Evaluating the impact of maintenance policies associated to SLA contracts on the dependability of data centers electrical infrastructures Due to the growth of cloud computing,xc2xa0  data centerxc2xa0  environment has grown in importance and in use.xc2xa0  Data centersxc2xa0  are responsible for maintaining and processing several criticalvalue applications. Therefore,xc2xa0  data centerxc2xa0  infrastructures must be evaluated in order to improve the high availability and reliability demanded for such environments. This work adopts Stochastic Petri Nets (SPN) to evaluate the impact of maintenance policies on the data center dependability. The main goal is to analyze maintenance policies, associated toxc2xa0  SLAxc2xa0  contracts, and to propose improvements. In order to accomplish this, an optimization strategy that uses Euclidean distance is adopted to indicate the most appropriate solution assuming conflicting requirements (e.g., cost and availability). To illustrate the applicability of the proposed models and approach, this work presents case studies comparing differentxc2xa0  SLAxc2xa0  contracts and maintenance policies (preventive and corrective) applied onxc2xa0  data centerxc2xa0  electrical infrastructures.

Analysis of Software Aging Impacts on Plant Anomaly Detection with Edge Computing Edge computing allows dataintensive analytic processes running on a cloud server to migrate to a local computing environment near the data sources, and as a result the architecture can benefit from a significant bandwidth reduction as well as improved security. However, due to the scarcity of resources on an edge device, a problem of software aging is likely to occur after longtime execution. The consequence of software aging should be significant, whereas such a risk has not been studied in the previous literature. In this paper, we propose a deterministic and stochastic Petri Net (DSPN) to quantitatively analyze the impacts of software aging phenomenon on a cyberphysical system using edge computing. As a data analytic application using realworld sensor data, we consider anomaly detection for a water treatment plant. We introduce two applicationoriented performance measures, namely detection loss probability and the expected number of false alarms in terms of plant anomaly detection. Our numerical and simulation experiments on the proposed DSPN show that software aging clearly has negative impacts on the defined performance measures that reveal the necessity of greater attention to software aging issues in edge computing systems.