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Dhipa, M.
- Enhancing Energy Efficiency in Sensor/Ad-Hoc Networks Through Dynamic Sleep Scheduling
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Authors
Affiliations
1 Department of Biomedical Engineering, Nandha Engineering College, IN
2 Department of Computer Science and Engineering, Amity University, Raipur, IN
3 Department of Computer Engineering, A.P. Shah Institute of Technology, IN
4 Department of Computer Science, College of Computer Science and Information Technology, Jazan University, SA
1 Department of Biomedical Engineering, Nandha Engineering College, IN
2 Department of Computer Science and Engineering, Amity University, Raipur, IN
3 Department of Computer Engineering, A.P. Shah Institute of Technology, IN
4 Department of Computer Science, College of Computer Science and Information Technology, Jazan University, SA
Source
ICTACT Journal on Communication Technology, Vol 14, No 3 (2023), Pagination: 2974-2981Abstract
Enhancing energy efficiency is a pivotal concern in sensor/ad-hoc networks, where devices are often constrained by limited power sources. Dynamic sleep scheduling emerges as a promising strategy to mitigate energy wastage and prolong network longevity. This approach involves orchestrating nodes to periodically transition between active and low-power sleep modes, aligning with data transmission requirements. Dynamic sleep scheduling optimizes energy usage, curbing the power-hungry nature of constant operation. This abstract explores the core concepts and applications of dynamic sleep scheduling, emphasizing its role in addressing the unique energy challenges encountered in sensor/ad-hoc networks. The benefits of dynamic sleep scheduling include extending network lifespan, minimizing interference, and promoting energy balance among nodes. Nevertheless, it also presents challenges like adapting to network dynamics, striking the right balance between energy savings and latency, and ensuring effective coordination among nodes. Various algorithms, including TDMA and LEACH, underpin dynamic sleep scheduling, with ongoing research driving advancements. These networks find application in environmental monitoring, disaster management, and industrial automation, among others.Keywords
Dynamic Sleep Scheduling, Sensor Networks, Ad-Hoc Networks, Energy Efficiency, Network Longevity.
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