@proceedings {Longo2011335, title = {A scalable availability model for Infrastructure-as-a-Service cloud}, journal = {Proceedings of the 41st IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)}, year = {2011}, note = {cited By 33; Conference of 2011 IEEE/IFIP 41st International Conference on Dependable Systems and Networks, DSN 2011 ; Conference Date: 27 June 2011 Through 30 June 2011; Conference Code:86090}, pages = {335-346}, publisher = {IEEE Computer Society}, address = {Hong Kong, Hong Kong, 27-30 June 2011}, abstract = {

High availability is one of the key characteristics of Infrastructure-as-a- Service (IaaS) cloud. In this paper, we show a scalable method for availability analysis of large scale IaaS cloud using analytic models. To reduce the complexity of analysis and the solution time, we use an interacting Markov chain based approach. The construction and the solution of the Markov chains is facilitated by the use of a high-level Petri net based paradigm known as stochastic reward net (SRN). Overall solution is composed by iteration over individual SRN sub-model solutions. Dependencies among the sub-models are resolved using fixed-point iteration, for which existence of a solution is proved. We compare the solution obtained from the interacting sub-models with a monolithic model and show that errors introduced by decomposition are insignificant. Additionally, we provide closed form solutions of the sub-models and show that our approach can handle very large size IaaS clouds. {\textcopyright} 2011 IEEE.

}, keywords = {Analytic models, availability analysis, Closed form solutions, Fixed-point iterations, High availability, Key characteristics, Large sizes, Markov Chain, Markov model, Markov processes, Petri nets, Scalability, Scalable methods, Solution time, Stochastic reward nets, Submodels}, isbn = {9781424492336}, doi = {10.1109/DSN.2011.5958247}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-80051928903\&partnerID=40\&md5=37f3360476d39837acf5098ca20408c7}, author = {Francesco Longo and Rahul Ghosh and Vijay K. Naik and Kishor S. Trivedi} } @proceedings {Distefano2010265, title = {Availability assessment of HA standby redundant clusters}, journal = {Proceedings of the 29th IEEE Symposium on Reliable Distributed Systems (SRDS)}, year = {2010}, note = {cited By 14; Conference of 29th IEEE Symposium on Reliable Distributed Systems, SRDS 2010 ; Conference Date: 31 October 2010 Through 3 November 2010; Conference Code:82914}, pages = {265-274}, publisher = {IEEE Computer Society}, address = {New Delhi, India, 31 October - 3 November 2010}, abstract = {

Computing systems are becoming the heart of modern technology, implementing critical tasks usually demanded to and implying human interactions. This highlights the problem of dependability in computer science contexts. High availability computing/clusters is a possible solution in such cases, implementing standby redundancy as a tradeoff between dependability and costs. From the engineering perspective, this implies the use of specific techniques and tools for adequately evaluating the reliability/availability of high availability clusters, also taking into account dependencies among nodes (standby, repair, etc.) and the effect of wear and tear into such nodes, especially when failure and repair times are not exponentially distributed. The solution proposed in this paper is based on the use of phase type distributions and Kronecker algebra. In fact, we represent the reliability and maintainability of each component by specific phase type distributions, whose interactions describe the system availability. This latter is thus modeled by an expanded Markov chain expressed in terms of Kronecker algebra in order to face the state space explosion problem of expansion techniques and to represent the memory policies related to the aging process. More specifically, the paper firstly details the technique and then applies it to the evaluation of a standby redundant system representing a high availability cluster taken as example with the aim of demonstrating its effectiveness. Moreover, in order to show the potentiality of the technique, different maintenance strategies are evaluated and therefore compared. {\textcopyright} 2010 IEEE.

}, keywords = {Aging process, Algebra, Availability assessment, Computing system, Critical tasks, Dynamic reliability, Engineering perspective, High availability, High-availability clusters, Human interactions, Kronecker algebra, Maintainability, Maintenance strategies, Markov Chain, Markov processes, Modern technologies, phase type distributions, Possible solutions, Quality assurance, Redundancy, Redundant system, Standby redundancy, State-space explosion, System availability, Wear and tear}, isbn = {9780769542508}, issn = {10609857}, doi = {10.1109/SRDS.2010.37}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-78650560407\&partnerID=40\&md5=9666fbfeaaae60d0a7d7ca8f388600e7}, author = {Salvatore Distefano and Francesco Longo and Marco Scarpa} } @proceedings {Distefano201045, title = {Symbolic representation techniques in dynamic reliability evaluation}, journal = {Proceedings of the 12th IEEE International Symposium on High Assurance Systems Engineering (HASE)}, year = {2010}, note = {cited By 9; Conference of 2010 IEEE 12th International Symposium on High Assurance Systems Engineering, HASE 2010 ; Conference Date: 3 November 2010 Through 4 November 2010; Conference Code:83929}, pages = {45-53}, publisher = {IEEE Computer Society}, address = {San Jose, CA, United States, 3-4 November 2010}, abstract = {

The increasing demand of quality presses towards more specific requirements, tighter constraints, and higher standards. It is thus necessary to provide new paradigms, techniques, and tools to adequately model and evaluate complex systems. This paper mainly focuses on reliability aspects, also taking into account dynamic-dependent interactions among components. Starting from the conservation of reliability principle, we characterize the time to failure of the system components through continuous phase type distributions. The system reliability is thus modeled by an expanded Markov chain expressed in terms of Kronecker algebra in order to face the state space explosion and to represent the memory policies related to the aging process. A two-component system is taken as example to demonstrate the effectiveness of the technique and to validate it. {\textcopyright} 2010 IEEE.

}, keywords = {Aging process, Algebra, Complex systems, Continuous phase, Dynamic reliability, Kronecker algebra, Markov Chain, Markov processes, phase type distributions, Quality assurance, Reliability, State-space explosion, symbolic representation, System components, System reliability, Systems engineering, Time to failure, Two component systems}, isbn = {9780769542928}, issn = {15302059}, doi = {10.1109/HASE.2010.28}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79951924261\&partnerID=40\&md5=8ed2be2a9f6a7e9d891ed3fb58789d6f}, author = {Salvatore Distefano and Francesco Longo and Marco Scarpa} }