• Journal of KIISE:Computer Systems and Theory
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• v.29 no.1
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• pp.10-15
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• 2002

This paper proposes the Pipelined Broadcast that broadcasts a message of size m in O(m+n-1) time in an n-dimensional hypercube. It is based on the replication tree, which is derived from the reachable sets. It greatly improves the performance compared to Ho-Kao s algorithm with the time of O(m[n/log(n+1)]). The communication in the broadcast uses all-port wormhole router with message replication capability. This paper includes the algorithm together with performance comparisons to previous schemes in practical implementation.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.2
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• pp.65-74
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• 2002

Recently star networks are considered as attractive alternatives to the widely used hypercube for interconnection networks in parallel processing systems by many researchers. One of the fundamental communication problems on star graph networks is broadcasing In this paper we consider the broadcasting problems in star graph networks using wormhole routing. In wormhole routed system minimizing link contention is more critical for the system performance than the distance between two communicating nodes. We use Hamiltonian paths in star graph to set up link-disjoint communication paths We present a broadcast algorithm in n-dimensional star graph of N(=n!) nodes such that the total completion time is no larger than $([long_n n!]+1)$ steps where $([long_n n!]+1)$ is the lower bound This result is significant improvement over the previous n-1 step broadcasting algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4644-4661
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• 2015

Wireless sensor networks are often organized in the form of clusters leading to the new framework of WSN called cluster or hierarchical WSN where each cluster head is responsible for its own cluster and its members. These hierarchical WSN are prone to various routing layer attacks such as Black hole, Gray hole, Sybil, Wormhole, Flooding etc. These routing layer attacks try to spoof, falsify or drop the packets during the packet routing process. They may even flood the network with unwanted data packets. If one cluster head is captured and made malicious, the entire cluster member nodes beneath the cluster get affected. On the other hand if the cluster member nodes are malicious, due to the broadcast wireless communication between all the source nodes it can disrupt the entire cluster functions. Thereby a scheme which can detect both the malicious cluster member and cluster head is the current need. Abnormal energy consumption of nodes is used to identify the malicious activity. To serve this purpose a learning based energy prediction algorithm is proposed. Thus a two level energy prediction based intrusion detection scheme to detect the malicious cluster head and cluster member is proposed and simulations were carried out using NS2-Mannasim framework. Simulation results achieved good detection ratio and less false positive.