Traditional problem determination techniques rely on static dependency models that are
difficult to generate accurately in today's large, distributed, and dynamic application …

Network anomaly detection is a vibrant research area. Researchers have approached this
problem using various techniques such as artificial intelligence, machine learning, and state …

Most Internet services (e-commerce, search engines, etc.) suffer faults. Quickly detecting
these faults can be the largest bottleneck in improving availability of the system. We present …

More and more information about processes is recorded in the form of so-called “event logs”.
High-tech systems such as X-ray machines and high-end copiers provide their …

The detection of network fault scenarios has been achieved using the statistical information
contained in the Management Information Base (MIB) variables. An appropriate subset of …

Server virtualization is now becoming an effective means to consolidate numerous
applications into a small number of machines. While such a strategy can lead to significant …

Process mining has made significant progress in less than a decade since its inception.
Process mining techniques attempt to extract non-trivial process related knowledge and …

Large scale systems (LSS) contain multiple subsystems that interact across multiple nodes
in sometimes unforeseen and complicated ways. As a result, pinpointing the subsystems …

In this paper we show how to reduce downtime of J2EE applications by rapidly and
automatically recovering from transient and intermittent software failures, without requiring …

A real-time knowledge-based network intrusion-detection model for a link-state routing
protocol is presented for the OSPF protocol. This model includes three layers: a data …