Abstract
Previous studies have considered scheduling schemes for Internet of Things (IoT)-based healthcare systems like First Come First Served (FCFS), and Shortest Job First (SJF). However, these scheduling schemes have limitations that range from large requests starving short requests, process starvation that results in long time to complete if short processes are continuously added, and performing poorly under overloaded conditions. To address the mentioned challenges, this paper proposes an analytical model of a prioritized scheme that provides service differentiation in terms of delay sensitive packets receiving service before delay tolerant packets and also in terms of packet size with the short packets being serviced before large packets. The numerical results obtained from the derived models show that the prioritized scheme offers better performance than FCFS and SJF scheduling schemes for both short and large packets, except the shortest short packets that perform better under SJF than the prioritized scheme in terms of mean slowdown metric. It is also observed that the prioritized scheme performs better than FCFS and SJF for all considered large packets and the difference in performance is more pronounced for the shortest large packets. It is further observed that reduction in packet thresholds leads to decrease in mean slowdown and the decrease is more pronounced for the short packets with larger sizes and large packets with shorter sizes.
Highlights
The recent advances in technologies have led to the emergence of Internet of Things (IoT) [1], [2] that interconnects everything around us, including sensors, devices and systems and supports a range of applications
Service differentiation is implemented, in this study, to differentiate the traffic based on the delay sensitivity of the traffic and based on the size of each packet, with the short packets being serviced before large packets in order to improve on the number of requests served per unit time
The numerical results www.ijacsa.thesai.org obtained from the derived models show the prioritized scheduling (PS) scheme generally reduces the mean slow down for most of the packet sizes considered
Summary
The recent advances in technologies have led to the emergence of Internet of Things (IoT) [1], [2] that interconnects everything around us, including sensors, devices and systems and supports a range of applications. While, scheduling traffic in healthcare systems, the following issues need to be addressed [13]: 1) Emergent medical situations should be given precedence in reporting than those with regular importance This is because excessive delays in the transmission of emergent medical situations may deteriorate health services to patients. Applying absolute priority rule can maintain the transmission priorities among different medical levels, but may lead to tremendously large waiting delays for “less important” packets and yet the “less important” medical packets are critical components of patients’ health profiles To address this issue, service differentiation is implemented, in this study, to differentiate the traffic based on the delay sensitivity of the traffic and based on the size of each packet, with the short packets being serviced before large packets in order to improve on the number of requests served per unit time.
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