Critical Analysis of Challenges Facing with Cloud Computing Based IoT and Techniques used to Improve Quality of Service

In last few years with the successive expansion of information technology, the term Internet of Things (IoT) has been hyped. There is an exponential growth of IoT devices, which plays a significant role in our daily life. It is like the different ways used for controlling home appliances with smart phone to tracking our daily activities with smart watches. Millions of sensors and devices are constantly generating the data and exchanging essential messages to provide various services to the client. In a current scenario data collected with various sensors and IoT devices are uploaded to cloud server (centralized servers) there it will go for computation and analysis with the help of advance machine learning techniques, big data techniques and many more, then after the results are sent back to the corresponding IoT devices to execute their task and provide services to client. In this process the bandwidth utilization is more as vast amount of data is uploaded to cloud server and simultaneously it increases latency as well due to the more distance between source of data and cloud server that is unbearable for time-sensitive IoT applications because these applications have to take quick decision to complete the task. In addition to that, many more challenges are faced by the cloud computing based IoT devices, which degrade the overall performance. Although by introducing some new technologies in recent years the performance of IoT devices are improved but still there are some key challenges that need more consideration. In this paper, our motive is to thoroughly analyze the challenges facing with cloud computing based IoT devices and then later briefly discuss a various advance techniques to overcome these challenges that results improved Quality of ervice (QoS).