5G mobile edge computing-based task unloading and resource allocation joint optimization method

Abstract

The invention relates to a 5G mobile edge computing-based task unloading and resource allocation joint optimization method, and belongs to the technical field of mobile communication. According to themethod, a task unloading decision, resource block distribution and computing resource distribution are jointly modeled into a minimum system overhead problem, and the minimum system overhead problemis decomposed into three sub-optimization problems to be solved. The method comprises the following steps of firstly, considering that UE delay sensitivity in an actual network is different, proposinga distributed resource block distribution algorithm based on the UE delay priority, dividing the UE into UE blocks with different priorities according to the UE delay sensitivity, preferentially allocating the resource blocks for the UE with high priorities, and meanwhile, ensuring the communication quality of the UE with low priority; secondly, enabling each piece of UE to make an unloading decision according to the task local computing overhead and the task unloading computing overhead; and finally, with the goal of minimizing the total execution time of the total unloading task in the MECas a target, allocating the computing resources to the UE.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to a joint optimization method of task offloading and resource allocation based on 5G mobile edge computing. Background technique [0002] In the future 5G network, ubiquitous cloud computing will be supported. The integration of mobile Internet and cloud computing technology forms mobile cloud computing technology. A host of new applications and services are emerging, such as real-time online gaming, virtual reality, and ultra-high-definition video streaming, all of which require unprecedentedly high access speeds and low latency. The past decade has seen the take-off of different visions of next-generation internet, including IoT, tactile internet (millisecond latency), internet and social networking. According to Cisco's forecast, by 2020, the Internet will add about 50 billion IoT devices (such as sensors and wearable devices), most of which resources are used for c...

AI Technical Summary

Problems solved by technology

On the other hand, due to the limited computing power of the MEC, it cannot accommodate too many UEs for task offloading at the same time.

Otherwise, MEC computing resources will be exhausted, and task computing time will be greatly increased.

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