Scalable Planning for Distributed Stream Processing Systems

Recently the problem of automatic composition of workflows has been receiving increasing interest. Initial investigation has shown that designing a practical and scalable composition algorithm for this problem is hard. A very general computational model of a workflow (e.g., BPEL) can be Turingcomplete, which precludes fully automatic analysis of compositions. However, in many applications, workflow model can be simplified. We consider a model known as the Stream Processing Planning Language (SPPL), applicable in stream processing and other related domains. SPPL replaces the notion of concurrency by timeless functional computation. In addition, SPPL defines workflow metrics of resource consumption and quality of service. Experiments have shown earlier that even a na

• Type: Conference
• Year: 2006
• Where: AIPS
• Authors: Anton Riabov, Zhen Liu
• Keywords: AIPS 2006, Artificial Intelligence, Scalable Composition Algorithm, Stream Processing, Workflow