REAL-TIME MONITORING OF GLOBAL VARIABLES IN LARGE-SCALE DYNAMIC SYSTEMS

Large-scale dynamic systems, such as the Internet, as well as emerging peerto-peer networks and computational grids, require a high level of awareness of the system state in real-time for proper and reliable operation. A key challenge is to develop monitoring functions that are efficient, scalable, robust and controllable. The thesis addresses this challenge by focusing on engineering protocols for distributed monitoring of global state variables. The global variables are network-wide aggregates, computed from local device variables using aggregation functions such as SUM, MAX, AVERAGE, etc. Furthermore, it addresses the problem of detecting threshold crossing of such aggregates. The design goals for the protocols are efficiency, quality, scalability, robustness and controllability. The work presented in this thesis has resulted in two novel protocols: a gossip-based protocol for continuous monitoring of aggregates called G-GAP, and a tree-based protocol for detecting threshold crossings of aggregates called TCA-GAP. The protocols have been evaluated against the desig