Showing papers by "Nesime Tatbul published in 2005"

The Design of the Borealis Stream Processing Engine

Abstract: Borealis is a second-generation distributed stream processing engine that is being developed at Brandeis University, Brown University, and MIT. Borealis inherits core stream processing functionality from Aurora [14] and distribution functionality from Medusa [51]. Borealis modifies and extends both systems in non-trivial and critical ways to provide advanced capabilities that are commonly required by newly-emerging stream processing applications. In this paper, we outline the basic design and functionality of Borealis. Through sample real-world applications, we motivate the need for dynamically revising query results and modifying query specifications. We then describe how Borealis addresses these challenges through an innovative set of features, including revision records, time travel, and control lines. Finally, we present a highly flexible and scalable QoS-based optimization model that operates across server and sensor networks and a new fault-tolerance model with flexible consistency-availability trade-offs.

Distributed operation in the Borealis stream processing engine

Abstract: Borealis is a distributed stream processing engine that is being developed at Brandeis University, Brown University, and MIT. Borealis inherits core stream processing functionality from Aurora and inter-node communication functionality from Medusa.We propose to demonstrate some of the key aspects of distributed operation in Borealis, using a multi-player network game as the underlying application. The demonstration will illustrate the dynamic resource management, query optimization and high availability mechanisms employed by Borealis, using visual performance-monitoring tools as well as the gaming experience.

Design Issues for Second Generation Stream Processing Engines

Abstract: Borealis is a second-generation distributed stream processing engine that is being developed at Brandeis University, Brown University, and MIT. Borealis inherits core stream processing functionality from Aurora [13] and distribution functionality from Medusa [49]. Borealis modifies and extends both systems in non-trivial and critical ways to provide advanced capabilities that are commonly required by newly-emerging stream processing applications. In this paper, we outline the basic design and functionality of Borealis. Through sample real-world applications, we motivate the need for dynamically revising query results and modifying query specifications. We then describe how Borealis addresses these challenges through an innovative set of features, including revision records, time travel, and control lines. Finally, we present a highly flexible and scalable QoS-based optimization model that operates across server and sensor networks and a new fault-tolerance model with flexible consistency-availability trade-offs.