|
A Scalable and Secure Peer-to-Peer Information Sharing Tool Collaboration Technologies Group Distributed Systems Department Computational Research Division Lawrence Berkeley National Laboratory |
| Home | Progress Reports | People | Publications and Presentations | Software |
Resource Discovery Infrastructure
Authors
W. Hoschek, K. Berket, and D. AgarwalAbstract
For large distributed multi-disciplinary science collaborations it is a difficult problem to find data, results, and resources. Typically, defining centralized storage and managing the resources as a single domain solves this problem. But this solution scales poorly and does not allow for opportunistic use of resources and data repositories. As a much more scalable alternative, we propose to research, design, develop, evaluate and benchmark a reusable software infrastructure for Peer-to-Peer resource discovery, thereby enabling a range of innovative research directions building on it. The infrastructure will address a number of scalability problems in a general way. It will provide flexible and uniform transport-independent resource discovery mechanisms to reduce both the client and network burden in multi-hop P2P systems. We hope that this research and resulting infrastructure will enable new types of DOE science applications.
Further future work will focus on enabling heterogeneous P2P networks of services for science applications, integrating many distinct infrastructures and application components. For example, such heterogeneous P2P networks provide an innovative and reusable productivity tool suite by integrating collaborative P2P chat, service discovery, databases, network monitoring, data sharing tools as well as end-to-end security mechanisms.
Reference
U.S. Department of Energy National Collaboratories Program Meeting, Argonne National Laboratory, Illinois, Aug. 10-12, 2004.Full-length Paper
Contact: Webmaster <webmaster@george.lbl.gov>
Credits: A Scalable and Secure Peer-to-Peer Information Sharing Tool research and development is funded by the U.S. Dept. of Energy, Office of Science, Office of Advanced Scientific Computing Research, Mathematical, Information, and Computational Sciences Division; Support Credits identify the funding sources and the organizational context of the work described in this document.