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ICMAS
1998
13 years 9 months ago
Multi-Machine Scheduling - A Multi-Agent Learning Approach
Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and comp...
Wilfried Brauer, Gerhard Weiß
OTM
2007
Springer
14 years 1 months ago
Decentralised Commitment for Optimistic Semantic Replication
Abstract. We study large-scale distributed cooperative systems that use optimistic replication. We represent a system as a graph of actions (operations) connected by edges that rei...
Pierre Sutra, João Barreto, Marc Shapiro
HPDC
2002
IEEE
14 years 20 days ago
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets. So...
Kavitha Ranganathan, Ian T. Foster
INFOCOM
2009
IEEE
14 years 2 months ago
Optimal Anycast Technique for Delay-Sensitive Energy-Constrained Asynchronous Sensor Networks
Abstract—In wireless sensor networks, asynchronous sleepwake scheduling protocols can significantly reduce energy consumption without incurring the communication overhead for cl...
Joohwan Kim, Xiaojun Lin, Ness B. Shroff
CASES
2011
ACM
12 years 7 months ago
Cost-effective safety and fault localization using distributed temporal redundancy
Cost pressure is driving vendors of safety-critical systems to integrate previously distributed systems. One natural approach we have previous introduced is On-Demand Redundancy (...
Brett H. Meyer, Benton H. Calhoun, John Lach, Kevi...