Resource Efficient and Scalable Routing using Intelligent Mobile Agents

Many of the contemporary routing algorithms use simple mechanisms such as flooding or broadcasting to disseminate the routing information available to them. Such routing algorithms cause significant network resource overhead due to the large number of messages generated at each host/router throughout the route update process. Many of these messages are wasteful since they do not contribute to the route discovery process. Reducing the resource overhead may allow for several algorithms to be deployed in a wide range of networks (wireless and ad-hoc) which require a simple routing protocol due to limited availability of resources (memory and bandwidth). Motivated by the need to reduce the resource overhead associated with routing algorithms a new implementation of distance vector routing algorithm using an agent-based paradigm known as Agent-based Distance Vector Routing (ADVR) has been proposed. In ADVR, the ability of route discovery and message passing shifts from the nodes to individual agents that traverse the network, co-ordinate with each other and successively update the routing tables of the nodes they visit

Distributed Hierarchical IDS For MANET Over AODV+.

In this paper, we introduce background knowledge of wireless ad hoc networking mobile ad hoc network (MANET) as well as intrusion detection system (IDS) and mobile agents. This research study surveys, studies and compares the existing intrusion detection based on mobile agent for mobile ad hoc networks. Based on our best knowledge from previous researches we design distributed hierarchical /D^S inclusive of network-based and host-based intrusion detection system with due consideration to their characteristics on ad hoc on4emand distance vector routing protocol (AODV+)

QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)

In this paper, a new algorithm, Intelligent agent AntNet based Routing Algorithm (IANRA) is proposed to enhance load balancing strategy in Wireless Networks (WNs). IANRA is based on Ants behaviour with some important factors such as: the specific self-organizing behaviour of ant colonies, the shortest path discovery and the related framework of Ant Colony Optimization (ACO). The main focus in IANRA is to find optimum and near optimum route by means of Genetic Algorithm (GA) using breeding capability of ants. Here, ants can produce a number of generations with the target to discover an optimized route. Hence IANRA is able to prevent of the difficulties which exist in existing routing algorithms, such as Ad hoc On-Demand Distance Vector (AODV), AntNet etc. The obtained results show that the efficiency of IANRA algorithm is better than AODV and AntNet or any other related algorithm. In addition, the proposed algorithm (IANRA) is able to reduce the end-to-end delay and increase the packet delivery ratio significantly