Scalability of Persistent Queries Dartmouth Dartmouth College Scalability of Persistent Queries (Contact: Daniela Rus, rus@cs.dartmouth.edu) Mobile Agent Persistent Query System Persistent Query Module Inside each Query A News articles S e r v a l Persistent Query Server Analyst’s machine at HQ A 1. Agent jumps to server machine with query. 2. Persistent query server retrieves and clusters existing documents. 3. Agent sends clusters back to analyst. Soldier in the field A Star Clustering Algorithm 3 4 1 2 Serval Architecture Estimate degrees of nodes by sampling similarities Find and mark star cluster centers Insert documents into appropriate clusters Scalability of Persistent Queries Lessons Learned: 1) sampled star is effective and scalable for persistent queries 2) agents can do local processing on the persistent-query results before sending the documents back 3) avoid information overload 4) current implementation can sustain 1,600 persistent queries 5) sampled star algorithm solves the memory problems observed with the star implementation 6) future direction for modeling and scalability experiments for the Mobility TIE Dartmouth