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Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints
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DOI：10.1007/s12083-017-0561-9.png)
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The explosive growth of mobile devices and the rapid development of wireless networks and mobile computing technologies have stimulated the emergence of many new computing paradigms, such as Fog Computing, Mobile Cloud Computing (MCC) etc. These newly emerged computation paradigms try to promote the mobile applications' Quality of Service (QoS) through allowing the mobile devices to offload their computation tasks to the edge cloud and provide their idle computation capabilities for executing other devices' offloaded tasks. Therefore, it is very critical to efficiently schedule the offloaded tasks especially when the available computation, storage, communication resources and energy supply are limited. In this paper, we investigate the MCC-assisted execution of multi-tasks scheduling problem in hybrid MCC architecture. Firstly, this problem is formulated as an optimization problem. Secondly, a Cooperative Multi-tasks Scheduling based on Ant Colony Optimization algorithm (CMSACO) is put forward to tackle this problem, which considers task profit, task deadline, task dependence, node heterogeneity and load balancing. Finally, a series of simulation experiments are conducted to evaluate the performance of the proposed scheduling algorithm. Experimental results have shown that our proposal is more efficient than a few typical existing algorithms.
Keyword:
Fog computing
Mobile cloud computing
Task scheduling
Ant colony optimization
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