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研究生:曾義憲
研究生(外文):Yi-Hsien Tseng
論文名稱:IEEE802.15.3無線多媒體網路之資源管理
論文名稱(外文):Resource Management for IEEE 802.15.3 Wireless Multimedia Networks
指導教授:陳健輝陳健輝引用關係
指導教授(外文):Gen-huey Chen
學位類別:博士
校院名稱:國立臺灣大學
系所名稱:資訊工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:英文
論文頁數:111
中文關鍵詞:資源管理流量預測允入控制排程多媒體
外文關鍵詞:resource managementtraffic predictionadmission controlschedulingmultimedia
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近來無線通訊技術的發展(例如:超寬頻)已經使得人們有機會在家中享受高品質的無線多媒體服務。對於高速無線個人網路,IEEE 802.15.3 為一新興的無線技術標準,此標準結合了低成本、省電、高傳輸速率以及強固的服務品質(QoS)保證等優勢。雖然IEEE 802.15.3 的媒體存取控制(MAC)層已經提供了服務品質保證的基本架構,然而他卻沒有提供資源管理的功能,例如: 頻寬配置、允入控制與資源排程。
為了滿足未來無線多媒體服務對於服務品質的要求,尤其是針對即時性多媒體服務的需求,以下三個問題為在 IEEE 802.15.3 多媒體網路上提供資源管理功能的主要挑戰。
(1) 如何針對不同的影片統計特性,以可調適(adaptively)的方式預測變動位元速率(VBR)的即時影片之頻寬需求?
(2) 如何設計一個可以保證變動位元速率的即時影片之服務品質以及可以同時增進頻道使用率(channel utilization)的允入控制方案?
(3) 如何排程變動位元速率的即時影片之流量以保證其服務品質且可以同時增進頻道使用率?
本論文之目的在於發展一系列適用於IEEE 802.15.3 多媒體網路的資源管理功能,以期可以保證傳輸的服務品質以及提升頻道使用率。對於問題(1),我們針對變動位元速率的即時影片提出一個可以克服轉場(scene change)問題的可適性預測器,此可適性預測器基於一個可變 step-size LMS 演算法來開發。當影片轉場時,這個預測器有能力去適應快速的流量變化。基於這個可適性預測器,我們也針對變動位元速率的即時影片提出一個動態配置頻寬的方法。然而使用一個固定step-size LMS 演算法,其最佳化的參數必須根據不同的影片在預測之前事先決定以致於難以運用於即時性的服務。所以我們的可適性預測器朝向可以自動根據不同的影片來調整其最佳化參數來設計。
對於問題(2),我們針對變動位元速率的即時影片提出一個基於線上觀測其流量總合的允入控制(MBAC)方法。其觀測程序將使用一個線性 Kalman filter 去估計變動位元速率的即時影片流量總合的統計參數。這些統計參數將被用於計算做為允入決策時所用之有效頻寬(effective bandwidth)。有效頻寬是一個對於已被使用資源的觀測值,其計算方式考慮了不同資源型態、變動的統計特性以及服務品質需求之間的相互取捨。MBAC 方法的目標在於可以同時保證變動位元速率的即時影片之服務品質以及提升頻道使用率。
最後,對於問題(3),我們提出一個有效率的排程演算法。此演算法運用超寬頻技術提供的定位資訊與IEEE 802.15.3 標準提供的傳輸功率控制功能,在服務品質可以被保證下以期可以最大化系統的吞吐量(throughput)與提升頻道使用率。
Recent progress in wireless technologies (e.g., Ultra-Wideband) has made it possible for people to enjoy high-quality wireless multimedia services at home. The IEEE 802.15.3 standard for high-rate wireless personal area networks (WPANs) is an emerging wireless technology that combines low cost and low power with high data rates and robust quality of service (QoS). Although the IEEE 802.15.3 MAC layer can provide a QoS supporting framework, it does not specify the functions of resource management such as bandwidth allocation, admission control and scheduling.
In order to meet QoS requirements for future wireless multimedia services, especially for real-time multimedia services, the following problems are the main challenges of resource management for IEEE 802.15.3 multimedia networks.
1. (P1) To predict bandwidth requirements adaptively for real-time VBR videos.
2. (P2) To design an effective admission control scheme which can guarantee the QoS properties of multimedia traffics and improve channel utilization for real-time VBR videos.
3. (P3) To schedule VBR video traffics so that the QoS properties of multimedia traffics can be guaranteed and better channel utilization can result.
The objective of this dissertation is to develop some functions of resource management for IEEE 802.15.3 multimedia networks, in order to support QoS transmissions for multimedia services and improve channel utilization. For (P1), we introduce a new adaptive VBR video predictor, based on a variable step-size LMS algorithm, which can overcome the problem caused by scene changes. We also propose a dynamic bandwidth allocation scheme using the VBR video predictor. The VBR video predictor is adaptive to rapid traffic variation while scene changes occur. Rather than using the fixed step-size adaptive LMS-type predictor, which is difficult to determine in advance the optimal parameters for different VBR video traffics, we enable the VBR video predictor to adjust its step size, automatically, according to the statistics of different VBR video traffics.
For (P2), we propose an on-line measurement-based admission control (MBAC) scheme for aggregate VBR video traffics. A linear Kalman filter is to be used in the measurement process to estimate statistical parameters of aggregate VBR videos. The estimated statistical parameters are used to calculate the effective bandwidth for admission decision. The effective bandwidth, which is a measure of resource usage, represents a trade-off between sources of different types. When it is calculated, varying statistical characteristics and QoS requirements should be taken into account. The goal of the MBAC scheme is to achieve QoS guarantee for real-time VBR video traffics and improve channel utilization.
Finally, for (P3), we propose an effective scheduling algorithm, which requires the location information provided by ultra-wideband technology and the transmission power control (TPC) supported by IEEE 802.15.3. With it, the system throughput can be maximized and the channel utilization can be enhanced, while the QoS requirements are satisfied.
摘 要 ..................................................I
Abstract ..............................................III
Contents ................................................V
Tables and Figures ....................................VII
Chapter 1 Introduction ..................................1
1.1 IEEE 802.15.3 Wireless Multimedia Networks ..........1
1.2 Problems ............................................4
1.3 Overviews of Previous Work ..........................7
1.4 Dissertation Overview ..............................10
Chapter 2 Scene-Change Aware Resource Prediction for VBR Videos .................................................12
2.1 Related Work .......................................14
2.1.1 Model-Type Predictor .............................16
2.1.2 LMS-Type Predictor with Fixed Step Size ..........19
2.1.3 LMS-Type Predictor with Variable Step Size .......21
2.2 Scene-Change Aware Dynamic Bandwidth Allocation Scheme .................................................23
2.2.1 Problem Analysis for LMS-Type Predictors with Fixed Step Size ..............................................23
2.2.2 Modified Variable Step-size LMS ..................28
2.2.3 SCADBA ...........................................33
2.3 Performance Evaluation .............................34
2.3.1 Prediction Error (Comparisons) ...................36
2.3.2 Channel Utilization (Comparisons) ................40
2.3.3 Buffer Usage and Data Loss (Comparisons) .........43
Chapter 3 An On-Line Measurement-Based Admission Control ................................................46
3.1 Related Work .......................................48
3.1.1 Measurement Processes ............................49
3.1.2 Admission Criteria ...............................50
3.2 A MBAC with Aggregate Effective Bandwidth Estimation .............................................52
3.2.1 Network Model and Aggregate VBR Video Traffic Model ..................................................53
3.2.2 Measurement Process Using Kalman Filter ..........57
3.2.3 Admission Decision Using Aggregate Effective Bandwidth ..............................................61
3.3 Performance Evaluation .............................64
Chapter 4 A Spatial Reused Resource Allocation Mechanism ..............................................70
4.1 UWB ................................................71
4.2 Related Work .......................................72
4.3 A Resource Allocation Mechanism ....................75
4.3.1 Grouping .........................................77
4.3.2 CAC ..............................................81
4.3.3 BETM .............................................83
4.4 Performance Evaluation .............................87
Chapter 5 Discussion and Conclusion ....................93
References .............................................99
[1] S. Stroh, "Ultra-wideband: Multimedia unplugged," IEEE Spectrum, vol. 40,
pp. 23-27, 2003.
[2] IEEE Std 802.15.3-2003: IEEE standard for information technology - telecommunications and information exchange between systems - local and metropolitan area networks - specific requirements part 15.3: wireless medium access control (MAC) and physical layer (PHY) specifications for high rate wireless personal area networks (WPANs).
[3] FCC Notice of Proposed Rule Making, Revision of Part 15 of the Commission''s Regarding Ultra-wideband Transmission Systems, ETDocket 98-153.
[4] J. Foerster, E. Green, S. Somayazulu, and D. Leeper, "Ultra-Wideband Technology for Short-or Medium-Range Wireless Communications," Journal of Intel Technology, vol. 2, pp. 1-11, 2001.
[5] I. Dalgic and F. A. Tobagi, "Performance evaluation of ATM networks carrying constant andvariable bit-rate video traffic," IEEE Journal of Selected Areas in Communications, vol. 15, pp. 1115-1131, 1997.
[6] K. Sriram and D. M. Lucantoni, "Traffic smoothing effects of bit dropping in a packet voicemultiplexer," IEEE Transactions on Communications, vol. 37, pp. 703-712, 1989.
[7] K. Joseph, D. Reininger, D. S. R. Center, and N. J. Princeton, "Source traffic smoothing and ATM network interfaces for VBR MPEGvideo encoders," Proceedings of the IEEE ICC, vol.2, pp. 447-454, 1995.
[8] S. S. Dixit and P. Skelly, "Video traffic smoothing and ATM multiplexer
performance," Proceedings of the IEEE GLOBECOM, pp. 239-243, 1991.
[9] S. Sen, J. L. Rexford, J. K. Dey, J. F. Kurose, and D. F. Towsley, "Online smoothing of variable-bit-rate streaming video," IEEE Transactions on Multimedia, vol. 2, pp. 37-48, 2000.
[10] J. R. M. Hosking, "Fractional differencing," Biometrika, vol. 68, pp. 165-176,
1981.
[11] W. E. Leland, M. S. Taqqu, W. Willinger, and D. V. Wilson, "On the self-similar nature of Ethernet traffic (extended version)," IEEE/ACM Transactions on Networking, vol. 2, pp. 1-15, 1994.
[12] O. Lazaro, D. Girma, and J. Dunlop, "Statistical analysis and evaluation of modelling techniques forself-similar video source traffic," Proceedings of the Personal, Indoor and Mobile Radio Communications (PIMRC), vol.2, pp. 1540-1544, 2000.
[13] M. Krunz, "On the limitations of the variance-time test for inference oflong-range dependence," Proceedings of the IEEE INFOCOM, vol.3, pp. 1254-1260, 2001.
[14] M. W. Garrett and W. Willinger, "Analysis, modeling and generation of self-similar VBR video traffic," ACM SIGCOMM Computer Communication Review, Proceedings of the Conference on Communications Architectures, Protocols and Applications, vol. 24, pp. 269-280, 1994.
[15] N. Sadek, A. Khotanzad, and T. Chen, "ATM dynamic bandwidth allocation using F-ARIMA prediction model," Proceedings of the 12th International Conference on Computer Communications and Networks, pp. 359-363, 2003.
[16] Y. Shu, Z. Jin, J. Wang, and O. W. Yang, "Prediction-based admission control using FARIMA models," Proceedings of the IEEE ICC, vol.3, pp. 1325–1329, 2000.
[17] Y. Shu, Z. Jin, L. Zhang, and L. Wang, "Traffic Prediction Using FARIMA
Models," Proceedings of the IEEE ICC, vol.2, pp. 891-895, 1999.
[18] A. M. Adas, "Using adaptive linear prediction to support real-time VBR videounder RCBR network service model," IEEE/ACM Transactions on Networking, vol. 6, pp. 635-644, 1998.
[19] G. Chiruvolu, R. Sankar, and N. Ranganathan, "Adaptive VBR video traffic management for higher utilization of ATM networks," ACM SIGCOMM Computer Communication Review, vol. 28, pp. 27-40, 1998.
[20] S. Feng and R. Sankar, "Limitation of and improvement to linear prediction andsmoothing-based bandwidth allocation for VBR traffic," Proceedings of the IEEE GLOBECOM, vol.1A, pp. 209-213, 1999.
[21] S. J. Yoo, "Efficient traffic prediction scheme for real-time VBR MPEG videotransmission over high-speed networks," IEEE Transactions on Broadcasting, vol. 48, pp. 10-18, 2002.
[22] Z. Dziong, M. Juda, and L. G. Mason, "A framework for bandwidth management in ATM networks—aggregate equivalent bandwidth estimation approach," IEEE/ACM Transactions on Networking, vol. 5, pp. 134-147, 1997.
[23] K. Shiomoto, S. Chaki, and N. Yamanaka, "A simple bandwidth management strategy based on measurements of instantaneous virtual path utilization in ATM networks," IEEE/ACM Transactions on Networking, vol. 6, pp. 625-634, 1998.
[24] H. Saito and K. Shiomoto, "Dynamic call admission control in ATM networks," IEEE Journal of Selected Areas in Communications, vol. 9, pp. 982-989, 1991.
[25] T. E. Tedijanto and L. Gun, "Effectiveness of dynamic bandwidth management mechanisms in ATMnetworks," Proceedings of the IEEE INFOCOM, pp. 358-367, 1993.
[26] K. Shiomoto and S. Chaki, "Adaptive Connection Admission Control Using Real-time Traffic Measurements in ATM Networks," IEICE Transactions on Communications, vol. 78, pp. 458-464, 1995.
[27] R. J. Gibbens, F. P. Kelly, and P. B. Key, "A decision-theoretic approach to call admission control in ATMnetworks," IEEE Journal of Selected Areas in Communications, vol. 13, pp. 1101-1114, 1995.
[28] K. Shiomoto, N. Yamanaka, and T. Takahashi, "Overview of measurement-based connection admission control methods in ATM networks," IEEE Communications Surveys & Tutorials, vol. 35, pp. 2-13, 1999.
[29] F. P. Kelly, "Notes on Effective Bandwidth," Stochastic Networks: Theory and
Applications, pp. 141--168, 1996.
[30] R. Guerin, H. Ahmadi, and M. Naghshineh, "Equivalent capacity and its application to bandwidth allocation inhigh-speed networks," IEEE Journal of Selected Areas in Communications, vol. 9, pp. 968-981, 1991.
[31] C. S. Chang and J. A. Thomas, "Effective bandwidth in high-speed digital networks," IEEE Journal on Selected Areas in Communications, vol. 13, pp. 1091-1100, 1995.
[32] G. Kesidis, J. Walrand, and C. S. Chang, "Effective bandwidths for multiclass Markov fluids and other ATMsources," IEEE/ACM Transactions on Networking, vol. 1, pp. 424-428, 1993.
[33] A. I. Elwalid and D. Mitra, "Effective bandwidth of bursty, variable rate sources for admissioncontrol to B-ISDN," Proceedings of the IEEE ICC, vol.3, pp. 1325-1330, 1993.
[34] S. Chong, S. Q. Li, and J. Ghosh, "Dynamic bandwidth allocation for efficient transport of real-timeVBR video over ATM," Proceedings of the IEEE INFOCOM, vol.1, pp. 81-90, 1994.
[35] S. Wars, "Bandwidth-Allocation Schemes for Variable-Bit-Rate MPEG Sources in ATM Networks," IEEE Transactions on Circuits and Systems for Video Technology, vol. 3, pp. 190-198, 1993.
[36] R. A. Guerin and A. Orda, "QoS routing in networks with inaccurate information: theory and algorithms," IEEE/ACM Transactions on Networking, vol. 7, pp. 350-364, 1999.
[37] C. Zhu, M. S. Corson, F. Technol, and N. J. Bedminster, "QoS routing for mobile ad hoc networks," Proceedings of the IEEE INFOCOM, vol.2, pp. 958- 967, 2002.
[38] P. Bhagwat, P. Bhattacharya, A. Krishna, and S. K. Tripathi, "Enhancing throughput over wireless LANs using channel state dependent packet scheduling," Proceedings of the IEEE INFOCOM, vol.3, pp. 1133-1140, 1996.
[39] S. Lu, V. Bharghavan, and R. Srikant, "Fair scheduling in wireless packet
networks," IEEE/ACM Transactions on Networking, vol. 7, pp. 473-489, 1999.
[40] T. S. Eugene Ng, I. Stoica, and H. Zhang, "Packet fair queueing algorithms for wireless networks with location-dependent errors," Proceedings of the IEEE INFOCOM, vol.3, pp. 1103-1111, 1998.
[41] P. Ramanathan and P. Agrawal, "Adapting packet fair queueing algorithms to
wireless networks," Proceedings of the ACM MOBICOM, pp. 1-9, 1998.
[42] A. K. Parekh and R. G. Gallager, "A generalized processor sharing approach to flow control inintegrated services networks: the single-node case," IEEE/ACM Transactions on Networking, vol. 1, pp. 344-357, 1993.
[43] H. M. Chaskar and U. Madhow, "Fair scheduling with tunable latency: a round-robin approach," IEEE/ACM Transactions on Networking, vol. 11, pp. 592-601, 2003.
[44] R. H. Kwong and E. W. Johnston, "A variable step size LMS algorithm," IEEE
Transactions on Signal Processing, vol. 40, pp. 1633-1642, 1992.
[45] A. R. Reibman and B. G. Haskell, "Constraints on variable bit-rate video for ATM networks," IEEE Transactions on Circuits and Systems for Video Technology, vol. 2, pp. 361-372, 1992.
[46] G. Ramamurthy and B. Sengupta, "Modeling and analysis of a variable bit rate
video multiplexer," Proceedings of the IEEE INFOCOM, pp. 817-827, 1992.
[47] J. Ilow, "Parameter estimation in FARIMA processes with applications tonetwork traffic modeling," Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing, pp. 505-509, 2000.
[48] G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time series analysis:
Forecasting and control. Englewood Cliffs: New Jersey: Prentice Hall, 1994.
[49] A. P. Lobo and W. A. Ainsworth, "Evaluation of a glottal ARMA model of
speech production," Proceedings of the IEEE ICASSP, vol.2, pp. 13-16, 1992.
[50] J. C. Lopez-Ardao, C. Lopez-Garcia, A. Suarez-Gonzalez, M. Fernandez-Veiga, and R. Rodriguez-Rubio, "On the Use of Self-Similar Processes in Network Simulation," ACM Transactions on Modeling and Computer Simulation, vol. 10, pp. 125-151, 2000.
[51] S. Haykin, Adaptive Filter Theory: Prentice Hall, 2002.
[52] B. Widrow and S. D. Stearns, Adaptive signal processing: Prentice-Hall, Inc.
Upper Saddle River, NJ, USA, 1985.
[53] D. P. Mandic, "A generalized normalized gradient descent algorithm," IEEE
Signal Processing Letters, vol. 11, pp. 115-118, 2004.
[54] J. Lassetter, S. Ratnam, F. H. P. Fitzek, and M. Reisslein, "Traffic and Quality Characterization of Scalable Encoded Video: A Large Scale Trace Based Study," Technical Report. Dept. of Electrical Engineering, Arizona State University.
[55] P. Seeling, M. Reisslein, and B. Kulapala, "Network performance evaluation using frame size and quality traces of single-layer and two-layer video: A tutorial," IEEE Communications Surveys & Tutorials, vol. 6, pp. 58-78, 2004.
[56] B. Maglaris, D. Anastassiou, P. Sen, G. Karlsson, and J. D. Robbins, "Performance models of statistical multiplexing in packet videocommunications," IEEE Transactions on Communications, vol. 36, pp. 834-844, 1988.
[57] Z. L. Zhang, J. Kurose, J. D. Salehi, and D. Towsley, "Smoothing, Statistical Multiplexing, and Call Admission Control for Stored Video," IEEE Journal on Selected Areas in Communications, vol. 15, pp. 1148-1166, 1997.
[58] A. R. Reibman and A. W. Berger, "Traffic descriptors for VBR video teleconferencing over ATMnetworks," IEEE/ACM Transactions on Networking, vol. 3, pp. 329-339, 1995.
[59] D. Le Gall, "MPEG: a video compression standard for multimedia
applications," Communications of the ACM, vol. 34, pp. 46-58, 1991.
[60] M. Hughes, "Statistical characteristics and multiplexing of MPEG streams,"
Proceedings of the IEEE INFOCOM, vol.2, pp. 455-462, 1995.
[61] C. Jcss Filho and P. Yacoub, "Simple accurate lognormal approximation to
lognormal sums," Electronics Letters, vol. 41, pp. 1016-1017, 2005.
[62] R. E. Kalman, "A new approach to linear filtering and prediction problems," Transaction of the ASME-Journal of Basic Engineering, vol. 82, pp. 35–45, 1960.
[63] C. Casetti, J. Kurose, and D. Towsley, "An adaptive algorithm for measurement-based admission control in integrated services packet networks," Journal of Computer Communications, vol. 23, pp. 1363-1376, 2000.
[64] S. Jamin, P. B. Danzig, S. J. Shenker, and L. Zhang, "A measurement-based admission control algorithm for integratedservice packet networks," ACM/IEEE Transactions on Networking, vol. 5, pp. 56-70, 1997.
[65] S. Jamin, S. J. Shenker, and P. B. Danzig, "Comparison of measurement based admission control algorithms for controlled-load service," Proceedings of the IEEE INFOCOM, vol.3, pp. 973-980, 1997.
[66] D. Tse and M. Grossglauser, "Measurement-based call admission control: analysis and simulation," Proceedings of the IEEE INFOCOM, vol.3, pp. 981-989, 1997.
[67] H. Saito, "Call admission control in an ATM network using upper bound of cell loss probability," IEEE Transactions on Communications, vol. 40, pp. 1512-1521, 1992.
[68] D. Anick, D. Mitra, and M. M. Sondhi, "Stochastic theory of a data handling system with multiple sources," Proceedings of the IEEE ICC, vol.1, pp. 13.1.1-13.1.5, 1980.
[69] M. Grossglauser, S. Keshav, and D. N. C. Tse, "RCBR: a simple and efficient service for multiple time-scaletraffic," IEEE/ACM Transactions on Networking, vol. 5, pp. 741-755, 1997.
[70] L. F. Fenton, "The sum of lognormal probability distributions in scatter transmission systems," IRE Transactions on Communications Systems, pp. 57-67, 1960.
[71] K. Nagarajan and G. T. Zhou, "A new resource allocation scheme for VBR video traffic sources," Proceedings of the 34th Asilomar Conference on Signals, Systems, and Computers, vol.2, pp. 1245–1249, 2000.
[72] A. Demers, S. Keshavt, and S. Shenker, "Analysis and Simulation of a Fair Queueing Algorithm," Proceedings of the ACM SIGCOMM, vol.19, pp. 1-12, 1989.
[73] J. C. R. Bennett and Z. Hui, "WF2Q: worst-case fair weighted fair queueing,"
Proceedings of the IEEE INFOCOM, vol.1, pp. 120-128 vol.1, 1996.
[74] P. Goyal, H. M. Vin, and H. Chen, "Start-time fair queueing: a scheduling algorithm for integrated services packet switching networks," IEEE/ACM Transactions on Networking, vol. 5, pp. 157-168, 1996.
[75] S. J. Golestani, "A self-clocked fair queueing scheme for broadband
applications," Proceedings of the IEEE INFOCOM, vol.2, pp. 636-646, 1994.
[76] H. Zhang, "Service disciplines for guaranteed performance service inpacket-switching networks," Proceedings of the IEEE, vol.83, pp. 1374-1396, 1995.
[77] S. Apkun, M. Hamdi, and J. P. Hubaux, "GPS-free Positioning in Mobile Ad
Hoc Networks," Journal of Cluster Computing, vol. 5, pp. 157-167, 2002.
[78] H. A. Peelle, "Graph coloring in J: an introduction," Proceedings of the ACM
SIGAPL APL Quote Quad Conference, vol.31, pp. 77-82, 2000.
[79] H. Karloff, Linear programming: Birkhauser: Boston, 1991.
[80] R. M. Karp, "Reducibility among combinatorial problems," Proceedings of the Symposium on the Complexity of Computer Computations, vol.43, pp. 85-103, 1972.
[81] D. Brelaz, "New methods to color the vertices of a graph," Communications of
the ACM, vol. 22, pp. 251-256, 1979.
[82] I. M. Diaz and P. Zabala, "A branch-and-cut algorithm for graph coloring," Proceedings of the Computational Symposium on Graph Coloring and Generalizations, 2002.
[83] M. M. Hallorsson, "A still better performance guarantee for approximate graph
coloring," Information Processing Letters, vol. 45, pp. 19-23, 1993.
[84] B. Avrim, "New approximation algorithms for graph coloring," Journal of the
ACM, vol. 41, pp. 470-516, 1994.
[85] D. Karger, R. Motwani, and M. Sudan, "Approximate graph coloring by
semidefinite programming," Journal of the ACM, vol. 45, pp. 246-265, 1998.
[86] G. B. Dantzig, "Programming of Interdependent Activities: II Mathematical
Model," Econometrica, vol. 17, pp. 200-211, 1949.
[87] N. Karmakar, "A new polynomial-time algorithm for linear programming,"
Combinatorica, vol. 4, pp. 373-395, 1984.
[88] A. B. Kurzhanskii and I. Valyi, Ellipsoidal Calculus for Estimation and
Control: Iiasa Research Center, 1997.
[89] G. Arfken, "Lagrange Multipliers," Mathematical Methods for Physicists,
Academic Press, pp. 945-950, 1985.
[90] Ns2, the VINT project, http://www.isi.edu/nsnam/ns/.
[91] M. Demirhan, IEEE 802.15.3 MAC model for ns-2,
http://www.winlab.rutgers.edu/~demirhan, Intel Corporation.
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1. 丁文玲(2003)。學校自我評鑑之探討,研習資訊,20(3),頁67-75。
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3. 王保進、王麗芬(1999)。師資培育機構自我評鑑現況與改進途徑之分析。暨大學報,3(2),13-42。
4. 吳俊佑(2003)。反省教育評鑑和教學評鑑的本質與問題。竹縣文教,28期,頁49-51。
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6. 邱錦昌(1993)。英國皇家督學視導措施之簡介(上),研習資訊,10(6),16-20。
7. 梁暖茱(2002)。學校自我評鑑觀念的釐析。商業職業教育季刊,87期,頁15-22。
8. 陳明印(2002)。美國2001年初等級中等教育修正法案之分析。教育研究資訊,10(1),頁205-228。
9. 陳美如 郭昭佑(民)教師如何從事課程評鑑:從賦權增能評鑑理念談起。教育研究月刊,88,頁83-93。
10. 陳美如 郭昭佑(2002)。賦權增能評鑑的理論探究:對課程評鑑的啟示。暨大學報,6(1),頁61-94。
11. 黃坤政(2001)。績效報告亦或組織改進-視評論校務評鑑。竹縣文教,25期,頁29-32。
12. 鄭崇趁(2001)。目標、願景與學校發展計劃,教育研究月刊,91期,頁45-51。
13. 鄭彩鳳(2004)。教育績效管理與績效責任。教育研究月刊,124期,頁5-21。
14. 盧增緒(1985)。教育評鑑初探。師大學報,30期,頁115-147。
15. 閻自安(2004)。學校品質團隊的發展與建立。教育研究月刊,123期,頁66-80。