Adaptation Conflicts of Heterogeneous Devices in Iot Smart-Home

A promising technology such as Internet-of-Things have been introduced into traditional homes, buildings and cities to become smart and offer a wide range of services to simplify and enhance people’s lifestyle, a complex rule structure with a large number of sensing and actuating devices increases the chances of creating rules with faulty behaviors. Detection of sophisticated conflicts in an IoT system is one example of such faulty systems. In this paper, a mechanism is presented to detect such sophisticated conflicts among multi-resident smart-home services. Formally a model considering the functional properties of devices to distinguish a specific new kind of conflicts among the other basic types. Service User Regularity (SUR) conflict detection algorithm is proposed to trace resident habitual usage and behaviour conflicts and regulate them within the rules of the smart-home IoT-system. The system achieved good result; it could detect a reasonable number of targeted type conflicts within a synthesized data set

Enabling High-Level Application Development for the Internet of Things

Application development in the Internet of Things (IoT) is challenging because it involves dealing with a wide range of related issues such as lack of separation of concerns, and lack of high-level of abstractions to address both the large scale and heterogeneity. Moreover, stakeholders involved in the application development have to address issues that can be attributed to different life-cycles phases. when developing applications. First, the application logic has to be analyzed and then separated into a set of distributed tasks for an underlying network. Then, the tasks have to be implemented for the specific hardware. Apart from handling these issues, they have to deal with other aspects of life-cycle such as changes in application requirements and deployed devices. Several approaches have been proposed in the closely related fields of wireless sensor network, ubiquitous and pervasive computing, and software engineering in general to address the above challenges. However, existing approaches only cover limited subsets of the above mentioned challenges when applied to the IoT. This paper proposes an integrated approach for addressing the above mentioned challenges. The main contributions of this paper are: (1) a development methodology that separates IoT application development into different concerns and provides a conceptual framework to develop an application, (2) a development framework that implements the development methodology to support actions of stakeholders. The development framework provides a set of modeling languages to specify each development concern and abstracts the scale and heterogeneity related complexity. It integrates code generation, task-mapping, and linking techniques to provide automation. Code generation supports the application development phase by producing a programming framework that allows stakeholders to focus on the application logic, while our mapping and linking techniques together support the deployment phase by producing device-specific code to result in a distributed system collaboratively hosted by individual devices. Our evaluation based on two realistic scenarios shows that the use of our approach improves the productivity of stakeholders involved in the application development

A UI-centric Approach for the End-User Development of Multidevice Mashups

In recent years, models, composition paradigms, and tools for mashup development have been proposed to support the integration of information sources, services and APIs available on the Web. The challenge is to provide a gate to a “programmable Web,” where end users are allowed to construct easily composite applications that merge content and functions so as to satisfy the long tail of their specific needs. The approaches proposed so far do not fully accommodate this vision. This article, therefore, proposes a mashup development framework that is oriented toward the End-User Development. Given the fundamental role of user interfaces (UIs) as a medium easily understandable by the end users, the proposed approach is characterized by UI-centric models able to support a WYSIWYG (What You See Is What You Get) specification of data integration and service orchestration. It, therefore, contributes to the definition of adequate abstractions that, by hiding the technology and implementation complexity, can be adopted by the end users in a kind of “democratic” paradigm for mashup development. This article also shows how model-to-code generative techniques translate models into application schemas, which in turn guide the dynamic instantiation of the composite applications at runtime. This is achieved through lightweight execution environments that can be deployed on the Web and on mobile devices to support the pervasive use of the created applications.</jats:p

Utilizing distributed web resources for enhanced knowledge representation

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Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject

Enhancement of the usability of SOA services for novice users

Recently, the automation of service integration has provided a significant advantage in delivering services to novice users. This art of integrating various services is known as Service Composition and its main purpose is to simplify the development process for web applications and facilitates reuse of services. It is one of the paradigms that enables services to end-users (i.e.service provisioning) through the outsourcing of web contents and it requires users to share and reuse services in more collaborative ways. Most service composers are effective at enabling integration of web contents, but they do not enable universal access across different groups of users. This is because, the currently existing content aggregators require complex interactions in order to create web applications (e.g., Web Service Business Process Execution Language (WS-BPEL)) as a result not all users are able to use such web tools. This trend demands changes in the web tools that end-users use to gain and share information, hence this research uses Mashups as a service composition technique to allow novice users to integrate publicly available Service Oriented Architecture (SOA) services, where there is a minimal active web application development. Mashups being the platforms that integrate disparate web Application Programming Interfaces (APIs) to create user defined web applications; presents a great opportunity for service provisioning. However, their usability for novice users remains invalidated since Mashup tools are not easy to use they require basic programming skills which makes the process of designing and creating Mashups difficult. This is because Mashup tools access heterogeneous web contents using public web APIs and the process of integrating them become complex since web APIs are tailored by different vendors. Moreover, the design of Mashup editors is unnecessary complex; as a result, users do not know where to start when creating Mashups. This research address the gap between Mashup tools and usability by the designing and implementing a semantically enriched Mashup tool to discover, annotate and compose APIs to improve the utilization of SOA services by novice users. The researchers conducted an analysis of the already existing Mashup tools to identify challenges and weaknesses experienced by novice Mashup users. The findings from the requirement analysis formulated the system usability requirements that informed the design and implementation of the proposed Mashup tool. The proposed architecture addressed three layers: composition, annotation and discovery. The researchers developed a simple Mashup tool referred to as soa-Services Provisioner (SerPro) that allowed novice users to create web application flexibly. Its usability and effectiveness was validated. The proposed Mashup tool enhanced the usability of SOA services, since data analysis and results showed that it was usable to novice users by scoring a System Usability Scale (SUS) score of 72.08. Furthermore, this research discusses the research limitations and future work for further improvements

Prediction, Recommendation and Group Analytics Models in the domain of Mashup Services and Cyber-Argumentation Platform

Mashup application development is becoming a widespread software development practice due to its appeal for a shorter application development period. Application developers usually use web APIs from different sources to create a new streamlined service and provide various features to end-users. This kind of practice saves time, ensures reliability, accuracy, and security in the developed applications. Mashup application developers integrate these available APIs into their applications. Still, they have to go through thousands of available web APIs and chose only a few appropriate ones for their application. Recommending relevant web APIs might help application developers in this situation. However, very low API invocation from mashup applications creates a sparse mashup-web API dataset for the recommendation models to learn about the mashups and their web API invocation pattern. One research aims to analyze these mashup-specific critical issues, look for supplemental information in the mashup domain, and develop web API recommendation models for mashup applications. The developed recommendation model generates useful and accurate web APIs to reduce the impact of low API invocations in mashup application development. Cyber-Argumentation platform also faces a similarly challenging issue. In large-scale cyber argumentation platforms, participants express their opinions, engage with one another, and respond to feedback and criticism from others in discussing important issues online. Argumentation analysis tools capture the collective intelligence of the participants and reveal hidden insights from the underlying discussions. However, such analysis requires that the issues have been thoroughly discussed and participant’s opinions are clearly expressed and understood. Participants typically focus only on a few ideas and leave others unacknowledged and underdiscussed. This generates a limited dataset to work with, resulting in an incomplete analysis of issues in the discussion. One solution to this problem would be to develop an opinion prediction model for cyber-argumentation. This model would predict participant’s opinions on different ideas that they have not explicitly engaged. In cyber-argumentation, individuals interact with each other without any group coordination. However, the implicit group interaction can impact the participating user\u27s opinion, attitude, and discussion outcome. One of the objectives of this research work is to analyze different group analytics in the cyber-argumentation environment. The objective is to design an experiment to inspect whether the critical concepts of the Social Identity Model of Deindividuation Effects (SIDE) are valid in our argumentation platform. This experiment can help us understand whether anonymity and group sense impact user\u27s behavior in our platform. Another section is about developing group interaction models to help us understand different aspects of group interactions in the cyber-argumentation platform. These research works can help develop web API recommendation models tailored for mashup-specific domains and opinion prediction models for the cyber-argumentation specific area. Primarily these models utilize domain-specific knowledge and integrate them with traditional prediction and recommendation approaches. Our work on group analytic can be seen as the initial steps to understand these group interactions

A Domain-Adaptable Heterogeneous Information Integration Platform: Tourism and Biomedicine Domains.

In recent years, information integration systems have become very popular in mashup-type applications. Information sources are normally presented in an individual and unrelated fashion, and the development of new technologies to reduce the negative effects of information dispersion is needed. A major challenge is the integration and implementation of processing pipelines using different technologies promoting the emergence of advanced architectures capable of processing such a number of diverse sources. This paper describes a semantic domain-adaptable platform to integrate those sources and provide high-level functionalities, such as recommendations, shallow and deep natural language processing, text enrichment, and ontology standardization. Our proposed intelligent domain-adaptable platform (IDAP) has been implemented and tested in the tourism and biomedicine domains to demonstrate the adaptability, flexibility, modularity, and utility of the platform. Questionnaires, performance metrics, and A/B control groups’ evaluations have shown improvements when using IDAP in learning environmentspost-print2139 K

Media, Information and Communication Contests: An Analysis

Reviews the implementation and design of the Knight News Challenge and other information communication technology contests to promote innovation. Examines goals, marketing, application process, criteria, judging process, winners, and supplemental support

Computing at massive scale: Scalability and dependability challenges

Large-scale Cloud systems and big data analytics frameworks are now widely used for practical services and applications. However, with the increase of data volume, together with the heterogeneity of workloads and resources, and the dynamic nature of massive user requests, the uncertainties and complexity of resource management and service provisioning increase dramatically, often resulting in poor resource utilization, vulnerable system dependability, and user-perceived performance degradations. In this paper we report our latest understanding of the current and future challenges in this particular area, and discuss both existing and potential solutions to the problems, especially those concerned with system efficiency, scalability and dependability. We first introduce a data-driven analysis methodology for characterizing the resource and workload patterns and tracing performance bottlenecks in a massive-scale distributed computing environment. We then examine and analyze several fundamental challenges and the solutions we are developing to tackle them, including for example incremental but decentralized resource scheduling, incremental messaging communication, rapid system failover, and request handling parallelism. We integrate these solutions with our data analysis methodology in order to establish an engineering approach that facilitates the optimization, tuning and verification of massive-scale distributed systems. We aim to develop and offer innovative methods and mechanisms for future computing platforms that will provide strong support for new big data and IoE (Internet of Everything) applications