Grant: Department of National Defence / NSERC Research Partnership

Information monitoring is essential in work-flow execution environments to provide statistical interpretation onexecuting processes, based on control functions on process parameters. Monitoring aims toward anoptimization trade-off between timely response and comprehensive data gathering. The problem usuallyinvolves multiple monitoring points reporting to a centralized coordination center. In contrast, distributedmonitoring requires physically distributed and autonomous agents bound by local and potentially inaccurateshared information collected in a dynamic and uncertain environment. In this proposal, we aim to elaborate aframework capable of distributed plan execution monitoring to address recent developments on the globalarena which require large-scale joint coalition operational plans. These operations need to be adaptive to thedynamic that unfolds during execution as exemplified by search and rescue operations and humanitarian aiddistribution. The goal of this initiative includes research contribution objectives in these areas: 1) dataexchange protocols; 2) distributed monitoring algorithms; 3) analysis of monitored data; 4) monitoringarchitecture and design; 5) concept validation through logistics distribution case study. The underlyingprocesses will receive decision vector feedback from distributed monitoring agents, each with its ownenvironment, information domain, goals, resources and capabilities. Moreover, analysis of monitoring data willbe used for ongoing adaptive planning efforts using on-line analytical processing (OLAP) and on-lineanalytical mining (OLAM). These techniques allow identifying emerging patterns or relevant trends. Also, toinduce accurate multi-player information exchanges, we propose the use of game theory and mechanismdesign. The architecture and design will support command and information perspectives necessary to separatedifferent hierarchical levels for localized task execution with respect to space, time, capability andenvironment. Finally, as test-bed exercise, we will conduct case studies on logistic distribution where theexecution of dynamic vehicle routing will be monitored from distributed locations.