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In this paper, we study the problem of finding optimal mappings for several independent but concurrent workflow applications, in order to optimize performance-related criteria together with energy consumption. Each application consists in a linear chain graph with several stages, and processes successive data sets in pipeline mode, from the first to the last stage. We study the problem complexity...
In this paper, we study a compositional approach to designing a class of stabilizing distributed systems. We show that the linear pipelined composition of a number of stabilizing modules is inherently stabilizing, and is a useful method of constructing scalable stabilizing solutions for streaming applications that are on the rise in peer-to-peer and sensor networks. We present the correctness proof...
Multi-pattern string matching remains a major performance bottleneck in network intrusion detection and anti-virus systems for high-speed deep packet inspection (DPI). Although Aho-Corasick deterministic finite automaton (AC-DFA) based solutions produce deterministic throughput and are widely used in today's DPI systems such as Snort [1] and ClamAV [2], the high memory requirement of AC-DFA (due to...
Pipelined workflows are a popular programming paradigm for parallel applications. In these workflows, the computation is divided into several stages, and these stages are connected to each other through first-in first-out channels. In order to execute these workflows on a parallel machine, we must first determine the mapping of the stages onto the various processors on the machine. After finding the...
The combination of low-cost sensors, low-cost commodity computing, and the Internet is enabling a new era of data-intensive science. The dramatic increase in this data availability has created a new challenge for scientists: how to process the data. Scientists today are envisioning scientific computations on large scale data but are having difficulty designing software architectures to accommodate...
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