The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
High Performance Scheduling Mechanism for Mobile Computing Based on Self-Ranking Algorithm
Abstract
Due to the rapidly increasing number of mobile devices connected to the Internet, a lot of research is being conducted to maximize the benefit of such integration. The main objective of this article is to enhance the performance of the scheduling mechanism of the mobile computing environment by distributing some of the responsibilities of the access point among the available attached mobile devices. To this aim, we investigate a scheduling mechanism framework that comprises an algorithm that provides the mobile device with the authority to evaluate itself as a resource. The proposed mechanism is based on the “self ranking algorithm” (SRA), which provides a lifetime opportunity to reach a proper solution. This mechanism depends on an event-based programming approach to start its execution in a pervasive computing environment. Using such a mechanism will simplify the scheduling process by grouping mobile devices according to their self-ranking value and assigning tasks to these groups. Moreover, it will maximize the benefit of the mobile devices incorporated with the already existing Grid systems by using their computational power as a subordinate value to the overall power of the system. Furthermore, we evaluate the performance of the investigated algorithm extensively, to show how it overcomes the connection stability problem of the mobile devices. Experimental results emphasized that the proposed SRA has a great impact in reducing the total error and link utilization compared with the traditional mechanism.
Related Content
|
Tapan Kumar Behera.
© 2023.
20 pages.
|
|
B. Narendra Kumar Rao.
© 2023.
17 pages.
|
|
Blendi Rrustemi, Deti Baholli, Herolind Balaj.
© 2023.
18 pages.
|
|
Alma Beluli.
© 2023.
11 pages.
|
|
Jona Ndrecaj, Shkurte Berisha, Erita Çunaku.
© 2023.
15 pages.
|
|
Yllka Totaj.
© 2023.
12 pages.
|
|
Hla Myo Tun, Devasis Pradhan.
© 2023.
31 pages.
|
|
|