Untangling the Braid: Finding Outliers in a Set of Streams

Monitoring the performance of large shared computing systems such as the cloud computing infrastructure raises many challenging algorithmic problems. One common problem is to track users with the largest deviation from the norm (outliers), for some measure of performance. Taking a streamcomputing perspective, we can think of each user's performance profile as a stream of numbers (such as response times), and the aggregate performance profile of the shared infrastructure as a "braid" of these intermixed streams. The monitoring system's goal then is to untangle this braid sufficiently to track the top k outliers. This paper investigates the space complexity of one-pass algorithms for approximating outliers of this kind, proves lower bounds using multi-party communication complexity, and proposes smallmemory heuristic algorithms. On one hand, stream outliers are easily tracked for simple measures, such as max or min, but our theoretical results rule out even good appr...

• Type: Conference
• Year: 2010
• Where: ALENEX
• Authors: Chiranjeeb Buragohain, Luca Foschini, Subhash Suri
• Keywords: ALENEX 2010, Algorithms, Cloud Computing Infrastructure, Outliers, Performance Profile