Queue‐based multiple path load balancing routing protocol for MANETs. (2nd May 2016)

• Record Type: Journal Article
• Authors: Naseem, Mohd; Kumar, Chiranjeev
• Is Part Of: International journal of communication systems. Volume 30:Number 6(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-05-02
• Subjects: mobile ad hoc networks -- routing protocol -- congestion -- load balancing -- node‐disjoint paths.; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3141
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: Congestion in the network is the main cause for packet drop and increased end‐to‐end transmission delay of packet between source and destination nodes. Congestion occurs because of the simultaneous contention for network resources. It is very important to efficiently utilize the available resources so that a load can be distributed efficiently throughout the network. Otherwise, the resources of heavily loaded nodes may be depleted very soon, which ultimately affects network performances. In this paper, we have proposed a new routing protocol named queue‐based multiple path load balancing routing protocol. This protocol discovers several node‐disjoint paths from source to destination nodes. It also finds minimum queue length with respect to individual paths, sorts the node‐disjoint paths based on queue length, and distributes the packets through these paths based on the minimum queue length. Simulation results show that the proposed routing protocol distributes the load efficiently and achieves better network performances in terms of packet delivery ratio, end‐to‐end delay, and routing overhead. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : Traffic sampling is a prominent strategy contributing to lightweight and scalable network measurements. Providing a modular view of sampling techniques is an important step to enlarge the sampling scope and improve the efficiency of measurement systems. This paper defines a taxonomy of traffic sampling techniques resorting to a comprehensive analysis of the inner components of existing proposals, including insights into their computational weight. Following this taxonomy, a general‐purpose architecture is established to sustain the development of flexible sampling‐based measurement systems.