A Service Delay Minimization Scheme for QoS-Constrained, Context-Aware Unified IoT Applications

Abstract

With the unprecedented advancements in the field of Internet of Things (IoT), novel increasingly complex services are getting conceived and implemented with the day. A new trend in this landscape of next-generation IoT applications has been those orchestrated by the seamless integration of numerous vertical IoT applications, also known as, unified IoT services. However, such unified IoT applications are resource hungry (computation, storage, as well as network resources) and are usually characterized by real-time constraints. These render cloud and fog enactments insufficient. This article employs a context-aware computing approach that helps alleviating massive data transfers across fog nodes in real time. User requests are managed at fog nodes were depending upon their required contexts, availability of such contexts in the fog node and respective deadline, the requests are serviced either locally or at other fog nodes and Quality of Service (QoS) is fulfilled. To this end, a distributed service management algorithm is proposed that services the user requests at every fog node by either sharing contexts among context requests within a fog node, or by bringing in unavailable contexts from other fog nodes or by migrating service requests to remote fog nodes with available contexts in a deadline-aware fashion. Accordingly, this article proposes a novel smart multichannel queuing (SMCQ) model that schedules requests to virtual machines (VMs) at individual fog nodes by assigning them to specific priority groups (based on deadline vicinity) and thus minimizes service delay. The proposed algorithms for delay-tolerant service migration have been presented and simulation results carried out to demonstrate the efficacy of the proposed methodology.