Toward Globally Optimal Event Monitoring & Aggregation For Large-scale Overlay Networks

Overlay networks have emerged as a powerful and flexible platform for developing new disruptive network applications. The performance and reliability of overlay applications depend on the capability of overlay networks to dynamically adapt to various factors such as link/node failures, overlay link quality, and overlay node characteristics. In order to achieve this, the overlay applications require scalable and open overlay monitoring services to monitor, aggregate globally distributed events and take appropriate control actions. In this paper, we propose the techniques and algorithms to create an optimal event monitoring and aggregation infrastructure (called MOON) that minimizes the monitoring latency (i.e., event retrival/detection time) and event aggregation cost (i.e., intrusiveness) considering the large-scale geographical and network distribution of overlay nodes. The proposed monitoring infrastructure, MOON, clusters and organizes overlay nodes efficiently such that overlay applications can globally monitor and query correlated events in an overlay network with minimum latency and monitoring cost. Our simulations and experimental studies show the evaluation of MOON under many various topological structures, network sizes, and event aggregation volumes.