Improving sensor network robustness with multi-channel convergecast

Intenerg

Precise Packet Loss Pattern Generation by Intentional Interference

Abstract—Intermediate-quality links often cause vulnerable connectivity in wireless sensor networks, but packet losses caused by such volatile links are not easy to trace. In order to equip link layer protocol designers with a reliable test and debugging tool, we develop a reactive interferer to generate packet loss patterns precisely. By using intentional interference to emulate parameterized lossy links with very low intrusiveness, our tool facilitates both robustness evaluation of protocols and flaw detection in protocol implementation

New Method of Measuring TCP Performance of IP Network using Bio-computing

The measurement of performance of Internet Protocol IP network can be done by Transmission Control Protocol TCP because it guarantees send data from one end of the connection actually gets to the other end and in the same order it was send, otherwise an error is reported. There are several methods to measure the performance of TCP among these methods genetic algorithms, neural network, data mining etc, all these methods have weakness and can't reach to correct measure of TCP performance. This paper proposed a new method of measuring TCP performance for real time IP network using Biocomputing, especially molecular calculation because it provides wisdom results and it can exploit all facilities of phylogentic analysis. Applying the new method at real time on Biological Kurdish Messenger BIOKM model designed to measure the TCP performance in two types of protocols File Transfer Protocol FTP and Internet Relay Chat Daemon IRCD. This application gives very close result of TCP performance comparing with TCP performance which obtains from Little's law using same model (BIOKM), i.e. the different percentage of utilization (Busy or traffic industry) and the idle time which are obtained from a new method base on Bio-computing comparing with Little's law was (nearly) 0.13%. KEYWORDS Bio-computing, TCP performance, Phylogenetic tree, Hybridized Model (Normalized), FTP, IRCDComment: 17 Pages,10 Figures,5 Table

Optimization of scale-free network for random failures

It has been found that the networks with scale-free distribution are very resilient to random failures. The purpose of this work is to determine the network design guideline which maximize the network robustness to random failures with the average number of links per node of the network is constant. The optimal value of the distribution exponent and the minimum connectivity to different network size are given in this paper. Finally, the optimization strategy how to improve the evolving network robustness is given.Comment: 6 pages, 1 figur