WCA-DGVC: A Weight Clustering Algorithm for Decentralized Group Key Management with Variable size Cluster
Pooja Singh1, Nasib Singh Gill2
1Pooja Singh, Department of Computer Science, Govt. College for Women, Faridabad, (U.P), India.
2Nasib Singh Gill, Department of Computer Scienceand Applications, Maharshi Dayanand University, Rohtak, (Haryana), India.
Manuscript received on 24 January 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 January 2019 | PP: 82-87 | Volume-7 Issue-6, March 2019 | Retrieval Number: E1968017519©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless Ad hoc networks are experiencing a rapid increase in its applicability as well as in security threats. The wireless communication medium makes them highly prone to security attacks. Key management plays a vital role in secured communication. Power efficient and secure key management is one of its major requirements. Group key management is a promising approach for efficient cryptographic key management for MANETs. In this paper, we proposed a weight clustering algorithm for a decentralized group key management. The whole network is divided into smaller subgroups called clusters. The cluster is locally managed by the cluster head (CH). The CHs mutually manage the security key process. All nodes have equal opportunities to take part in CH selection. The CHs are selected by a weight clustering algorithm based on the computational power and the neighbor count of the node. The elected CH selects next CH from its neighbor by comparing their computational power, neighbor nodes and their distance from it. This eliminates the need of gateway nodes for inter-cluster communications. The size of the cluster is directly proportional to the weight of the cluster head that is the cluster head with high weight will manage the large cluster. Therefore the group key management activities are proportionally divided among the cluster heads according to their power. This eliminates the risk of frequent drowning of cluster heads. The performance of our algorithm is assessed through stimulation and compare with two popular weight clustering algorithms.
Keywords: Cluster, Decentralized group key management, weight clustering algorithm, Wireless ad hoc ntwork.
Scope of the Article: Wireless Communication