@article {Distefano201722, title = {Marking dependency in non-Markovian stochastic Petri nets}, journal = {Performance Evaluation}, volume = {110}, year = {2017}, note = {cited By 0}, pages = {22-47}, publisher = {Elsevier B.V.}, abstract = {

Marking dependency is a powerful tool that allows different firing time distributions to be associated with a stochastic Petri net transition, depending on the marking. Through this feature, the modeler can easily and compactly represent advanced properties and behaviors of the system. While a semantics and specific solution techniques have been provided for generalized stochastic Petri nets thus covering homogeneous Markovian aspects, in the non-homogeneous/non-Markovian case marking dependency still needs to be investigated. To fill this gap, this paper provides a formalization of marking dependent semantics in non-Markovian stochastic Petri nets (NMSPNs) and a solution technique, based on phase type distributions and Kronecker algebra, able to deal with such a feature allowing both transient and steady-state analyses. To motivate the actual need of marking dependency in NMSPN modeling and to demonstrate the potential of such a feature as well as the validity of the proposed solution technique a case study on a multi-core CPU system with power management facilities is explored. {\textcopyright} 2017 Elsevier B.V.

}, keywords = {Algebra, energy management, Kronecker algebra, Marking dependency, Multi-core cpus, non-Markovian stochastic Petri nets, Petri nets, phase type distributions, Power management, Program processors, Random access storage, Semantics, Stochastic systems}, issn = {01665316}, doi = {10.1016/j.peva.2017.03.001}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016027299\&doi=10.1016\%2fj.peva.2017.03.001\&partnerID=40\&md5=a00a4d3147bd499b5f8879d3573b4670}, author = {Salvatore Distefano and Francesco Longo and Marco Scarpa} } @article {Longo20152506, title = {Variable operating conditions in distributed systems: Modeling and evaluation}, journal = {Concurrency Computation Practice and Experience}, volume = {27}, number = {10}, year = {2015}, note = {cited By 1}, pages = {2506-2530}, publisher = {John Wiley and Sons Ltd}, abstract = {

SummaryPerformance and dependability evaluation plays a key role in the design of a broad range of systems, especially when strict requirements need to be met. This is particularly challenging in distributed contexts, where several components may interact among themselves by influencing each other. In this paper, we present an analytical method that allows the study of a class of systems where different operating conditions alternate by changing the stochastic behavior of the system components but still preserving the continuity of the performance and dependability quantities to investigate. The proposed solution technique, based on phase type distributions, Kronecker algebra, and ad-hoc fitting algorithms, can be applied for the analytical evaluation of a wide class of distributed systems. Examples are provided to show the usefulness and the applicability of the methodology, characterizing and investigating different performance and dependability aspects of three distributed computing systems, that is, a connection-oriented network, an Internet of Things application, and an Infrastructure-as-a-Service Cloud. Copyright {\textcopyright} 2014 John Wiley \& Sons, Ltd.

}, keywords = {Algebra, cloud computing, Conservative systems, Dependability, Distributed computer systems, Internet, Internet of Things, Kronecker algebra, Markov processes, Non-Markovian, Performance, phase type distributions, Stochastic systems}, issn = {15320626}, doi = {10.1002/cpe.3419}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84932604392\&partnerID=40\&md5=b8f197a50fa177e85f0c1ac2a93fe392}, author = {Francesco Longo and Dario Bruneo and Salvatore Distefano and Marco Scarpa} } @article {Bruneo20131072, title = {Workload-based software rejuvenation in cloud systems}, journal = {IEEE Transactions on Computers - IEEE Computer Society}, volume = {62}, number = {6}, year = {2013}, note = {cited By 21}, pages = {1072-1085}, abstract = {

Cloud computing is a promising paradigm able to rationalize the use of hardware resources by means of virtualization. Virtualization allows to instantiate one or more virtual machines (VMs) on top of a single physical machine managed by a virtual machine monitor (VMM). Similarly to any other software, a VMM experiences aging and failures. Software rejuvenation is a proactive fault management technique that involves terminating an application, cleaning up the system internal state, and restarting it to prevent the occurrence of future failures. In this work, we propose a technique to model and evaluate the VMM aging process and to investigate the optimal rejuvenation policy that maximizes the VMM availability under variable workload conditions. Starting from dynamic reliability theory and adopting symbolic algebraic techniques, we investigate and compare existing time-based VMM rejuvenation policies. We also propose a time-based policy that adapts the rejuvenation timer to the VMM workload condition improving the system availability. The effectiveness of the proposed modeling technique is demonstrated through a numerical example based on a case study taken from the literature. {\textcopyright} 1968-2012 IEEE.

}, keywords = {Algebraic techniques, Application programs, cloud computing, Endocrinology, Kronecker algebra, Numerical methods, phase type distributions, Proactive fault managements, Reliability theory, Software rejuvenation, System availability, Time-based Rejuvenation, Virtual machine monitors, Virtual reality}, issn = {00189340}, doi = {10.1109/TC.2013.30}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84877311601\&partnerID=40\&md5=185051c9b74e6577b5b06c39cbaf7cc7}, author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Antonio Puliafito and Marco Scarpa} } @proceedings {250, title = {Workload-Based Software Rejuvenation in Cloud Systems}, journal = {IEEE TRANSACTIONS ON COMPUTERS}, volume = {62}, year = {2013}, pages = {1072{\textendash}1085}, abstract = {

Cloud Computing is a promising paradigm able to rationalize the use of hardware resources by means of virtualization. Virtualization allows to instantiate one or more virtual machines (VMs) on top of a single physical machine managed by a virtual machine monitor (VMM). Similarly to any other software, a VMM experiences aging and failures. Software rejuvenation is a proactive fault management technique that involves terminating an application, cleaning up the system internal state, and restarting it in order to prevent the occurrence of future failures. In this work, we propose a technique to model and evaluate the VMM aging process and to investigate the optimal rejuvenation policy that maximizes the VMM availability under variable workload conditions. Starting from dynamic reliability theory and adopting symbolic algebraic techniques, we investigate and compare existing time-based VMM rejuvenation policies. We also propose a time-based policy that adapts the rejuvenation timer to the VMM workload condition improving the system availability. The effectiveness of the proposed modeling technique is demonstrated through a numerical example based on a case study taken from the literature.

}, keywords = {cloud computing, Dynamic Availability, Kronecker algebra, phase type distributions, Time-based Rejuvenation}, doi = {10.1109/TC.2013.30}, author = {Bruneo D. and Distefano S. and Longo F. and Puliafito A and Scarpa M} } @proceedings {256, title = {Evaluating wireless sensor node longevity through Markovian techniques}, journal = {COMPUTER NETWORKS}, volume = {56}, year = {2012}, pages = {521{\textendash}532}, abstract = {

Wireless sensor networks are constituted of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, nodes undergo active-sleep periods that, on the other hand, limit their ability to send/receive data. The aim of this paper is to analyze the longevity of a battery-powered sensor node. A battery discharge model able to capture both linear and non linear discharge processes is presented. Then, two different models are proposed to investigate the longevity, in terms of reliability, of sensor nodes with active-sleep cycles. The first model, well known in the literature, is based on the Markov reward theory and on the evaluation of the accumulated reward distribution. The second model, based on continuous phase type distributions and Kronecker algebra, represents the main contribution of the present work, since it allows to relax some assumptions of the Markov reward model, thus increasing its applicability to more concrete use cases. In the final part of the paper, the results obtained by applying the two techniques to a case study are compared in order to validate and highlight the benefits of our approach and demonstrate the utility of the proposed model in a quite complex and real scenario.

}, keywords = {Battery discharge process, Continuous phase type distributions, Energy consumption, Kronecker algebra, Markov reward models, Reliability}, doi = {10.1016/j.comnet.2011.10.003}, author = {Bruneo D. and Distefano S. and Longo F. and Puliafito A. and Scarpa M.} } @article {Bruneo2012521, title = {Evaluating wireless sensor node longevity through Markovian techniques}, journal = {Computer Networks - Elsevier }, volume = {56}, number = {2}, year = {2012}, note = {cited By 13}, pages = {521-532}, abstract = {

Wireless sensor networks are constituted of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, nodes undergo active-sleep periods that, on the other hand, limit their ability to send/receive data. The aim of this paper is to analyze the longevity of a battery-powered sensor node. A battery discharge model able to capture both linear and non linear discharge processes is presented. Then, two different models are proposed to investigate the longevity, in terms of reliability, of sensor nodes with active-sleep cycles. The first model, well known in the literature, is based on the Markov reward theory and on the evaluation of the accumulated reward distribution. The second model, based on continuous phase type distributions and Kronecker algebra, represents the main contribution of the present work, since it allows to relax some assumptions of the Markov reward model, thus increasing its applicability to more concrete use cases. In the final part of the paper, the results obtained by applying the two techniques to a case study are compared in order to validate and highlight the benefits of our approach and demonstrate the utility of the proposed model in a quite complex and real scenario. {\textcopyright} 2011 Published by Elsevier B.V.

}, keywords = {Algebra, Battery discharge, Continuous phase, Discharge process, Electric network synthesis, Energy utilization, Kronecker algebra, Markov reward, Markov reward model, Markov reward models, Markovian, Randomly distributed, Reliability, Reliability theory, Sensor nodes, Sensors, Wireless sensor node}, issn = {13891286}, doi = {10.1016/j.comnet.2011.10.003}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84856063119\&partnerID=40\&md5=ecbae538bceec8598d787ee3b936a8e1}, author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Antonio Puliafito and Marco Scarpa} } @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 {Bruneo2010, title = {Reliability assessment of wireless sensor nodes with non-linear battery discharge}, journal = {2010 IFIP Wireless Days, WD 2010}, year = {2010}, note = {cited By 8; Conference of 2010 IFIP Wireless Days, WD 2010 ; Conference Date: 20 October 2010 Through 22 October 2010; Conference Code:83354}, publisher = {IEEE Computer Society}, address = {Venice, Italy, 20-22 October 2010}, abstract = {

Wireless sensor networks are constituted of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, nodes undergo cycles of active-sleep periods that reduce their ability to send/receive data. Aim of this paper is to analyze the reliability of a battery-powered sensor node with active-sleep cycles considering both linear and non linear discharge processes. The approach used in the evaluation is based on continuous phase type distributions and Kronecker algebra. The technique is thus applied to the evaluation of an example in order to demonstrate its effectiveness. The obtained results strongly encourage future work, figuring out possible application in wider network context with complex topology, redundant nodes, and unreliable links, due to the Kronecher algebra capabilities to manage the state space explosion problem. {\textcopyright} 2010 IEEE.

}, keywords = {Algebra, Battery discharge, Continuous phase, Electric network synthesis, Energy consumption, Energy utilization, Kronecker algebra, Markov reward model, Reliability analysis, sensor networks, Sensor nodes, Telecommunication equipment, Wireless sensor, Wireless sensor networks}, isbn = {9781424492299}, doi = {10.1109/WD.2010.5657711}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-78751474054\&partnerID=40\&md5=86f6f2fa864d7e52672ab4e4bd83d78a}, author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Antonio Puliafito 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} }