Kazuki Iwamoto

Discrete availability models to rejuvenate a telecommunication billing application

Software rejuvenation is a proactive fault management technique that has been extensively studied in the recent literature. We focus on an example for a telecommunication billing application considered in Huang et al. (1995) and develop the discrete-time stochastic models to estimate the optimal software rejuvenation schedule. More precisely, two software availability models with rejuvenation are formulated via the discrete semi-Markov processes, and the optimal software rejuvenation schedules which maximize the steady-state availabilities are derived analytically. Further, we develop statistically nonparametric algorithms to estimate the optimal software rejuvenation schedules, provided that the complete sample data of failure times are given. Then, a new statistical device, called discrete total time on test statistics, is introduced. Finally, we examine asymptotic properties for the statistical estimation algorithms proposed in this paper through a simulation experiment.

A DP-BASED CHECKPOINTING SCHEME IN REAL-TIME APPLICATIONS

In this paper, we consider computation algorithms for checkpoint placement in real-time applications. Under the condition that the processing time is bounded by a time limit, we derive sequentially the optimal checkpoint time based on the dynamic programming. In numerical examples, we examine the dependence of optimal checkpoint sequence on both failure time and processing time distributions, and investigate the effectiveness of sequential checkpoint placement.

A Dynamic Programming Algorithm for Software Rejuvenation Scheduling under Distributed Computation Circumstance

Recently, a complementary approach to handle transient software failures, called software rejuvenation, is becoming popular as a proactive fault management technique in operational software systems. In this paper, we consider a scheduling problem of software rejuvenation for a distributed computation. Based on the dynamic programming approach, we derive the optimal software rejuvenation schedule which minimizes the expected total time of computation. In numerical examples, we examine the sensitivity of model parameters characterizing failure phenomenon to the resulting optimal rejuvenation schedule

Discrete-time cost analysis for a telecommunication billing application with rejuvenation

Software rejuvenation is a proactive fault management technique that has been extensively studied in the recent literature. In this paper, we focus on an example for a telecommunication billing application considered in [1] and develop the discrete-time stochastic models to estimate the optimal software rejuvenation schedules. More precisely, two software cost models with rejuvenation are formulated via the discrete semi-Markov processes, and the optimal software rejuvenation schedules which minimize the expected costs per unit time in the steady state are derived analytically. Further, we develop statistically nonparametric algorithms to estimate the optimal software rejuvenation schedules, provided that the complete sample data of failure times are given. Then, a new statistical device, called discrete total time on test statistics, is introduced. Finally, we examine asymptotic properties for the statistical estimation algorithms proposed in this paper through a simulation experiment.

Estimating Periodic Software Rejuvenation Schedules under Discrete-Time Operation Circumstance

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider periodic software rejuvenation models based on the expected cost per unit time in the steady state under discrete-time operation circumstance. By applying the discrete renewal reward processes, we describe the stochastic behavior of a telecommunication billing application with a degradation mode, and determine the optimal periodic software rejuvenation schedule minimizing the expected cost. Similar to the earlier work by the same authors, we develop a statistically non-parametric algorithm to estimate the optimal software rejuvenation schedule, by applying the discrete total time on test concept. Numerical examples are presented to estimate the optimal software rejuvenation schedules from the simulation data. We discuss the asymptotic behavior of estimators developed in this paper.

DISCRETE REPAIR-COST LIMIT REPLACEMENT POLICIES WITH/WITHOUT IMPERFECT REPAIR

This paper addresses statistical estimation problems of the optimal repair-cost limits minimizing the long-run average costs per unit time in discrete seting. Two discrete repair-cost limit replacement models with/without imperfect repair are considered. We derive the optimal repair-cost limits analytically and develop the statistical non-parametric procedures to estimate them from the complete sample of repair cost. Then the discrete total time on test (DTTT) concept is introduced and applied to propose the resulting estimators. Numerical experiments through Monte Carlo simulation are provided to show their asymptotic convergence properties as the number of repair-cost data increases. A comprehensive bibliography in this research topic is also provided.

ESTIMATING DISCRETE-TIME PERIODIC SOFTWARE REJUVENATION SCHEDULES UNDER COST EFFECTIVENESS CRITERION

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider the similar periodic software rejuvenation model to Garg et al.13 under the different operation circumstance. That is, we model the stochastic behavior of telecommunication billing applications by using a discrete-time Markov regenerative process, and determine the optimal periodic software rejuvenation schedule maximizing the so-called cost effectiveness, in discrete-time setting. Also, we provide a statistically non-parametric method to estimate the optimal software rejuvenation schedule, based on the discrete total time on test concept. Numerical examples are devoted to illustrate the determination/estimation of the optimal software rejuvenation schedule and to examine the asymptotic behavior of the estimator developed here.

Monitoring the health condition of a ubiquitous system: rejuvenation vs. recovery

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider a periodic software rejuvenation model based on the steady-state system availability in discrete operational circumstance. More precisely, we treat a telecommunication billing application as a simple ubiquitous application, and describe its stochastic behavior by applying the discrete renewal reward process. The main objective is the determination of the optimal frequency to rejuvenate the ubiquitous application, maximizing the steady-state system availability. Also, we develop a statistically non-parametric algorithm to estimate the optimal rejuvenation schedule with the discrete total time on test concept.