Latency and Reliability-Aware Task Offloading and Resource Allocation for Mobile Edge Computing

By Chen-Feng Liu, Medhi Bennis, H. Vincent Poor. 2017

188 citations recorded by the source corpus.

While mobile edge computing (MEC) alleviates the computation and power limitations of mobile devices, additional latency is incurred when offloading tasks to remote MEC servers. In this work, the power-delay tradeoff in the context of task offloading is studied in a multi-user MEC scenario. In contrast with current system designs relying on average metrics (e.g., the average queue length and average latency), a novel network design is proposed in which latency and reliability constraints are taken into account. This is done by imposing a probabilistic constraint on users' task queue lengths and invoking results from extreme value theory to characterize the occurrence of low- probability events in terms of queue length (or queuing delay) violation. The problem is formulated as a computation and transmit power minimization subject to latency and reliability constraints, and solved using tools from Lyapunov stochastic optimization. Simulation results demonstrate the effectiveness of the proposed approach, while examining the power-delay tradeoff and required computational resources for various computation intensities.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

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Citations in the corpus

Wireless Edge Computing With Latency and Reliability Guarantees (2019, methodology): “Extreme Event-Controlled MEC : For the extreme event-controlling computation and communication co-design in [99], [100], we studied a multi-user MEC scenario as shown in Fig.”
Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale (2018, background): “Although mobile devices can wirelessly oﬄoad their computation-intensive tasks to proximal MEC servers, oﬄoading tasks incurs extra latency.”
A Tutorial on Ultrareliable and Low-Latency Communications in 6G: Integrating Domain Knowledge Into Deep Learning (2021, background): “Liu et al. [92] minimized the average power consumption of users subject to the constraint on delay bound violation probability.”
Multi-Objective Resource Optimization for Hierarchical Mobile Edge Computing (2018, methodology): “of researchers have proposed techniques to minimize task latency [4] or maximize energy efficiency [5].”
Ultra-Reliable Low-Latency Vehicular Networks: Taming the Age of Information Tail (2018, unknown): “, σk ≤ σ k and ξk ≤ ξ k [21].”