The integration of ad hoc sensor and cellular networks for multi-class data transmission

  • Authors:
  • Fei Hu;Sunil Kumar

  • Affiliations:
  • Computer Engineering, RIT, 83 Lomb memorial Drive, Rochester, NY 14623-5603, United States;Electrical and Computer Engineering, Clarkson University, P.O. Box 5720, Potsdam, NY 13699-5720, United States

  • Venue:
  • Ad Hoc Networks
  • Year:
  • 2006

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Abstract

This paper targets mobile telemedicine applications that can be supported using third generation (3G) cellular networks, to provide highly flexible medical services. On the other hand, large-scale Ad hoc Sensor Networks (ASN), when deployed among mobile patients who may carry different kinds of micro-sensors to measure ECG, blood pressure, basal temperature or other physiological data, can provide a dynamic data query architecture to allow the medical specialists to monitor patients at any place. So far very little research has been conducted to explore the possibility of integrating ASN with mobile telemedicine. In this paper: 1. we suggest an integrated architecture that takes advantage of the low cost mobile sensor networks and 3G cellular networks to support multimedia medical calls with differentiated Quality-of-Service (QoS) requirements. 2. We propose a low-energy, distributed, concentric-zone-based data query mechanism that has the advantages of both proactive and reactive ad hoc routing algorithms to collect medical results from large-scale mobile patients for medical specialists who use cellular network to report patient data to the medical center. 3. In order to minimize the ambulance wireless call-dropping rate, we adopt accurate resource reservation call admission control (CAC) scheme to allocate the necessary bandwidth in the destination cell. 4. In order to meet the QoS requirements of patients' wireless calls, we use dynamic guard channel CAC scheme to keep their handoff-call dropping rate below a certain threshold. We evaluate the validity of our schemes through simulations and analyze their performance. Our results clearly indicate the efficiency of the proposed CAC and sensor network query algorithms to meet the multimedia telemedicine QoS requirements.