Abstract
Edge computing is an emerging computing model that extends the cloud and its services to the edge of network. In edge-cloud computing, a set of servers are deployed near the mobile devices such that these devices can offload tasks to the servers with low latency. Most existing works usually focus on offloading tasks under the premise that sufficient resources are owned by edge servers while ignoring budget constraint of user. If failed to consider about this, the existing offloading schemes may cause user to overspend, this is unacceptable to user. Thus, in this paper, we investigate the task offloading problem in edge-cloud computing aiming to minimize the task duration while tasks are generated by user with constrainted budget. Besides edge servers are equipped with limited computation and storage resources. Specifically, the problem we formulate is an NP-hard problem. In order to solve it, we propose a heuristic strategy. The simulation results prove that the proposed scheme can improve the success ratio and reduce the task duration, compared to random and greedy offloading schemes.
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Acknowledgement
This paper is supported by the NSFC under Grant No. 61472383, U1709217, and 61472385, and the Natural Science Foundation of Jiangsu Province in China under No. BK20161257.
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He, L., Xu, H., Wang, H., Huang, L., Ma, J. (2018). Task Offloading in Edge-Clouds with Budget Constraint. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_25
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DOI: https://doi.org/10.1007/978-3-030-05057-3_25
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