Volume 9, Issue 4, December 2014, Pages 1620–1625
Deepak Kapila1 and S. S. Gill2
1 Electronics & Communication, Chandigarh University, Gharuan, Mohali, Punjab, India
2 Electronics & Communication, Guru Nanak Dev Engg. College, Ludhiana, Punjab, India
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Wireless sensor networks consist of hundreds or thousands of applications such as environmental monitoring, traffic analysis, tactical systems and industrial process monitoring. Most of the packet-scheduling mechanisms of WSN use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms incur a high processing overhead and long end-to-end data transmission delay due to the FCFS concept .These algorithms are not dynamic to the changing requirements of WSN applications since their scheduling policies are predetermined. Developing packet scheduling algorithms in wireless sensor networks can efficiently enhance delivery of packets through wireless links. Packet scheduling can guarantee quality of service and improve transmission rate in wireless sensor networks. Considering this combination we are basically focusing on the nodes of wireless sensor network as the process required shortest coverage area to reach. We apply FCFS algorithm & priority algorithm for calculating delay. We can use it for mixing with coverage area for further process. After priority on the basis of time reduction we have to apply SJF (shortest job first) execution time finding. Finally, we have to compare on the basis of delay and execution time. Improve the performance of task scheduling schemes in terms of end to end delay and deadlock prevention.
Author Keywords: WSN, Scheduling, CPU, Delay, Matlab.
Deepak Kapila1 and S. S. Gill2
1 Electronics & Communication, Chandigarh University, Gharuan, Mohali, Punjab, India
2 Electronics & Communication, Guru Nanak Dev Engg. College, Ludhiana, Punjab, India
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Wireless sensor networks consist of hundreds or thousands of applications such as environmental monitoring, traffic analysis, tactical systems and industrial process monitoring. Most of the packet-scheduling mechanisms of WSN use First Come First Served (FCFS), non-preemptive priority and preemptive priority scheduling algorithms. These algorithms incur a high processing overhead and long end-to-end data transmission delay due to the FCFS concept .These algorithms are not dynamic to the changing requirements of WSN applications since their scheduling policies are predetermined. Developing packet scheduling algorithms in wireless sensor networks can efficiently enhance delivery of packets through wireless links. Packet scheduling can guarantee quality of service and improve transmission rate in wireless sensor networks. Considering this combination we are basically focusing on the nodes of wireless sensor network as the process required shortest coverage area to reach. We apply FCFS algorithm & priority algorithm for calculating delay. We can use it for mixing with coverage area for further process. After priority on the basis of time reduction we have to apply SJF (shortest job first) execution time finding. Finally, we have to compare on the basis of delay and execution time. Improve the performance of task scheduling schemes in terms of end to end delay and deadlock prevention.
Author Keywords: WSN, Scheduling, CPU, Delay, Matlab.
How to Cite this Article
Deepak Kapila and S. S. Gill, “A Hybrid Approach for Scheduling in WIMAX for Reduction of Process Waiting Time,” International Journal of Innovation and Applied Studies, vol. 9, no. 4, pp. 1620–1625, December 2014.
