DLBS: Decentralize Load-Balance Scheduling Algorithm for Real-Time IoT Services in Mist Computing

Abstract

Internet of Things (IoT) has been industrially investigated as Platforms as a Services (PaaS). The naive design of these types of services is to join the classic centralized Cloud computing infrastructure with IoT services. This joining is also called CoT (Cloud of Things). In spite of the increasing resource utilization of cloud computing, but it faces different challenges such as high latency, network failure, resource limitations, fault tolerance and security etc. In order to address these challenges, fog computing is used. Fog computing is an extension of the cloud system, which provides closer resources to IoT devices. It is worth mentioning that the scheduling mechanisms of IoT services work as a pivotal function in resource allocation for the cloud, or fog computing. The scheduling methods guarantee the high availability and maximize utilization of the system resources. Most of the previous scheduling methods are based on centralized scheduling node, which represents a bottleneck for the system. In this paper, we propose a new scheduling model for manage real time and soft service requests in Fog systems, which is called Decentralize Load-Balance Scheduling (DLBS). The proposed model provides decentralized load balancing control algorithm. This model distributes the load based on the type of the service requests and the load status of each fog node. Moreover, this model spreads the load between system nodes like wind flow, it migrates the tasks from the high load node to the closest low load node. Hence the load is expanded overall the system dynamically. Finally, The DLBS is simulated and evaluated on truthful fog environment.