Measuring Test Coverage of SoA Services
Abstract: One of the challenges of testing in a SoA environment is that testers do not have access to the source code of the services they are testing. Therefore they are not able to measure test coverage at the code level as is done in a conventional white-box testing. They are compelled to measure test coverage in other ways which satisfy the constraints of black-box testing. This paper proposes some alternate means of measuring test coverage by focusing on the structure and content of the service interface without regarding the code. The result is a new way of measuring test coverage which can apply to testing in a SoA environment.
Modeling and Evaluation of Mixed Redundancy Strategy with Instant Switching in Cloud-based Systems
Abstract: Mixed redundancy strategy is generally used in cloud-based sys-tems, with different node switch mechanism from traditional mixed strategy. However, related researches often concentrates on traditional mixed redundancy strategy in which cold standby components is working only after all active nodes fail. So a model is developed to evaluate the reliability and performance of cloud-based degraded system subjected to mixed active and cold standby redundancy strategy with continual monitoring and detection mechanism. It is assumed that the node switching pro-cess is triggered once some active nodes fail and there are availa-ble standby nodes. A continuous-time Markov chain is built on top of the state transition process and both transient and steady state availability and expected job completion rate are used to evaluate system metrics with or with repair facilities. Numerical method is used to solve the model and sensitivity analysis is con-ducted on different redundancy strategy. Illustrative examples were presented to explain the process of calculating the probabil-ity of each state and in turn, the different kinds of availability and performance. The comparison with traditional mixed redun-dancy strategy proved that the system behavior was different using different kinds of mixed strategy and the analysis model for traditional strategy was not suitable for strategies in cloud-bases system.
Architectural Run-Time Models for Operator-in-the-Loop Adaptation of Cloud Applications
Abstract: Building software systems by composing third-party cloud services promises many benefits. However, the increased complexity, heterogeneity, and limited observability of cloud services brings fully automatic adaption to its limits. We propose architectural run-time models as a means for combining automatic and operator-in-the-loop adaptations of cloud services.
Sustainability forecast for cloud migration
Abstract: Cloud computing is an emerging technology to support an organization for meeting its business objectives specifically relating to significant cost savings, accessibility, and maintenance overhead. Cloud enable services are now heavily used from a single user to the large organization. However, there are also many challenges relating to unique cloud characteristics and dependency with a cloud service provider which can pose any potential risks. Therefore, despite of these well documented benefits, it is necessary to determine whether it is viable of considering cloud to support the business. This paper contributes towards this direction, in particular we propose a sustainability driven approach to measure the viability of cloud migration. Our work considers four dimensions of sustainability, i.e., economic, environment, social, and technology and consider risk as a cross cutting concern among these dimensions. Sustainability dimensions are prioritized according to their relative importance using Analytic Hierarchy Process and are assessed using fuzzy scale. Risks are then identified for each prioritized sustainable dimensions so that a balance decision can be made for cloud migration. Finally, we use a practical migration use case from Ministry of Health (MoH), Malaysia to demonstrate the applicability of our work. The results from the studied context concluded that economic and business continuity are the key concerns that influence for a sustainable cloud migration.
Challenges and assessment in migrating IT legacy applications to the Cloud
Abstract: The incessant trend where software engineers need to redesign legacy systems adopting a service-centric engineering ap-proach brings new challenges for software architects and developers. Today, engineering and deploying software as a service requires specific Internet protocols, middleware and languages that often complicate the interoperability of software at all levels. Moreover, cloud computing demands stringent quality requirements, such as security, scalability, and interoperability among others, to provide ser-vices and data across networks more efficiently. As software engi-neers must face the problem to redesign and redeploy systems as services, we explore in this paper the challenges found during the migration of an existing system to a cloud solution and based on a set of quality requirements that includes the vendor lock-in factor. We also present a set of assessment activities and guidelines to support migration to the Cloud by adopting SOA and Cloud modeling standards and tools.
Cloud compliant applications: A reference framework to assess the maturity of software applications with respect to Cloud
Abstract: Over the last years several standards and reports have been published and released (ISO CCRA, TOSCA), where best practices with respect to Cloud based application design, development and deployment are described. Other frameworks such as ITIL or EFQM provide recommendations for identifying, planning, delivering and supporting IT services to the business through adaptation of the business models and processes. All this best practices are scattered through different sources and there is not a unique criteria covering all the aspects.This paper proposes a maturity assessment approach support-ed by tools based on standards widely adopted in the industry. It covers best practices in the three dimensions and ranks the possi-ble solutions in terms of the most suitable alternatives for cloud based solutions. The maturity assessment has been also comple-mented with the functionality of capturing user information, and transforming it in useful information in terms of reports and files for the migration process.
MonSLAR: A Middleware for Monitoring SLA for RESTFUL Services in Cloud Computing
Abstract: Assuring users’ satisfaction with respect to expected services in a cloud-computing environment and detecting viola-tions in Service Level Agreements (SLAs) has been gaining im-portance in recent years. Measuring the quality of cloud compu-ting provision from the client’s point of view is important in or-der to ensure that the service conforms to the level specified in the agreement; this is usually referred to as Quality of Experi-ence (QoE). With a view to avoid SLA violation, the main param-eters should be determined in the agreement and then used to evaluate the fulfillment of the SLA terms at the client’s side. Cur-rent studies in cloud monitoring only handle monitoring the pro-vider resources with little or no consideration to the client’s side. This paper presents MonSLAR, a user-centric middleware for Monitoring SLA for Restful services in SaaS cloud computing environments. MonSLAR uses a distributed architecture which allows SLA parameters and the monitored data to be embedded in the requests and responses of the REST protocol. The pro-posed middleware will help to maintain confidence between the client and the provider and gives the client flexibility in selecting services provided by cloud providers.
Service-Oriented Software Evolution Toolchains
Abstract: Software evolution projects need to be supported by integrated toolchains, yet can suffer from inadequate tool interoperability. Practitioners are forced to deal with technical integration issues, instead of focusing on their projects’ actual objectives. Lacking integration support, the resulting toolchains are rigid and inflexible, impeding project progress.This paper presents SENSEI, a service-oriented support framework for toolchain-building, that clearly separates software evolution needs from implementing tools and interoperability issues. It aims to improve interoperability using component-based principles, and provides model-driven code generation to partly automate the integration process.The approach has been prototypically implemented, and was applied in the context of the Q-MIG project, to build parts of an integrated software migration and quality assessment toolchain.
Evaluating Cluster Configurations for Big Data Processing: An Exploratory Study
Abstract: As data continues to grow rapidly, NoSQL clusters have been increasingly adopted to address the storage and processing demands of these large amounts of data. In parallel, cloud computing is also increasingly being adopted due to its flexibility, cost efficiency and scalability. However, evaluating and modelling NoSQL clusters present many challenges. In this work, we explore these challenges by performing a series of experiments with various configurations. The intuition is that this process is laborious and expensive and the goal of our experiments is to confirm this intuition and to identify the factors that impact the performance of a Big Data cluster. Our experiments mostly focus on three factors: data compression, data schema and cluster topology. We performed a number of experiments based on these factors and measured and compared the response times of the resulting configurations. Eventually, the outcomes of our study are encapsulated in a performance model that predicts the cluster’s response time as a function of the incoming workload and evaluates the cluster’s performance less costly and faster. This systematic and effortless evaluation method will facilitate the selection and migration to a better cluster as the performance and budget goals change. We use HBase as the large data processing cluster and we conduct our experiments on traffic data from a large city and on a distributed community cloud infrastructure.