Enhanced Energy Storage and Management Scheme in MH-CRSNs with ACO Algorithm
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2019 by IJCTT Journal | ||
| Volume-67 Issue-4 |
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| 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.
Abstract
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.
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Keywords
CRCN, Energy harvesting, POMDP, ACO, Energy storage and management.