A new efficient error control algorithm for wireless sensor networks in smart grid – sciencedirect gas constant for air

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Error detection and correction is an important issue in the design and maintenance of a smart grid communication network to provide reliable communication between sender and receiver. Various error-control coding techniques are employed to reduce bit error rates (BER) in wireless sensor networks (WSNs). The performance of these techniques is also compared and evaluated to find the most suitable technique for WSNs. This is the first study to compare the most efficient coding techniques in the smart grid environment, and it suggests b games 2 a new error correction algorithm based on this comparison result. Therefore, this article first examines and compares two forward error control (FEC) coding techniques such as Bose-Chaudhuri-Hochquenghem code (BCH electricity youtube billy elliot) and Reed Solomon code (RS) with various modulation methods including frequency shift keying (FSK), offset quadrature phase-shift keying (OQPSK), and differential phase shift keying (DPSK) in a 500 kV line-of-sight (LoS) substation smart grid environment. Second, as a result of this comparison, a new adaptive error control (AEC) algorithm is proposed. Adaptive error control adaptively changes error correction code (ECC) based on the channel behavior that is observed through the packet error rate (PER) in the recent previous transmissions. The link-quality-aware capacitated minimum hop spanning tree (LQ-CMST) algorithm and the multi-channel scheduling algorithm are used for data transmission over the log-normal channel. Therefore electricity worksheets ks1, the performance of compared coding techniques and AEC are also evaluated when multiple channels are used during transmission. Further, AEC is compared with static RS and without-FEC methods based on performance metrics such as the throughput, BER, and delay in different smart grid environments, e.g., 500 kV Substation (LoS), underground network transformer vaults (UTV) (LoS), and main power control room (MPR) (LoS). Our simulation results indicate that the proposed AEC algorithm achieves better performances than all those techniques.

Vehbi Cagri Gungor received 76 gas station jobs his B.S. and M.S. degrees in Electrical and Electronics Engineering from METU, Ankara, Turkey, in 2001 and 2003, respectively. He received his Ph.D. degree in electrical and computer engineering from the Broadband and Wireless Networking Laboratory, Georgia Institute of Technology, Atlanta, GA, USA, in 2007. Currently, he is a Professor and Chair of Computer Engineering Department, Abdullah electricity dance moms episode Gul University (AGU), Kayseri, Turkey. His current research interests are in smart grid communications, machine-to-machine communications, next-generation wireless networks, wireless ad hoc and sensor networks, cognitive radio networks, and IP networks. Dr. Gungor has authored several papers in refereed journals and international conference proceedings, and has been serving as an editor, reviewer and program committee member to numerous journals and conferences in these areas. He is also the recipient of the e payment electricity bill mp IEEE Trans. on Industrial Informatics Best Paper Award in 2012, the European Union FP7 Marie Curie IRG Award in 2009, Turk Telekom Research Grant Awards in 2010 and 2012, and the San-Tez Project Awards supported by Alcatel-Lucent, and the Turkish Ministry of Science, Industry and Technology in 2010. View full text