Abstract
Internet of Things (IoT) is transforming the technical setting of conventional systems and finds applicability in smart cities, smart healthcare, smart industry, etc. In addition, the application areas relating to the IoT enabled models are resource-limited and necessitate crisp responses, low latencies, and high bandwidth, which are beyond their abilities. Cloud computing (CC) is treated as a resource-rich solution to the above mentioned challenges. But the intrinsic high latency of CC makes it nonviable. The longer latency degrades the outcome of IoT based smart systems. CC is an emergent dispersed, inexpensive computing pattern with massive assembly of heterogeneous autonomous systems. The effective use of task scheduling minimizes the energy utilization of the cloud infrastructure and rises the income of service providers by the minimization of the processing time of the user job. With this motivation, this paper presents an intelligent Chaotic Artificial Immune Optimization Algorithm for Task Scheduling (CAIOA-RS) in IoT enabled cloud environment. The proposed CAIOA-RS algorithm solves the issue of resource allocation in the IoT enabled cloud environment. It also satisfies the makespan by carrying out the optimum task scheduling process with the distinct strategies of incoming tasks. The design of CAIOA-RS technique incorporates the concept of chaotic maps into the conventional AIOA to enhance its performance. A series of experiments were carried out on the CloudSim platform. The simulation results demonstrate that the CAIOA-RS technique indicates that the proposed model outperforms the original version, as well as other heuristics and metaheuristics.
Highlights
Internet of Things (IoT) [1] permits to achievement of useful and actionable information, multiple tasks, and glean
This paper has developed an effective CAIOA-resource scheduling (RS) technique in the IoT enabled cloud environment
The proposed CAIOA-RS algorithm resolved the problem of resource allocation in the IoT enabled cloud environment
Summary
Internet of Things (IoT) [1] permits to achievement of useful and actionable information, multiple tasks, and glean. The exploitation of heterogeneous server devices and systems should assist in scheduling multiple tasks and share resources for meeting the user QoS needs. Such exploitations are based on the kind of priority of task scheduling, allocation policy selection, and flexibility. Traditional optimization methods aren’t effective because deterministic algorithms cannot generate fulfilling, or optimum, or best solutions within a moderate computation time for NP-hard problems. The proposed CAIOA-RS algorithm resolves the problem of resource allocation in the IoT enabled cloud environment It fulfills the makespan by carrying out the optimal task scheduling process with the different policies of incoming tasks. An extensive set of simulations take place on the CloudSim platform and examined the outcomes interms of different performance measures
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