臺灣博碩士論文加值系統

當前的網路架構是在1960年代被發明的，而網路是讓兩個地方可以做溝通來使用的。而在過去幾十年間，網路的使用者有著巨量的成長。而網路的用途也從溝通的媒介變成讓使用者取得他們所想要的資料。即使目前有許多額外的設計來讓網路可以更符合使用者的需求，但是這些設計也使的網路架構變得更為複雜，更難以維護。而內容核心網路(Content Centric-Networks)是一個新穎的網路架構且符合使用者的需求。在內容核心網路中，內容核心網路給予每一個資料一個獨一無二的ID，而使用者可以透過這個ID直接取得他們所想要的資料。此外，在內容核心網路中，路由器可以擁有一定的儲存空間來暫時存放所經過的資料。藉由這項特色，路由器如果有存放使用者想取得的資料可以直接提供給使用者，如此一來可以有效的減少網路流量。然而，如何讓路由器有效的暫存資料是內容核心網路中一項很重要的議題。在這篇論文中，我們提出一個基於匈牙利演算法的內容放置機制。在我們所提出的方法中，我們考慮了請求以及資料所傳遞的距離、資料的受歡迎程度以及資料的大小來決定資料所放置的位置。除此之外，我們同時也掌控了資料在網路中所放置的份數，減少過多冗餘的資料。透過實驗結果，我們的機制比目前現有的機制有著較好的表現結果。

The network was create in the 1960s, and its goal is to contact two place. As time goes by, the users of network had increase very fast in the last decades. The goal of network also change to that provide data which is user want. Even though there are some patch to make network provide stable service, it make the network architecture more complicated and hard to maintain. Content Centric Network is a new paradigm of networking to meet the needs of users. It given every data a unique ID that make users can request the data directly. It also let routers has the cache capability to cache data. This feature make router can provide the data and also reduce the network traffic. However, how to cache data effectively is a big issue. In this paper, we model this cache problem as an assignment problem and propose a cache scheme which is based on the Hungarian Algorithm. Our cache scheme consider distance, content popularity and data size. We also allocate the number of data duplicates by considering their potential importance. We also make a simulation to verify. As shown in the simulation, our cache scheme has better performance than the others scheme.

Abstract
Ch. 1 Introduction
Ch. 2 Related Work
Ch. 3 Problem statement
3.1 System model
3.2 Problem definition
Ch. 4 Minimum Network Traffic placement
4.1 Overview
4.2 Proposed Scheme
Ch. 5 Performance and Result
5.1 Simulation Environment
5.2 Simulation Results
Ch. 6 Conclusions and Future Works
6.1 Conclusion
6.2 Future Works
Reference

[1] G. Xylomenos et al., “A Survey of Information-Centric Networking Research”, IEEE Communications Surveys & Tutorials, vol. 16, no. 2, 2014.
[2] J. Xiaoke, Bi Jun, Nan Guoshun, Li Zhaogeng, “A Survey on Information-Centric Networking: Rationales, Designs and Debates”, China Communications, vol12, no.8, pp.1-12, July 2015.
[3] B. Ahlgren, C. Dannewitz, C. Imbrenda, D. Kutscher, and B. Ohlman, “A Survey of Information-Centric Networking”, IEEE Communications Magazine, vol.50, no.7, pp.26-36, July 2012.
[4] V. Jacobson et al., “Networking Named Content,” ACM CoNEXT, pp.1-12, 2009.
[5] M. Mangili, F. Martignon and A. Capone, “A Comparative Study of Content-Centricand Content-Distribution Networks:Performance and Bounds”, IEEE Global Communications Conference (GLOBECOM), 2013.
[6] G. Zhang, Y. Li, and T. Lin, “Caching in information centric networking: A survey,” Computer Networks, vol. 57, no. 16, pp. 3128 – 3141, 2013.
[7] Yu Wang, M. Xu, Z. Feng, “Hop-based Probabilistic Caching for
Information -Centric Networks”, IEEE Global Communications Conference (GLOBECOM), 2013
[8] J. Ren, Wen Qi, C. Westphal, J. Wang, K. Lu, S. Liu and S. Wang, “MAGIC: a Distributed MAx-Gain In-network Caching Strategy in Information-Centric Networks”, IEEE Computer Communications Workshops (INFOCOM WKSHPS), 2014.
[9] H. Wu, Jun Li, J. Zhi, “MBP: a Max-Benefit Probability-based Caching Strategy in Information-Centric Networking”, IEEE International Conference on Communications (ICC), 2015.
[10] S.-W. Lee, D. Kim, Y.-B. Ko, J.-H. Kim, M.-W. Jang, “Cache Capacity-aware CCN: Selective Caching and Cache-aware Routing”, IEEE Global Communications Conference (GLOBECOM), 2013.
[11] I. Psaras, Wei Koong Chai, G. Pavlou, S. Member, “In-Network Cache Management and Resource Allocation for Information-Centric Networks”, IEEE Transactions on Parallel and Distributed Systems, vol.25, no.14, Nov.2014.
[12] D. Rossi, G. Rossini, “On sizing CCN content stores by exploiting topological information”, IEEE Computer Communications Workshops (INFOCOM WKSHPS), 2012.
[13] Wei Wang, Yi Sun, Y. Guo, D. Kaafar, J. Jin, Jun Li, Z. Li, “CRCache: Exploiting the Correlation between Content Popularity and Network Topology Information for ICN Caching”, IEEE International Conference on Communications (ICC), 2014.
[14] X. Hu, J. Gong, G. Cheng, C. Pan, “Enhancing In-network Caching by Coupling Cache Placement, Replacement and Location”, IEEE International Conference on Communications (ICC), 2015.
[15] M. Mangili, F. Martignon, A. Capone and F. Malucelli, “Content-Aware Planning Models for Information-Centric Networking”, IEEE Global Communications Conference (GLOBECOM), 2014.
[16] Y. XU, Y. LI, T. LIN, G. ZHANG, Z. WANG and Song CI1, “A Dominating-set-based Collaborative Caching with Request Routing in Content Centric Networking”, IEEE International Conference on Communications (ICC), 2013.
[17] S. Saha, A. Lukyanenko, A. Yl¨a-J¨a¨aski Department, “Cooperative Caching through Routing Control in Information-Centric Networks”, IEEE INFOCOM, 2013.
[18] H. Shimizu, H. Asaeda, M. Jibiki, N. Nishinaga, “Content Hunting for In-Network Cache: Design and Performance Analysis”, IEEE International Conference on Communications (ICC), 2014.
[19] A. Xu X. T.-Y. Tian, “Design and Evaluation of a Utility-based Caching Mechanism for Information-centric Networks”, IEEE International Conference on Communications (ICC), 2015.
[20] “Munkres' Assignment Algorithm”, http://csclab.murraystate.edu/~bob.pilgrim/445/munkres.html
[21] H. W. Kuhn, "Variants of the Hungarian method for assignment problems", Naval Research Logistics Quarterly, no.3, pp. 253–258, 1956.
[22] J. Munkres, "Algorithms for the Assignment and Transportation Problems", Journal of the Society for Industrial and Applied Mathematics, vol.5, no.1, pp. 32-38, March 1957.
[23] R. Chiocchetti, D. Rossi, G. Rossini, “ccnSim: An highly scalable CCN simulator”, IEEE International Conference on Communications (ICC). 2013