The number of users and their network utilization will enumerate the traffic of the network. The accurate and timely estimation of network traffic is increasingly becoming important in achieving guaranteed Quality of Service (QoS) in a wireless network. The better QoS can be maintained in the network by admission control, inter or intra network handovers by knowing the network traffic in advance. Here wireless network traffic is modeled as a nonlinear and nonstationary time series. In this framework, network traffic is predicted using neural network and statistical methods. The results of both the methods are compared on different time scales or time granularity. The Neural Network(NN) architectures used in this study are Recurrent Radial Basis Function Network (RRBFN) and Echo state network (ESN).The statistical model used here in this work is Fractional Auto Regressive Integrated Moving Average (FARIMA) model. The traffic prediction accuracy of neural network and statistical models are in the range of 96.4% to 98.3% and 78.5% to 80.2% respectively

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Technology, as we know, has aided in the growth of humankind since its advent. Due to this advance, a new computation and communication surrounded such as the Internet of Things (IoT) has entered the scene. Much research work is being done in the area of IoT which aids the overall advancement of society and marks life simpler and more agreeable. Yet, in the asset restricted surrounding of Wireless Sensor Network (WSN) and IoT, it is practically incomprehensible to build up a totally safe framework. so we move quick, innovation turns out to be progressively powerless against security hazards. Later on, the quantity of individuals associated with the web will be not as much as that of powerful articles, so we need to set up a vigorous framework to keep the previously mentioned conditions safe and normalize it for smooth correspondence between IoT objects. In this audit archive, refinements of the relevant threat model for the safety of WSN and IoT-based correspondences are given. The security prerequisites and different potential attacks in WSN-based and IoT-based correspondence conditions are examined likewise. At that point refinements of various designs of correspondence conditions dependent on WSN and IoT are also given. Next, the ongoing concerns and moves related to WSN and IoT are discussed. A logical arrangement of security and assurance defending shows in WSN and IoT is moreover included. Lastly, some investigation incites that should be tended to soon is also presented in this article. The integrated IoT-WSN with performance metrics is tabulated to show the possibilities of securing the network systems.

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