8,749 research outputs found
An ACO Algorithm for Effective Cluster Head Selection
This paper presents an effective algorithm for selecting cluster heads in
mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc
network consists of a cluster head and cluster members which are at one hop
away from the cluster head. The cluster head allocates the resources to its
cluster members. Clustering in MANET is done to reduce the communication
overhead and thereby increase the network performance. A MANET can have many
clusters in it. This paper presents an algorithm which is a combination of the
four main clustering schemes- the ID based clustering, connectivity based,
probability based and the weighted approach. An Ant colony optimization based
approach is used to minimize the number of clusters in MANET. This can also be
considered as a minimum dominating set problem in graph theory. The algorithm
considers various parameters like the number of nodes, the transmission range
etc. Experimental results show that the proposed algorithm is an effective
methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information
Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan
An Overview of Mobile Ad Hoc Networks for the Existing Protocols and Applications
Mobile Ad Hoc Network (MANET) is a collection of two or more devices or nodes
or terminals with wireless communications and networking capability that
communicate with each other without the aid of any centralized administrator
also the wireless nodes that can dynamically form a network to exchange
information without using any existing fixed network infrastructure. And it's
an autonomous system in which mobile hosts connected by wireless links are free
to be dynamically and some time act as routers at the same time, and we discuss
in this paper the distinct characteristics of traditional wired networks,
including network configuration may change at any time, there is no direction
or limit the movement and so on, and thus needed a new optional path Agreement
(Routing Protocol) to identify nodes for these actions communicate with each
other path, An ideal choice way the agreement should not only be able to find
the right path, and the Ad Hoc Network must be able to adapt to changing
network of this type at any time. and we talk in details in this paper all the
information of Mobile Ad Hoc Network which include the History of ad hoc,
wireless ad hoc, wireless mobile approaches and types of mobile ad Hoc
networks, and then we present more than 13 types of the routing Ad Hoc Networks
protocols have been proposed. In this paper, the more representative of routing
protocols, analysis of individual characteristics and advantages and
disadvantages to collate and compare, and present the all applications or the
Possible Service of Ad Hoc Networks.Comment: 24 Pages, JGraph-Hoc Journa
Scalable energy-efficient routing in mobile Ad hoc network
The quick deployment without any existing infrastructure makes mobile ad hoc networks (MANET) a striking choice for dynamic situations such as military and rescue operations, disaster recovery, and so on and so forth. However, routing remains one of the major issues in MANET due to the highly dynamic and distributed environment. Energy consumption is also a significant issue in ad hoc networks since the nodes are battery powered. This report discusses some major dominating set based approaches to perform energy efficient routing in mobile ad hoc networks. It also presents the performance results for each of these mentioned approaches in terms of throughput, average end to end delay and the life time in terms of the first node failure. Based on the simulation results, I identified the key issues in these protocols regarding network life time. In this report, I propose and discuss a new approach “Dynamic Dominating Set Generation Algorithm” (DDSG) to optimize the network life time. This algorithm dynamically selects dominating nodes during the process of routing and thus creates a smaller dominating set. DDSG algorithm thereby eliminates the energy consumption from the non-used dominating nodes. In order to further increase the network life time, the algorithm takes into consideration the threshold settings which helps to distribute the process of routing within the network. This helps to eliminate a single dominating node from getting drained out by continuous transmission and reception of packets. In this report, the detailed algorithmic design and performance results through simulation is discussed
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