Acyclic fork-join queuing networks
Journal of the ACM (JACM)
On the execution of parallel programs on multiprocessor systems—a queuing theory approach
Journal of the ACM (JACM)
Graph classes: a survey
Rate-based query optimization for streaming information sources
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Introduction to Algorithms
A smart hill-climbing algorithm for application server configuration
Proceedings of the 13th international conference on World Wide Web
Distributed stream join query processing with semijoins
Distributed and Parallel Databases
Resource reconstruction algorithms for on-demand allocation in virtual computing resource pool
International Journal of Automation and Computing
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Data streaming applications are becoming more and more common due to the rapid development in the areas such as sensor networks, multimedia streaming, and on-line data mining, etc. These applications are often running in a decentralized, distributed environment. The requirements for processing large volumes of streaming data at real time have posed many great design challenges. It is critical to optimize the ongoing resource consumption of multiple, distributed, cooperating, processing units. In this paper, we consider a generic model for the general stream data processing systems. We address the resource allocation problem for a collection of processing units so as to maximize the weighted sum of the throughput of different streams. Each processing unit may require multiple input data streams simultaneously and produce one or many valuable output streams. Data streams flow through such a system after processing at multiple processing units. Based on this framework, we develop distributed algorithms for finding the best resource allocation schemes in such data stream processing networks. Performance analysis on the optimality and complexity of these algorithms are also provided.