Satyam Shrivastava, Dr. Abhay Kothari

PhD Scholar SAGE University, Indore, Professor SAGE University, Indore,

Abstract— With the increasing advancement in the applications of the Internet of Things (IoT), the integrated Cloud Computing (CC) faces numerous threats such as performance, security, latency, and network breakdown. With the discovery of Fog Computing these issues are addressed by taking CC nearer to the Internet of Things (IoT). The key functionality of the fog is to provide the data generated by the IoT devices near the edge. Processing of the data and data storage is done locally at the fog node rather than moving the information to the cloud server. In comparison with the cloud, Fog Computing delivers services with high quality and quick response time. Hence, Fog Computing might be the optimal option to allow the Internet of Things to deliver an efficient and highly secured service to numerous IoT clients In this article, we talk about the most important parts of RPL applications for the Internet of Things. In the past few years, advances in sensing and communication technologies have led to a rapid growth in the number of ways the Internet of Things can be used. This is possible because of how quickly different Internet of Things devices are being made (IoT). The Internet of Things is made up of devices that work together to form their own network architecture. In this architecture, each device has a limited amount of battery power, and the link isn’t very reliable. This kind of network is sometimes called a “low-power and lossy network.” In this paper, we describe a routing protocol that works well for networks with low power and high loss. The proposed protocol adds a new rank value so that the source node can send packets to the destination node using an appropriate destination-oriented directed acyclic network. This makes it easier for the source node and the destination node to talk to each other. The main thing that goes into figuring out the proposed rank value is the number of transmissions that are expected. We also use the amount of energy left over to decide which node should act as a relay for the packet on its way to its final destination. We ran simulations to test performance, and the results show that the suggested routing protocol increases the number of packets that are delivered. This was especially true in places where the bit error rate was high. Compared to the strategy that had been used before, the results showed that our method successfully keeps the amount of energy used by all nodes at the same level. In this paper, we newly propose a linear IoT model to deploy processes and data to devices, fog nodes, and servers in IoT so that the total electric energy consumption of nodes can be reduced

Keywords: fog computing  internet of things; IoT; RPL routing protocol; network lifetime optimization; energy load balancing; ELB; performance evaluation.