Task Scheduling Using Edge Computing System In Smart City

A smart city will become an inevitable trend of social development. It includes many Cyber Physical Systems (CPSs) that can be endowed with different levels of intelligence. With the combination of CPS and cloud computing, smart sensor cloud system becomes popular in many areas where the physical nodes can be shared with multiple users, which can obtain high performance computing. In view of this idea, this paper studies the specific application of smart city-online task scheduling. We treat each task as a physical node, and the scheduling of multiple computing tasks is to achieve sustainable services. However, when a physical sensor node receives commands from multiple tasks simultaneously, namely, resource conflict management problem. This conflicting resource management problem leads to the failures of services. To solve the resource conflict problem, we propose an extended Hungarian algorithm based on edge computing, which can obtain smaller delay and achieve sustainable service. Edge computing can be viewed as a buffer and controller between CPS and the cloud and can build a sustainable service system by handling malicious attacks. The experimental results show that our proposed method can effectively reduce resource conflicts, improve resource utilization, and make services more sustainable.