The goal of service oriented architectures (SOAs) is to enable the creation of business applications through the automatic discovery and composition of independently developed and deployed (Web) services. Automatic discovery of Web services (WSs) can be achieved by incorporating semantics into a richer WS description model (WSDM) and by the use of semantic Web (SW) technologies in the WS matchmaking and selection (i.e., discovery) process. A sufficiently rich WSDM should encompass not only functional but also nonfunctional aspects like quality of service (QoS). QoS is a set of performance and domain-dependent attributes that has a substantial impact on WS requesters' expectations. Thus, it can be used for distinguishing between many functionally equivalent WSs that are available nowadays. This paper starts by defining QoS in the context of WSs. Its main contribution is the analysis of the requirements for a semantically rich QoS-based WSDM and an accurate, effective QoS-based WS Discovery (WSDi) process. In addition, a road map of extending current WS standard technologies for realizing semantic, functional, and QoS-based WSDi, respecting the above requirements, is presented.

Currently, the data to be explored and exploited by computing systems increases at an exponential rate. The massive amount of data or so-called “Big Data” put pressure on existing technologies for providing scalable, fast and efficient support. Recent applications and the current user support from multi-domain computing, assisted in migrating from data-centric to knowledge-centric computing. However, it remains a challenge to optimally store and place or migrate such huge data sets across data centers (DCs). In particular, due to the frequent change of application and DC behaviour (i.e., resources or latencies), data access or usage patterns need to be analyzed as well. Primarily, the main objective is to find a better data storage location that improves the overall data placement cost as well as the application performance (such as throughput). In this survey paper, we are providing a state of the art overview of Cloud-centric Big Data placement together with the data storage methodologies. It is an attempt to highlight the actual correlation between these two in terms of better supporting Big Data management. Our focus is on management aspects which are seen under the prism of non-functional properties. In the end, the readers can appreciate the deep analysis of respective technologies related to the management of Big Data and be guided towards their selection in the context of satisfying their non-functional application requirements. Furthermore, challenges are supplied highlighting the current gaps in Big Data management marking down the way it needs to evolve in the near future.

Quality of service (QoS) can be a critical element for achieving the business goals of a service provider, for the acceptance of a service by the user, or for guaranteeing service characteristics in a composition of services, where a service is defined as either a software or a software-support (i.e., infrastructural) service which is available on any type of network or electronic channel. The goal of this article is to compare the approaches to QoS description in the literature, where several models and metamodels are included. consider a large spectrum of models and metamodels to describe service quality, ranging from ontological approaches to define quality measures, metrics, and dimensions, to metamodels enabling the specification of quality-based service requirements and capabilities as well as of SLAs (Service-Level Agreements) and SLA templates for service provisioning. Our survey is performed by inspecting the characteristics of the available approaches to reveal which are the consolidated ones and which are the ones specific to given aspects and to analyze where the need for further research and investigation lies. The approaches here illustrated have been selected based on a systematic review of conference proceedings and journals spanning various research areas in computer science and engineering, including: distributed, information, and telecommunication systems, networks and security, and service-oriented and grid computing.

As the Web service paradigm gains popularity for its promise to transform the way business is conducted, the number of deployed Web services grows with a fast rate. While sophisticated semantic discovery mechanisms have been invented to overcome the UDDI's syntactic discovery solution in order to provide more recallable and precise results, the amount of functionally equivalent Web services returned is still large. The solution to this problem is the description of the QoS non-functional aspect of Web services. QoS encompasses the performance of Web services and can be used as a discriminator factor for refining Web service advertisement result lists. However, most scientific efforts presented so far are purely syntactic and are not capturing all aspects of QoS-based Web service description leading to imprecise syntactic discovery mechanisms. This paper presents a novel, rich and extensible ontology-based approach for describing QoS of Web services that complements OWL-S. It is shown that, by using this approach and by introducing the concept of semantic QoS metric matching, QoS-based syntactic matchmaking and selection algorithms are transformed to semantic ones leading to better results

QoS-based Web service (WS) discovery has been recognized as the main solution for filtering and selecting between functionally equivalent WSs stored in registries or other types of repositories. There are two main techniques for QoS-based WS matchmaking (filtering): ontology-based and constraint programming (CP)-based. Unfortunately, the first technique is not efficient as it is based on the rather immature technology of ontology reasoning, while the second one is not accurate as it is based on syntactic QoS-based descriptions and faulty matchmaking metrics. In our previous work, we have developed an extensible and rich ontology language for QoS-based WS description. Moreover, we have devised a semantic alignment algorithm for aligning QoS-based WS descriptions so as to increase the accuracy of QoS-based WS matchmaking algorithms. Finally, we have developed two alternative CP-based QoS-based WS matchmaking algorithms: a unary-constrained and n-ary-constrained one. In this paper, we claim that mixed-integer programming (MIP) should be used as a matchmaking technique instead of CP and we provide experimental results proving it. In addition, we analyze and experimentally evaluate our matchmaking algorithms against a competing techniques one in order to demonstrate their efficiency and accuracy.

Serverless computing is a new computing paradigm that promises to revolutionize the way applications are built and provisioned. In this computing kind, small pieces of software called functions are deployed in the cloud with zero administration and minimal costs for the software developer. Further, this computing kind has various applications in areas like image processing and scientific computing. Due to the above advantages, the current uptake of serverless computing is being addressed by traditional big cloud providers like Amazon, who offer serverless platforms for serverless application deployment and provisioning. However, as in the case of cloud computing, such providers attempt to lock-in their customers with the supply of complementary services which provide added-value support to serverless applications. To this end, to resolve this issue, serverless frameworks have been recently developed. Such frameworks either abstract away from serverless platform specificities, or they enable the production of a mini serverless platform on top of existing clouds. However, these frameworks differ in various features that do have an impact on the serverless application lifecycle. To this end, to assist the developers in selecting the most suitable framework, this paper attempts to review these frameworks according to a certain set of criteria that directly map to the application lifecycle. Further, based on the review results, some remaining challenges are supplied, which when confronted will make serverless frameworks highly usable and suitable for the handling of both serverless as well as mixed application kinds.