729 research outputs found

    A Semantic-Agent Framework for PaaS Interoperability

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    Suchismita Hoare, Na Helian, and Nathan Baddoo, 'A Semantic-Agent Framework for PaaS Interoperability', in Proceedings of the The IEEE International Conference on Cloud and Big Data Computing, Toulouse, France, 18-21, July 2016. DOI: 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0126 © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cloud Platform as a Service (PaaS) is poised for a wider adoption by its relevant stakeholders, especially Cloud application developers. Despite this, the service model is still plagued with several adoption inhibitors, one of which is lack of interoperability between proprietary application infrastructure services of public PaaS solutions. Although there is some progress in addressing the general PaaS interoperability issue through various devised solutions focused primarily on API compatibility and platform-agnostic application design models, interoperability specific to differentiated services provided by the existing public PaaS providers and the resultant disparity owing to the offered services’ semantics has not been addressed effectively, yet. The literature indicates that this dimension of PaaS interoperability is awaiting evolution in the state-of-the-art. This paper proposes the initial system design of a PaaS interoperability (IntPaaS) framework to be developed through the integration of semantic and agent technologies to enable transparent interoperability between incompatible PaaS services. This will involve uniform description through semantic annotation of PaaS provider services utilizing the OWL-S ontology, creating a knowledgebase that enables software agents to automatically search for suitable services to support Cloud-based Greenfield application development. The rest of the paper discusses the identified research problem along with the proposed solution to address the issue.Submitted Versio

    Ontology-Based Resolution of Cloud Data Lock-in Problem

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    Cloud computing is nowadays becoming a popular paradigm for the provision of computing infrastructure that enables organizations to achieve financial savings. On the other hand, there are some known obstacles, among which vendor lock-in stands out. Furthermore, due to missing standards and heterogeneities of cloud storage systems, the migration of data to alternative cloud providers is expensive and time-consuming. We propose an approach based on Semantic Web services and AI planning to tackle cloud vendor data lock-in problem. To complete the mentioned task, data structures and data type mapping rules between different types of cloud storage systems are defined. The migration of data among different providers of platform as a service is presented in order to prove the practical applicability of the proposed approach. Additionally, this concept was also applied to software as a service model of cloud computing to perform one-shot data migration from Zoho CRM to Salesforce CRM

    A template description framework for services as a utility for cloud brokerage

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    Integration and mediation are two core functions that a cloud service broker needs to perform. The description of services involved plays a central role in this endeavour to enable services to be considered as commoditised utilities. We propose a conceptual framework for a cloud service broker based on two parts: a reference architecture for cloud brokers and a service description template that describes the mediated and integrated cloud services. Structural aspects of that template will be identified, formalised in an ontology and mapped onto a set of sublanguages that can be aligned to the cloud development and deployment process

    City Data Fusion: Sensor Data Fusion in the Internet of Things

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    Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

    Knowledge organization system for partial automation to improve the security posture of IoMT networks

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    Remote patient monitoring is a healthcare delivery model that uses technology to collect and transmit patient data from a remote location to healthcare providers for analysis and treatment. Remote patient monitoring systems rely on a network infrastructure to gather and transmit data from patients to healthcare providers through a network. While these systems become more prevalent, they may also become targets for cyberattacks. This paper deals with the development of a domain ontology to facilitate partial automation to improve the security posture of IoT networks used in remote patient monitoring. For this purpose, it captures the semantics of the concepts and properties of the main security aspects of IoT medical devices. This is complemented by a comprehensive ruleset, evaluated by using SPARQL queries, and automated reasoning over the aggregated knowledge

    CYCLONE Unified Deployment and Management of Federated, Multi-Cloud Applications

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    Various Cloud layers have to work in concert in order to manage and deploy complex multi-cloud applications, executing sophisticated workflows for Cloud resource deployment, activation, adjustment, interaction, and monitoring. While there are ample solutions for managing individual Cloud aspects (e.g. network controllers, deployment tools, and application security software), there are no well-integrated suites for managing an entire multi cloud environment with multiple providers and deployment models. This paper presents the CYCLONE architecture that integrates a number of existing solutions to create an open, unified, holistic Cloud management platform for multi-cloud applications, tailored to the needs of research organizations and SMEs. It discusses major challenges in providing a network and security infrastructure for the Intercloud and concludes with the demonstration how the architecture is implemented in a real life bioinformatics use case

    Context Aware Computing for The Internet of Things: A Survey

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    As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

    Survey of Service Description Languages and Their Issues in Cloud Computing

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    Along with the growing popularity of cloud computing technology, the amount of available cloud services and their usage frequency are increasing. In order to provide a mechanism for the efficient enforcement of service-relevant operations in cloud environment, such as service discovery, service provision, and service management, a completed and precise service specification model is highly required. In this paper, we conducted a survey on existing service description languages applied in three different domains - general services, Web/SOA services, and cloud services. We discussed and compared the past literature from seven major aspects, which are: (1) domain, (2) coverage, (3) purpose, (4) representation, (5) semantic expressivity, (6) intended users, and (7) features. Additionally, two core dimensions semantic expressivity and coverage are employed to categorize and analyse the key service description languages by using Magic Quadrant methodology. These two dimensions are regarded as the most essential factors for the evaluation of a service description model. Based on this analysis, we concluded that Unified Service Description Language (USDL) is the language with the widest coverage from business, technical and operational aspects, while OWL-S is the one that has the highest semantic expressivity. At last, critical research issues on cloud service description languages are identified and analysed. The solution of these issues requires more research efforts on the standardization of cloud service specification, which will eventually enhance the development of cloud industry

    Semantic Techniques for Multi-Cloud Applications Portability and Interoperability

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    The composition of Cloud Services to satisfy customer requirements is a complex task, owing to the huge number of services that arecurrentlyavailable. TheadventofBigDataandInternetofThings(IoT),whichrelyonCloudresourcesforbetterperformances and scalability, is pushing researchers to find new solutions to the Cloud Services composition problem. In this paper a semanticbased representation of Application Patterns and Cloud Services is presented, with an example of its use in a typical distributed application, which shows how the proposed approach can be successfully employed for the discovery and composition of Cloud Services.
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