TODG: Distributed Task Offloading with Delay Guarantees for Edge Computing
Sheng Yue, Ju Ren, Nan Qiao, Yongmin Zhang, Hongbo Jiang, Yaoxue, Zhang, Yuanyuan Yang

TL;DR
This paper introduces TODG, a distributed online algorithm for task offloading in edge computing that guarantees delay constraints and adapts to stochastic environments, improving resource allocation and performance in IoT applications.
Contribution
The paper proposes TODG, a novel distributed online algorithm for delay-constrained task offloading in edge computing, addressing multiple issues simultaneously.
Findings
TODG effectively guarantees delay constraints in stochastic environments.
Simulation results show improved resource utilization and task completion times.
The approach outperforms existing methods in complex, practical scenarios.
Abstract
Edge computing has been an efficient way to provide prompt and near-data computing services for resource-and-delay sensitive IoT applications via computation offloading. Effective computation offloading strategies need to comprehensively cope with several major issues, including the allocation of dynamic communication and computational resources, the deadline constraints of heterogeneous tasks, and the requirements for computationally inexpensive and distributed algorithms. However, most of the existing works mainly focus on part of these issues, which would not suffice to achieve expected performance in complex and practical scenarios. To tackle this challenge, in this paper, we systematically study a distributed computation offloading problem with hard delay constraints, where heterogeneous computational tasks require continually offloading to a set of edge servers via a limiting…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Age of Information Optimization · Stochastic Gradient Optimization Techniques
