A battlefield task distribution strategy optimization model based on edge computing

Abstract

The harsh environment of the battlefield challenges the delay and reliability of the cloud computing system composed of soldier terminals and BeiDou satellites. Based on this, this paper focuses on common problems in computational crowdsourcing under multi-agent and proposes a task distribution strategy optimization model based on battlefield edge computing. The process introduces the concept of flow pressure to solve these issues, load balancing and cascading congestion. Flow pressure means multiple servers can communicate and partially offload tasks that exceed the computational load to other servers. The computational overflow problem can be solved by task offloading based on flow pressure. Several different mainstream task allocation strategies are compared through experiments to demonstrate the model’s performance. The experimental results show that the model has lower latency and failure rate and reasonable computational resource occupation, which has a particular theoretical value and reference significance.