Design and analysis of stream scheduling algorithms in distributed reservation based multimedia systems

DESIGN AND ANALYSIS OF STREAM SCHEDULING ALGORITHMS IN DISTRIBUTED RESERVATION-BASED MULTIMEDIA SYSTEMS LI, XIAORONG (B.Eng., Beijing University of Posts and Telecommunications, PRC ) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL & COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2005 To my beloved families ii Acknowledgements I am most indebted to my supervisor, Associate Professor Dr. Bharadwaj Veeravalli, for helping me learn to access the Ph.D program and inspiring me all the way during this work. His broad vision, insightful comments, and rigorous research style leave me a deep impression and will definitely influence me in my future study. I would like to express my thanks to National University of Singapore (NUS) for granting me the research scholarship. Thanks to Faculty of Engineering E-IT Unit for permission to rent us a Linux cluster, and thanks to Mr. Kwa Lam Koon for giving us valuable technical suggestions. Many thanks to the support from the project - High Speed Information Retrieval, Processing, Management and Communications on Very Large Scale Distributed Networks (funded by SingAREN and NSTB Broadband 21 Programme). My sincere thanks to my beloved parents and husband for their hearty encouragement and supports. Special thanks to my husband, Hailong, for his understanding and support throughout the Ph.D. journey. His selfless love, endless patience, and encouragement always accompany me when they were most required. Hearty thanks to all my friends in Open Source Software Lab and elsewhere in NUS. Their friendship made my study and life in NUS fruitful, enjoyable and unforgettable. iii Contents Acknowledgements Summary ii viii List of Tables xi List of Figures xii List of Symbols xvi Introduction 1.1 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Multimedia personalized services . . . . . . . . . . . . . . . . . . . . . 1.1.2 Quality of Services (QoS) requirements . . . . . . . . . . . . . . . . . . 1.1.3 Continuous media streaming . . . . . . . . . . . . . . . . . . . . . . . . 1.1.4 Stream distribution based on a central server system . . . . . . . . . . iv 1.1.5 Stream distribution based on a multi-server system . . . . . . . . . . . 12 1.1.6 Load balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.1.7 Stream caching schemes . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.1.8 Media segmentation and partial caching . . . . . . . . . . . . . . . . . 22 1.1.9 QoS-aware multicasting . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 1.3 Issues to be Studied and Main Contributions . . . . . . . . . . . . . . . . . . . 31 1.4 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 System Modelling and Problem Formulation 34 2.1 Network-based VOR system . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2.2 Cost Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.3 Notations and Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.4 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.4.1 Motivation example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Mathematical modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 2.5.1 Analysis of average service cost per request (C) . . . . . . . . . . . . . 44 2.5.2 Analysis of acceptance ratio (α) . . . . . . . . . . . . . . . . . . . . . . 49 2.5 Source-Based Stream Scheduling Algorithms 51 v 3.1 Source-Based Stream Scheduling Algorithm1 (SBS1) . . . . . . . . . . . . . . 52 3.1.1 Procedure SLCP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.1.2 Algorithm SBS1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.2 Source-Based Stream Scheduling Algorithm2 (SBS2) . . . . . . . . . . . . . . 59 3.3 Simulation studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 3.3.1 Simulation model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 3.3.2 Comparison of average service cost . . . . . . . . . . . . . . . . . . . . 66 3.3.3 Effect of finite cache space and link bandwidth . . . . . . . . . . . . . . 70 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.4 A Destination-Based Stream Scheduling Algorithm 76 4.1 Motivating example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.2 Procedure DLCP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.3 Destination-Based Streams Scheduling algorithm (DBS) . . . . . . . . . . . . . 83 4.4 Simulation study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.4.1 Comparison of average service cost . . . . . . . . . . . . . . . . . . . . 86 4.4.2 Effect of finite cache space and link bandwidth . . . . . . . . . . . . . . 88 4.4.3 Effect of video partitioning . . . . . . . . . . . . . . . . . . . . . . . . . 91 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 4.5 vi Strategies of Video Partitioning and Caching 5.1 5.2 5.3 Video Partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 5.1.1 Mathematical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.1.2 Window-Assisted Video Partitioning (WAVP) . . . . . . . . . . . . . . 105 5.1.3 Efficient resource utilization by video partitioning . . . . . . . . . . . . 108 Performance Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 5.2.1 Comparison of average service cost per request . . . . . . . . . . . . . . 115 5.2.2 Effect of finite cache space and link bandwidth . . . . . . . . . . . . . . 118 5.2.3 Effect of balancing cache and bandwidth resources . . . . . . . . . . . . 120 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Experimental Study of Video Distribution Strategies 6.1 6.2 6.3 95 124 Experimental System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 6.1.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 6.1.2 Hardware and software . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Experimental Results and analysis . . . . . . . . . . . . . . . . . . . . . . . . . 129 6.2.1 Experimental network and parameters . . . . . . . . . . . . . . . . . . 129 6.2.2 Pattern of request arrival . . . . . . . . . . . . . . . . . . . . . . . . . . 129 6.2.3 Results and analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 vii Conclusions and Future Work 137 Bibliography 142 Author’s Publications 161 viii Summary Video-on-Reservation (VoR) serves as an attractive service providing personalized multimedia services over the networks. In such multimedia services, clients can view high resolution videos at any time they prefer and have flexible controls of video playback. However, due to the large size and the special requirements of multimedia documents/streams, it requires a large number of network resources to offer personalized multimedia services. As the demand for network-based multimedia services increases, how to reduce the service cost and how to improve the Quality of Service (QoS) under the limitation of network resources have become the main challenges. In this thesis, we present a distributed VoR system and carry out design, analysis, and experimental verification of stream distribution strategies to provide networkbased multimedia services with the QoS guarantee. The essential idea of VoR services is to manage the network resources according to client preferred viewing times. In VoR services, requests are encouraged to be submitted earlier in advance to the actual viewing times, so that the system can make a careful plan for the resources management. This mechanism enables the system to improve the resource utilization and to provide services with client-preferred QoS. We design a distributed multimedia system, in which a pool of media servers are cooperative in transmitting and caching media streams to serve requests according to the clients’ requirements. The objective is to maximize the percent ix of requests which can be successfully served and at the same time minimize the average service cost per user. When a group of destinations demand a certain media stream in the network, it is cost-efficient to deliver the stream following a Steiner Tree. To provide a guaranteed QoS, generation of multicast trees with end-to-end delay constraints is recommended to minimize the costs. Since the issue in a generic form is NP-problem, we designed and analyzed source-based (SBS) or destination-based (DBS) stream scheduling algorithms to obtain suboptimal solutions with less time complexity. Both the two kinds of algorithms judiciously combine the concept of multicast routing and network caching, and the copies of multimedia documents are dynamically cached in the network. With these algorithms, media servers are cooperative in distributing media streams and the total services cost associated with both transmission cost and caching cost can be reduced dramatically. Furthermore, we study the issue of segmenting/partitioning media streams and caching streams partially so as to improve the resource utilization. We propose a novel strategy, referred to as Window-Assisted Video Partitioning strategy (WAVP), in which video partitions are delivered by adaptive schedule windows. 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(8) 4, pp. 337-344, 1997. 161 Author’s Publications [1] Xiaorong Li, Terence Hung Gih Guang, and Bharadwaj Veeravalli, “Design and Implementation of a Multimedia Personalized Service over Large Scale Networks”, in Proc. IEEE International Conference on Multimedia and Expo (ICME), July 2006. [2] Xiaorong Li and Bharadwaj Veeravalli, “Design and Performance Analysis of Multimedia Document Retrieval Strategies for Networked Video-on-Reservation Systems,” Computer Communications, Vol. 28, No. 17, pp. 1910-1924, 2005. [3] Xiaorong Li and Bharadwaj Veeravalli, “Design and Implementation of Stream Partitioning Strategies in a Distributed Multimedia System”, in Proc. IEEE Tencon, Nov. 2005. [4] Xiaorong Li and Bharadwaj Veeravalli, “A Novel Stream Partitioning Strategy for Realtime Video Delivery in Distributed Multimedia Systems,” in Proc. IEEE Consumer Communications and Networking Conference, pp. 313 - 318, Jan 2005. 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[9] Xiaorong Li and Bharadwaj Veeravalli, “Cost-effective Multicast Approaches for TimeCritical Applications in Dynamic Network Environments,” Journal paper, under review, 2005. [...]... performance In [53], Kim et al proposed to combine batching and piggybacking, and derived optimal cache-up window to minimize the bandwidth consumption In [54], batching is combined with patching to improve the performance in terms of both lower bandwidth consumption and less access latency In [55], a method of combining unicasting, patching, staggered broadcasting, and streambundling broadcasting was... for Window, Flash) to support streaming videos over internet In this thesis, we will indistinguishably use multimedia documents”, “media streams”, “video streams”, “streaming videos” and “videos” to refer to continuous streaming media Our research focuses on distributing continuous streaming videos over the networks 1.1.4 Stream distribution based on a central server system In multimedia systems, streams... the ratio of the queue length qi to the root of the average request rate of i-th video fi Stream merging [41, 46, 47, 48] Stream merging schemes reduce the bandwidth consumption by merging multiple adjacent streams of a same video One method of merging is called piggybacking [41], which slows down the playback of leading streams and/ or speeds up the playback of lagging streams Another merging strategy... videos of various popularity Lee [56] analyzed the combination of unicasting, patching, staggered broadcasting and designed the admission Chapter 1 Introduction 12 mechanisms to cooperate video delivery Poon et al [57] considered the combination of unicasting, bridging, and staggered broadcasting to minimize the reneging probability 1.1.5 Stream distribution based on a multi-server system In a single-server... size of an M M D (GB) 38 |Src| Number of sources available in the system 36 |Srco | Number of original sources initialized in the system 36 t[j] The requested viewing time of Rq[j] 37 T Interval between the arrival time of a request and its viewing time (min) 37 vwhp Id of a video warehouse 37 |V | Total number of VWHs in the network 36 1 Chapter 1 Introduction With the advent of high-speed networking... tape For multimedia services, the concerned resources are mainly referred to as the cache space Chapter 1 Introduction 17 and the bandwidth capacity of servers The server bandwidth capacity is constrained by the minimum of the I/O bandwidth and the network bandwidth The I/O bandwidth is generally determined by the bandwidth of storage device drives (e.g., disk, tape, CD, etc ) and the speed of interfaces... participate equally in serving a request Media servers [1, 5, 11, 63, 64] cooperate in both serving each request and in making decision of stream transmission and caching Papadimitriou et al [1] suggested providing cost-effective MPSs using information caching paradigm and derived caching strategies for hierarchical service architecture via Chapter 1 Introduction 14 metropolitan-area networks Won and Srivastava... extent -based, cylinder -based, log-structure, zone -based and constrained, which are effective in minimizing the retrieval time by disk caching Strategies such as striping [78] and data replication [79] are employed to place data across multiple disks of RAID so as to balance the load and enhance the access speed In [80, 75], the authors considered reducing the number of disk access by caching media data in. .. area of memory or an independent high-speed storage device The two most common types of caching are memory caching and disk caching In memory caching, the high-speed main memory is used as the cache of the relatively slowspeed disk In disk caching, the near-distance disk (e.g., in proxy) is used as the cache of the far-distance disk (e.g., in original server), or the disk is used as the cache of tertiary... capacity of vwhp 37 Cratep Pricing rate for caching per-GB data on vwhp for a minute ($/GB − min) 38 D(Lp,q ) Transmission delay on link Lp,q 52 k Total number of requests that have been successfully served 38 xvii Symbol Meaning Page Lp,q The directed link from vwhp and vwhq 37 LETp,q (i) Ending time of the i-th interval that link Lp,q is available 37 LSTp,q (i) Starting time of the i-th interval that link . DESIGN AND ANALYSIS OF STREAM SCHEDULING ALGORITHMS IN DISTRIBUTED RESERVATION- BASED MULTIMEDIA SYSTEMS LI, XIAORONG (B.Eng., Beijing University of Posts and Telecommunications,. constraints is recommended to minimize the costs. Since the issue in a generic form is NP-problem, we designed and analyzed source -based (SBS) or destination -based (DBS) stream scheduling algorithms. to obtain suboptimal solutions with less time complexity. Both the two kinds of algorithms judiciously combine the concept of mul- ticast routing and network caching, and the copies of multimedia