Abstract
The edge computing paradigm is featured by the ability to offload computing tasks from mobile devices to edge clouds and provide high cost-efficient computing resources, storage and network services closer to the edge. A key question for workflow scheduling in the edge computing environment is how to reduce the monetary cost while fulfilling Service-Level-Agreement in terms of performance and quality-of-service requirements. However, it’s still a challenge to guarantee user-perceived quality of service of applications deployed upon edge infrastructures due to the fact that such applications are constantly subject to negative impacts, e.g., network congestions, unexpected long message delays, shrinking coverage range of edge servers due to battery depletion. In this paper, we study the multi-workflow scheduling problem and propose a novel approach to Cost-Efficient Scheduling of Multi-Workflows in the Edge Computing Environment With Proximity Constraint. The proposed approach aims at minimizing edge computing costs while meeting user-specified workflow completion deadlines and leverages a discrete firefly algorithm for yielding the scheduling plan. We conduct experimental case studies based on multiple well-known scientific workflow templates and a real-world dataset of edge resource locations as well. Experimental results clearly suggest that our proposed approach outperforms traditional ones in terms of cost and makespan.
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Acknowledgment
This work is in part supported by Fundamental Research Funds for the Central Universities under project Nos. 106112014CDJZR185503 and CDJZR12180012; Science foundation of Chongqing Nos. cstc2014jcyjA40010 and cstc2014jcyjA90027; Chongqing Social Undertakings and Livelihood Security Science and Technology Innovation Project Special Program No. cstc2016shms-zx90002; China Postdoctoral Science Foundation No. 2015M570770; Chongqing Postdoctoral Science special Foundation No. Xm2015078; Universities Sci-tech Achievements Transformation Project of Chongqing No. KJZH17104.
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Ma, Y. et al. (2020). A Novel Approach to Cost-Efficient Scheduling of Multi-workflows in the Edge Computing Environment with the Proximity Constraint. In: Wen, S., Zomaya, A., Yang, L. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2019. Lecture Notes in Computer Science(), vol 11944. Springer, Cham. https://doi.org/10.1007/978-3-030-38991-8_43
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