Full Text:   <877>

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CLC number: TP393.0

On-line Access: 2019-11-11

Received: 2019-03-11

Revision Accepted: 2019-04-18

Crosschecked: 2019-10-10

Cited: 0

Clicked: 2654

Citations:  Bibtex RefMan EndNote GB/T7714


Xiao-hong Zhang


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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.10 P.1404-1414


Measurement and analysis of content diffusion characteristics in opportunity environments with Spark

Author(s):  Xiao-hong Zhang, Kai Qian, Jian-ji Ren, Zong-pu Jia, Tian-peng Jiang, Quan Zhang

Affiliation(s):  College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, China; more

Corresponding email(s):   xh.zhang@hpu.edu.cn, renjianji@hpu.edu.cn

Key Words:  Content dissemination, Device-to-device communication, Opportunity network, Linear threshold model

Xiao-hong Zhang, Kai Qian, Jian-ji Ren, Zong-pu Jia, Tian-peng Jiang, Quan Zhang. Measurement and analysis of content diffusion characteristics in opportunity environments with Spark[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(10): 1404-1414.

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author="Xiao-hong Zhang, Kai Qian, Jian-ji Ren, Zong-pu Jia, Tian-peng Jiang, Quan Zhang",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

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%T Measurement and analysis of content diffusion characteristics in opportunity environments with Spark
%A Xiao-hong Zhang
%A Kai Qian
%A Jian-ji Ren
%A Zong-pu Jia
%A Tian-peng Jiang
%A Quan Zhang
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1900137

T1 - Measurement and analysis of content diffusion characteristics in opportunity environments with Spark
A1 - Xiao-hong Zhang
A1 - Kai Qian
A1 - Jian-ji Ren
A1 - Zong-pu Jia
A1 - Tian-peng Jiang
A1 - Quan Zhang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 10
SP - 1404
EP - 1414
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1900137

opportunity networks provide a chance to offload the tremendous cellular traffic generated by sharing popular content on mobile networks. Analyzing the content spread characteristics in real opportunity environments can discover important clues for traffic offloading decision making. However, relevant published work is very limited since it is not easy to collect data from real environments. In this study, we elaborate the analysis on the dataset collected from a real opportunity environment formed by the users of Xender, which is one of the leading mobile applications for content sharing. To discover content transmission characteristics, scale, speed, and type analyses are implemented on the dataset. The analysis results show that file transmission has obvious periodicity, that only a very small fraction of files spread widely, and that application files have much higher probability to be popular than other files. We also propose a solution to maximize file spread scales, which is very helpful for forecasting popular files. The experimental results verify the effectiveness and usefulness of our solution.




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[1]Andreev S, Pyattaev A, Johnsson K, et al., 2014. Cellular traffic offloading onto network-assisted device-to-device connections. IEEE Commun Mag, 52(4):20-31.[doi:10.1109/MCOM.2014.6807943]

[2]Bao XY, Zhou XJ, Zhang Y, et al., 2016. Cellular traffic offloading utilizing set-cover based caching in mobile social networks. J China Univ Posts Telecommun, 23(2): 46-55.

[3]Brin S, Page L, 1998. The anatomy of a large-scale hypertextual Web search engine. Comput Netw ISDN Syst, 30(1-7):107-117.

[4]Cha M, Kwak H, Rodriguez P, et al., 2007. I tube, you tube, everybody tubes: analyzing the world’s largest user generated content video system. Proc 7$^rm th$ ACM SIGCOMM Conf on Internet Measurement, p.1-14.

[5]Che HL, Cao Y, 2014. Examining WeChat users’ motivations, trust, attitudes, and positive word-of-mouth: evidence from China. Comput Human Behav, 41:104-111.

[6]Cheng RG, Chen NS, Chou YF, et al., 2015. Offloading multiple mobile data contents through opportunistic device-to-device communications. Wirel Pers Commun, 84(3):1963-1979.

[7]Chuang YJ, Lin KCJ, 2012. Cellular traffic offloading through community-based opportunistic dissemination. IEEE Wireless Communications and Networking Conf, p.3188-3193.

[8]Cisco, 2017. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast.https://www.cisco.com/c/en/us/solutions/collateral/ service-provider/visual-networking-index-vni/white-paper-c11-738429.html [Accessed on Feb. 27, 2019].

[9]Gao G, Xiao M, Wu J, et al., 2016. Deadline-sensitive mobile data offloading via opportunistic communications. 13th Annual IEEE Int Conf on Sensing, Communication, and Networking (SECON), p.1-9.

[10]Goyal A, Lu W, Lakshmanan L, 2011. CELF++: optimizing the greedy algorithm for influence maximization in social networks. 20thInt Conf Companion on World Wide Web, p.47-48.

[11]Guan W, Gao H, Yang M, et al., 2013. Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events. Phys A Stat Mech Appl, 395:340-351.

[12]Ioannidis S, Chaintreau A, Massoulie L, 2009. Optimal and scalable distribution of content updates over a mobile social network. IEEE INFOCOM, p.1422-1430.

[13]Jiang J, Zhang S, Li B, et al., 2016. Maximized cellular traffic offloading via device-to-device content sharing. IEEE J Select Areas Commun, 34(1):82-91.

[14]Jiang N, Guo L, Li J, et al., 2016. Data dissemination protocols based on opportunistic sharing for data offloading in mobile social networks. 22ndInt Conf on Parallel and Distributed Systems, p.705-712.

[15]Kempe D, Kleinberg J, Tardos E, 2003. Maximizing the spread of influence through a social network. Proc 9th ACM SIGKDD Int Conf on Knowledge Discovery and Data Mining, p.137-146.

[16]Leskovec J, Kleinberg J, Faloutsos C, 2007a. Graph evolution: densification and shrinking diameters. ACM Trans Knowl Discov Data, 1(1):1-40.

[17]Leskovec J, Krause A, Guestrin C, et al., 2007b. Cost-effective outbreak detection in networks. Proc 13th ACM SIGKDD Int Conf on Knowledge Discovery and Data Mining, p.420-429.

[18]Leskovec J, Huttenlocher D, Kleinberg J, 2010. Signed networks in social media. 10th SIGCHI Conf on Human Factors in Computing Systems, p.1361-1370.[doi:10.1145/1753326.1753532]

[19]Lin KCJ, Chen CW, Chou CF, 2012. Preference-aware content dissemination in opportunistic mobile social networks. IEEE INFOCOM, p.1960-1968.

[20]Lu Z, Wen Y, Cao G, 2014. Information diffusion in mobile social networks: the speed perspective. IEEE Conf on Computer Communications, p.1932-1940.

[21]Mashhadi AJ, Mokhtar SB, Capra L, 2012. Fair content dissemination in participatory DTNs. Ad Hoc Netw, 10(8):1633-1645.

[22]Obar JA, Wildman S, 2015. Social media definition and the governance challenge: an introduction to the special issue. Telecommun Pol, 39(9):745-750.

[23]Pietilänen AK, Diot C, 2012. Dissemination in opportunistic social networks: the role of temporal communities. 13th ACM Int Symp on Mobile Ad Hoc Networking and Computing, p.165-174.

[24]Rahimkhani K, Aleahmad A, Rahgozar M, et al., 2015. A fast algorithm for finding most influential people based on the linear threshold model. Expert Syst Appl, 42(3): 1353-1361.

[25]Rebecchi F, de Amorim MD, Conan V, 2016. Should I seed or should I not: on the remuneration of seeders in D2D offloading. 17th Int Symp on a World of Wireless, Mobile and Multimedia Networks, p.1-9.

[26]Tang R, 2017. Performance tradeoff between energy conservation and user fairness for D2D communication underlaying cellular networks. Chin J Electron, 26:600-607.

[27]Thilakarathna K, Viana AC, Seneviratne A, et al., 2012. {The Power of Hood Friendship for Opportunistic Content Dissemination in Mobile Social Networks. Research Report No. 8042, Teams HIPERCOM, Université Paris-Saclay, France.}

[28]Thilakarathna K, Seneviratne A, Viana AC, et al., 2014. User generated content dissemination in mobile social networks through infrastructure supported content replication. Perv Mob Comput, 11(2):132-147.

[29]Tian F, Liu B, Xiong J, et al., 2016. Movement-based incentive for cellular traffic offloading through D2D communications. IEEE Int Symp on Broadband Multimedia Systems and Broadcasting, p.1-5.

[30]Wang G, Liu PZ, Yang Z, et al., 2018. Joint college admissions game and auction theory for data offloading in heterogeneous networks. Chin J Electron, 27(1):168-174.

[31]Wang H, Wang S, Zhang Y, et al., 2017a. Measurement and analytics on social groups of device-to-device sharing in mobile social networks. Int Conf on Communications, p.1-6.

[32]Wang H, Wang X, Li K, et al., 2017b. A measurement study of device-to-device sharing in mobile social networks based on Spark. Concurr Comput Pract Exp, 29(16):e4021.

[33]Wang X, Chen M, Han Z, et al., 2014. TOSS: traffic offloading by social network service-based opportunistic sharing in mobile social networks. IEEE Conf on Computer Communications, p.2346-2354.

[34]Wang Z, Sun L, Zhang M, et al., 2016. Social- and mobility-aware device-to-device content delivery.http://arxiv.org/abs/1606.04195

[35]Zhang S, Wu J, Qian Z, et al., 2015. Mobicache: cellular traffic offloading leveraging cooperative caching in mobile social networks. Comput Netw, 83:184-198.

[36]Zhang Y, Pan E, Song L, et al., 2015. Social network aware device-to-device communication in wireless networks. IEEE Trans Wirel Commun, 14(1):177-190.

[37]Zhao Y, Song W, 2016. Social-aware energy-efficient data dissemination with D2D communications. IEEE 83rd Vehicular Technology Conf, p.1-5.

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