Towards critical event monitoring, detection and prediction for self-adaptive future Internet applications

The Future Internet (FI) will be composed of a multitude of diverse types of services that offer flexible, remote access to software features, content, computing resources, and middleware solutions through different cloud delivery models, such as IaaS, PaaS and SaaS. Ultimately, this means that loosely coupled Internet services will form a comprehensive base for developing value added applications in an agile way. Unlike traditional application development, which uses computing resources and software components under local administrative control, FI applications will thus strongly depend on third-party services. To maintain their quality of service, those applications therefore need to dynamically and autonomously adapt to an unprecedented level of changes that may occur during runtime. In this paper, we present our recent experiences on monitoring, detection, and prediction of critical events for both software services and multimedia applications. Based on these findings we introduce potential directions for future research on self-adaptive FI applications, bringing together those research directions

An Approach to Transform Public Administration into SOA-based Organizations

Nowadays, Service-Oriented Architectures (SOA) is widely spread in private organizations. However, when transferring this knowledge to Public Administration, it is realized that it has not been transformed in terms of its legal nature into organizations capable to operate under the SOA paradigm. This fact prevents public administration bodies from offering the efficient services they have been provided by different boards of governments. A high-level framework to perform this transformation is proposed. Taking it as starting point, an instance of a SOA Target Meta-Model can be obtained by means of an iterative and incremental process based on the analysis of imperatives and focused on the particular business context of each local public administration. This paper briefly presents a practical experience consisting in applying this process to a Spanish regional public administration.Junta de Andalucía TIC-578

Modeling cloud resources using machine learning

Cloud computing is a new Internet infrastructure paradigm where management optimization has become a challenge to be solved, as all current management systems are human-driven or ad-hoc automatic systems that must be tuned manually by experts. Management of cloud resources require accurate information about all the elements involved (host machines, resources, offered services, and clients), and some of this information can only be obtained a posteriori. Here we present the cloud and part of its architecture as a new scenario where data mining and machine learning can be applied to discover information and improve its management thanks to modeling and prediction. As a novel case of study we show in this work the modeling of basic cloud resources using machine learning, predicting resource requirements from context information like amount of load and clients, and also predicting the quality of service from resource planning, in order to feed cloud schedulers. Further, this work is an important part of our ongoing research program, where accurate models and predictors are essential to optimize cloud management autonomic systems.Postprint (published version

Automatic test case generation for WS-Agreements using combinatorial testing

In the scope of the applications developed under the service-based paradigm, Service Level Agreements (SLAs) are a standard mechanism used to flexibly specify the Quality of Service (QoS) that must be delivered. These agreements contain the conditions negotiated between the service provider and consumers as well as the potential penalties derived from the violation of such conditions. In this context, it is important to assure that the service based application (SBA) behaves as expected in order to avoid potential consequences like penalties or dissatisfaction between the stakeholders that have negotiated and signed the SLA. In this article we address the testing of SLAs specified using the WS-Agreement standard by means of applying testing techniques such as the Classification Tree Method and Combinatorial Testing to generate test cases. From the content of the individual terms of the SLA, we identify situations that need to be tested. We also obtain a set of constraints based on the SLA specification and the behavior of the SBA in order to guarantee the testability of the test cases. Furthermore, we define three different coverage strategies with the aim at grading the intensity of the tests. Finally, we have developed a tool named SLACT (SLA Combinatorial Testing) in order to automate the process and we have applied the whole approach to an eHealth case study

Network emulation focusing on QoS-Oriented satellite communication

This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication

Coverage Based Testing for Service Level Agreements

Service level agreements (SLAs) are typically used to specify rules regarding the consumption of services that are agreed between the providers of the service-based applications (SBAs) and their consumers. An SLA includes a list of terms that contain the guarantees that must be fulfilled during the provisioning and consumption of the services. Since the violation of such guarantees may lead to the application of potential penalties, it is important to assure that the SBA behaves as expected. In this paper, we propose a proactive approach to test SLA-aware SBAs by means of identifying test requirements, which represent situations that are relevant to be tested. To address this issue, we define a four-valued logic that allows evaluating both the individual guarantee terms and their logical relationships. Grounded in this logic, we devise a test criterion based on the modified condition decision coverage (MCDC) in order to obtain a cost-effective set of test requirements from the structure of the SLA. Furthermore by analyzing the syntax and semantics of the agreement, we define specific rules to avoid non-feasible test requirements. The whole approach has been automated and applied over an eHealth case study