Affiliation:
1. University of Science and Technology of China, China
2. University of Science and Technology of China, China and USTC-Deqing Alpha Innovation Research Institute, China
3. Center on Frontiers of Computing Studies, Peking University, China
4. Microsoft Research Asia, China
Abstract
In Mobile Edge Computing, edge servers have limited storage and computing resources that can only support a small number of functions. Meanwhile, mobile applications are becoming more complex, consisting of multiple dependent tasks, modeled as a Directed Acyclic Graph (DAG). When a request arrives, typically in an online manner with a deadline specified, we need to configure the servers and assign the dependent tasks for efficient processing. This work jointly considers the problem of dependent task placement and scheduling with on-demand function configuration on edge servers, aiming to meet as many deadlines as possible. For a single request, when the configuration on each edge server is fixed, we derive
FixDoc
to find the optimal task placement and scheduling. When the on-demand function configuration is allowed, we propose
GenDoc
, a novel approximation algorithm, and analyze its additive error from the optimal theoretically. For multiple requests, we derive
OnDoc
, an online algorithm easy to deploy in practice. Our extensive experiments show that
GenDoc
outperforms state-of-the-art baselines in processing 86.14% of these unique applications, and reduces their average completion time by at least 24%. The number of deadlines that
OnDoc
can satisfy is at least 1.9× that of the baselines.
Funder
National Key R&D Program of China
NSFC
Fundamental Research Funds for the Central Universities at China
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
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