An Alleviation of Cloud Congestion Analysis of Fluid Retrial User on Matrix Analytic Method in IoT-based Application

Cloud Computing (CC) and Internet of Things (IoT) are upgrowing human intervention to enhance the daily lifestyle. Currently, heavy loaded traffic congestion is a very big challenge over IoT-based applications. For that purpose, researchers approached various ways overcome mechanism in recent years. Even though, they have futile acheive best resource storage accessing capacity expectation other than, Computing. Data sharing key impediment as well Things. These constituent give rise combination IoT cloud computing paradigm Cloud. Though, preserving missed data during execution time factor indulge Retrial Queueing Theory (RQT), who facing issue upon Service Provider (CSP) enter into virtual pool preserve for reuse. The paper imposes Markov Fluid analysis with Matrix Analytic Method (MAM) allows continuous length rather than individual avoid congestion. orbit queue follow constant retrial rate discipline, is, head orbital users makes attempt occupy server assumed be independent identically distributed (i.i.d). Steady-state expression presented study behaviour An illustrative produced gain deep perception system model.