Κρητικός Κυριάκος

Περίληψη:
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.

Περίληψη:
Cloud computing offers a flexible pay-as-you-go model for provisioning application resources, which enables applications to scale on-demand based on the current workload. In many cases, though, users face the single vendor lock-in effect, missing opportunities for optimal and adaptive application deployment across multiple clouds. Several cloud modelling languages have been developed to support multi-cloud resource management, but still they lack holistic cloud management of all aspects and phases. This work defines the Cloud Application Modelling and Execution Language (CAMEL), which (i) allows users to specify the full set of design time aspects for multi-cloud applications, and (ii) supports the models@runtime paradigm that enables capturing an application’s current state facilitating its adaptive provisioning. CAMEL has been already used in many projects, domains and use cases due to its wide coverage of cloud management features. Finally, CAMEL has been positively evaluated in this work in terms of its usability and applicability in several domains (e.g., data farming, flight scheduling, financial services) based on the technology acceptance model (TAM).

Περίληψη:
The Cloud offers enhanced flexibility in the management of resources for any kind of application while it promises the reduction of its cost as well as its infinite scalability. In this way, due to these advantages, there is a recent move towards migrating business processes (BPs) in the Cloud. Such a move is currently performed in a manual manner and only in the context of one Cloud. However, a multi- & cross-Cloud configuration of a BP can be beneficial as it can allow exploiting the best possible offers from multiple Clouds and enable to avoid the lock-in effect by also having the ability to deploy different instances of the BP in different Clouds close to the locations of BP customers. In this respect, this article presents a novel architecture of an environment which realises the vision of multi-Cloud BP provisioning. This environment involves innovative components which support the cross-level orchestration of cloud services as well as the cross-level monitoring and adaptation of BPs. It also relies on a certain language called CAMEL which has been extended to support the adaptive provisioning of multi-Cloud BPs.

Περίληψη:
This White Paper reports the outcome of a Workshop on “Research Data Service Discoverability” held in the island of Santorini (GR) on 21–22 April 2016 and organized in the context of the EU funded Project “RDA-E3”. The Workshop addressed the main technical problems that hamper an efficient and effective discovery of Research Data Services (RDSs) based on appropriate semantic descriptions of their functional and non-functional aspects. In the context of this White Paper, by RDSs are meant those data services that manipulate/transform research datasets for the purpose of gaining insight into complicated issues. In this White Paper, the main concepts involved in the discovery process of RDSs are defined; the RDS discovery process is illustrated; the main technologies that enable the discovery of RDSs are described; and a number of recommendations are formulated for indicating future research directions and making an automatic RDS discovery feasible.

Περίληψη:
Multi-cloud adaptive application provisioning can solve the vendor lock-in problem and allows optimising user requirements by selecting the best from the multitude of services offered by different cloud providers. To this end, such provisioning type is increasingly supported by new or existing research prototypes and platforms. One major concern, actually preventing users from moving to the cloud, comes with respect to security, which becomes more complex in multi-cloud settings. Such a concern spans two main aspects: (a) suitable access control on user personal data, VMs and platform services and (b) planning and adapting application deployments based on security requirements. As such, this paper addresses both security aspects by proposing a novel model-driven approach and architecture which secures multi-cloud platforms, enables users to have their own private space and guarantees that application deployments are not only constructed based on but can also maintain a certain user-required security level. Such a solution exploits state-of-the-art security standards, security software and secure model management technology. Moreover, it covers different access control scenarios involving external, web-based and programmatic user authentication.

Περίληψη:
Effective and accurate service discovery and composition rely on complete specifications of service behaviour, containing inputs and preconditions that are required before service execution, outputs, effects and ramifications of a successful execution and explanations for unsuccessful executions. The previously defined Web Service Specification Language (WSSL) relies on the fluent calculus formalism to produce such rich specifications for atomic and composite services. In this work, we propose further extensions that focus on the specification of QoS profiles, as well as partially observable service states. Additionally, a design framework for service-based applications is implemented based on WSSL, advancing state of the art by being the first service framework to simultaneously provide several desirable capabilities, such as supporting ramifications and partial observability, as well as non-determinism in composition schemas using heuristic encodings; providing explanations for unexpected behaviour; and QoS-awareness through goal-based techniques. These capabilities are illustrated through a comparative evaluation against prominent state-of-the-art approaches based on a typical SBA design scenario.

Περίληψη:
The Web has been evolving to a sink of disparate informa- tion sources which are totally isolated from each other. The technology of Linked Data (LD) promises to connect such information sources in order to enable their better exploitation by humans or automated pro- grams. While various LD management systems have been proposed, only few of them are able to handle geospatial data which are becoming quite popular nowadays and lead to the creation of large geospatial footprints. However, none of the few systems that support Linked Open Geospa- tial Data is able to scale well to handle the increasing load from user queries. In addition, the publishing of geospatial LD also becomes quite advantageous due to complexity reasons. To this end, this article pro- poses a novel, cloud-based geospatial LD management system which can scale out or scale in according to the incoming load in order to serve the respective user requests with the appropriate service level. On top of this system lies a LD-as-a-service offering which abstracts away the user from any LD publishing complexities and provides all the appro- priate functionality for enabling a full LD management. We also study and propose architectural solutions for the distributed update problem. The proposed system is evaluated under heavy load scenarios and the results show that the respective improvement in performance incurred is quite satisfactory and that the scaling actions are performed at the appropriate time points.

Περίληψη:
Cloud computing promises to transform applications and services on the web into elastic and fault-tolerant software. To aid at this target, various research prototypes and products have been already proposed. However, especially with respect to the design phase of cloud-based applications, such prototypes do not enable the appropriate composition of cloud services at different levels to realise not only the functionality but also the underlying infrastructure support for such applications. Moreover, most existing prototypes and products lack the appropriate semantics to guarantee that the respective design product is the most suitable and accurate one according to the various types of user requirements posed. To this end, this article proposes a semantic cloud application management framework that addresses the aforementioned issues by relying on ontologies to semantically describe cloud service capabilities and application requirements, on semantic cloud service matchmakers considering both functional and non-functional aspects as well as on a novel cloud service composition approach which is able to perform concurrently service concretisation and deployment plan reasoning, thus catering for the different levels involved in a cloud environment and their respective dependencies by also satisfying all types of user requirements posed. The service composition approach is experimentally evaluated deriving quite promising results indicating that the state-of-the-art is advanced.

Περίληψη:
Service-orientation paves the way for the Internet of Services (IoS), where millions of services will be available to realize the everyday user applications or tasks. Consequently, as a great number of functionally equivalent services will be available for a specific user task, the service nonfunctional aspect should be considered for filtering and selecting among these services. The state-of-the-art approaches in nonfunctional service discovery exploit constraint solving techniques to optimize the matchmaking time between a service offer and demand pair. However, they do not scale well, as matchmaking time is proportional to the offer number, so they are not yet suitable for the IoS. To this end, this article proposes three novel alternative techniques that intelligently organize the service offer space to improve the overall matchmaking time. These techniques are theoretically and experimentally evaluated. The results show that all techniques optimize the matchmaking time without sacrificing accuracy and that each technique is better in different circumstances.

Περίληψη:
The Service-Oriented Computing (SOC) paradigm is currently being adopted by many developers, as it promises the construction of applications through reuse of existing Web Services (WSs). However, current SOC tools produce applications that interact with users in a limited way. This limitation is overcome by model-based Human-Computer Interaction (HCI) approaches that support the development of applications whose functionality is realized with WSs and whose User Interface (UI) is adapted to the user's context. Typically, such approaches do not consider various functional issues, such as the applications' semantics and their syntactic robustness in terms of the WSs selected to implement their functionality and the automation of the service discovery and selection processes. To this end, we propose a model-driven design method for interactive service-based applications that is able to consider the functional issues and their implications for the UI. This method is realized by a semiautomatic environment that can be integrated into current model-based HCI tools to complete the development of interactive service front-ends. The proposed method takes as input an HCI task model, which includes the user's view of the interactive system, and produces a concrete service model that describes how existing services can be combined to realize the application's functionality. To achieve its goal, our method first transforms system tasks into semantic service queries by mapping the task objects onto domain ontology concepts; then it sends each resulting query to a semantic service engine so as to discover the corresponding services. In the end, only one service from those associated with a system task is selected, through the execution of a novel service concretization algorithm that ensures message compatibility between the selected services.

Περίληψη:
As organizations operate under a highly dynamic business world, they can only survive by optimizing their business processes (BPs) and outsourcing complementary functionality to their core business. To this end, they adopt service-orientation as the underlying mechanism enabling BP optimization and evolution. BPs are now seen as business services (BSs) that span organization boundaries and ought to satisfy cross-organizational objectives. As such, various BS design approaches have been proposed. However, these approaches cannot re-use existing business and software services (SSs) to realize the required BS functionality. Moreover, non-functional requirements and their impact on BS design are not considered. This research gap is covered by a novel, goal-oriented method able to discover those BS and SS compositions fulfilling the required BS functional and non-functional goals at both the business and IT level. This method coherently integrates the design steps involved and properly handles the lack of required BS components. It also advances the state-of-the-art in service composition by being able to both select the best composition plan and the best services realizing the plan tasks based on novel plan and service selection criteria.

Περίληψη:
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.

Περίληψη:
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.

Περίληψη:
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.

Περίληψη:
The ARION system provides basic e-services of search and retrieval of objects in scientific collections, such as datasets, simulation models and tools necessary for statistical and/or visualization processing. These collections may represent application software of scientific areas, they reside in geographically disperse organizations and constitute the system content. The user may invoke on-line computations of scientific datasets when the latter are not found into the system. The underlying grid used consists of hardware and software resources in the various participating organizations. ARION manages these resources providing a computing framework that produces datasets required by the user. In addition, the system offers semantic description of its content in terms of scientific ontologies and metadata information. Thus, ARION provides the basic infrastructure for accessing and deriving scientific information in an open, distributed and federated system.