43 research outputs found

    Semantic Approach for Service Oriented Requirements Modeling

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    A Reengineering Approach to Reconciling Requirements and Implementation for Context - Aware Web Services Systems

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    In modern software development, the gap between software requirements and implementation is not always conciliated. Typically, for Web services-based context-aware systems, reconciling this gap is even harder. The aim of this research is to explore how software reengineering can facilitate the reconciliation between requirements and implementation for the said systems. The underlying research in this thesis comprises the following three components. Firstly, the requirements recovery framework underpins the requirements elicitation approach on the proposed reengineering framework. This approach consists of three stages: 1) Hypothesis generation, where a list of hypothesis source code information is generated; 2) Segmentation, where the hypothesis list is grouped into segments; 3) Concept binding, where the segments turn into a list of concept bindings linking regions of source code. Secondly, the derived viewpoints-based context-aware service requirements model is proposed to fully discover constraints, and the requirements evolution model is developed to maintain and specify the requirements evolution process for supporting context-aware services evolution. Finally, inspired by context-oriented programming concepts and approaches, ContXFS is implemented as a COP-inspired conceptual library in F#, which enables developers to facilitate dynamic context adaption. This library along with context-aware requirements analyses mitigate the development of the said systems to a great extent, which in turn, achieves reconciliation between requirements and implementation

    A semantic framework for unified cloud service search, recommendation, retrieval and management

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    Cloud computing (CC) is a revolutionary paradigm of consuming Information and Communication Technology (ICT) services. However, while trying to find the optimal services, many users often feel confused due to the inadequacy of service information description. Although some efforts are made in the semantic modelling, retrieval and recommendation of cloud services, existing practices would only work effectively for certain restricted scenarios to deal for example with basic and non-interactive service specifications. In the meantime, various service management tasks are usually performed individually for diverse cloud resources for distinct service providers. This results into significant decreased effectiveness and efficiency for task implementation. Fundamentally, it is due to the lack of a generic service management interface which enables a unified service access and manipulation regardless of the providers or resource types.To address the above issues, the thesis proposes a semantic-driven framework, which integrates two main novel specification approaches, known as agility-oriented and fuzziness-embedded cloud service semantic specifications, and cloud service access and manipulation request operation specifications. These consequently enable comprehensive service specification by capturing the in-depth cloud concept details and their interactions, even across multiple service categories and abstraction levels. Utilising the specifications as CC knowledge foundation, a unified service recommendation and management platform is implemented. Based on considerable experiment data collected on real-world cloud services, the approaches demonstrate distinguished effectiveness in service search, retrieval and recommendation tasks whilst the platform shows outstanding performance for a wide range of service access, management and interaction tasks. Furthermore, the framework includes two sets of innovative specification processing algorithms specifically designed to serve advanced CC tasks: while the fuzzy rating and ontology evolution algorithms establish a manner of collaborative cloud service specification, the service orchestration reasoning algorithms reveal a promising means of dynamic service compositions

    Identity Management in M2M Networks

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    Evolving communication technologies stimulate a rapid growth in utilisation of communication-capable devices and therefore amount of transmitted data. This imposes new requirements for automatic device and data management necessary for successful exploitation of new opportunities. Unfortunately, currently developed systems, including Internet of Things and Machine-to-Machine communications, mainly focus on industrial applications that involve fixed users, proprietary environments as well as ad-hoc devices and things, whereas regular users along with possibilities and challenges created by growing sets of personal user equipment remain ignored. This thesis addresses the defined problem by analysing currently developed and utilised communication technologies and identity management systems as well as proposing an advanced identity management system that considers user-related needs and enables user-aware automatic device-to-device communications. Our system is unique compared to other automatic communication systems in that it enables global communication of devices owned or used by different parties and supports dynamic connection and relationship establishment based on data administered in a sophisticated identity management infrastructure. Unlike existing identity management mechanisms, our system extends the notion of an identified and authenticated entity to a combination of both user and device. Furthermore, the system introduces an original Single Device Sign-On feature that simplifies user login procedure when accessing a service with multiple devices. As a consequence, this thesis suggests a new direction for evolution of communication technologies as well as user-targeted Internet-based services and applications

    IaaS-cloud security enhancement: an intelligent attribute-based access control model and implementation

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    The cloud computing paradigm introduces an efficient utilisation of huge computing resources by multiple users with minimal expense and deployment effort compared to traditional computing facilities. Although cloud computing has incredible benefits, some governments and enterprises remain hesitant to transfer their computing technology to the cloud as a consequence of the associated security challenges. Security is, therefore, a significant factor in cloud computing adoption. Cloud services consist of three layers: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Cloud computing services are accessed through network connections and utilised by multi-users who can share the resources through virtualisation technology. Accordingly, an efficient access control system is crucial to prevent unauthorised access. This thesis mainly investigates the IaaS security enhancement from an access control point of view. [Continues.

    Tuning adaptive computations for the performance improvement of applications in JEE server

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    With the increasing use of autonomic computing technologies, a Java Enterprise Edition (JEE) application server is implemented with more and more adaptive computations for self-managing the Middleware as well as its hosted applications. However, these adaptive computations consume resources such as CPU and memory, and can interfere with the normal business processing of applications at runtime due to resource competition, especially when the whole system is under heavy load. Tuning these adaptive computations from the perspective of resource management becomes necessary. In this article, we propose a tuning model for adaptive computations. Based on the model, tuning is carried out dynamically by upgrading or degrading the autonomic level of an adaptive computation so as to control its resource consumption. We implement the RSpring tuner and use it to optimize autonomic JEE servers such as PkuAS and JOnAS. RSpring is evaluated on ECperf and RUBiS benchmark applications. The results show that it can effectively improve the application performance by 13.6 % in PkuAS and 19.2 % in JOnAS with the same amount of resources. ? 2012 The Brazilian Computer Society.EI02143-158

    Goal-based Workflow Adaptation for Role-based Resources in the Internet of Things

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    In recent years, the Internet of Things (IoT) has increasingly received attention from the Business Process Management (BPM) community. The integration of sensors and actuators into Process-Aware Information Systems (PAIS) enables the collection of real-time data about physical properties and the direct manipulation of real-world objects. In a broader sense, IoT-aware workflows provide means for context-aware workflow execution involving virtual and physical entities. However, IoT-aware workflow management imposes new requirements on workflow modeling and execution that are outside the scope of current modeling languages and workflow management systems. Things in the IoT may vanish, appear or stay unknown during workflow execution, which renders their allocation as workflow resources infeasible at design time. Besides, capabilities of Things are often intended to be available only in a particular real-world context at runtime, e.g., a service robot inside a smart home should only operate at full speed, if there are no residents in direct proximity. Such contextual restrictions for the dynamic exposure of resource capabilities are not considered by current approaches in IoT resource management that use services for exposing device functionalities. With this work, we aim at providing the modeling and runtime support for defining such restrictions on workflow resources at design time and enabling the dynamic and context-sensitive runtime allocation of Things as workflow resources. To achieve this goal, we propose contributions to the fields of resource management, i.e., resource perspective, and workflow management in the Internet of Things (IoT), divided into the user perspective representing the workflow modeling phase and the workflow perspective representing the runtime resource allocation phase. In the resource perspective, we propose an ontology for the modeling of Things, Roles, capabilities, physical entities, and their context-sensitive interrelations. The concept of Role is used to define non-exclusive subsets of capabilities of Things. A Thing can play a certain Role only under certain contextual restrictions defined by Semantic Web Rule Language (SWRL) rules. At runtime, the existing relations between the individuals of the ontology represent the current state of interactions between the physical and the cyber world. Through the dynamic activation and deactivation of Roles at runtime, the behavior of a Thing can be adapted to the current physical context. In the user perspective, we allow workflow modelers to define the goal of a workflow activity either by using semantic queries or by specifying high-level goals from a Tropos goal model. The goal-based modeling of workflow activities provides the most flexibility regarding the resource allocation as several leaf goals may fulfill the user specified activity goal. Furthermore, the goal model can include additional Quality of Service (QoS) parameters and the positive or negative contribution of goals towards these parameters. The workflow perspective includes the Semantic Access Layer (SAL) middleware to enable the transformation of activity goals into semantic queries as well as their execution on the ontology for role-based Things. The SAL enables the discovery of fitting Things, their allocation as workflow resources, the invocation of referenced IoT services, and the continuous monitoring of the allocated Things as part of the ontology. We show the feasibility and added value of this work in relation to related approaches by evaluation within several application scenarios in a smart home setting. We compare the fulfillment of quantified criteria for IoT-aware workflow management based on requirements extracted from related research. The evaluation shows, that our approach enables an increase in the context-aware modeling of Things as workflow resources, in the query support for workflow resource allocation, and in the modeling support of activities using Things as workflow resources.:1 Introduction 15 1.1 Background 17 1.2 Motivation 17 1.3 Aim and Objective 19 1.3.1 Research Questions and Scope 19 1.3.2 Research Goals 20 1.4 Contribution 20 1.5 Outline 21 2 Background for Workflows in the IoT 23 2.1 Resource Perspective 24 2.1.1 Internet of Things 24 2.1.2 Context and Role Modeling 27 2.2 User Perspective 37 2.2.1 Goal Modeling 38 2.2.2 Tropos Goal Modeling Language 38 2.3 Workflow Perspective 39 2.3.1 Workflow Concepts 39 2.3.2 Workflow Modeling 40 2.3.3 Internet of Things-aware Workflow Management 43 2.4 Summary 44 3 Requirements Analysis and Approach 45 3.1 Requirements 45 3.1.1 IoT Resource Perspective 46 3.1.2 Workflow Resource Perspective 50 3.1.3 Relation to Research Questions 51 3.2 State of the Art Analysis 53 3.2.1 Fulfillment Criteria 54 3.2.2 IoT-aware workflow management 56 3.3 Discussion 65 3.4 Approach 70 3.4.1 Contribution to IoT-aware workflow management 71 3.5 Summary 73 4 Concept for Adaptive Workflow Activities in the IoT 75 4.1 Resource Perspective 75 4.1.1 Role-based Things 75 4.1.2 Semantic Modeling Concepts 79 4.1.3 SWRL Modeling Concepts 81 4.2 User Perspective 81 4.2.1 Semantic Queries in Workflow Activites 81 4.2.2 Goals for Workflow Activites 81 4.2.3 Mapping from Goals to Semantic Queries 82 4.3 Workflow Perspective 83 4.3.1 Workflow metamodel Extensions 83 4.3.2 Middleware for Dynamic Resource Discovery and Allocation 85 4.4 Summary 86 5 Modeling Adaptive Workflow Activities in the IoT 87 5.1 Resource Perspective 87 5.1.1 Role-based Modeling of Context-sensitive Things 87 5.1.2 Ontology Classes 90 5.1.3 Ontology Object properties 93 5.1.4 Ontology Data properties 99 5.1.5 DL-safe SWRL Rules 100 5.2 Discussion of Role Modeling Features 101 5.3 Example Application Scenario Modeling 102 5.3.1 Resource Perspective 102 5.3.2 User Perspective 105 5.3.3 Workflow Perspective 109 5.4 Summary 113 6 Architecture for Adaptive Workflow Activities in the IoT 115 6.1 Overview of the System Architecture 115 6.2 Specification of System Components 117 6.2.1 Resource Perspective 118 6.2.2 User Perspective 118 6.2.3 Workflow Perspective 118 6.3 Summary 123 7 Implementation of Adaptive Workflow Activities in the IoT 125 7.1 Resource Perspective 125 7.2 Workflow Perspective 125 7.2.1 PROtEUS 125 7.2.2 Semantic Access Layer 127 7.3 User Perspective 128 7.4 Summary 128 8 Evaluation 129 8.1 Goal and Evaluation Approach 129 8.1.1 Definition of Test Cases 130 8.2 Scenario Evaluation 134 8.2.1 Ambient Assisted Living Setting 135 8.2.2 Resource Perspective 135 8.2.3 User Perspective 137 8.2.4 Workflow Perspective 138 8.2.5 Execution of Test Cases 139 8.2.6 Discussion of Results 146 8.3 Performance Evaluation 148 8.3.1 Experimental Setup 148 8.3.2 Discussion of Results 151 8.4 Summary 152 9 Discussion 153 9.1 Comparison of Solution to Research Questions 153 9.2 Extendability of the Solutions 155 9.3 Limitations 156 10 Summary and Future Work 157 10.1 Summary of the Thesis 157 10.2 Future Work 159 Appendix 161 Example Semantic Context Model for IoT-Things 171 T-Box of Ontology for Role-based Things in the IoT 178 A-Box for Example Scenario Model 201 A-Box for Extended Example Scenario Model 21
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