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Most of the studies on single-server VoD systems employ the server-push delivery model. This model allows the system designer to devise periodic schedules at the server for reading data off the disk and then transmitting to the client. If we extend the server-push model to a parallel video server, a new problem arises due to the parallel transmissions from multiple independently running servers. For example, let us consider a system with N S servers using xed-size space striping. To start a new video session, a client will send a request to the proxy, which in turn will send requests to all N S servers to start a new video session. Due to variations in processing delay, network delay, and scheduling delay, the servers will start transmitting data at different time instances. It is possible that the rst stripe unit will arrive at the proxy later than the subsequent stripe units. Consequently, the proxy has to buffer the later stripe units to wait for the rst stripe unit to arrive for playback, thereby increasing the client buffer requirement and start-up delay. This synchronization problem has been investigated by Biersack et al. in [8]. For scenarios where network delays between servers and a client are different, they proposed adding different delays to the starting times of each server to compensate for delay differences. They also extended this model to include bounded network delay jitters. In another study by Buddhikot and Parulkar [11], they designed a closely-coupled system in which each storage node is connected by a custom high-speed interconnection network (APIC). The proximity of the storage nodes enables them to be accurately synchronized through the common APIC. We will return to this synchronization issue in subsequent chapters.



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He grinned and now looked happy that he had helped me Although he couldn t answer any more questions, I didn t see why I couldn t stick around and watch what happened next He didn t mind, and he even said that he d make sure no one bothered me I sneaked over to a nearby desk that was closer to the CBNC television, and settled in for a little while This made me really, really happy Even if I couldn t learn much about the new methods of trading from this old man, he at least would cover for me while I watched some television to see more of the reaction in the market And I wasn t going to leave here empty-handed From just a few moments on this trading floor, I knew about one more economic event that needed my attention: the NFP.





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Data modelling versus ontology engineering SIGMOD Record Web Edition, 31(4) Special Section on Semantic Web and Data Management, Meersman R, Sheth A (eds) Available at http:/ /wwwacm org/sigmod/record/ Staab S, Schnurr H-P 2002 Knowledge and business processes: Approaching an integration In Management and Organizational Memories, Dieng-Kuntz R, Matta N (eds) Knowledge Kluwer Academic Publishers: Boston, Dordrecht, London pp 75 88 Staab S, Studer R (eds) 2004 Handbook on Ontologies in Information Systems International Handbooks on Information Systems Springer Stojanovic L, Maedche A, Motik B, Stojanovic N 2002 User-driven ontology evolution management In Proceedings of the 13th European Conference on Knowledge Engineering and Knowledge Management EKAW, Madrid, Spain Sure Y 2003 Methodology, Tools and Case Studies for Ontology based Knowledge Management PhD thesis, University of Karlsruhe Sure Y, Angele J (eds) 2002 Proceedings of the First International Workshop on Evaluation of Ontology based Tools (EON 2002), Vol.

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In Section 934 we discussed how data redundancy can be introduced among the servers to support server-level fault tolerance The redundant data enable the receiver to mask a server failure by computing lost stripe units stored in the failed server from the parity units together with the remaining stripe units Using concepts similar to Forward Error Correction (FEC), the servers can send redundant data along with normal data to the receiver at all times In this way, the receiver can recover lost packets using the received data together with the redundant data This approach can be extended to parallel video servers to recover stripe units lost in failed servers FEC has the distinct advantage that the receiver does not need to detect a server failure As redundant data are always transmitted and received by the receiver, lost stripe units can readily be recovered if a server fails.

However, like the case in network communications, FEC incurs constant transmission overhead even when no server fails According to coding theory, we need one redundant symbol for every lost symbol we want to recover Therefore, if we use K to denote the number of lost symbols we want to recover per parity group (or stripe), the transmission overhead will be K /(N S K ) Note that this overhead could become signi cant for systems having a small number of servers, or a high level of redundancies Alternatively, for redundancy levels larger than one (ie, K > 1), we can adopt a Progressive Redundancy Transmission (PRT) algorithm to reduce the transmission overhead Speci cally, PRT initially does not transmit all available redundant data but only a portion of them.

62 of CEUR Workshop Proceedings, Siguenza, Spain CEUR-WS Publication, available at http:/ / CEUR-WSorg/Vol-62/ Sure Y, Angele J, Staab S 2003 OntoEdit: Multifaceted inferencing for ontology engineering Journal on Data Semantics, LNCS(2800):128 152 Sure Y, Erdmann M, Angele J, Staab S, Studer R, Wenke D 2002 OntoEdit: Collaborative ontology development for the semantic web In Horrocks I, Hendler JA (eds) Proceedings of the First International Semantic Web Conference: The Semantic Web (ISWC 2002), volume 2342 of Lecture Notes in Computer Science (LNCS), pp 221 235 Sardinia, Italy Springer Swartout B, Ramesh P, Knight K, Russ T 1997 Toward distributed use of largescale ontologies In Symposium on Ontological Engineering of AAAI, Stanford, CA Tempich C, Pinto HS, Sure Y, Staab S 2005 An argumentation ontology for distributed, loosely-controlled and evolving engineering processes of ontologies (DILIGENT) In Bussler C, Davies J, Fensel D, Studer R (eds).

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