Energy and Cache Aware Routing for Socially Aware Networking in the Big Data Environment

In the big data environment, Socially Aware Networking (SAN) can obtain a large amount of status data and social contacts of network nodes. If the information is fully analyzed and utilized, it will effectively improve the energy efficiency and performance of SAN. To address this issue, Energy and Cache Aware Routing Algorithm (ECARA) is proposed that comprehensively utilizes node energy and cache information. First, a probability model of encounters is established by using the historical encounter information between nodes in the network. Then, the residual energy ratio of the node is introduced. They are used to predict the delivery probability of the current node. At the same time, a node cache utilization ratio model is also established. In the end, the algorithm comprehensively considers the prediction value of delivery probability and node cache utilization ratio. The optimal relay node is selected to forward the message. Through the forwarding of many relay nodes, the message is finally delivered to the destination node. Simulation results demonstrate that the ECARA exhibits a superior message delivery ratio compared to other classical algorithms. It also can effectively prevent network congestion and improve network throughput.