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The growth of vehicles and inadequate road capacity in the urban area trigger traffic congestion and raise the frequency of road accident. Therefore the need of drastically reducing traffic congestion is a significant concern. Advancement in the technology like fog computing, Internet of Things (IoT) in Intelligent Transportation Systems (ITS) aid in the more constructive management of traffic congestion. Three IoT based Fog computing oriented models are designed in the present work for mitigating traffic congestion. The first two schemes are vehicle dependent as they control traffic congestion depending upon the number of vehicles and their direction of movement across the intersections. The third scheme is environment dependent as the agent senses the environment and controls the sequence of green signal at different routes dynamically. The performances of the three schemes in ITS are analyzed along with the comparison of storage, communication and computation overhead. The efficacy of the schemes is studied theoretically and quantitatively. The quantitative performance of the three schemes is compared with five existing schemes. On the basis of the result of the comparison, it can be concluded that the proposed schemes are capable of alleviating congestion more optimally than existing schemes due to the substantial reduction in vehicle waiting time Traffic signal control, VANET, Congestion con-trol.