TL;DR: This paper presents A2thOS, a framework to calculate the availability of partially outsourcing IT services in the presence of SLAs and to achieve a cost-optimal choice of availability levels for outsourced IT components while guaranteeing a target availability level for the service.
A framework to calculate the availability of partially outsourced IT services in the presence of SLAs and to achieve a cost-optimal choice of availability levels for outsourced IT components while guaranteeing a target availability level for the service.the authors.
Figure 4 shows one possible scheduling for the failure of the components on which Service1 depends on, resulting in Service1 having an availability of αService1 (0.984).
To this end the authors distinguish among three types of nodes in a dependency graph: target availability nodes, variable availability nodes and given availability nodes.
The analysis engine solves the availability analysis problem, described in Section 3.
TL;DR: A graph-based framework for modelling the availability dependencies of the components of an IT infrastructure is proposed and techniques based on this framework are developed to support availability planning.
Abstract: The availability of an organisation’s IT infrastructure is of vital importance for supporting business activities. IT outages are a cause of competitive liability, chipping away at a company financial performance and reputation. To achieve the maximum possible IT availability within the available budget, organisations need to carry out a set of analysis activities to prioritise efforts and take decisions based on the business needs. This set of analysis activities is called IT availability planning. Most (large) organisations address IT availability planning from one or more of the three main angles: information risk management, business continuity and service level management. Information risk management consists of identifying, analysing, evaluating and mitigating the risks that can affect the information processed by an organisation and the information-processing (IT) systems. Business continuity consists of creating a logistic plan, called business continuity plan, which contains the procedures and all the useful information needed to recover an organisations’ critical processes after major disruption. Service level management mainly consists of organising, documenting and ensuring a certain quality level (e.g. the availability level) for the services offered by IT systems to the business units of an organisation. There exist several standard documents that provide the guidelines to set up the processes of risk, business continuity and service level management. However, to be as generally applicable as possible, these standards do not include implementation details. Consequently, to do IT availability planning each organisation needs to develop the concrete techniques that suit its needs. To be of practical use, these techniques must be accurate enough to deal with the increasing complexity of IT infrastructures, but remain feasible within the budget available to organisations. As we argue in this dissertation, basic approaches currently adopted by organisations are feasible but often lack of accuracy. In this thesis we propose a graph-based framework for modelling the availability dependencies of the components of an IT infrastructure and we develop techniques based on this framework to support availability planning.
TL;DR: A Petri net Monte Carlo simulation is developed that estimates the availability and costs of a specific design of an IT service redundancy allocation problem and two meta-heuristics, namely a genetic algorithm and tabu search, are adapted.
TL;DR: The approach is based on model-driven principles and uses both UML and Bayesian Networks to capture, analyse and optimise cloud deployment configurations and is extensible to the operational phases of the life-cycle.
Abstract: This paper proposes an approach to support cloud brokers finding optimal configurations in the deployment of dependability and security sensitive cloud applications. The approach is based on model-driven principles and uses both UML and Bayesian Networks to capture, analyse and optimise cloud deployment configurations. While the paper is most focused on the initial allocation phase, the approach is extensible to the operational phases of the life-cycle. In such a way, a continuous improvement of cloud applications may be realised by monitoring, enforcing and re-negotiating cloud resources following detected anomalies and failures.
TL;DR: The use of this language for allocating cloud resources to maximise service dependability by definition of a model-driven approach able to guide the software engineering to define a cloud infrastructure using a semi-automated process using both high-level languages such as UML as well as Bayesian networks.
Abstract: Bayesian networks have demonstrated their capability in several applications spanning from reasoning under uncertainty in artificial intelligence to dependability modelling and analysis. This paper focuses on the use of this language for allocating cloud resources to maximise service dependability. This objective is accomplished by the definition of a model-driven approach able to guide the software engineering to define a cloud infrastructure (applications, services, virtual and concrete resources) using a semi-automated process. This process exploits both high-level languages such as UML as well as Bayesian networks. Using all their features (backward analysis, ease of usage, low analysis time), Bayesian networks are used in this process as a driver for the optimization, learning and estimation phases. The paper discusses all the issues that the application of Bayesian networks in the proposed process arises.
TL;DR: A general methodology for reliability modeling of complex systems based on Bayesian networks is developed, which allows for modeling complex systems, such as a bridge type, and dependencies between failures, which are difficult to obtain with conventional reliability analysis techniques.
Abstract: This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We developed a general methodology for reliability modeling of complex systems based on Bayesian networks. A reliability structure represented as a reliability block diagram is transformed to a Bayesian network representation, and with this, the reliability of the system can be obtained using probability propagation techniques. This allows for modeling complex systems, such as a bridge type, and dependencies between failures, which are difficult to obtain with conventional reliability analysis techniques. The relation between a BN and fault tree, and some advantages of BN for modeling system reliability are shown. We present some examples of the application of this methodology in solving difficult cases, which occur in reliability analysis of power plants.
204 citations
"A 2 thOS: availability analysis and..." refers methods in this paper
...Torres‐Toledano and Sucar [13] use Bayesian networks, and Leangsuksun et al....
[...]
...J. Network Mgmt 2012; 22: 104–130 DOI: 10.1002/nem
109A2THOS
proposed; e.g. Torres‐Toledano and Sucar [13] use Bayesian networks, and Leangsuksun et al. [14] use a UML representation (although in this second case the authors do not provide the mathematical support for reliability analysis)....
TL;DR: This paper studies the end-to-end QoS issues of composite service by utilizing a QoS broker that is responsible for coordinating the individual service component to meet the quality constraint by modeling the problem as the multiple choice knapsack problem (MCKP) and providing efficient solutions.
Abstract: Web services are new forms of Internet software that can be universally deployed and invoked using standard protocol. Services from different providers can be integrated to provide composite services. In this paper, we study the end-to-end QoS issues of composite service by utilizing a QoS broker that is responsible for coordinating the individual service component to meet the quality constraint. We design the service selection algorithms used by QoS brokers to meet end-to-end QoS constraints. The objective of the algorithms is to maximize the user-defined utility while meeting the end-to-end delay constraint. We model the problem as the multiple choice knapsack problem (MCKP) and provide efficient solutions. The algorithms are tested for their performance.
TL;DR: This paper presents QUEST, a QoS framework that can simultaneously achieve QoS assurances and good load balancing in SON, and provides an initial service composition and dynamic service composition, to address the problem.
Abstract: Many value-added and content delivery services are being offered via service level agreements (SLAs). These services can be interconnected to form a service overlay network (SON) over the Internet. Service composition in SON has emerged as a cost-effective approach to quickly creating new services. Previous research has addressed the reliability, adaptability, and compatibility issues for composed services. However little has been done to manage generic quality-of-service (QoS) provisioning for composed services, based on the SLA contracts of individual services. In this paper we present QUEST a QoS assUred composEable Service infrasTructure, to address the problem. QUEST framework provides: (1) initial service composition, which can compose a qualified service path under multiple QoS constraints (e.g., response time, availability). If multiple qualified service paths exist, QUEST chooses the best one according to the load balancing metric; and (2) dynamic service composition, which can dynamically recompose the service path to quickly recover from service outages and QoS violations. Different from the previous work, QUEST can simultaneously achieve QoS assurances and good load balancing in SON.
202 citations
"A 2 thOS: availability analysis and..." refers background in this paper
...[24] propose QUEST, a framework to schedule dynamically a composite IT service while satisfying QoS requirements (e....
TL;DR: Galileo is a dynamic fault tree modeling and analysis tool that combines the innovative DIF-Tree analysis methodology with a rich user interface built using package-oriented programming.
Abstract: We present Galileo, a dynamic fault tree modeling and analysis tool that combines the innovative DIF-Tree analysis methodology with a rich user interface built using package-oriented programming. DIFTree integrates binary decision diagram and Markov methods under the common notation of dynamic fault trees, allowing the user to exploit the benefits of both techniques while avoiding the need to learn additional notations and methodologies. Package-oriented programming (POP) is a software architectural style in which large-scale software packages are used as components, exploiting their rich functionality and familiarity to users. Galileo can be obtained for free under license for evaluation, and can be downloaded from the World-Wide Web.
196 citations
"A 2 thOS: availability analysis and..." refers methods in this paper
...Galileo [20], Coral [21], Relex [22] and BlockSim [23] are tools operating with dynamic FTs....
TL;DR: In this paper, the authors model the service composition problem as a mixed integer linear problem where local constraints, i.e., constraints for component Web services, and global constraints for the whole application, can be specified.
Abstract: In Service Oriented systems, complex applications can be composed from a variety of functionally equivalent Web services which may differ for quality parameters. Under this scenario, applications are defined as high level business processes and service composition can be implemented dynamically by identifying the best set of services available at run time. In this paper, we model the service composition problem as a mixed integer linear problem where local constraints, i.e., constraints for component Web services, and global constraints, i.e., constraints for the whole application, can be specified. Our approach proposes the formulation of the optimization problem as a global optimization, not optimizing separately each possible execution path as in other approaches. Experimental results demonstrate the effectiveness of our approach.
Q1. What are the contributions in "A2thos: availability analysis and optimisation in slas" ?
In this paper the authors present ATHOS, a framework to calculate the availability of partially outsourced IT services in the presence of SLAs and to achieve a cost-optimal choice of availability levels for outsourced IT components while guaranteeing a target availability level for the service.