Algorithm

Chaotic

Engineering

Efficient energy use

Lyapunov optimization

Operating system

Resource allocation

Telecommunications

Computer science

Mathematical optimization

Stochastic optimization

Distributed computing

Computer network

Mathematics

Lyapunov redesign

Lyapunov exponent

Enhanced Data Rates for GSM Evolution

Mobile edge computing

Artificial intelligence

Schedule

Mobile wireless

Wireless

Optimization problem

Wireless network

Electrical engineering

IEEE Transactions on Wireless Communications

The integration of Mobile-edge Computing (MEC) and Wireless Energy Transfer (WET) has been recognized as a promising technique to enhance computation capability and to prolong battery lifetime of resource-constrained wireless devices in the Internet of Things (IoT) era. However, it is challenging to jointly schedule energy, radio, and computational resources for coordinating heterogeneous performance requirements in wireless powered MEC systems. To fill this gap, this paper investigates the fundamental tradeoff between Energy Efficiency (EE) and delay in a multi-user wireless powered MEC system. Considering the random channel conditions and task arrivals, we formulate a stochastic optimization problem to study the EE-delay tradeoff, which optimizes network EE subject to network stability, maximum central processing unit frequency, peak transmission power, available communication resource, and energy causality constraints. Further, we propose the online computation offloading and resource allocation algorithm by transforming the original problem into a series of deterministic optimization problems in each time block based on Lyapunov optimization theory. In addition, theoretical analysis shows that the algorithm achieves the EE-delay tradeoff as [O(1/V), O(V)] and introduces a control parameter V to balance the EE-delay performance. Numerical results verify the theoretical analysis and reveal the impact of various parameters to the system performance.

Energy Efficiency and Delay Tradeoff for Wireless Powered Mobile-Edge Computing Systems With Multi-Access Schemes