Energy Efficient Resource Management in Fog Computing Supported Medical Cyber-Physical System

The sufficient resources in the cloud data center allow plenties of the Internet of Things(IoT) application that has to be deployed on the server to provide services for different industries. However the major drawbacks faced nowadays is the centralized nature of computing framework for processing latency sensitive application especially health monitoring, processing medical data generated from the sensor devices attached in the body of the patients. The major drawback being faced in these cloud frameworks is their limited scalability and hence incapable to cater the requirements of the centralized IoT based environment. Fog computing architecture is considered as a promising solution that extends the feature of existing Cloud Computing and brings the resources close to the IoT devices which meets the requirements imposed by the devices in the network of IoT. The main issue of fog computing is the distribution of resources. As fog computing is still in the infancy stage there is no such Service Level Agreement(SLA) defined. In fog computing resource management is an important issue if efficiently managed then we can enhance the performance of the system up to a large extent. In this paper we are considering smart health care which is now a trend for smart city people used to get access health-care from the home, so we have proposed to design an architecture for efficient health-care by using fog computing which is collaboration with cloud. Service placement is considered as an important problem for designing such architecture to process the latency based application that can provide innovative solutions by bringing resources closer to the user and provide low latency and energy-efficient solutions for data processing compared to cloud. We have employed to form a fog cluster based on the hop count and place the services within that cluster so that node to node latency get minimized and network cost is minimized for users perspective, we also minimize the network utilization so that load on the network devices is balanced. In this work, we have discussed service placement problems in fog computing environments for a specific use case of health monitoring over a large geographical area. A new Dynamic Cluster Algorithm has been proposed and compare with existing two other Algorithm named as latency aware and resource aware.The result shown that our algorithm performs better than other two Algorithms.