International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 186 - Number 15 |
Year of Publication: 2024 |
Authors: Manideep Yenugula |
10.5120/ijca2024923483 |
Manideep Yenugula . Markov Chain-based Optimization for Efficient and Reliable Wireless Sensor Networks: A Comprehensive Analysis and Enhanced TDMA-CSMA Hybrid Protocol. International Journal of Computer Applications. 186, 15 ( Apr 2024), 7-13. DOI=10.5120/ijca2024923483
This paper presents a comprehensive analysis of various protocols using Markov chain-based optimization techniques for wireless sensor networks (WSNs). Markov chain models have been used to address the challenges faced by WSNs, including limited resources, QoS requirements, energy consumption, network reliability, adaptability, and real-time decision-making. An Enhanced TDMA-CSMA Hybrid protocol is proposed to overcome existing protocol limitations. It combines the advantages of TDMA and CSMA, dynamically allocating time slots based on traffic patterns. The protocol incorporates collision avoidance mechanisms, synchronization techniques, and energy-saving mechanisms to reduce delay, improve network throughput, and enhance reliability in wireless networks. Through performance analysis and comparison with existing protocols, the proposed Enhanced TDMA-CSMA Hybrid protocol demonstrates its superiority in terms of throughput, delay, channel utilization, and energy consumption. This research contributes to efficient and reliable communication in wireless networks, benefiting IoT, smart cities, and industrial automation applications.