An Innovative Approach for Solving Clock Drift Management Problem using Differential Evolution Algorithm
Nibha Tiwari1, Sheela Verma2
1Nibha Tiwari, M. Tech. Scholar, Department of Computer & Engineering, SSEC, Bhilai (C.G.), India.
2Sheela Verma, Asst. Processor, Department of Computer & Engineering, SSCET, Bhilai (C.G.), India.
Manuscript received on 18 October 2012 | Revised Manuscript received on 25 October 2012 | Manuscript published on 30 October 2012 | PP: 25-28 | Volume-1 Issue-4, October 2012 | Retrieval Number: D0320091412/2012©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: Like distributed systems, wireless sensors networks often require a synchronization of time for consistency and coordination of data. Time synchronization is a critical piece of infrastructure in any distributed system. Time synchronization is mostly required in wireless sensor network. Having time synchronization in sensor network it allows collective signal processing, and helps in efficient sharing of the communication channel. Time synchronization is a critical piece of infrastructure for any distributed system. Distributed, wireless sensor networks make extensive use of synchronized time, but often have unique requirements in the scope, lifetime, and precision of the synchronization achieved, as well as the time and energy required to achieve it. The protocol which was developed for time synchronization of wireless sensor networks was Flooding Time Synchronization Protocol (FTSP) In this paper, FTSP is taken under the consideration for clock drift management using differential evolution (DE) algorithm. The paper calculates clock skew and the clock offset, generates linear line and optimizes the value of average time synchronization error using Genetic and DE algorithm. This paper dictates implementation and experimental results that produce reduced average time synchronization error optimized using DE, compared to that of linear regression used in FTSP.
Keywords: Differential Evolution (DE), Flooding Time Synchronization Protocol (FTSP).Time Synchronization, Average Time Synchronization Error, Clock Drift, Wireless sensor network.
Scope of the Article: Wireless Sensor Networks