Abstract
With the flourishing of big data and the 5G era, the amount of data to be transmitted in the communication process is increasing, and end-to-end communication in traditional social networks has been unable to meet the current communication needs. Therefore, in order to improve the success rate of data forwarding, social networks propose that the sender of the message should reasonably choose the next hop node. However, existing routing and forwarding algorithms do not take into account nodes that are live in different scenarios, and the applicable next hop node metrics are also different. These algorithms only consider the forwarding preferences of the nodes during working hours and do not consider the forwarding preferences of the nodes during non-working hours. We propose a routing algorithm based on fuzzy decision theory, which aims at a more accurate decision on selecting the next hop. A routing and forwarding algorithm based on fuzzy decision is proposed in this paper. This algorithm symmetrical divides scenes in opportunistic social networks into working time and non-working time according to real human activity. In addition, metrics are designed symmetrically for these two scenarios. Simulation results demonstrate that, in the best case, the proposed scheme presents an average delivery ratio of 0.95 and reduces the average end-to-end delay and average overhead compared with the epidemic routing algorithm, the EIMSTalgorithm, the ICMT algorithm, and the FCNSalgorithm.
Highlights
In recent years, due to the rapid development of 5G networks and big data [1], each of us has mobile communication devices, such as smartphones and iPads with Bluetooth, WiFi, etc
It was compared with four other algorithms, three of which were the latest routing algorithms, one of which was a traditional algorithm in opportunistic social networks: EIMST(effective information transmission based on socialization nodes) [33], ICMT
Delivery ratio: This measurement metric refers to the probability of choosing a suitable node as the hop node, which is expressed as: Dnode = Dreceive /Dsend where Dreceive is the number of received messages by surrounding neighbor nodes and Dsend is the number of forwarded messages by nodes
Summary
Due to the rapid development of 5G networks and big data [1], each of us has mobile communication devices, such as smartphones and iPads with Bluetooth, WiFi, etc. Since opportunistic social networks are closely related to social life, another problem arises This problem is how to integrate human mobility characteristics into complex routing algorithms and propose effective solutions for selecting hop nodes. Choosing the best hop node according to different attributes is a problem to be solved To solve these urgent issues, an effective transmission strategy based on a fuzzy control system [20,21] is proposed in this work, which is known as a fuzzy control routing-forwarding algorithm. Through reasonable weight adjustments and fuzzy decision-supporting system, the optimum hop is obtained in this paper In a nutshell, this algorithm is a novel routing-forwarding method, which completely considers the real-life scenarios.
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