Gribble, S. Simplifying Cluster-Based Internet Service Construction with Scalable Distributed Data Structures. Ph.D. Candidacy Qualifying Exam. Apr 1999. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Universal Inbox: Providing Extensible Personal Mobility and .. - Raman, Katz, Joseph (2000) (13 citations) (Correct)
....the bulk of transformations, and have Java wrappers at the back end nodes. The PR also has a front end and a back end. The backend implements the storage of the user preference scripts, and the front end processes them. The back end uses a distributed, persistent, cluster based storage mechanism [7]. The scripts are represented in TCL and the front end uses a Jacl interpreter to process them [16] For all the tests, we used 500Mhz Pentium III 2 way multiprocessor machines for the servers (i.e. the functional components) and a 400MHz Pentium II machine for the client. The servers had 256MB ....
S. Gribble. Simplifying Cluster-Based Internet Service Construction with Scalable Distributed Data Structures. PhD Candidacy Qualifying Exam, U.C.Berkeley, April 1999.
Safe and Efficient Hardware Specialization of Java Applications - Welsh (Correct)
....application. sulting in a 15 20 increase in peak bandwidth and a 25 reduction in round trip latency. Using Java s protection model in place of the traditional systemcall boundary could improve other aspects of application performance, including support for high I O concurrency and throughput [38, 15]. 6 Conclusion Java server applications must necessarily make use of functionality not directly provided by the JVM. These applications require both access to lowlevel system resources, such as fast communication and I O interfaces, as well as management of memory external to the Java heap. ....
Steven Gribble. Simplifying Cluster-Based Internet Service Construction with Scalable Distributed Data Structures. http://www.cs.berkeley.edu/- ~gribble/papers/quals/sdds-cluster.ppt.
Jaguar: Enabling Efficient Communication and I/O in Java - Welsh, Culler (1999) (1 citation) (Correct)
....implement an ecient RPC and data persistence mechanism for Java; combining the use of JaguarVIA and PSOs should enable a high performance RPC mechanism for workstation clusters. We are also investigating the use of PSOs to implement distributed data structures for cluster based Internet services [8] and databases [9] The prototype implementation of Pre Serialized Objects has several important limitations. The fact that cross PSO references are only recoverable if both PSOs are within the same container implies an informed programming model which makes this limitation explicit. Currently, ....
Steven Gribble. Simplifying Cluster-Based Internet Service Construction with Scalable Distributed Data Structures. http://www.cs.berkeley.edu/- ~gribble/papers/quals/sdds-cluster.ppt.
Jaguar: Enabling Efficient Communication and I/O in Java - Welsh, Culler (9 citations) (Correct)
....implement an e cient RPC and data persistence mechanism for Java; combining the use of JaguarVIA and PSOs should enable a high performance RPC mechanism for workstation clusters. We are also investigating the use of PSOs to implement distributed data structures for cluster based Internet services [10] and databases [11] The prototype implementation of Pre Serialized Objects has several important limitations. The fact that cross PSO references are only recoverable if both PSOs are within the same container implies an informed programming model which makes this limitation explicit. Currently, ....
Steven Gribble. Simplifying cluster-based internet service construction with scalable distributed data structures. http://www.cs.berkeley.edu/- ~gribble/papers/quals/sdds-cluster.ppt.
The Ninja Jukebox - Goldberg, Gribble, Wagner, Brewer (1999) (9 citations) Self-citation (Gribble) (Correct)
....the same office, a useful combination would be to play songs that are in the intersection of the students sets of likable songs. The DJ extensions to the core Jukebox service 3 We actually used a distributed, persistent hash table to keep track of user preferences. This hash table (described in [9]) is partitioned and replicated across nodes in a dedicated workstation cluster, and provides the DJ fault tolerant access to the persistent user preferences data. resulted in minimal changes to the existing codebase; rather, the extensions were mostly encapsulated within the new DJ component ....
Steven D. Gribble. Simplifying Cluster-Based Internet Service Construction with Scalable Distributed Data Structures. Ph.D. Qualifying exam, available at http://www.cs.berkeley.edu/ ~gribble/papers/quals/sdds-cluster.ps.gz, April 1999.
The Data Management Problem in Post-PC Devices and a Solution - Gummadi, Katz (2000) (Correct)
No context found.
Gribble, S. Simplifying Cluster-Based Internet Service Construction with Scalable Distributed Data Structures. Ph.D. Candidacy Qualifying Exam. Apr 1999.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC