Content caching based on mobility prediction and joint user Prefetch in Mobile edge networks

Yu, Genghua; Wu, Jia

doi:10.1007/s12083-020-00954-x

Cited by 40 publications

(25 citation statements)

References 26 publications

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“…Through formula (2) to get node (1,2 ) sim and node 1 to 2 directly trust, s=1, we can get (1,2 ) trust .…”

Section: Definition 2 Node Similaritymentioning

confidence: 99%

“…With the continuous development of 5G network technology, mobile network equipment has proliferated in recent years. In the future, the 5G network technology industry will gradually develop to improve mobile communications quality, reduce operating costs [1] and provide a foundation for large-scale data transmission. 5G derivatives, such as mobile devices (mobile phones, tablets, and other human-computer interaction devices), sensing devices (applications for transmission and collection), vehicle networks (autonomous driving, vehicle equipment) [2][3][4] continue to spread.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Liu

Luo

et al. 2021

IEEE Access

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With the continuous development of 5G network technology, the amount of data has surged. Network data transmission technology needs improvement. To ensure the reliable transmission of data, reduce network congestion and network energy consumption, the paper proposed an effective edge cache collaboration routing strategy of opportunistic social networks in the trust community, namely the edge collaboration cache trust community routing algorithm (ECTC). The algorithm proposes that the nodes are used to carry information through the cache. Based on the node trust degree, the efficient trust relay node is identified. Build a trusted network based on the trust degree of nodes. Divide local trust community modules into clusters to realize efficient community retrieval. Under the concept of edge nodes, trust nodes are found in the trust community. Edge caches cooperate to share transmitted data, reducing backbone network congestion. The data update efficiency is greatly improved. Through edge nodes in trust community cooperation and communication, efficient data packet delivery is realized, thereby improving the community trust network's routing performance. The simulation experiment results show that the edge collaboration cache trust community routing algorithm (ECTC) can significantly improve delivery effectiveness and reduce network overhead. INDEX TERMScommunity routing; trust community; edge node; cache collaboration X. Wu et al: Efficient edge cache collaboration transmission strategy of opportunistic social network in trust community (March 2021) X. Wu et al: Efficient edge cache collaboration transmission strategy of opportunistic social network in trust community (March 2021) X. Wu et al: Efficient edge cache collaboration transmission strategy of opportunistic social network in trust community (March 2021

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“…Through formula (2) to get node (1,2 ) sim and node 1 to 2 directly trust, s=1, we can get (1,2 ) trust .…”

Section: Definition 2 Node Similaritymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Liu

Luo

et al. 2021

IEEE Access

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“…All of this information will be converted into data, which can be stored, sent, and received by users. As people move, everyone can become a data centre, providing a data source for social communications [4][5][6][7][8][9]. Traditional methods in wireless network are not well adapted to opportunistic social network under heavy data traffic.…”

Section: Introductionmentioning

confidence: 99%

Effective path prediction and data transmission in opportunistic social networks

Zou

Long

2021

IET Communications

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With the development of social media, social networks have become an important platform for people to share and communicate. In social network communication, when people carry mobile devices for data transmission, they need to find a definite transmission destination to ensure the normal conduct of information exchange activities. This is manifested in the process of data transmission by nodes, which requires analysis and judgment of surrounding areas, and finds suitable nodes for effective data classification and transmission. However, the node cache space in social networks is limited, and the process of waiting for the target node will cause end-to-end transmission delay. In order to improve such a transmission environment, this paper proposes a node trajectory prediction method named EDPPM algorithm. The EDPPM algorithm guarantees that nodes with high probability are given priority to obtain data information, which realized an effective data transmission mechanism. Through experiments and comparison of opportunistic transmission algorithms in social networks, such as Epidemic algorithm, Spray and Wait algorithm, and PRoPHET algorithm, the proposed scheme outperforms ProPhet by 47% in terms of cache utilization of nodes, 55% in terms of data transmission delay, and 32% in terms of network efficiency; compared with Epidemic by 53% in terms of cache utilization of nodes, 62% in terms of data transmission delay, and 47% in terms of network efficiency; same thing with regard to the Spray and wait by 27% in terms of cache utilization of nodes, 31% in terms of data transmission delay, and 17% in terms of network efficiency.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…With the booming of information technology and the popularization of wireless network equipment [1], people have a growing demand for the network. As a fresh type of self-organizing network [2], an opportunistic social network has attracted researchers' attention [3].…”

Section: Introductionmentioning

confidence: 99%

Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks

Xiaokaiti

Qian

2021

Complexity

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With the rapid development of 5G era, the number of messages on the network has increased sharply. The traditional opportunistic networks algorithm has some shortcomings in processing data. Most traditional algorithms divide the nodes into communities and then perform data transmission according to the divided communities. However, these algorithms do not consider enough nodes’ characteristics in the communities’ division, and two positively related nodes may divide into different communities. Therefore, how to accurately divide the community is still a challenging issue. We propose an efficient data transmission strategy for community detection (EDCD) algorithm. When dividing communities, we use mobile edge computing to combine network topology attributes with social attributes. When forwarding the message, we select optimal relay node as transmission according to the coefficients of channels. In the simulation experiment, we analyze the efficiency of the algorithm in four different real datasets. The results show that the algorithm has good performance in terms of delivery ratio and routing overhead.

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Content caching based on mobility prediction and joint user Prefetch in Mobile edge networks

Cited by 40 publications

References 26 publications

Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Efficient Edge Cache Collaboration Transmission Strategy of Opportunistic Social Network in Trusted Community

Effective path prediction and data transmission in opportunistic social networks

Efficient Data Transmission for Community Detection Algorithm Based on Node Similarity in Opportunistic Social Networks

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