocasting from gateway to the mesh network while considering the multiple anycast groups and intergroup communication. The network is modeled, simulated and analyzed for its various parameters using OMNET++ simulator.

Efficient multicasting over Wireless Mesh Network (WMN) is challenging due to dynamic and multi-hop wireless communication among multicast group members. Multicast Ad hoc On-Demand Distance Vector (MAODV) protocol is a tree based multicast routing protocol that enables dynamic, self-starting, multi-hop routing between participating mobile nodes wishing to join or participate in a multicast group in Wireless Mesh Network (WMN). The mobility of mobile nodes often causes link breakage in the tree-based protocols which sometime results in tree partitioning and poor performance. In MAODV, when a broken link is detected between two nodes on the multicast tree, the node downstream to the break is responsible for initiating the repair of the broken link. After link repair, it is likely that the previous distance between the nodes (nodes downstream to the link breakage) and the group leader will not remain same. The shortest path from the group leader to the nodes downstream to the node which initiates link breakage is not ensured. Moreover, if the node attempting to repair a tree link break does not receive a response after certain attempts, it assumes that the multicast tree is not repairable currently and this leads to tree partitioning. In this paper, an improved link repair technique is proposed which ensures shortest path from any node to the group leader. Simulation results demonstrate significant improvement in performance metrics compared to standard MAODV.

Design of certification authority using secret redistribution and multicast routing in wireless mesh networks

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.

Recently, importance of wireless networks increased significantly. Wireless Mesh Networks (WMNs) are receiving growing attention and offer many advantages in terms of connectivity and reliability. Multicast communication is an important technology for wireless networks in which the same content of data should be delivered to a group of receiver nodes simultaneously. So multicast routing provides efficient data distribution among a group of nodes rather than other traditional unicast routing strategies. Here we focus on the Channel Allocation (CA) scheme which efficiently utilizes multiple wireless interfaces to achieve better throughput and improving the radio interference. This kind of problem has been proved to be NP-hard. Hence, solving the multicast channel assignment problem in MCMR WMNs will be more complicated than that of traditional networks. The research in this paper is aimed at improving the network performance for efficient joint channel assignment and multicast routing problem in MCMR WMNs by using the Q-learning scheme. We also implement our proposed channel assignment algorithm, and evaluate and compare its performance with LAMR. Simulations and experimental results demonstrate that QLMR outperforms the previous works in terms of achieved average throughput, average end-to-end delay, average packet delivery ratio and so on. We will evaluate the performance of the proposed scheme.

Reinforcement learning for QoS-guaranteed intelligent routing in Wireless Mesh Networks with heavy traffic load

Wireless mesh networks are popular due to their adaptability, easy-setup, flexibility, cost, and transmission time-reductions. The routing algorithm plays a vital role in transferring the data between the nodes. The network’s performance is significantly impacted by the route opted by the algorithm. The router takes the decision to send the packet to the next router as per the policy of that algorithm. So even though that decision does not favor the right path selection, the router tends to follow its policy. This can be avoided by having intelligent routers that can make routing decisions on the fly. This paper presents the QL-Feed Forward routing algorithm (QFFR), a new generation of routing algorithms that combines reinforcement learning based on the Q-learning algorithm with a Feed Forward neural network. This algorithm (QFFR) can learn from the network environment and make routing decisions based on the algorithm’s learnings. The AI agent’s ability to select the fastest path, which enhances the efficiency of the routing operation, is demonstrated by the working of the suggested QFFR algorithm. This paper also evaluates the performance of traditional algorithms, namely, Ad-hoc On-Demand Distance-Vector, Optimized-Link-State-routing, Destination-Sequenced Distance-Vector and Distance Source routing. The evaluation parameters include throughput, packet delivery ratio, and delay. The parameters are the outcomes of the time the information takes to reach from source to destination. This analysis highlights the improvement in the routing decision ability of a router. As per analysis, Ad hoc On-Demand Distance Vector Algorithm outperforms with throughput 723.13 Kbps, delay 343.73 ns. Q-learning agent identifies the route and reaches the destination in average of 3.7s in non-grid architecture. The Q-learning agent takes 0.49sec with a grid size ten by ten and 0.53sec in three by four grid size. The suggested QFFR takes 7.62s score-over time with stable, consistent performance.

Design and experimental performance analysis of a B.A.T.M.A.N.-based double Wi-Fi interface mesh network

Field Based Routing (FBR) is the next promising class of routing algorithms especially for wireless mesh networks. The inherent nature of shared medium wireless mesh networks, however, poses fundamental challenges to the design of effective routing policies that are optimal with respect to speed, time and resource utilization. In this paper, globally optimized routing algorithm for multiple subscribers in wireless mesh networks is proposed. Mesh network with multiple nodes will serve as an environment that optimizes some global utility function limited by the mobile nodes position in underlying MAC (Media Access Control) layer. By solving the optimization problem, the network is brought to a point of efficient operation with a certain routing policy for each node. This information will be the operating point that can be used to find better ways adaptive, which is able to steer the network towards the optimal routing. Global optimization of FBR is depicted through path estimation using PSO (Particle Swarm Optimization).

Routing is a critical component in wireless mesh networks. The inherent shared-medium nature of the wireless mesh networks, however, poses fundamental challenges to the design of effective routing policies that are optimal with respect to the resource utilization. Node churns and traffic fluctuations exacerbate such a problem. In this paper, we propose a novel adaptive routing algorithm for multiple subscribers in wireless mesh networks. We view a mesh network with multiple nodes as an entity that optimizes some global utility function constrained by the underlying MAC layer interference. By solving the optimization problem, the network is driven to an efficient operating point with a certain routing policies for each node. We then use this operating point information to adaptively find better paths, which is able to gear the network towards optimal routing. Further, we take the fluctuations of the network into consideration and thus render our algorithm more robust for a variety of network situations. Simulations demonstrate the efficiency and efficacy of our algorithm.

Wireless mesh networks (WMNs) are known for possessing good attributes such as low up-front cost, easy network maintenance, and reliable service coverage. This has largely made them to be adopted in various environments such as; school campus networks, community networking, pervasive healthcare, office and home automation, emergency rescue operations and ubiquitous wireless networks. The routing nodes are equipped with self-organized and self-configuring capabilities. However, the routing mechanisms of WMNs depend on the collaboration of all participating nodes for reliable network performance. The authors of this paper have noted that most routing algorithms proposed for WMNs in the last few years are designed with the assumption that all the participating nodes will collaboratively be involved in relaying the data packets originated from a source to a multi-hop destination. Such design approach however exposes WMNs to vulnerability such as malicious packet drop attack. This paper presents an evaluation of the effect of the black hole attack with other influential factors in WMNs. In this study, NS-3 simulator was used with AODV as the routing protocol. The results show that the packet delivery ratio and throughput of WMN under attack decreases sharply as compared to WMN free from attack. On an average, 47.41% of the transmitted data packets were dropped in presence of black hole attack.

To support reliable multicast routing in wireless mesh networks, it is important to protect multicast sessions against link or node failures. The issue of protecting multicast sessions in wireless mesh networks is a new problem to the best of our knowledge. In this paper, we propose a resilient forwarding mesh approach for protecting a multicast session in wireless mesh networks. Utilizing the wireless broadcast advantage, a resilient forwarding mesh effectively establishes two node disjoint paths for each source-destination pair. This allows a multicast session to be immune from any single link or intermediate node failure. We introduce four heuristic algorithms to obtain approximate solutions that seek to minimize the number of required broadcast transmissions. We evaluate the performance of these heuristic algorithms against the optimal resilient forwarding mesh (ORFM) obtained by solving an integer linear programming (ILP) formulation of the problem. Experimental results demonstrate that one of these heuristic algorithms, which we call the minimal disjoint mesh algorithm (MDM), performs sufficiently close to ORFM. Besides, we find that the resilient forwarding mesh approach provides efficient 1+ 1 protection (Pioro and Medhi, 2004) to the multicast session without incurring much additional overhead on a single minimal cost multicast tree

A multi-radio Wireless Mesh Network (WMN) is a multi-hop network that consists of mesh routers and mesh clients, where mesh routers are equipped with multiple radio interfaces and form the backbone of the mesh network. To provide backbone support, it is necessary to reduce interference and balance load in Wireless Mesh Networks (WMNs). We propose load-aware routing metric (LARM), which captures the difference in transmission rates, packet loss ratio, intra/inter-flow interference and traffic load in multi-radio mesh networks. The LARM metric helps finding paths that are better in terms of balancing load and reducing the inter-flow and intra-flow interference in multi-radio networks. Simulation results show that LARM metric significantly outperforms several existing routing metrics in multi-radio wireless mesh networks.