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This study introduces DT-MAC, an enhanced wireless sensor network protocol for healthcare applications. DT-MAC significantly improves packet delivery and response times, addressing challenges in mobile body area networks.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless sensor networks (WSNs) are crucial for IoT applications, but face challenges like low node computing capacity and message loss in mobile healthcare body area networks.
  • Mobility in healthcare WSNs can lead to topological manipulation and significant message loss, impacting network reliability.
  • Existing protocols like MT-MAC struggle with efficient message delivery in dynamic healthcare environments.

Purpose of the Study:

  • To propose an enhanced algorithm, DT-MAC, for wireless sensor networks to ensure successful message delivery in mobile healthcare applications.
  • To improve network integrity and energy utilization through a novel node handover mechanism and minimum connected dominating set for network formation.
  • To evaluate the performance of DT-MAC against existing algorithms like MT-MAC.

Main Methods:

  • Developed DT-MAC, an enhanced version of the MT-MAC algorithm.
  • Incorporated a node handover mechanism within virtual clusters to maintain network integrity.
  • Utilized the concept of minimum connected dominating set for efficient network formation and energy utilization.

Main Results:

  • DT-MAC demonstrated a 13-17% improvement in packet delivery compared to MT-MAC.
  • The proposed protocol achieved a 15% improvement in response time.
  • A marginal increase of approximately 3% in latency was observed with DT-MAC.

Conclusions:

  • DT-MAC is highly suitable for real-time applications requiring high packet delivery and rapid response times.
  • The enhanced protocol effectively addresses message loss and network integrity issues in mobile healthcare WSNs.
  • DT-MAC offers a superior solution for reliable data transmission in challenging wireless sensor network environments.