FRRF: A Fuzzy Reasoning Routing-Forwarding Algorithm Using Mobile Device Similarity in Mobile Edge Computing-Based Opportunistic Mobile Social Networks

Abstract

The arrival of 5G is accompanied by massive data transmission between mobile devices (MDs) and huge transmission energy consumption in the wireless networks. Therefore, how message applications select the appropriate relay MDs to complete the efficient data transmission process in the opportunistic mobile social networks (OMSNs)? At present, designing an efficient routing-forwarding algorithm is extremely challenging. Some routing-forwarding algorithms choose appropriate nodes as relay nodes based on the similarity between nodes, but most existing routing-forwarding algorithms only consider a few similar factors and even completely ignore the importance of movement similarity in data transmission of the node. In particular, existing routing-forwarding algorithms will bring extra energy consumption to the nodes in the wireless networks, and excessive energy consumption will further affect the delay and data transmission efficiency. In order to solve the problems in the existing strategies, we apply the mobile edge computing (MEC) to OMSNs, and we propose the fuzzy reasoning routing-forwarding (FRRF) algorithm that integrates the movement and social similarity in the MEC-based OMSNs. In detail, the fuzzy evaluation of the movement and social similarity is integrated to determine the transmission priority value between MDs, and finally, the transmission priority between MDs is compared to make transmission decision. Through simulation experiment and comparison with other algorithms, the correctness of the theoretical analysis and the efficiency of the FRRF algorithm in energy consumption, delay, and transmission efficiency are verified.

Keywords

• Opportunistic mobile social networks
• mobile edge computing
• routing-forwarding algorithm
• mobile device similarity
• fuzzy reasoning system