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M-ATTEMPT: A New Energy-Efficient Routing Protocol for Wireless Body Area Sensor Networks (1303.5260v1)

Published 21 Mar 2013 in cs.NI

Abstract: In this paper, we propose a new routing protocol for heterogeneous Wireless Body Area Sensor Networks (WBASNs); Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficientMulti-hop ProTocol (M-ATTEMPT). A prototype is defined for employing heterogeneous sensors on human body. Direct communication is used for real-time traffic (critical data) or on-demand data while Multi-hop communication is used for normal data delivery. One of the prime challenges in WBASNs is sensing of the heat generated by the implanted sensor nodes. The proposed routing algorithm is thermal-aware which senses the link Hot-spot and routes the data away from these links. Continuous mobility of human body causes disconnection between previous established links. So, mobility support and energy-management is introduced to overcome the problem. Linear Programming (LP) model for maximum information extraction and minimum energy consumption is presented in this study. MATLAB simulations of proposed routing algorithm are performed for lifetime and successful packet delivery in comparison with Multi-hop communication. The results show that the proposed routing algorithm has less energy consumption and more reliable as compared to Multi-hop communication.

Citations (165)

Summary

  • The paper presents M-ATTEMPT, a novel routing protocol for WBASNs combining direct and multi-hop communication with thermal awareness and an LP model to optimize energy and reliability.
  • Simulation results show M-ATTEMPT provides 20% longer stability and 29% enhanced network lifetime compared to existing methods due to improved energy efficiency and mobility management.
  • Practically, M-ATTEMPT is significant for reliable remote health monitoring and theoretically offers a framework for designing dynamic, heterogeneous wireless sensor network protocols.

M-ATTEMPT: An Energy-Efficient Routing Protocol for WBASNs

This paper presents the Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficient Multi-hop ProTocol (M-ATTEMPT), a novel routing algorithm designed specifically for heterogeneous Wireless Body Area Sensor Networks (WBASNs). Addressing challenges such as energy consumption, heat generation from implanted sensor nodes, and connectivity issues caused by continuous body movement, M-ATTEMPT offers noteworthy advancements in the domain of patient monitoring and physiological data management.

Key Contributions

M-ATTEMPT combines direct and multi-hop communication methods to optimize data transmission efficiency while preserving sensor node energy. Direct communication is employed for critical, real-time traffic, while multi-hop communication serves as the conduit for routine data. This dual approach overcomes the limitations of traditional multi-hop paradigms, such as increased sensor temperature and latency due to congestion or disconnections.

The protocol's thermal-aware feature mitigates potential tissue damage by detecting link hot-spots—areas of high temperature—and rerouting data to reduce heat impact. Additionally, M-ATTEMPT utilizes a Linear Programming (LP) model that strategically balances maximum data extraction with minimum energy use, ultimately prolonging network operation and bolstering packet delivery reliability.

Simulation and Results

Using MATLAB simulations, M-ATTEMPT was rigorously benchmarked against existing multi-hop communication methods. Results demonstrated superior energy efficiency and increased network stability, as evidenced by fewer dead nodes over time and improved throughput. Specifically, M-ATTEMPT realized a 20% longer stability period and a 29% enhancement in network lifetime compared to traditional multi-hop approaches. This is attributed to the integrated mobility management mechanism that ensures continuous link reestablishment when sensors reposition on the human body.

Practical and Theoretical Implications

Practically, the M-ATTEMPT protocol is poised to make significant contributions to remote health monitoring systems, wherein constant data transmission reliability and energy efficiency are paramount for patient safety and accurate diagnostics. The theoretical implications extend to the design of routing protocols for dynamic, heterogeneous networks, providing a framework that balances between energy conservation and robust data throughput.

Moving forward, future developments in AI can further enhance the adaptability and decision-making capabilities of such protocols, integrating more complex machine learning algorithms to predict and mitigate network disruptions before they occur. The modular nature of M-ATTEMPT also suggests potential for extensions into broader areas of wireless sensor networks beyond medical applications.

In conclusion, M-ATTEMPT stands as a pivotal development in the routing protocols for Wireless Body Area Networks, effectively addressing the unique challenges posed by the dynamic and heat-sensitive environments in which these sensors operate.