This link has been bookmarked by 117 people . It was first bookmarked on 02 Mar 2006, by Joel Liu.
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J MMy Ph.D. thesis work at UC Berkeley focused on the development of a robust, high-performance platform for Internet services, called SEDA. The goal is to build a system capable of supporting massive concurrency (on the order of tens of thousands of simultaneous client connections) and avoid the pitfalls which arise with traditional thread and event-based approaches.
SEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event and thread scheduling from application logic. By performing admission control on each event queue, the service can be well-conditioned to load, preventing resources from being overcommitted when demand exceeds service capacity. SEDA employs dynamic control to automatically tune runtime parameters (such as the scheduling parameters of each stage), as well as to manage load, for example, by performing adaptive load shedding. Decomposing services into a set of stages also enables modularity and code reuse, as well as the development of debugging tools for complex event-driven applications. -
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stoyan stoyaninteresting architecture model
programming framework network scalability server distributed concurrent multiprocess multithreading
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SEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event and thread scheduling from application logic.
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koei kimMy Ph.D. thesis work at UC Berkeley focused on the development of a robust, high-performance platform for Internet services, called SEDA.
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chunzhong zhangSEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues.
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er of open source and commercial systems are based on SEDA and NBIO. These include: * LimeWire runs runs its server based Web crawler on NBIO.
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Tony SutherlandSEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event
server applications applicationDevelopment webApplications web_development webDevelopment load scheduling adaptive reuse architecture distributed programming performance patterns webServices webServer webdev
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13 Apr 07
Robert KaymanSEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event
academic Architecture concurrency design development model patterns performance programming reference research scalability distributed seda Delicious
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Sean O'Halpin"SEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues..." - prototype in Java
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SEDA: An Architecture for Highly Concurrent Server Applications
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David Rousseljava event based server platform
architecture scalability performance java network distributed development software :to_read
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drewferSEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues.
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16 Nov 05
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SEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event and thread scheduling from application logic. By performing admission control on each event queue, the service can be well-conditioned to load, preventing resources from being overcommitted when demand exceeds service capacity. SEDA employs dynamic control to automatically tune runtime parameters (such as the scheduling parameters of each stage), as well as to manage load, for example, by performing adaptive load shedding. Decomposing services into a set of stages also enables modularity and code reuse, as well as the development of debugging tools for complex event-driven applications.
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The goal is to build a system capable of supporting massive concurrency (on the order of tens of thousands of simultaneous client connections) and avoid the pitfalls which arise with traditional thread and event-based approaches.
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Ed DanielAn Architecture for Highly Concurrent Server Applications
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SEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event and thread scheduling from application logic. By performing admission control on each event queue, the service can be well-conditioned to load, preventing resources from being overcommitted when demand exceeds service capacity. SEDA employs dynamic control to automatically tune runtime parameters (such as the scheduling parameters of each stage), as well as to manage load, for example, by performing adaptive load shedding. Decomposing services into a set of stages also enables modularity and code reuse, as well as the development of debugging tools for complex event-driven applications.
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13 Jun 04
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SEDA is an acronym for staged event-driven architecture, and decomposes a complex, event-driven application into a set of stages connected by queues. This design avoids the high overhead associated with thread-based concurrency models, and decouples event and thread scheduling from application logic. By performing admission control on each event queue, the service can be well-conditioned to load, preventing resources from being overcommitted when demand exceeds service capacity. SEDA employs dynamic control to automatically tune runtime parameters (such as the scheduling parameters of each stage), as well as to manage load, for example, by performing adaptive load shedding. Decomposing services into a set of stages also enables modularity and code reuse, as well as the development of debugging tools for complex event-driven applications.
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11 Feb 04
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