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Author: search.filters.author.Ben Othman, JalelSubject: search.filters.subject.Congestion control

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    CCS_WHMS: A Congestion Control Scheme for Wearable Health Management System
    (Springer Link, 2015-10-21) Kafi, Mohamed Amine; Ben Othman, Jalel; Bagaa, Miloud; Badache, Nadjib
    Wearable computing is becoming a more and more attracting field in the last years thanks to the miniaturisation of electronic devices. Wearable healthcare monitoring systems (WHMS) as an important client of wearable computing technology has gained a lot. Indeed, the wearable sensors and their surrounding healthcare applications bring a lot of benefits to patients, elderly people and medical staff, so facilitating their daily life quality. But from a research point of view, there is still work to accomplish in order to overcome the gap between hardware and software parts. In this paper, we target the problem of congestion control when all these healthcare sensed data have to reach the destination in a reliable manner that avoids repetitive transmission which wastes precious energy or leads to loss of important information in emergency cases, too. We propose a congestion control scheme CCS_WHMS that ensures efficient and fair data delivery while used in the body wearable system part or in the multi-hop inter bodies wearable ones to get the destination. As the congestion detection paradigm is very important in the control process, we do experimental tests to compare between state of the art congestion detection methods, using MICAz motes, in order to choose the appropriate one for our scheme.
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    CCS_WHMS: A Congestion Control Scheme for Wearable Health Management System
    (Springer US, 2015-12) Kafi, Mohamed Amine; Ben Othman, Jalel; Bagaa, Miloud; Badache, Nadjib
    Wearable computing is becoming a more and more attracting field in the last years thanks to the miniaturisation of electronic devices. Wearable healthcare monitoring systems (WHMS) as an important client of wearable computing technology has gained a lot. Indeed, the wearable sensors and their surrounding healthcare applications bring a lot of benefits to patients, elderly people and medical staff, so facilitating their daily life quality. But from a research point of view, there is still work to accomplish in order to overcome the gap between hardware and software parts. In this paper, we target the problem of congestion control when all these healthcare sensed data have to reach the destination in a reliable manner that avoids repetitive transmission which wastes precious energy or leads to loss of important information in emergency cases, too. We propose a congestion control scheme CCS_WHMS that ensures efficient and fair data delivery while used in the body wearable system part or in the multi-hop inter bodies wearable ones to get the destination. As the congestion detection paradigm is very important in the control process, we do experimental tests to compare between state of the art congestion detection methods, using MICAz motes, in order to choose the appropriate one for our scheme.
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    Congestion Detection Strategies in Wireless Sensor Networks: A Comparative Study with Testbed Experiments
    (Elsevier, 2014) Kafi, Mohamed Amine; Djenouri, Djamel; Ben Othman, Jalel; Ouadjaout, Abdelraouf; Badache, Nadjib
    Event based applications of Wireless Sensor Networks (WSNs) are prone to traffic congestion, where unpredicted event detection yields simultaneous generation of traffic at spatially co-related nodes, and its propagation towards the sink. This results in loss of information and waste energy. Early congestion detection is thus of high importance in such WSN applications to avoid the propagation of such a problem and to reduce its consequences. Different detection metrics are used in the congestion control literature. However, a comparative study that investigates the different metrics in real sensor motes environment is missing. This paper focuses on this issue and compares some detection metrics in a testbed network with MICAz motes. Results show the effectiveness of each method in different scenarios and concludes that the combination of buffer length and channel load constitute the better candidate for early and fictive detection.