Abstract
In most existing cases, the computing time of edge devices are assumed consecutive. This is impractical because edge servers are selfish in nature. As a consequence, edge servers have higher priority to process their own tasks. This delays computing for both mobile end users and neighboring edge servers, causing service quality degradation. We design an offloading network with edge-edge collaboration accounting for interrupted service time. Dependent subtasks of an application can be offloaded to each available computing intervals on edge devices. Our aim is to minimize the total application completion time. We formulate the problem as a mixed integer non-linear programming, and prove it is NP-hard. When global knowledge is known before offloading, we propose a greedy off-line algorithm GKGO to offload subtasks among edge devices. Real-world trace experiments show that the proposed algorithm outperforms benchmark algorithm by over \(50\%\) on the average application completion time.
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Notes
- 1.
In the next paragraphs, we use private time slots and primary time slots interchangeably.
- 2.
It is worthy noting that the size could be any possible size within \(T_n\), because the real available interval start time is adjusted via some distributions within each generating window. And the total available computing time of edge device n is controlled by \(\gamma _n\). As shown in Fig. 2.
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Acknowledgement
This work was supported by the Guangzhou Municipal Science and Technology Bureau Research Project on Basic and Applied Basic Research. Part of this work was supported by the National Natural Science Foundation of China under grant no. 62072118.
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Zhou, B., Chen, L., Wu, J. (2021). Available Time Aware Offloading for Dependent Tasks with Cooperative Edge Servers. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12937. Springer, Cham. https://doi.org/10.1007/978-3-030-85928-2_38
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