Routing Problem In Mobile Ad Hoc Network Research Articles

A New Approach based Bee Colony for the Resolution of Routing Problem in Mobile Ad-Hoc Networks

A mobile ad hoc network (MANET) is an autonomous system of mobile hosts (nodes) connected by a wireless link that forms a temporary network without the aid of any established infrastructure or centralized administration. The main problem of MANETs is the design of routing protocols that allow for communication among the hosts. The dynamic nature of such networks makes this problem especially challenging. The routing problems in ad hoc networks are due to their unpredictable and dynamic nature and the few resources (speed and autonomy). Therefore, bio-inspired algorithms are widely used to design adaptive routing strategies for MANETs. In this study, the authors propose a new approach based on the bee colony for the resolution of the routing problem in MANETs. The implementation (simulation) of the method is realized by Matlab, and the authors select Random WayPoint as mobility model. To validate the work, the authors compare the proposed approach with the AODV routing protocol in terms of the Quality of Service parameters, namely, End-to-End Delay, Packet Delivery Ratio and the Normalized Overhead Load.

New Approaches to Routing in Mobile Ad hoc Networks

Worldwide Interoperability for Microwave Access (Wimax) is power station through which mobile network, commonly known as A Mobile Ad-hoc Network (MANET) is used by the people. A MANET can be described as an infrastructure-less and self-configure network with autonomous nodes. Participated nodes in MANETs move through the network constantly causing frequent topology changes. Designing suitable routing protocols to handle the dynamic topology changes in MANETs can enhance the performance of the network. In this regard, this paper proposes four algorithms for the routing problem in MANETs. First, we propose a new method called Classical Logic-based Routing Algorithm for the routing problem in MANETs. Second is a routing algorithm named Fuzzy Logic-based Routing Algorithm (FLRA). Third, a Reinforcement Learning-based Routing Algorithm is proposed to construct optimal paths in MANETs. Finally, a fuzzy logic-based method is accompanied with reinforcement learning to mitigate existing problems in FLRA. This algorithm is called Reinforcement Learning and Fuzzy Logic-based (RLFLRA) Routing Algorithm. Our proposed approaches can be deployed in dynamic environments and take four important fuzzy variables such as available bandwidth, residual energy, mobility speed, and hop-count into consideration. Simulation results depict that learning process has a great impact on network performance and RLFLRA outperforms other proposed algorithms in terms of throughput, route discovery time, packet delivery ratio, network access delay, and hop-count.

A Game Theoretical Model for Energy-Aware DTN Routing in MANETs with Nodes’ Selfishness

Many existing studies just considered that nodes in a Mobile Ad Hoc NETwork (MANET) would fully cooperate to forward packets for one another. However, this assumption does not hold in many scenarios. The node selfishness in relay cooperation will certainly influence the overall performance of routing in MANETs. In this work, we investigate the energy-aware routing problem in MANETs with nodes' selfishness. We model the situation of node cooperation in energy-aware routing by using game theory. We consider the competitive and cooperative relationship between the nodes to formulate the game for MANETs. An incentive mechanism is given in order to encourage forwarding cooperation during energy-aware routing. Nodes are encouraged to forward more data packets for others in order to acquire more services from others. We also carry out a simulation for the proposed method and perform detailed analysis in this work. From the results of the simulation, we argue that it's possible to find out a suitable configuration for a MANET to support more efficient energy-aware routing through our method.

Dynamic Genetic Algorithms with Hyper-Mutation Schemes for Dynamic Shortest Path Routing Problem in Mobile Ad Hoc Networks

In recent years, the static shortest path (SP) routing problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless mesh network (WMN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. This paper proposes to use two types of hyper-mutation GAs to solve the dynamic SP routing problem in MANETs. The authors consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the two hyper-mutation GAs can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.