Optimal Fault-tolerant Strategy Research Articles

Fault tolerating multi-tenant service-based systems with dynamic quality

The rapid development of multi-tenant service-based systems (SBSs) is mainly due to the popularity of cloud computing. SBS combines the existing services in the form of business processes to meet the needs of multiple tenants. There are two kinds of services: functional and non-functional. Multiple services can have the same functionality while changing their non-functional properties, or QoS (Quality of Service). QoS value is an important criterion for service selection or recommendation. In the existing work, QoS value in service selection or recommendation is regarded as a constant. However, in the dynamic and volatile cloud environment, the performance of services may fluctuate due to various factors (e.g. techniques of service studied, network conditions, etc.). A constant value does not reflect the consistency of the service. This paper proposes FT4MTS-D (fault-tolerant strategies for multi-tenant service-based systems with dynamic quality), a novel method that evaluates the criticality of dynamic cost-effective fault tolerance strategies for multi-tenant service-based systems. First, the consistency of each given service is evaluated based on the feature vector of the cloud model. Second, this paper measures the consistency of given service by the sensitivity of probability degradation of an SBS in comparison to the probability degradation of that service. The goal is to find the critical services in the SBS and then determine the optimal fault-tolerant strategy for the given service. The experimental results show that FT4MTS-D has obvious advantages compared with several existing representative methods.

Formulating Criticality-Based Cost-Effective Fault Tolerance Strategies for Multi-Tenant Service-Based Systems

The proliferation of cloud computing has fueled the rapid growth of multi-tenant service-based systems (SBSs), which serve multiple tenants simultaneously by composing existing services in the form of business processes. In a distributed and volatile operating environment, runtime anomalies may occur to the component services of an SBS and cause end-to-end quality violations. Engineering multi-tenant SBSs that can quickly handle runtime anomalies cost effectively has become a significant challenge. Different approaches have been proposed to formulate fault tolerance strategies for engineering SBSs. However, none of the existing approaches has sufficiently considered the service criticality based on multi-tenancy where multiple tenants share the same SBS instance with different multi-dimensional quality preferences. In this paper, we propose Criticality-based Fault Tolerance for Multi-Tenant SBSs (CFT4MTS), a novel approach that formulates cost-effective fault tolerance strategies for multi-tenant SBSs by providing redundancy for the critical component services. First, the criticality of each component service is evaluated based on its multi-dimensional quality and multiple tenants sharing the component service with differentiated quality preferences. Then, the fault tolerance problem is modelled as an Integer Programming problem to identify the optimal fault tolerance strategy. The experimental results show that, compared with three existing representative approaches, CFT4MTS can alleviate degradation in the quality of multi-tenant SBSs in a much more effective and efficient way.

Optimized cloud migration using reliabilty framework

The on-demand use, high scalability, and low maintenance cost nature of cloud computing have attracted more and more enterprises to migrate their legacy applications to the cloud environment. Although the cloud platform itself promises high reliability, ensuring high quality of service is still one of the major concerns, since the enterprise applications are usually complicated and consist of a large number of distributed components. Thus, improving the reliability of an application during cloud migration is a challenging and critical research problem. To address this problem, we propose a reliability-based optimization framework, named RO Cloud, to improve the application reliability by fault tolerance. RO Cloud includes two ranking algorithms. The first algorithm ranks components for the applications that all their components will be migrated to the cloud. The second algorithm ranks components for hybrid applications that only part of their components are migrated to the cloud. Based on the ranking result, optimal fault-tolerant strategy will be selected automatically for the most significant components with respect to their predefined constraints. The experimental results show that by refactoring a small number of error-prone components and tolerating faults of the most significant components, the reliability of the application can be greatly improved.

A Survey on Optimal Fault Tolerant Strategyfor Reliability Improvement in CloudMigration

Cloud Computing gives convenient, on-demand network access to shared pool of computing resources like network storage and servers. With On demand use, high scalability and low maintenance cost of Cloud computing more and more enterprises wishes to migrate their legacy application to the cloud environment. Cloud platform itself promises high reliability. And also ensures high quality of service. But due to complicated structure of enterprises application and also large no of distributed components of legacy application the things are becoming complicated. So while migrating any legacy application to the cloud becomes critical and challenging task. To improve reliability proposed system gives ROcloud framework i.e. Reliability- Based optimized framework. ROCloud improves the application Reliability by using Fault tolerance. ROCloudes includes two ranking algorithms. First Ranking Algorithm is used to rank components for the application when all their components of the application will be migra ted to the cloud. And second ranking algorithm is used to rank components those are hybrid application i.e. when only part of their components are migrated to the cloud. For components both the Ranking algorithms make use of the Application structure information and historical reliability information. On the basis of ranking results for the most significant components with respect to their predefined components Optimal fault tolerant strategy will be selected automatically.

Service fault tolerance for highly reliable service-oriented systems: an overview

Service-oriented systems are widely-employed in e-business, e-government, finance, management systems, and so on. Service fault tolerance is one of the most important techniques for building highly reliable service-oriented systems. In this paper, we provide an overview of various service fault tolerance techniques, including sections on fault tolerance strategy design, fault tolerance strategy selection, and Byzantine fault tolerance. In the first section, we introduce the design of static and dynamic fault tolerance strategies, as well as the major problems when designing fault tolerance strategies. After that, based on various fault tolerance strategies, in the second section, we identify significant components from a complex service-oriented system, and investigate algorithms for optimal fault tolerance strategy selection. Finally, in the third section, we discuss a special type of service fault tolerance techniques, i.e., the Byzantine fault tolerance.

Selecting an Optimal Fault Tolerance Strategy for Reliable Service-Oriented Systems with Local and Global Constraints

Functionally equivalent web services can be composed to form more reliable service-oriented systems. However, the choice of fault tolerance strategy can have a significant effect on the quality-of-service (QoS) of the resulting service-oriented systems. In this paper, we investigate the problem of selecting an optimal fault tolerance strategy for building reliable service-oriented systems. We formulate the user requirements as local and global constraints and model the selection of fault tolerance strategy as an optimization problem. A heuristic algorithm is proposed to efficiently solve the optimization problem. Fault tolerance strategy selection for semantically related tasks is also investigated in this paper. Large-scale real-world experiments are conducted to illustrate the benefits of the proposed approach. The experimental results show that our problem modeling approach and the proposed selection algorithm make it feasible to manage the fault tolerance of complex service-oriented systems both efficiently and effectively.

Reliability-Based Design Optimization for Cloud Migration

The on-demand use, high scalability, and low maintainance cost nature of cloud computing have attracted more and more enterprises to migrate their legacy applications to the cloud environment. Although the cloud platform itself promises high reliability, ensuring high quality of service is still one of the major concerns, since the enterprise applications are usually complicated and consist of a large number of distributed components. Thus, improving the reliability of an application during cloud migration is a challenging and critical research problem. To address this problem, we propose a reliability-based optimization framework, named ROCloud, to improve the application reliability by fault tolerance. ROCloud includes two ranking algorithms. The first algorithm ranks components for the applications that all their components will be migrated to the cloud. The second algorithm ranks components for hybrid applications that only part of their components are migrated to the cloud. Both algorithms employ the application structure information as well as the historical reliability information for component ranking. Based on the ranking result, optimal fault-tolerant strategy will be selected automatically for the most significant components with respect to their predefined constraints. The experimental results show that by refactoring a small number of error-prone components and tolerating faults of the most significant components, the reliability of the application can be greatly improved.

Component Ranking for Fault-Tolerant Cloud Applications

Cloud computing is becoming a mainstream aspect of information technology. More and more enterprises deploy their software systems in the cloud environment. The cloud applications are usually large scale and include a lot of distributed cloud components. Building highly reliable cloud applications is a challenging and critical research problem. To attack this challenge, we propose a component ranking framework, named FTCloud, for building fault-tolerant cloud applications. FTCloud includes two ranking algorithms. The first algorithm employs component invocation structures and invocation frequencies for making significant component ranking. The second ranking algorithm systematically fuses the system structure information as well as the application designers' wisdom to identify the significant components in a cloud application. After the component ranking phase, an algorithm is proposed to automatically determine an optimal fault-tolerance strategy for the significant cloud components. The experimental results show that by tolerating faults of a small part of the most significant components, the reliability of cloud applications can be greatly improved.

Optimal Fault Tolerance Strategy Selection for Web Services

Service-oriented systems are usually composed by heterogeneous Web services, which are distributed across the Internet and provided by organizations. Building highly reliable service-oriented systems is a challenge due to the highly dynamic nature of Web services. In this paper, the authors apply software fault tolerance techniques for Web services, where the component failures are handled by fault tolerance strategies. In this paper, a distributed fault tolerance strategy evaluation and selection framework is proposed based on versatile fault tolerance techniques. The authors provide a systematic comparison of various fault tolerance strategies by theoretical formulas, as well as real-world experiments. This paper also presents the optimal fault tolerance strategy selection algorithm, which employs both the QoS performance of Web services and the requirements of service users for selecting optimal fault tolerance strategy. A prototype is implemented and real-world experiments are conducted to illustrate the advantages of the evaluation framework. In these experiments, users from six different locations perform evaluation of Web services distributed in six countries, where over 1,000,000 test cases are executed in a collaborative manner to demonstrate the effectiveness of this approach.