12,655 research outputs found
Design and Analysis of SD_DWCA - A Mobility based clustering of Homogeneous MANETs
This paper deals with the design and analysis of the distributed weighted
clustering algorithm SD_DWCA proposed for homogeneous mobile ad hoc networks.
It is a connectivity, mobility and energy based clustering algorithm which is
suitable for scalable ad hoc networks. The algorithm uses a new graph parameter
called strong degree defined based on the quality of neighbours of a node. The
parameters are so chosen to ensure high connectivity, cluster stability and
energy efficient communication among nodes of high dynamic nature. This paper
also includes the experimental results of the algorithm implemented using the
network simulator NS2. The experimental results show that the algorithm is
suitable for high speed networks and generate stable clusters with less
maintenance overhead
Multimedia Content Distribution in Hybrid Wireless Networks using Weighted Clustering
Fixed infrastructured networks naturally support centralized approaches for
group management and information provisioning. Contrary to infrastructured
networks, in multi-hop ad-hoc networks each node acts as a router as well as
sender and receiver. Some applications, however, requires hierarchical
arrangements that-for practical reasons-has to be done locally and
self-organized. An additional challenge is to deal with mobility that causes
permanent network partitioning and re-organizations. Technically, these
problems can be tackled by providing additional uplinks to a backbone network,
which can be used to access resources in the Internet as well as to inter-link
multiple ad-hoc network partitions, creating a hybrid wireless network. In this
paper, we present a prototypically implemented hybrid wireless network system
optimized for multimedia content distribution. To efficiently manage the ad-hoc
communicating devices a weighted clustering algorithm is introduced. The
proposed localized algorithm deals with mobility, but does not require
geographical information or distances.Comment: 2nd ACM Workshop on Wireless Multimedia Networking and Performance
Modeling 2006 (ISBN 1-59593-485
Enhanced Cluster Based Routing Protocol for MANETS
Mobile ad-hoc networks (MANETs) are a set of self organized wireless mobile
nodes that works without any predefined infrastructure. For routing data in
MANETs, the routing protocols relay on mobile wireless nodes. In general, any
routing protocol performance suffers i) with resource constraints and ii) due
to the mobility of the nodes. Due to existing routing challenges in MANETs
clustering based protocols suffers frequently with cluster head failure
problem, which degrades the cluster stability. This paper proposes, Enhanced
CBRP, a schema to improve the cluster stability and in-turn improves the
performance of traditional cluster based routing protocol (CBRP), by electing
better cluster head using weighted clustering algorithm and considering some
crucial routing challenges. Moreover, proposed protocol suggests a secondary
cluster head for each cluster, to increase the stability of the cluster and
implicitly the network infrastructure in case of sudden failure of cluster
head.Comment: 6 page
Overlapping Multi-hop Clustering for Wireless Sensor Networks
Clustering is a standard approach for achieving efficient and scalable
performance in wireless sensor networks. Traditionally, clustering algorithms
aim at generating a number of disjoint clusters that satisfy some criteria. In
this paper, we formulate a novel clustering problem that aims at generating
overlapping multi-hop clusters. Overlapping clusters are useful in many sensor
network applications, including inter-cluster routing, node localization, and
time synchronization protocols. We also propose a randomized, distributed
multi-hop clustering algorithm (KOCA) for solving the overlapping clustering
problem. KOCA aims at generating connected overlapping clusters that cover the
entire sensor network with a specific average overlapping degree. Through
analysis and simulation experiments we show how to select the different values
of the parameters to achieve the clustering process objectives. Moreover, the
results show that KOCA produces approximately equal-sized clusters, which
allows distributing the load evenly over different clusters. In addition, KOCA
is scalable; the clustering formation terminates in a constant time regardless
of the network size
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