Enhanced Energy Storage and Management Scheme in MH-CRSNs with ACO Algorithm
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2019 by IJCTT Journal|
|Year of Publication : 2019|
|Authors : Shabeeba E, Harikrishnan N|
|DOI : 10.14445/22312803/IJCTT-V67I4P111|
MLA Style: Shabeeba E, Harikrishnan N "Enhanced Energy Storage and Management Scheme in MH-CRSNs with ACO Algorithm" International Journal of Computer Trends and Technology 67.4 (2019): 49-54.
APA Style:Shabeeba E, Harikrishnan N (2019). Enhanced Energy Storage and Management Scheme in MH-CRSNs with ACO Algorithm. International Journal of Computer Trends and Technology, 67(4), 49-54.
Energy efficient scheme in cognitive radio sensor networks (CRSNs) has many advantages compared to traditional networks. In cognitive radio (CR) system, the efficiency of the routing algorithm directly affects the system performance. We propose an energy storage and management scheme for improving network throughput and energy efficiency. Energy harvesting is adopted in cognitive radio sensor networks with battery-free secondary users that perform multi-hop transmission to reduce the network congestion and data loss. The proposed scheme is designed based on partially observable Markov decision process (POMDP) framework. In the case of multi-hop energy harvesting, in order to minimize the delay and energy consumption, an optimization concept is introduced which is named as Ant Colony Optimization (ACO). By using this method, shortest path from source node to the sink node is obtained and delay as well as consumption of energy is reduced. The simulation results show that the proposed scheme operates energy-efficiently while properly protecting packet loss.
 Gyanendra Prasad Joshi, SeungYeob Nam and Sung Won Kim, ?Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends?. Sensors, 13(9), 11196–11228.
 Xiao-ou Song, ?Utilization and Fairness in Spectrum Assignment for Cognitive Radio Networks: An Ant Colony Optimization’s Perspective? 2014 International Conference on Wireless Communication and Sensor Network.
 C. Peng, H. Zheng and B. Y. Zhao: ?Utilization and fairness in spectrum assignment for opportunistic spectrum access? ACM Mobile Networks and Applications, vol. 11(2006), p. 555-576.
 Z. Zhao, Z. Peng, S. Zheng, and J Shang: ?Cognitive radio spectrum allocation using evolutionary algorithms? IEEE Trans. Mobile Commun, vol. 8(2009), p. 4421-4425.
 Y. H. Li, P. Wan, Y. H. Wang, Q. Deng, and J. Yang: ?Cognitive radio spectrum assignment based on binary bacterial forging optimization algorithm? Computer Science, vol. 40 (2013), p. 49-52.
 H. Y. Gao, J. L. Cao: ?Quantum-inspired bee colony optimization algorithm and its application for cognitive radio spectrum allocation? Journal of Central South University, vol. 43(2012), p. 4743-4749.
 B. W. Zhang, Y. L. Zhang and K. Y. Zhang: ?Spectrum assignment algorithm based on particle swarm optimization for cognitive radio? Journal of Computer Applications, vol. 31 (2011), p. 3184-3186.
 Tu-Liang Lin, Yu-Sheng Chen, Hong-Yi Chang ?Performance Evaluations of an Ant Colony Optimization Routing Algorithm for Wireless Sensor Networks? 2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.
 V. Kawadia and P. Kumar, "Power control and clustering in ad hoc networks," in INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies, 2003, pp. 459-469.
 Yanjie Li, Baoqun Yin, and Hongsheng Xi ?Partially Observable Markov Decision Processes and Performance Sensitivity Analysis? IEEE transactions on systems, man, and cybernetics—part b: cybernetics, vol. 38, no. 6, december 2008
 Yanlong Li, Junyi Wang, YuqingQu, Mei Wang, HongbingQiu ?A New Energy-efficient Transmission SchemeBased Ant Colony Algorithm for Wireless SensorNetworks?2013 8th International Conference on Communications and Networking in China (CHINACOM)
CRCN, Energy harvesting, POMDP, ACO, Energy storage and management.