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Several recent studies have reported the phenomenon of "software aging", one in which the state of a software system degrades with time. This may eventually lead to performance degradation of the software or crash/hang failure or both. "Software rejuvenation" is a pro-active technique aimed to prevent unexpected or unplanned outages due to aging. The basic idea is to stop the running software, clean its internal state and restart it. In this paper, we discuss software rejuvenation as applied to cluster systems. This is both an innovative and an efficient way to improve cluster system availability and productivity. Using Stochastic Reward Nets (SRNs), we model and analyze cluster systems which employ software rejuvenation. For our proposed time-based rejuvenation policy, we determine the optimal rejuvenation interval based on system availability and cost. We also introduce a new rejuvenation policy based on prediction and show that it can dramatically increase system availability and reduce downtime cost. These models are very general and can capture a multitude of cluster system characteristics, failure behavior and performability measures, which we are just beginning to explore. We then briefly describe an implementation of a software rejuvenation system that performs periodic and predictive rejuvenation, and show some empirical data from systems that exhibit aging

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The IBM eServere BladeCentert system physically consolidates the server and network into a common chassis. It was introduced as a new server architecture that provides many benefits over the traditional data center model of clustered independent systems linked by a network fabric. This paper describes the BladeCenter networking architecture and relates it to user requirements for multi-tier servers, scale-out models, networking technology advances, and industry trends. Design decisions and challenges, the switch subsystem and input/output technology options, services that are currently supported by the architecture, and future enhancements and extensions are addressed.

Several recent studies have reported the phenomenon of "software aging", one in which the state of a software system degrades with time. This may eventually lead to performance degradation of the software or crash/hang failure or both. "Software rejuvenation" is a pro-active technique aimed to prevent unexpected or unplanned outages due to aging. The basic idea is to stop the running software, clean its internal state and restart it. In this paper, we discuss software rejuvenation as applied to cluster systems. This is both an innovative and an efficient way to improve cluster system availability and productivity. Using Stochastic l~eward Nets (SRNs), we model and analyze cluster systems which employ software rejuvenation. For our proposed time-based rejuvenation policy, we determine the optimal rejuvenation interval based on system availability and cost. We also introduce a new rejuvenation policy based on prediction and show that it can dramatically increase system availability and reduce downtime cost. These models are very general and can capture a multitude of cluster system characteristics, failure behavior and performability measures, which we are just beginning to explore. We then briefly describe an implementation of a software rejuvenation system that performs periodic and predictive rejuvenation, and show some empirical data from systems that exhibit aging Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.