Presentation 42,43

Presentation 42
Monitoring Distributed Data Streams
Prof. Asaf schuster
Computer Science, Technion

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Monitoring data streams in a distributed system is the focus of much research in recent years. A distributed monitoring task consists of accurately detecting, at each point in time, whether the data complies with a certain global criteria. An example of a distributed monitoring task is using agents installed on a set of routers to detect When traffic to a certain IP address raises above a predetermined threshold. Another example of a distributed monitoring task is detecting When the average temperature reading taken by sensors in a sensor network exceeds a predetermined threshold.

Most of the proposed monitoring schemes deal with monitoring simple aggregated values. More involved challenges, such as the important task of distributed feature selection (e.g., for collectively identifying spam email or for collaborative intrusion detection), or monitoring the variance in the temperature (pressure, pollusion, etc) readings taken by sensors in a sensor network, still require very high communication (and power) overhead using naive, centralized algorithms.

We present a novel geometric approach by which an arbitrary global monitoring task can be split into a set of constraints applied locally on each of the streams. The constraints are used to locally filter out data increments that do not affect the monitoring outcome, thus avoiding unnecessary communication. As a result, our approach enables monitoring arbitrary threshold functions over distributed data streams in an efficient manner. Real-WOrld data W8s used in proving the efficiency of the new approach.

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Presentation43
Changing The Economics Of Data Storage Through Exanet Technology Innovation
Yossi Ben-Shoshan
Exanet

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Data storage is a crucial component of any enterprise IT solution. Applications and users are generating ever-expanding amounts of data, as they ride the wave of digital pictures, videos, web downloads, etc. This growth has had a tremendous impact on data storage requirements. The inherent limitations of most storage systems and technologies force organizations to take short-term, cumbersome and costly measures to respond to their growing data needs.

A more strategic investment can lead to a simplified architecture and lower costs, especially for organizations anticipating significant data growth. When looking to deploy strategic storage solutions, performance, scalability, and price performance become increasingly important.

ExaStore, Exanet's high-performance grid-based NAS solution, sets a new standard for data storage. Comprised of ExaStore software and standard, off-the-shelf hardware, the ExaStore system offers record-breaking price performance, along with automation and perpetual access to data. Its distributed computing architecture enables unlimited performance and capacity scalability, providing a solution for any short or long-term business requirement.

ExaStore is the first storage solution that allows customers to choose their hardware, maximizing existing investments. It is the only system to independentlyscale capacity, performance and I/O, while drastically simplifying operation and management. The performance-optimized architecture of ExaStore is changing the economics of storage. The system's superior performance and response time enable it to support a larger number of users. This leads to a lower cost of storage per user, fewer hardware components, a simplified operating environment and a lower Total Cost of Ownership.