iFlow is a replication-based system that can achieve both fast and reliable processing of high volume data streams on the Internet scale. iFlow uses a low degree of replication in conjunction with detouring techniques to overcome network congestion and outages. Computation over iFlow can be expressed as a graph of operators. To cope with varying system conditions these operators continually migrate in a manner that improves performance and availability at the same time.

Network coordinate systems can efficiently predict the round-trip time between any pair of nodes on the Internet. These systems map nodes onto a multi-dimensional coordinate space such that the round-trip time between two arbitrary nodes can be estimated by the distance between the corresponding pair of points in the coordinate space. In these systems, each node continuously updates its coordinates based on the latencies of new communications and the coordinates of other nodes. Node coordinates obtained in this manner, however, may be misled by erroneous information, such as extraordinary roundtrip times. Previous techniques attempt to overcome this problem by having nodes reject new information if it is inconsistent with the current coordinates. These techniques are still inappropriate if the coordinates are not sufficiently accurate. In this paper, we develop a new approach where each node preserves recent communication history. To update a node's coordinates more accurately, our approach re-evaluates the records in the node's history while ignoring inconsistent communication records and applying a higher weight to more reliable records. This approach thus can prevent node coordinates from being affected by erroneous information that was difficult to detect in the past. Through evaluations based on real network trace data, we demonstrate that our approach can reduce network latency prediction errors by 50% compared to previous approaches.

We propose to demonstrate iFlow, our replication-based system that supports both fast and reliable processing of data streams over the Internet. iFlow uses a low degree of replication in conjunction with detouring techniques to overcome network outages. iFlow also deploys replicas in a manner that improves performance and availability at the same time, and can cope with varying system conditions by continually migrating replicas. Based on a live network monitoring application, our demonstration will substantiate the strengths of iFlow. During the demonstration, various visual tools will provide graphical evidence of improvements with regards to availability, performance, and resource usage. To show iFlow's adaptivity, these tools will also allow us to control the demonstration situation including injecting different types of failures.

Web applications have become major driving forces for world business. Effective and efficient testing of evolving Web applications is essential for providing reliable services. In this paper, we present a user session based testing technique that clusters user sessions based on the service profile and selects a set of representative user sessions from each cluster. Then each selected user session is tailored by augmentation with additional requests to cover the dependence relationships between Web pages. The created test suite not only can significantly reduce the size of the collected user sessions, but is also viable to exercise fault sensitive paths. We conducted two empirical studies to investigate the effectiveness of our approach- one was in a controlled environment using seeded faults, and the other was conducted on an industrial system with real faults. The results demonstrate that our approach consistently detected the majority of the known faults by using a relatively small number of test cases in both studies.