A New AOMDV Lifetime Prolonging Routing Algorithm for Ad-Hoc Networks

A New AOMDV Lifetime Prolonging Routing Algorithm for Ad-Hoc Networks

Ibtihel Baddari (Limose Laboratory, Department of Computer Science M'hamed, Bouguerra University, Algeria), Mohamed Amine Riahla (Limose Laboratory, Department of Computer Science M'hamed, Bouguerra University, Algeria) and Mohamed Mezghiche (Limose Laboratory, Department of Computer Science M'hamed, Bouguerra University, Algeria)
DOI: 10.4018/IJITN.2019100104

Abstract

Network lifetime is a key design metric in MANETs, it is considered as one of the most important parameters algorithms to be used in ad hoc networks. Each network node works completely independently and acts as a router for relaying communications. If some nodes die prematurely because of battery depletion, the network lifetime will be adversely affected, and the network will get disconnected. This article presents AOMDV-LP, a new AOMDV lifetime-prolonging routing algorithm for MANETs. This new algorithm helps to maximize the network lifetime by managing nodes energy, link cost and controlling the networks congestion. Simulations quantify the performance gains of the authors algorithm.
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1. Introduction

Recent evolution in wireless communication technologies and the emergence of mobile terminals have made it possible to access the network anytime and anywhere without the need to connect communicating equipment to an infrastructure. An undeniable advantage of these wireless technologies is the possibility to be mobile while staying connected. But unfortunately, this mobility creates new problems such as frequent disconnection, low communication rate, modest resources and, a limited power source…etc. (Blum, Eskandarian, & Hoffman, 2004). Wireless mobile networks are classified into two main classes (Sarkar, Basavaraju, & Puttamadappa, 2016): Wireless networks with infrastructure that typically use the cellular communication model (an infrastructure that can be an access point or a base station) and Infrastructure Less Networks also named Mobile Ad-hoc networks or “MANETS” that are represented as a set of mobile entity which may be combined routers and hosts themselves form the network routing infrastructure in an Ad-hoc mode, interconnected by a wireless technology which communicate only through radio waves and self-organize quickly. MANET can be represented as directed graph 𝐺 = (𝑉, 𝐸) (Pan & Xiao, 2006). The vertices V ∈ 𝑉 are a symbol of the mobile stations. An edge (𝑢,V) ∈ 𝐸 is a symbol of a wireless link between this stations 𝑢,V, which forward packets to others. In this class, the wireless network can adapt to different traffic conditions, propagation and movements due to the mobility of the nodes knowing that the network size can contain hundreds or thousands of mobile nodes which means that the area size is not limited. Mobile Ad-hoc networks are characterized by the absence of the infrastructure as we have said before that mobile nodes are responsible for establishing and maintaining network connectivity in a continuous manner, MANETs are also characterized by the dynamic topology due to the mobility of the nodes who move in a free and arbitrary way. Therefore, the network topology can change, at unpredictable moments, in a rapid and random manner. Mobile nodes are powered by independent energy sources, such as batteries or other consumable sources. This is why the energy parameter must be taken into account in any control performed by the system. Mobile devices have limited batteries, and consequently a reduced processing time knowing that some of the energy is already consumed by the routing functionality, it limits the services and applications supported by each node. This is why, the routing in such a network is complex. The routing problem has always aroused great interest in the research community. Although the proposal of several protocols, the latter represents certain limits especially if we consider the high mobility of nodes and high network density (Naimi, 2015). It has given birth to several routing mechanisms, among these mechanisms, we find the multipath routing, which allows finding multiple paths between a source and a destination node for the data’s transmission. These multiple paths can be used to compensate for the mobile nature of nodes and the unpredictable nature of ad-hoc networks (Mueller, Tsang, & Ghosal, 2004). Our work is based on this type of routing.

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