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Grid Computing Research LaboratoryState University of New York (SUNY) BinghamtonDepartment of Computer Science |
Deger C. Erdil, Michael J. Lewis, and Nael Abu-Ghazaleh,
"An Adaptive Algorithm for Information Dissemination
in Self-Organizing Grids",
The 2nd IEEE International Conference on e-Science and Grid Computing
(eScience 2006),
Silicon Valley, CA, July 19-21, 2006.
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[bibtex]
Abstract
Effective scheduling in large-scale computational grids is challenging
because it requires tracking the dynamic state of the
large number of distributed resources that comprise the grid.
Classical distributed information dissemination approaches
such as push, pull, and their combinations, are not well suited
to the problem of resource tracking, where resources are redundant
and full information about all resources everywhere
is neither necessary nor desirable. Aggregated, partial, or
probabilistic forwarding protocols result in more efficient (but
incomplete) dissemination, while maintaining sufficient information
to enable effective scheduling. However, a static approach
to dissemination in which all information is treated
identically, is ineffective in the presence of spatial and temporal
non-uniformity of resources and demands. For example, a
single forwarding probability for gossipping-based dissemination
may result in unnecessarily high overhead in some areas
of the grid. Moreover, the right forwarding probability values
can change over time, with changes in offered load and node
utilization. Adaptive protocols can adjust the aggressiveness
with which information is disseminated, based on current grid
conditions, and can in turn increase query satisfaction rates,
reduce overhead, or both. This paper explores the characteristics
and behavior of adaptive probabilistic and changesensitive
information forwarding protocols, identifying and addressing
several issues and problems, and introducing dissemination
protocols that are better able to reduce overhead and
increase query satisfaction rates for a variety of grid conditions.
Key Words:
Adaptive information dissemination, self-organizing
grids, grid resource discovery.