Internet of Things (IoT) based Network Integrated with Sensor Nodes for Intruder Detection and Low Energy Consumption

Abstract

The applications in Internet of Things (IoT) for a large-scale Network which necessitates the storage resources and computing tasks, are gradually deployed in most of the wireless network environments. The computing model of traditional techniques when compared with features of cloud such as unlimited expansion, dynamic acquisition and payas-you-go are represented in different IoT architectures based on the conveniences of applications. Thus, one of the key challenges is to consider the service requirements when sensors are assigned to the tasks and the network performance is improved. In the presented work, the two-phase service system using Enhanced Bernoulli Vacation (EBV) scheduling algorithm and Intrusion Detection framework is proposed to minimize the energy consumed by the sensors while the service is provided. The performance variation of Virtual Machine (VM) and its achieved delay is considered, while first the tasks are divided into different tasks at different levels. The proposed work deals with a queuing system ‘M/G/1’ for Bernoulli Vacation scheduling model at one phase and intrusion detection technique at second phase. The sensing distance is also calculated with its density of network. The tasking scheduling algorithm is considered for execution cost and residual energy where the deadlines or threshold are proposed. The delay time, accuracy, detection rate and False Alarm Positive rate are evaluated during simulation time. Based on the work flows, experiments conducted are simulated for controlled tasks of IoT which demonstrates the algorithm achieving high success rate and that the network performs better when compared with the existing algorithms.