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28 Jul 2010 performance of mobility-based clustering based on real traffic sit- uations. Experimental results show that using 0.3 % of vehicles as the samples, mobility-based clustering can accurately identify hot spots which can hardly be obtained by the latest representative algorithm UMicro. Categories and Subject
19 May 2009 lowest mobility among its neighbors becomes the cluster head. Selection of low mobile nodes as the cluster heads ensures better cluster stability. A example. Section IV focuses on the energy consumption model of the nodes and section V explains the simulation carried out and its results obtained.
We propose a distributed clustering algorithm, MOBIC, based on the use of this mobility metric for selection . to calculate the mobility metric for each node and outlines the clustering algorithm that is based upon this mobility metric. The wired Internet, for example, cannot be managed without hierarchical addressing and
Abstract—Clustering in vehicular ad hoc networks (VANETs) is a challenging issue due to the highly dynamic vehicle mobility and frequent communication disconnections problems. Recent years' research have proven that mobility-based clustering mech- anisms considering speed, moving direction, position, destination.
I. Introduction. A mobile ad hoc network [8] is a collection of mobile nodes that dynamically form a network without any infrastructure or pre- defined topology. Mobile nodes in the network are continuously moving in different direction with different speed. In this network environment, each node acts as an information source
Also, we propose clustering algorithm based on the trust and mobility metric to select CA and to establish public key infrastructure (PKI) in each cluster. Furthermore, we introduce new and mobility metric for the selection of the cluster head (CH) [4] is an example of system proposed by using a web-of-trust authentication
CLUSTERING ALGORITHMS IN MANET. We present below a survey of different clustering algorithms. 2.1 Identifier-based clustering. A unique ID is assigned to . This algorithm is based on mobility metric and the diameter of a cluster is adaptable with respect to node mobility. This clustering algorithm assumes that each
Mobility Based Clustering Algorithm for Ad Hoc. Network: MBCA. Ira Nath, Soumitra Das. JIS College of Engineering. Kalyani, Nadia, India. Abstract- A Mobile Ad-hoc network (MANET) is formed when group of mobile wireless nodes collaborate between them to communicate through wireless links in the absence of the
bution function of these random variables is assumed to be unknown. In this paper, we propose a learning automata- based weighted cluster formation algorithm called MCFA in which the mobility parameters of the hosts are assumed to be random variables with unknown distributions. In the pro- posed clustering algorithm
We propose a context-awareness routing algorithm—the DDV- (Dynamic Direction Vector-) hop algorithm—in mobile ad hoc networks. The existing algorithm in MANET has the limitations of the dynamic network topology and the absence of network expandability of the mobility of nodes. The proposed algorithm performs

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February 2018