Electrical computers and digital processing systems: multicomput – Computer-to-computer protocol implementing – Computer-to-computer data streaming
Reexamination Certificate
2006-06-13
2009-02-17
Vaughn, Jr., William C (Department: 2141)
Electrical computers and digital processing systems: multicomput
Computer-to-computer protocol implementing
Computer-to-computer data streaming
C709S240000
Reexamination Certificate
active
07493406
ABSTRACT:
Disclosed is a method, upstream processing node, and computer readable medium for processing data packets. The method includes receiving an allocation for at least one computing resource. At least one data packet at one or more upstream processing elements in an upstream processing node is received. The method also includes determining if at least one output queue of the upstream processing elements includes available space for processing of the data packet. The data packet is processed in response to the output queue including available space to form a resulting data packet. The method further includes determining that an input queue of at least one downstream processing element of a plurality of downstream processing elements includes available space for receiving the resulting data packet In response to the determining, the resulting data packet is transmitted from the upstream processing element to the downstream processing element.
REFERENCES:
patent: 6999419 (2006-02-01), Ise et al.
patent: 7159219 (2007-01-01), Chen et al.
patent: 7359971 (2008-04-01), Jorgensen
Microsoft DirectX version 9.0 software development toolkit. Http://msdn.microsoft.com/directx/directxSDK/default.aspx.
Arasu, A. et al., “Stream: The Stanford Stream Data Manager (demonstration description)”, Proceedings of the 2003 ACM International Conference on Management of Data (SIGMOD 2003), San Diego, CA., Jun. 2003.
Azar, Y. et al., “Management of Multi-Queue Switches in QoS Networks,” 2003.
Balazinska, M. et al., “Load Management and High Availability in the Medusa Distributed Stream Processing System,” In SIGMOD '04: Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data, pp. 929-930, New York, NY USA 2004, ACM Press.
Baptiste, P. et al., “Preemptive Scheduling of Equal-Length Jobs to Maximize Weighted Throughput,” Mar. 5, 2003.
Bartal, Y. et al., “Online Competitive Algorithms for Maximizing Weighted Throughput of Unit Jobs,” 2004.
Buck, J.T. et al., “Ptolemy: A Framework for Simulating and Prototyping Heterogeneous Systems,” Int. Journal of Computer Simulation, special issue on “Simulation Software Development,” vol. 4, pp. 155-182, Apr. 1994.
Chandra, A. et al., Surplus Fair Scheduling: A Proportional-Share CPU Scheduling Algorithm for Symmetric Multiprocessors, pp. 45-58.
Chandrasekaran, S. et al., “TelegraphCQ: Continuous Dataflow Processing for an Uncertain World,” In Proceedings of the 2003 Conference on Innovative Data Systems Research (CIDR 2003), Asilomar, CA 2003.
de Niz, D., et al., “Resource Sharing in Reservation-Based Systems,” In RTSS '01: Proceedings of the 22ndIEEE Real-Time Systems Symposium (RTSS'01), p. 171, Washington, D.C., USA 2001, IEEE Computer Society.
Hoang, P., et al., “Scheduling of DSP Programs onto Multiprocessors for Maximum Throughput,” IEEE Transactions on Signal Processing, 41(6):2225-2235, Jun. 1993.
Hollot, C.V., et al., “On Designing Improved Controllers for AQM Routers Supporting TCP Flows,” In INFOCOM, pp. 1726-1734, 2001.
Humphreys, G., et al., “Chromium: A Stream-Processing Framework for Interactive Rendering on Clusters,” 2002.
Koster, R., et al., “Infopipes for Composing Distributed Information Flows,” In Proceedings of the 2001 ACM Multimedia Workshop on Multimedia Middleware, Ottawa, Canada, Oct. 2001.
Lam, T., et al., “On the Speed Requirement for Optimal Deadline Scheduling in Overloaded Systems,” In Proc. 15thInternational Parallel and Distributed Processing Symposium, p. 202, 2001.
Lee, E.A., et al., “Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing,” IEEE Transactions on Computing, 36(1):24-35, Jan. 1987.
Nagar, S., et al., “Improving Linux Resource Control Using CKRM,” In Proceedings of the 2004 Ottawa Linux Symposium, Ottawa, Canada, Jul. 2004.
Park, I., et al., “Stable Load Control with Load Prediction in Multipath Packet Forwarding,” In ICOIN, pp. 437-444, 2001.
Pietzuch, P., et al., “Network-Aware Operator Placement for Stream-Processing Systems,” To Appear: Proceedings of the 22ndInternational Conference on Data Engineering (ICDE '06), Atlanta, GA, Apr. 2006,
Saewong, S., et al., “Cooperative scheduling of Multiple Resources,” In RTSS '99: Proceedings of the 20thIEEE Real-Time Systems Symposium, p. 90, Washington, D.C., USA, 1999, IEEE Computer Society.
Schwetman, H., “CSIM: A C-Based Process-Oriented Simulation Language,” In WSC '86: Proceedings of the 18thConference on Winter Simulation pp. 387-396, New York, NY USA 1986, ACM Press.
Zdonik, S., “The Aurora and Medusa Projects;” Bulletin of the IEEE Technical Committee on Data Engineering, Mar. 2003.
Amini Lisa D.
Sehgal Anshul
Silber Jeremy I.
Verscheure Olivier
Wolf Joel L.
Fleit Gibbons Gutman Bongini & Bianco P.L.
Gibbons Jon A.
International Business Machines - Corporation
Mortinger Alison D.
Shingles Kristie D.
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