我們規劃了以物件為基礎的多媒體模式，來描述使用者所要求的服務品質(Quality of Service)，像是最大的資料丟棄率(data-dropping rate)或是最大的資料延遲率(data-delay rate)。我們也展示了資源配置模式，稱之為淨利(net-profit)模式，其定義為使用者服務品質的滿意度是依據系統獲得的利益來衡量。基於這樣的模式，當系統配置足夠的資源給多媒體傳輸的需求者，同時滿足使用者對服務品質的要求，該系統將獲得獎賞。否則，如果系統沒有足夠的資源給多媒體傳輸的需求者，則該系統將獲得懲罰。
我們的研究是在有限的網路頻寬下，去發展多媒體傳輸的最佳解決方案。為了滿足使用者的服務品質要求，頻寬資源應該要被預先保留。因此，假設使用者服務品質的需求事先知道，首先我們研究如何配置資源使得服務品質的滿意度達到最佳化。我們提出的最佳解與最早截止優先法則(Earliest Deadline First algorithm)比較下，具有顯著的改善效果。
從上述的問題所得到的所有最佳解，其淨利可能不均勻的被分佈在那些多媒體傳輸需求者上，因此，我們著手處理公平性問題----如何有效率地配置資源，使得任意兩個多媒體需求者的淨利差是最小的，而且所有多媒體需求者的淨利和是最大的。我們以動態規劃的演算法去找出所有可能的最佳解，另外，我們建構了三個篩選方法去改善這個演算法的效率。實驗的結果顯示出這些篩選方法能夠削減不必要的搜尋而且顯著地改善效率，尤其在所需處理的工作數增多時。
對於一些多媒體物件可能需要傳輸全部，亦即不可分割的物件，我們延伸這個物件為基礎的模式包含這樣的需求，並使用動態規劃的演算法去找出系統的淨利和是最大的。

We propose an object-based multimedia model for specifying the QoS (quality of service) requirements, such as the maximum data-dropping rate or the maximum data-delay rate. We also present a resource allocation model, called the net-profit model, in which the satisfaction of user’s QoS requirements is measured by the benefit earned by the system. Based on the net-profit model, the system is rewarded if it can allocate enough resources to a multimedia delivery request and fulfill the QoS requirements specified by the user. At the same time, the system is penalized if it cannot allocate enough resources to a multimedia delivery request.
In this dissertation, we present our research in developing optimal solutions for multimedia stream delivery in bandwidth limited networks. To fulfill the QoS requirements, the resource, such as bandwidth, should be reserved in advance. Hence, we first investigate how to allocate a resource such that the QoS satisfaction is maximized, assuming that the QoS requirements are given a priori. The proposed optimal solution has significant improvement over the based line algorithm, EDF (Earliest Deadline First).
Among all the optimal solutions found from the above problem, the net-profit may be distributed unevenly among the multimedia delivery requests. Furthermore, we tackle the fairness problem -- how to allocate a resource efficiently so that the difference of the net-profit between two requests is minimized over all the possible optimal solutions of the maximum total net-profit. A dynamic programming based algorithm is proposed to find all the possible optimal solutions and, in addition, three filters are conducted to improve the efficiency of the proposed algorithm. The experimental results show that the filters prune out unnecessary searches and improve the performance significantly, especially when the number of tasks increases.
For some multimedia objects, they might need to be delivered in whole, indivisible, so we extend the proposed multimedia object-based model to indivisible objects. A dynamic programming based algorithm is presented to find an optimal solution of the delivery problem, where the total net-profit is maximized.

Chapter 1 Introduction 1
1.1 Problem description and objective 4
1.2 Contributions 4
1.3 Organization 6
Chapter 2 Related works 7
Chapter 3 System model 14
3.1 Object-based multimedia model 14
3.2 Precedence constraints 16
3.3 The net-profit model 18
Chapter 4 Schedulability analysis 22
Chapter 5 Optimal delivery 27
5.1 Problem formulation 27
5.2 Optimization analysis 29
5.3 Suboptimal solution 36
5.4 Experimental results 40
Chapter 6 Fairness delivery 46
6.1 Problem formulation 46
6.2 Optimization analysis 48
6.3 Experimental results 57
Chapter 7 Optimal delivery with indivisible objects 61
7.1 Problem formulation 61
7.2 Optimization analysis 62
Chapter 8 Conclusion 68
BIBLIOGRAPHY 70

[1]. Sun, Huey-Min., Chen, Chia-Mei., and Shu, LihChyun., “Real-Time Scheduling for Multimedia Streams Over Resource-Constrained Networks”, Proceedings of Real-Time Computing Systems and Applications, Tokyo, Japan,18-20 March 2002, Page(s):331-335.
[2]. ISO/IEC JTC1/SC29/WG11, “Overview of the MPEG-4 Standard”, N1729 & N1730, Stockholm meeting, July 1997.
[3]. Lin, Hao., Wu, Wei., Ren, Yong., ans Shan, Xiuming., “A time-scale decomposition approach to optimize wireless packet resource allocation and scheduling”, Proceedings of Wireless Communications and Networking Conference, Mar 2002 , Volume: 2 , Page(s): 699 –70.
[4]. Wha, Sook Jeon., and Dong, Guen Jeong., “Call admission control for mobile multimedia communications with traffic asymmetry between uplink and downlink”, IEEE Transactions on Vehicular Technology, Volume: 50, Issue: 1 , Jan. 2001, Page(s): 59 –66.
[5]. Chen, I. and Chen, C., “Threshold-based admission control policies for multimedia servers”, Computer Journal, 39(9), 1996, Page(s): 1-10.
[6]. Furini, M. and Towsley, D.F., “Real-time traffic transmissions over the internet”, IEEE Transactions on Multimedia, Volume: 3, Issue: 1, March 2001, Page(s): 33 – 40.
[7]. Zhang, Zhi-Li., Nelakuditi, S., Aggarwal, R., and Tsang, R.P., “Efficient selective frame discard algorithms for stored video delivery across resource constrained networks”, INFOCOM '99. Proceedings. IEEE, Volume:2 ,1999 , Page(s): 472 –479.
[8]. Tsou, Fu-Ming., Chiou, Hong-Bin., and Tsai, Zsehong., “A novel ATM traffic scheduler for real-time multimedia data transport with improved packet level QOS”, Multimedia and Expo, ICME Conf., Volume:2 , 2000, Page(s): 1047 –1050.
[9]. Hamdaoui, M. and Ramanathan, P., “A dynamic priority assignment technique for streams with (m, k)-firm deadlines”, IEEE Transactions on Computers, Volume: 44, Issue: 12 , 1995, Page(s):1443 –1451.
[10]. Koren, G. and Shasha, D., “Skip-Over: algorithms and complexity for overloaded systems that allow skips”, Proceedings of the16th Real-Time Systems Symposium, 5-7 Dec 1995, Page(s):110 –117.
[11]. Baruah, S., Gehrke, J., and Plaxton, G., “Fast scheduling of periodic tasks on multiple resources”, Proceedings of the 9th International Parallel Processing Symposium, 1995, Page(s):280-288.
[12]. Moir, M. and Ramamurthy, S., “ Pfair scheduling of fixed and migrating periodic tasks on multiple resources”, Proceedings of the 20th Real-Time Systems Symposium, 1999, Page(s):294 –303.
[13]. Shamala, S., Ramani, A.K., Yazid, M., and Othman, M., “Pro-active QoS scheduling algorithms for real-time multimedia applications in communication system”, Proceedings of TENCON 2000, Volume:2, 2000, Page(s): 466 –471.
[14]. Lee, F.K.L., and Hamdi, M. “Providing deterministic quality of service guarantee in a wireless environment”, IEEE 49th Vehicular Technology Conference, Volume:2, 1999, Page(s): 1727 –1731.
[15]. Goel, A., Shor, M.H., Walpole, J., Steere, D., and Pu, C., “Using feedback control for a network and CPU resource management application”, Proceedings of American Control Conference, Volume:5 , 2001, Page(s): 2974 –2980.
[16]. Baruah, S.K. and Lin, Shun-Shii., “ Improved scheduling of generalized pinwheel task systems”, Proceedings of Fourth International Workshop on Real-Time Computing Systems and Applications, 27-29 Oct 1997, Page(s):73 –79.
[17]. West, R. and Poellabauer, C., “Analysis of a window-constrained scheduler for real-time and best-effort packet streams”, Proceedings of the 21st IEEE Real-Time Systems Symposium, 2000, Page(s):239 –248.
[18]. Holte, R., Mok, A., Rosier, L., Tulchinsky, I., and Varvel, D., “The pinwheel: A real-time scheduling problem”, Proceedings of the 22nd Hawaii International Conference on System Science, January 1989, Page(s): 693-702.
[19]. Harju, J., Koucheryavy, Y., Laine, J., Saaristo, S., Kilkki, K., Ruutu, J., Waris, H.; Forsten, J., and Oinonen, J., “Performance measurements and analysis of TCP flows in a differentiated services WAN”, Local Computer Networks, Proceedings. 25th Annual IEEE Conference, 8-10 Nov. 2000, Page(s): 296 –305.
[20]. Laine, J., Saaristo, S., Lemponen, J., and Harju, J., “Implementation and measurements of simple integrated media access (SIMA) network nodes”, IEEE International Conference on Communications, Volume:2 , 18-22 June 2000, Page(s):796 –800.
[21]. Little, T.D.C., and Ghafoor, A., “Network considerations for distributed multimedia object composition and communication”, IEEE Network, Volume: 4 Issue: 6, Nov. 1990, Page(s): 32 -40, 45-49.
[22]. Ng, Joseph Kee-Yin. and Hui, Calvin Kin-Cheung, “The design of a QoS-aware MPEG-4 video system”, Proceedings of Real-Time Computing Systems and Applications, 2003, Page(s):460-479.
[23]. Sun, Huey-Min., Shu, LihChyun., and Chen, Chia-Mei., “Real-Time multimedia delivery over wireless networks”, Proceedings of Distributed Multimedia Systems, September 26-28, 2001, Page(s):138-143.
[24]. Herpel, C., “Elementary stream management in MPEG-4”, IEEE Transactions on Circuits and Systems for Video Technology, Volume:9 , Issue:2, 1999, Page(s):315 –324.
[25]. Eleftheriadis, A., “MPEG-4 Systems”, Proceedings of SPIE Int’l Symposium on Voice, Video, and Data Communications, Boston, MA, Vol. 4, November 2000, Page(s):1-12.
[26]. Chen, L.H., “The Implementation and Application of MPEG-4 Based Object Description Framework and Streaming Manager”, Master thesis, Dept. of Computer Science and Information Engineering, National Taiwan University, Taiwan, 2000.
[27]. Liu, J.W.-S., Lin, K.-J., Shih,W.-K., Yu, A.C.-S., Chung, C., Yao, J., and Zhao, W., “Fast Algorithms for Scheduling Imprecise Computations”, Computer, Volume:24, No. 5, May 1991, Page(s). 58-68.
[28]. Shih, W.-K., Liu, J.W.S., and Chung, J.-Y. “Fast algorithms for scheduling imprecise computations” ,Real Time Systems Symposium, 1989,Page(s): 12 –19.
[29]. Shih, W.-K. and Liu, J.W.S., “On-line scheduling of imprecise computations to minimize error”, Real-Time Systems Symposium, 1992 , 2-4 Dec 1992, Page(s): 280 –289.
[30]. Baruah, S.K., and Hickey, M.E., “Competitive on-line scheduling of imprecise computations”, IEEE Transactions on Computers, Volume: 47, Issue: 9, Sep 1998, Page(s): 1027 –1032.
[31]. Radha, H.M., Van, Der Schaar M., and Chen, Yingwei., “The MPEG-4 fine-grained scalable video coding method for multimedia streaming over IP”, IEEE Trans. on Multimedia, Volume: 3, No.1, Mar. 2001, Page(s):53-68.
[32]. Lawer, E.L. and Moore, J.M., “A functional equation and its application to resource allocation and sequencing problems”, Management Science, Volume:16, No.1, Sep. 1969, Page(s):77-84.
[33]. Aydin, H., Melhem, R., Mosse, D., and Mejia-Alvarez, P. “Optimal reward-based scheduling for periodic real-time tasks”, IEEE Transactions on Computers, Volume: 50, Issue: 2 , 2001, Page(s):111 –130.
[34]. Krishna, C.M. and Shin, Kang. G., “Task Assignment and Scheduling, Real-Time Systems”, Chapter 3, McGRAW-HILL Internatonal editions, 1997.
[35]. Tarjan, R.E., “Data Structure and Network Algorithms”, Soc. Ind. Appl. Math., Philadelphia, PA, 1983.
[36]. Liu, C.L., and Layland, J.W., “Scheduling Algorithms for Multiprogramming in a Hard Real-Time Environments”, Journal of the ACM 20(1), 1973, Page(s):40-61.
[37]. Salehi, J. D., Zhang, Z., Kurose, J., and Towsley, D., “Supporting Stored Video: Reducing Rate Variability and End-to-End Resource Requirements Through Optimal Smoothing”, IEEE/ACM Trans. on Networking, Vol. 6, No. 4,1998, Page(s):397-410.
[38]. Freman, M.L. and Tarjan, R.E., “Fibonacci heaps and their users in improved network optimization algorithms”, Journal of the ACM, Volume: 34, 1987, Page(s):596-615.
[39]. Garey, Michael R. and Johnson, David S. “Computers and Intractability: A Guide to the Theory of NP-Completeness”, Bell Laboratories Murray Hill, New Jersey, 1979.
[40]. Rothberg, Ed., “Implementation of Algorithms for Maximum Matching on Nonbipartite Graphs”, Ph.D. thesis, Stanford University, 1973.