Path Optimization in Stream-Based Overlay Networks

The emergence of sensor networks and distributed applications that generate data streams has created a need for Internet overlays designed for streaming data. Such stream-based overlay network (SBONs) consist of a set of Internet hosts that collect, process, and deliver stream-based data to multiple applications. A key challenge in the design and implementation of SBONs is efficient path optimization when mapping logical query streams to physical network hosts and paths. Suboptimal placements can induce poor utilization of network resources, leading to severe performance penalties, link saturation, and network hotspots. Our goal is to realize efficient stream placement that takes the physical topology of the Internet into account, thereby minimizing overall network utilization. In this paper, we describe a novel, network-aware path optimization algorithm for stream-based overlay networks. Our approach is based on a spring relaxation model that operates in a metric space defined by the pairwise node latency within the SBON. This relaxation placement algorithm utilizes the underlying network resources efficiently, is capable of performing inter-stream optimization, and can be implemented in a scalable and decentralized way. To evaluate its performance, we define a set of evaluation metrics for path optimization in terms of network utilization, application delay, and resource contention. Our simulation experiments with a realistic network topology show that relaxation placement approaches optimal network utilization without introducing an undue delay penalty or resource contention. Compared to an optimal placement strategy, relaxation placement causes only 15% more network traffic on average, while adding a 24% delay penalty for the application. We validate our simulation results with actual measurements involving 70 PlanetLab nodes.