Software rejuvenation: analysis, module and applications

Abstract

Software rejuvenation is the concept of gracefully terminating an application and immediately restarting it at a clean internal state. In a client-server type of application where the server is intended to run perpetually for providing a service to its clients, rejuvenating the server process periodically during the most idle time of the server increases the availability of that service. In a long-running computation-intensive application, rejuvenating the application periodically and restarting it at a previous checkpoint increases the likelihood of successfully completing the application execution. We present a model f o r analyzing software rejuvenation in such continuously-running applicataons and express downtime and costs due to downtime during rejuvneation an t e r n s of the parameters in that model. Threshold conditions f o r rejuvenation to be beneficial are also derived. W e implemented a reusable module to perform software rejuvenation. That module can be embedded in any existing application on a UNIX platform with minimal efort. Experiences with software rejuvenation in a billing data collection subsystem of a telecommunications operations system and other continuouslyrunning systems and scientific applications in A T & T are described.

An Adaptive Cost-Based Software Rejuvenation Scheme With Nonparametric Predictive Inference Approach

“…We here introduce the software rejuvenation model proposed by Dohi et al [15], which is an extension of CTMC model by Huang et al [26]. The model based on the semi-Markov process has the following four states: Here, State 1 means that the memory leakage is over a threshold or the system lapses from the highly robust state into an unstable state.…”

“…Just after the state becomes the failure probable state, system failure may occur with positive probability. Without loss of generality, we assume that the random variable Z is observable during the system operation (Huang et al [26]). Let X denote the failure time from State 1, having the probability distribution function Pr{X ≤ t} = F f (t) and the survival function S(t) = 1 − F f (t) with finite mean λ f (> 0).…”

“…Software rejuvenation is a complementary approach to handle transient software failures caused by the aging-related bugs (Huang et al [26]) which can be regarded as a preventive and proactive maintenance solution. It is one of software environment diversity techniques and involves stopping the running software occasionally, cleaning its internal state and restarting it.…”

“…Typical examples of software rejuvenation are garbage collection, flushing operating system kernel tables, reinitializing internal data structures, as well as retry, reconfiguration, and reboot of systems. Since the seminal contribution by Huang et al [26], a number of authors concern the problem how frequent software rejuvenation is triggered, because it has a tradeoff relationship between system down cost at failure and planned down cost by preventive rejuvenation. First, Huang et al [26] propose a simple continuous-time Markov chain (CTMC) model with four states, i.e., initial robust (clean), failure probable, rejuvenation and failure states, to describe the stochastic behavior of a telecommunication billing application.…”

“…Since the seminal contribution by Huang et al [26], a number of authors concern the problem how frequent software rejuvenation is triggered, because it has a tradeoff relationship between system down cost at failure and planned down cost by preventive rejuvenation. First, Huang et al [26] propose a simple continuous-time Markov chain (CTMC) model with four states, i.e., initial robust (clean), failure probable, rejuvenation and failure states, to describe the stochastic behavior of a telecommunication billing application. They evaluate both the system unavailability and the operating cost in steady state under the random software rejuvenation schedule.…”