An energy-saving method for multi-user and multi-task mobile edge computing based on heterogeneous energy acquisition

Abstract

The invention discloses a multi-user and multi-task mobile edge computing energy-saving method based on heterogeneous energy acquisition. On the premise of satisfying data queue stability constraints and energy queue stability constraints, the problem of minimizing average energy consumption under delay guarantee is firstly constructed. . In order to solve the stochastic optimization problem, the problem is transformed into two deterministic subproblems, which are solved by convex optimization technique and linear programming technique respectively. The method does not require prior knowledge of stochastic processes such as channel state, data arrival and green energy harvesting. Realized [O(1 / V), O(V)] energy-delay trade-off. As a non-negative weight, V can effectively control energy consumption-delay performance.

Description

technical field [0001] The invention belongs to the field of mobile edge computing, and in particular relates to a multi-user and multi-task mobile edge computing energy-saving method based on heterogeneous energy acquisition. Background technique [0002] As a ubiquitous computing paradigm, IoT is exploding in computing-intensive mobile applications such as autonomous driving, virtual reality, and interactive online games. Based on the consideration of the size and production cost of wireless devices (such as sensors) in the Internet of Things, the battery capacity of wireless devices is often limited, while being energy-efficient and low-performance processors. Therefore, resource-constrained devices severely limit the development of computationally intensive applications. Therefore, in the field of research and development of modern Internet of Things technology, how to eliminate this bottleneck is a key issue. [0003] Today, this limitation is addressed by offloading ...

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Problems solved by technology

[0005] In order to solve the problem of challenging resource management and allocation in the prior art due to the unpredictability of task arrival, wireless channel state and energy consumption, the present invention proposes a multi-user multi-task based on heterogeneous energy acquisition The energy-saving method of mobile edge computing adopts Lyapunov optimization theory and convex optimization theory for joint resource management and allocation to reduce the time-average energy consumption of multi-user and multi-task MEC systems in heterogeneous energy collection sites

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