Energy-Aware Task Scheduling: Towards Enabling Mobile Computing over MANETs

  • Authors:
  • Waleed Alsalih;Selim Akl;Hossam Hassanein

  • Affiliations:
  • Queen's University Kingston, ON, Canada;Queen's University Kingston, ON, Canada;Queen's University Kingston, ON, Canada

  • Venue:
  • IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 12 - Volume 13
  • Year:
  • 2005

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Abstract

Enabling high performance, persistent mobile computing has recently become a very active research area. The widespread popularity of mobile computing devices, such as laptops, handheld devices and cell phones, as well as the recent advances in wireless communication technologies are the principal motivators of this research area. However, battery energy limitation is the main challenge towards enabling persistent mobile computing. Several hardware based techniques have been proposed; this has led to more energy-efficient systems. Nevertheless, the problem still remains and there is a consensus that software based techniques have the potential to reduce energy demand and contribute to solve the problem. In this paper, we look into the problem of distributing computational tasks amongst a set of mobile computing devices in a Mobile wireless Ad hoc NETwork (MANET) in such a way that conserves energy and improves performance. In such a distributed environment, the assignment of computational tasks to different devices and the order of their execution play a vital role in energy conservation and performance improvement. The main contributions of this paper are formulating a novel energy-aware scheduling problem and proposing a heuristic algorithm to solve it. Our scheduling algorithm schedules a set of computational tasks, which may have dependencies and communication, into a set of heterogeneous processors in such a way that minimizes both the total consumed energy and the makespan (i.e., the time by which all tasks complete their execution). Experiments show that significant improvement can be achieved by using our scheduler.