Routing In Large-scale Networks Research Articles

A Survey on Scalable Multicasting in Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) have gained significant interest and popularity since they have enormous potential in several fields of applications. Infrastructure-free, self-configuring and mobility are the main reasons behind this popularity. Recently, group-oriented applications over MANET gains high popularity. Multicast communication is the ideal communication technique for supporting these types of applications. However, multicast routing in large-scale networks faces several difficulties and challenges that need to be addressed. These challenges include dynamic MANET topology, multicast packet forwarding and shared wireless medium. During the last years, active research work resulted in a variety of proposals. A number of protocols, each with a particular property and often optimized for a specific application area, have been designed. They follow different design principles and exhibit substantial variations in performance depending on various parameters. In this paper, most of the existing scalable multicast routing protocols in MANETs are briefly discussed and analyzed to provide a comprehensive understanding of these protocols and pave the way for further research.

Artificial immune based hybrid GA for QoS based multicast routing in large scale networks (AISMR)

In this paper, we propose a novel multiple-constrained multicast routing algorithm based on hybrid genetic algorithm. Artificial immune based method is used to handle the constraints and it removes the difficulties faced by penalty factor method. Our artificial immune algorithm simulates the interaction between antigens and antibodies. Our algorithm has the following features: (1) Affinity measure method is used for handling the constraints. (2) Local search heuristic function along with ‘m’ (random) point crossover and mutation is used for moving antigens to better position; (3) Clonal selection method along with heuristic hyper-mutation operator is used for driving the antibodies to better position. Algorithm for handling dynamism is also embedded into GA. Experimental results show that our algorithm yields constrained least-cost solutions for various sized random networks.

Statistical behaviors of mobile agents in network routing

Mobile agent-based network routing is a new technique for routing in large-scale networks. An analysis of the searching activity and population growth of mobile agents is important for improving performance in agent-driven networks. In this paper, we describe a general execution model of mobile agents for network routing and classify it into two cases. For each case, we analyze the population distribution of mobile agents (the distribution of mobile agents running in the network) and the probability of success (the probability that an agent can find its destination). We also perform extensive experiments for various network topologies to validate our analytical results. Both theoretical and experimental results show that the population distribution and the probability of success of mobile agents can be controlled by locally adjusting relevant parameters, such as the number of agents generated per request, the number of jumps each mobile agent can move, etc. Our results reveal new theoretical insights into the statistical behaviors of mobile agents and provide useful tools for effectively managing mobile agents in large networks.

Heuristic Methods for Solving Large Scale Network Routing Problems: The Telpaking Problem

An approach to a large scale network routing problem with nonlinear cost function is described, along with an example of its application. The approach to the problem involves a multistage construction process. This approach is applied to the telpaking problem. Results are obtained in applying this method to a 53 node sample problem.