Cloud computing has been consolidated as a support for the vast majority of current and emerging technologies. However, there are some barriers that prevent the exploitation of the full potential of this technology. First, the major cloud providers currently put the onus of implementing the mechanisms that ensure compliance with the desired service levels on cloud consumers. However, consumers do not have the required expertise. Since each cloud provider exports a different set of low-level metrics, the strategies defined to ensure compliance with the established service-level agreement (SLA) are bound to a particular cloud provider. This fosters provider lock-in and prevents consumers from benefiting from the advantages of multi-cloud environments. This paper presents a solution to the problem of automatically translating SLAs into objectives expressed as metrics that can be measured across multiple cloud providers. First, we propose an intelligent knowledge-based system capable of automatically translating high-level SLAs defined by cloud consumers into a set of conditions expressed as vendor-neutral metrics, providing feedback to cloud consumers (intelligent tutoring system). Secondly, we present the set of vendor-neutral metrics and explain how they can be measured for the different cloud providers. Finally, we report a validation based on two use cases (IaaS and PaaS) in a multi-cloud environment formed by leading cloud providers. This evaluation has demonstrated that, thanks to the complementarity of the two solutions, cloud consumers can automatically and transparently exploit the multi-cloud in many application domains, as endorsed by the cloud experts consulted in the course of this study.

Event-driven architectures are becoming more prevalent recently in multiple technological paradigms, especially in web applications, with message brokers being the cornerstone of these architectures. One of the most relevant implementations of these message brokers are content-based publish/subscribe systems. The performance of these systems is a critical factor for web engineering, since the web applications they support need to be reactive despite increases and fluctuations in workloads. However, an obstacle to the research of these systems is the lack of real and publicly available workloads, due to the privacy issue involved in disclosing the interests (subscriptions) of users and other commercial interests of the companies. In this paper we present a parameterizable automated system designed to syntactically translate workloads from different content-based publish/subscribe systems as a means to increase the availability of public workloads to solve the aforementioned problem. As a case study, we describe the evolution of a context-aware content-based publish/subscribe system (i.e. E-SilboPS) designed by the authors, which improves up to 5 times the performance of its previous version by reaching the maximum throughput limited by the physical resources of the hardware where it is deployed, as demonstrated by the conducted quantitative evaluation. Then, we validate the utility of the proposed automated workload generation system by using it to make the performance comparison between this new version E-SilboPS and one of the most cited publish/subscribe systems called PADRES, through a real trace of a massively multiplayer online game (MMOG) generated by the latter.

Abstract Outlier detection is an important problem occurring in a wide range of areas. Outliers are the outcome of fraudulent behaviour, mechanical faults, human error, or simply natural deviations. Many data mining applications perform outlier detection, often as a preliminary step in order to filter out outliers and build more representative models. In this paper, we propose an outlier detection method based on a clustering process. The aim behind the proposal outlined in this paper is to overcome the specificity of many existing outlier detection techniques that fail to take into account the inherent dispersion of domain objects. The outlier detection method is based on four criteria designed to represent how human beings (experts in each domain) visually identify outliers within a set of objects after analysing the clusters. This has an advantage over other clustering‐based outlier detection techniques that are founded on a purely numerical analysis of clusters. Our proposal has been evaluated, with satisfactory results, on data (particularly time series) from two different domains: stabilometry, a branch of medicine studying balance‐related functions in human beings and electroencephalography (EEG), a neurological exploration used to diagnose nervous system disorders. To validate the proposed method, we studied method outlier detection and efficiency in terms of runtime. The results of regression analyses confirm that our proposal is useful for detecting outlier data in different domains, with a false positive rate of less than 2% and a reliability greater than 99%.

There has recently been a major advance with respect to how information fusion is performed. Information fusion has gone from being conceived as a purely hierarchical procedure, as is the case of traditional military applications, to now being regarded collaboratively, as holonic fusion, which is better suited for civil applications and edge organizations. The above paradigm shift is being boosted as information fusion gains ground in different non-military areas, and human–computer and machine–machine communications, where holarchies, which are more flexible structures than ordinary, static hierarchies, become more widespread. This paper focuses on showing how holonic structures tend to be generated when there are constraints on resources (energy, available messages, time, etc.) for interactions based on a set of fully intercommunicating elements (peers) whose components fuse information as a means of optimizing the impact of vagueness and uncertainty present message exchanges. Holon formation is studied generically based on a multiagent system model, and an example of its possible operation is shown. Holonic structures have a series of advantages, such as adaptability, to sudden changes in the environment or its composition, are somewhat autonomous and are capable of cooperating in order to achieve a common goal. This can be useful when the shortage of resources prevents communications or when the system components start to fail.

Many of the problems arising from rapid urbanization and urban population growth can be solved by making cities “smart”. These smart cities are supported by large networks of interconnected and widely geo‐distributed devices, known as Internet of Things or IoT, that generate large volumes of data. Traditionally, cloud computing has been the technology used to support this infrastructure; however, some of the essential requirements of smart cities such as low‐latency, mobility support, location‐awareness, bandwidth cost savings, and geo‐distributed nature of such IoT systems cannot be met. To solve these problems, the fog computing paradigm proposes extending cloud computing models to the edge of the network. However, most of the proposed architectures and frameworks are based on their own private data models and interfaces, which severely reduce the openness and interoperability of these solutions. To address this problem, we propose a standard‐based fog computing architecture to enable it to be an open and interoperable solution. The proposed architecture moves the stream processing tasks to the edge of the network through the use of lightweight context brokers and Complex Event Processing (CEP) to reduce latency. Moreover, to communicate the different smart cities domains we propose a Context Broker based on a publish/subscribe middleware specially designed to be elastic and low‐latency and exploit the context information of these environments. Additionally, we validate our architecture through a real smart city use case, showing how the proposed architecture can successfully meet the smart cities requirements by taking advantage of the fog computing approach. Finally, we also analyze the performance of the proposed Context Broker based on microbenchmarking results for latency, throughput, and scalability.

Modern IoT deployments do require considerable investments that might only be justified if the data being gathered could be monetized, which leads to the need for a digital data marketplace. In many cases, the provider of the IoT data needs to process it locally for data curation, aggregation, stream processing, etc. At the same time, the consumer could be interested in nearby data. This scenario resembles a fog computing architecture where companies require being able, keeping data under their control, to securely make it available to other companies in a peer‐to‐peer fashion, without needing a cloud intermediary (like traditional marketplaces do), thus maximizing the locality of the processing and avoiding the existence of a bottleneck when the intermediary makes the data delivery for accounting purposes. Nevertheless, this imposes a hard requirement: by not having a central marketplace, the peers (seller and customer) need to trust each other, which, in turn, requires enforcing a nonrepudiation schema. In this paper, the authors propose a distributed peer‐to‐peer architecture for such a data marketplace that takes advantage of the architectural fundamentals of fog computing, in which data processing, filtering, and stream based event generation is done in a fog node along with the data, and where relationships, both commercial agreements and data delivery, are performed directly between producers and consumers without the need of mutual trust thanks to the usage of blockchain principles (e.g., distributed ledger, consensus mechanism). The proposed architecture is validated through a case study involving a set of key issues regarding nonrepudiation commonly identified when moving from a centralized marketplace to a distributed one. Moreover, it is shown that the proposed solution does not bring in any limitation with regard to a centralized marketplace solution, in terms of pricing models (subscriptions, pay‐per‐use, etc.) or usage conditions (contract duration, updates rate, etc.).

The development of IoT (Internet of Things) applications poses a number of scientific and technological challenges which stem from the characteristics of the IoT domain itself. These include the huge and increasing number of connected entities (devices, physical objects, people,...) populating the physical environment, the variety of their types which leads to heterogeneity of the data produced or consumed by those connected entities. In this paper we argue that semantic modeling takes up many of these challenges and explain how the core platform developed by the FI-WARE project supports IoT application developers. After a short introduction of the characteristics and requirements of IoT applications we identify the contribution of semantic technologies to address some of them. We describe the FI-WARE platform enablers which support these technologies and illustrate through a real application how these enablers help developers satisfy these requirements.

This article addresses one of the major end-user software engineering (EUSE) challenges, namely, how to motivate end users to apply unfamiliar software engineering techniques and activities to achieve their goal: translate requirements into software that meets their needs. EUSE activities are secondary to the goal that the program is helping to achieve and end-user programming is opportunistic. The challenge is then to find ways to incorporate EUSE activities into the existing workflow without users having to make substantial changes to the type of work they do or their priorities. In this article, we set out an approach to EUSE for web-based applications. We also propose a software lifecycle that is consistent with the conditions and priorities of end users without programming skills and is well-aligned with EUSE's characteristic informality, ambiguity and opportunisticness. Users applying this lifecycle manage to find solutions that they would otherwise be unable to identify. They also develop quality products. Users of this approach will not have to be acquainted with software engineering, as a framework will take them through the web-centred EUSE lifecycle step-by-step. We also report a statistical experiment in which users develop web software with and without a framework to guide them through the lifecycle. Its aim is to validate the applicability of our framework-driven lifecycle.

Although context could be exploited to improve the performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) model of communication, only very few works have explored domains with highly dynamic context, whereas most adopted models are context agnostic. In this paper, we present the key design principles underlying a novel context-aware content-based P/S (CA-CBPS) model of communication, where the context is explicitly managed, focusing on the minimization of network overhead in domains with recurrent context changes thanks to contextual scoping. We highlight how we dealt with the main shortcomings of most of the current approaches. Our research is some of the first to study the problem of explicitly introducing context-awareness into the P/S model to capitalize on contextual information. The envisioned CA-CBPS middleware enables the cloud ecosystem of services to communicate very efficiently, in a decoupled, but contextually scoped fashion.

Over the past few years, traditional software products, sales and licensing schemes have declined, whereas business value and revenues have shifted to SaaS-based schemes. Even so, most research has focused primarily on the technical layer (i.e. service invocation, integration, coordination, etc.). As a result, most SOA solutions available on market still do not feature a service "face" for human users. The SOA front-end of those that do is typically based on monolithic, rigid and non-customizable user interfaces and portals that invoke back-end services and processes ad-hoc. This paper presents the rationale behind a novel user-centered visual service composition system being developed by the European FP7 FAST Project consortium. This service composition system aims to enable service composition by guiding non-technical users through an open innovation process. The proposal formally models the component model, techniques and languages. Also it leverages some well-known Web 2.0 principles in order to bridge the gap between the service technical layer of a SOA and its end users. This should improve user appreciation of the benefits of such a system, enabling them to easily mash up their own service front-end from its basic and/or available building blocks.

Service oriented architectures (SOAs) based on Web Services have attracted a great interest and IT investments during the last years, principally in the context of business-to-business integration within corporate intranets. However, they are nowadays evolving to break through enterprise boundaries, in a revolutionary attempt to make the approach pervasive, leading to what we call a user-centric SOA, i.e. a SOA conceived as a Web of Services made up of compositional resources that empowers end-users to ubiquitously exploit these resources by collaboratively remixing them. In this paper we explore the architectural basis, technologies, frameworks and tools considered necessary to face this novel vision of SOA. We also present the rationale behind EzWeb/FAST: an undergoing EU funded project whose first outcomes could serve as a preliminary proof of concept.

To make the most of a global network effect and to search and filter the Long Tail, a collaborative tagging approach to social search should be based on the global activity of tagging, rating and filtering. We take a further step towards this objective by proposing a shared conceptualization of both the activity of tagging and the organization of the tagosphere in which tagging takes place. We also put forward the necessary data standards to interoperate at both data format and semantic levels. We highlight how this conceptualization makes provision for attaching identity and meaning to tags and tag categorization through a Wikipedia-based collaborative framework. Used together, these concepts are a useful and agile means of unambiguously defining terms used during tagging, and of clarifying any vague search terms. This improves search results in terms of recall and precision, and represents an innovative means of semantics-aware collaborative filtering and content ranking.

This paper discusses the rationale behind Telef´onica’s strategic decision for Enterprise Mobility Solutions and presents MorfeoMC: an open source vertical componentbased platform for rapidly developing mobile applications and services that can be used to create comprehensive and integrated mobility solutions while concealing the complexity involved in managing multiple devices. The key architectural decisions in MorfeoMC are described, and the reasoning behind their selection is presented and compared with related work. For these purposes, the paper focuses on the MorfeoMC’s Rendering Layer, and describes how it allows for the development of applications and services according to a Channel Model supported by the principles of Service Oriented Architectures (SOA). It is stressed how this approach avoids the need for duplicating the services that implement the business logic when another access channel is added, thanks to its architecture of code generators. Finally, other key elements and techniques in MorfeoMC are also discussed.

Content adaptation is crucial for universal Web access under varying conditions that may depend on device capabilities, network connectivity, user preferences, or user disabilities. Semantic annotations provide additional information about Web contents so that a content adaptation engine, based on Semantic Web technologies, can make better decisions on content repurposing. This paper presents MorfeoSMC: an open source advanced component-based platform that enables the development of semantics-aware mobile applications and services, and that solves the problem of how to make Web content usable on mobile devices. In particular, the paper focuses on how MorfeoSMC tackles the use of semantic markup in the information rendered for users through the mobility platform and in the Web content adaptation process. It also presents an innovative semantic matching framework for both services delivered in mobile environments and Web contents produced by these services. This framework is at the core of the semantics-aware Web content adaptation process.