隨著車載網路的使用越來越頻繁，大量的使用者希望利用這個網路有效地接收他們需要的資訊。為了達到此目標，車輛從道路兩旁的可用路側基地台 (Roadside Unit，RSU)上接收資料，而 RSU 是一個連接外部世界的路由器以及擁有一個高容量存儲的快取記憶體，可以提供服務區內的車輛下載流行資料。由於 RSU 的通信範圍有限，車輛在覆蓋範圍內行駛速度通常很快，RSU 必須在有限的時間向服務區中的車輛提供資料。因此，要達成優化目的，必須規劃 在 RSU 中資料擺放的順序及位置，以便最多數的車輛可以從 RSU 的快取記憶體中獲益。本文通過兩種方法將 RSU 分組以配置熱門檔案，第一種是依據車輛行進的時程，第二種是所有 RSU 中取行經機率大於門閥的來分組，有效地解決了 車載網路中資料傳輸問題。我們最主要的目標是在有限的時間中提升最大限度 的下載量，然而有些資料無法在需要使用之前都從 RSU 下載完畢，這時使用 者就要自費行動網路的費率把資料載完。從結果顯示，我們的方案在密集網路以及城市場景中具有良好的效果。

As vehicular ad-hoc networks (VANETs) have become more popular and attracted recently, a large number of vehicles thirst for utilizing the information efficiently in the networks. Due to this, vehicles receive data from available Roadside Units(RSUs) across the road. Since RSUs act as routers to connect with the world outside, they have high-capacity storage where popular data is stored. If the storage keep the target data of these vehicles, they are allowed to download it, when they move across the service area. However, RSUs have limited communication range and the vehicles usually move at a high speed across the coverage of RSUs. Consequently, RSUs have limited time to send the data to vehicles. To optimize the situation, RSUs have to distribute data to maximize the amount of downloaded data to vehicles. There are many algorithms proposed in the past to distribute data to RSUs. In this thesis, we propose two methods of clustering RSUs to allocate the popular data. The first is based on vehicle travel time, and the second is according to whether the probability of vehicles passing through the next RSU is beyond the certain threshold or not. These two methods solve content delivery problems effectively in VANETs by caching popular data in RSUs. The main purpose is to maximize the total amount of downloaded data, and minimize the cost of downloading the remaining data whose deadline is about to expire from the cellular transaction. This scheme has performed better in dense network and fitted in urban scenario.

[1] B. B. Dubey, N. Chauhan, N. Chand, and L. K. Awasthi, “Priority based efficient data scheduling technique for vanets,” Wireless Networks, vol. 22, no. 5, pp. 1641– 1657, 2016.
[2] Cisco, “Cisco visual networking index: global mobile data traffic forecast update, 2016–2021,” White Paper, 2017.
[3] C.-F. Chiasserini, R. Gaeta, M. Garetto, M. Gribaudo, and M. Sereno, “Efficient broadcasting of safety messages in multihop vehicular networks,” in Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International. IEEE, 2006, pp. 8–pp.
[4] F. D. Da Cunha, A. Boukerche, L. Villas, A. C. Viana, and A. A. Loureiro, “Data communication in vanets: a survey, challenges and applications,” Ph.D. dissertation, INRIA Saclay; INRIA, 2014.
[5] J. B. Kenney, “Dedicated short-range communications (dsrc) standards in the united states,” Proceedings of the IEEE, vol. 99, no. 7, pp. 1162–1182, 2011.
[6] G. M. N. Ali, M. A. S. Mollah, S. K. Samantha, and S. Mahmud, “An efficient cooperative load balancing approach in rsu-based vehicular ad hoc networks (vanets),” in Control System, Computing and Engineering (ICCSCE), 2014 IEEE International Conference on. IEEE, 2014, pp. 52–57.
[7] X. Jiang and D. H. Du, “Bus-vanet: a bus vehicular network integrated with traffic infrastructure,” IEEE Intelligent Transportation Systems Magazine, vol. 7, no. 2, pp. 47–57, 2015.
[8] V. Jacobson, D. K. Smetters, J. D. Thornton, M. F. Plass, N. H. Briggs, and R. L.
Braynard, “Networking named content,” in Proceedings of the 5th international
conference on Emerging networking experiments and technologies. ACM, 2009,
pp. 1–12.
[9] M. Ohtani, K. Tsukamoto, Y. Koizumi, H. Ohsaki, M. Imase, K. Hato, and J. Mu-
rayama, “Vccn: Virtual content-centric networking for realizing group-based com-
munication,” in Communications (ICC), 2013 IEEE International Conference on.
IEEE, 2013, pp. 3476–3480.
[10] Z. Su, Y. Hui, and Q. Yang, “The next generation vehicular networks: A content-
centric framework,” IEEE Wireless Communications, vol. 24, no. 1, pp. 60–66,
2017.
[11] J. He, Y. Ni, L. Cai, J. Pan, and C. Chen, “Optimal dropbox deployment algo-
rithm for data dissemination in vehicular networks,” IEEE Transactions on Mobile
Computing, vol. 17, no. 3, pp. 632–645, 2018.
[12] S. Abdelhamid, H. S. Hassanein, and G. Takahara, “On-road caching assistance for
ubiquitous vehicle-based information services,” IEEE Transactions on Vehicular
Technology, vol. 64, no. 12, pp. 5477–5492, 2015.
[13] Z. Hu, Z. Zheng, T. Wang, L. Song, and X. Li, “Roadside unit caching: Auction-
based storage allocation for multiple content providers,” IEEE Transactions on
Wireless Communications, vol. 16, no. 10, pp. 6321–6334, 2017.
[14] R. Ding, T. Wang, L. Song, Z. Han, and J. Wu, “Roadside-unit caching in ve-
hicular ad hoc networks for efficient popular content delivery,” in Wireless Com-
munications and Networking Conference (WCNC), 2015 IEEE. IEEE, 2015, pp.
1207–1212.
[15] U. Shevade, Y.-C. Chen, L. Qiu, Y. Zhang, V. Chandar, M. K. Han, H. H. Song,
and Y. Seung, “Enabling high-bandwidth vehicular content distribution,” in Pro-
ceedings of the 6th International COnference. ACM, 2010, p. 23.
36[16] B. B. Chen and M. C. Chan, “Mobtorrent: A framework for mobile internet access
from vehicles,” in INFOCOM 2009, IEEE. IEEE, 2009, pp. 1404–1412.
[17] C. Lochert, B. Scheuermann, M. Caliskan, and M. Mauve, “The feasibility of
information dissemination in vehicular ad-hoc networks,” in Wireless on Demand
Network Systems and Services, 2007. WONS’07. Fourth Annual Conference on.
IEEE, 2007, pp. 92–99.
[18] N. Kumar and J.-H. Lee, “Peer-to-peer cooperative caching for data dissemination
in urban vehicular communications,” IEEE Systems Journal, vol. 8, no. 4, pp.
1136–1144, 2014.
[19] P. Salvo, F. Cuomo, A. Baiocchi, and A. Bragagnini, “Road side unit coverage
extension for data dissemination in vanets,” in Wireless On-demand Network Sys-
tems and Services (WONS), 2012 9th Annual Conference on. IEEE, 2012, pp.
47–50.
[20] F. Malandrino, C. Casetti, C.-F. Chiasserini, and M. Fiore, “Optimal content
downloading in vehicular networks,” IEEE Transactions on Mobile Computing,
vol. 12, no. 7, pp. 1377–1391, 2013.
[21] Q. Wang, P. Fan, and K. B. Letaief, “On the joint v2i and v2v scheduling for coop-
erative vanets with network coding,” IEEE Transactions on Vehicular Technology,
vol. 61, no. 1, pp. 62–73, 2012.
[22] K. Liu, J. K. Ng, V. Lee, S. H. Son, and I. Stojmenovic, “Cooperative data schedul-
ing in hybrid vehicular ad hoc networks: Vanet as a software defined network,”
IEEE/ACM Transactions on Networking (TON), vol. 24, no. 3, pp. 1759–1773,
2016.
[23] S. Abdelhamid, H. Hassanein, and G. Takahara, “Vehicle as a resource (vaar),”
IEEE Network, vol. 29, no. 1, pp. 12–17, 2015.
[24] L. Breslau, P. Cao, L. Fan, G. Phillips, and S. Shenker, “Web caching and zipf-like
distributions: Evidence and implications,” in INFOCOM’99. Eighteenth Annual
37Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, vol. 1. IEEE, 1999, pp. 126–134.
[25] G. Demange, D. Gale, and M. Sotomayor, “Multi-item auctions,” Journal of Political Economy, vol. 94, no. 4, pp. 863–872, 1986.
[26] D. B. West et al., Introduction to graph theory. Prentice hall Upper Saddle River, 2001, vol. 2.
[27] M. Aslan and N. A. Baykan, “A performance comparison of graph coloring algorithms,” International Journal of Intelligent Systems and Applications in Engineering, vol. 4, no. Special Issue-1, pp. 1–7, 2016.
[28] A. Schrijver, Combinatorial optimization: polyhedra and efficiency. Springer Science & Business Media, 2003, vol. 24.