Threshold Accepting Scheduling Algorithm for Scientific Workflows in Wireless Grids

Wireless grid is a collection of distributed computing resources such as low-powered mobile, patient monitoring sensors, wired grid and nomadic devices over a wide geographical connectivity that appear to an end-user as one large virtual computing system. The wireless grid has emerged as an attractive platform to tackle various large scale problems or applications, especially in science, medical and engineering. Key services such as resource discovery, monitoring, energy management and scheduling are inherently more complicated in a wireless grid environment. In this paper, we present a threshold accepting scheduling (TAS) mechanism to obtain the nearer-to-optimal solution faster on scheduling scientific workflows in wireless grids. In addition, we have compared the proposed scheduling mechanism with other mechanisms, namely, simulated annealing (SA) and the combination of genetic algorithm with local search (GA-LS) algorithm in terms of lateness, job completion ratio and average CPU running time. The computational results reveal that the proposed method is more effective.