A cluster-head selection and update algorithm for ad hoc networks

A novel cluster-head selection and update algorithm “Type-based Cluster-forming Algorithm (TCA)” is proposed, which outperforms both the lowest node ID (LID) and the Weighted Clustering Algorithm (WCA) in the ad hoc network scenario considered. The system’s performance is investigated in a scenario, when the 50 communicating nodes belong to three different groups, for example, a group of rescue workers, fire-fighters and paramedics. It is demonstrated that the carefully designed protocol is capable of outperforming the above-mentioned benchmarkers both in terms of a reduced number of cluster-head updates and cluster-change events. Hence its quality-of-service may be deemed higher

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

Energy Efficient Design of Wireless Ad Hoc Networks

The concept of wireless is not new. When the packet switching technology, the fabric of the Internet was introduced by the Department of Defense, the ARPANET ,it understood the potential of packet switched radio technology to interconnect mobile nodes .The DARPA around early 70’s helped establish the base of ad hoc wireless networking. This is a technology that enables untethered wireless networking environments where there is no wired or cellular infrastructure. Wireless Ad hoc Networks since then is a fast developing research area with a vast spectrum of applications. Wireless sensor network systems enable the reliable monitoring of a variety of environments for both civil and military applications. The Energy efficiency continues to be a key factor in limiting the deployability of ad-hoc networks. Deploying an energy efficient system exploiting the maximum lifetime of the network has remained a great challenge since years. The time period from the instant at which the network starts functioning to the time instant at which the first network node runs out of energy, i.e. the network lifetime is largely dependent on the system energy efficiency. This thesis looks at energy efficient protocols, which can have significant impact on the lifetime of these networks. The cluster heads get drain out maximum energy in the wireless ad hoc networks. The proposed algorithm deals with minimizing the rate of dissipation of energy of cluster heads. The algorithm LEAD deals with energy efficient round scheduling of cluster head followed by allocation of nodes to the cluster heads maximizing network lifetime using ANDA

Cluster-based Routing Protocols for Energy-Efficiency in Wireless Sensor Networks

22 page

Self-stabilizing cluster routing in Manet using link-cluster architecture

We design a self-stabilizing cluster routing algorithm based on the link-cluster architecture of wireless ad hoc networks. The network is divided into clusters. Each cluster has a single special node, called a clusterhead that contains the routing information about inter and intra-cluster communication. A cluster is comprised of all nodes that choose the corresponding clusterhead as their leader. The algorithm consists of two main tasks. First, the set of special nodes (clusterheads) is elected such that it models the link-cluster architecture: any node belongs to a single cluster, it is within two hops of the clusterhead, it knows the direct neighbor on the shortest path towards the clusterhead, and there exist no two adjacent clusterheads. Second, the routing tables are maintained by the clusterheads to store information about nodes both within and outside the cluster. There are two advantages of maintaining routing tables only in the clusterheads. First, as no two neighboring nodes are clusterheads (as per the link-cluster architecture), there is no need to check the consistency of the routing tables. Second, since all other nodes have significantly less work (they only forward messages), they use much less power than the clusterheads. Therefore, if a clusterhead runs out of power, a neighboring node (that is not a clusterhead) can accept the role of a clusterhead. (Abstract shortened by UMI.)