3,389 research outputs found

    Big data analytics:Computational intelligence techniques and application areas

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    Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

    Large-scale offloading in the Internet of Things

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    Large-scale deployments of IoT devices are subject to energy and performance issues. Fortunately, offloading is a promising technique to enhance those aspects. However, several problems still remain open regarding cloud deployment and provisioning. In this paper, we address the problem of provi- sioning offloading as a service in large-scale IoT deployments. We design and develop an AutoScaler, an essential component for our offloading architecture to handle offloading workload. In addition, we also develop an offloading simulator to generate dynamic offloading workload of multiple devices. With this toolkit, we study the effect of task acceleration in different cloud servers and analyze the capacity of several cloud servers to handle multiple concurrent requests. We conduct multiple experiments in a real testbed to evaluate the system and present our experiences and lessons learned. From the results, we find that the AutoScaler component introduces a very small overhead of ≈150 milliseconds in the total response time of a request, which is a fair price to pay to empower the offloading architectures with multi-tenancy ability and dynamic horizontal scaling for IoT scenarios

    Voice Recognition Systems for The Disabled Electorate: Critical Review on Architectures and Authentication Strategies

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    An inevitable factor that makes the concept of electronic voting irresistible is the fact that it offers the possibility of exceeding the manual voting process in terms of convenience, widespread participation, and consideration for People Living with Disabilities. The underlying voting technology and ballot design can determine the credibility of election results, influence how voters felt about their ability to exercise their right to vote, and their willingness to accept the legitimacy of electoral results. However, the adoption of e-voting systems has unveiled a new set of problems such as security threats, trust, and reliability of voting systems and the electoral process itself. This paper presents a critical literature review on concepts, architectures, and existing authentication strategies in voice recognition systems for the e-voting system for the disabled electorate. Consequently, in this paper, an intelligent yet secure scheme for electronic voting systems specifically for people living with disabilities is presented

    An Emerging Decision Support Systems Technology for Disastrous Actions Management

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    The purpose of the chapter is to introduce a conceptual approach of emerging decision \ud \ud support systems (DSS) development in enhancing contextual support in decision making. \ud \ud We analyse the requirements of outlining a technological solution model for addressing \ud \ud disaster management problem situations in which decision makers at different levels can \ud \ud have the information support to respond effectively

    Cloud engineering is search based software engineering too

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    Many of the problems posed by the migration of computation to cloud platforms can be formulated and solved using techniques associated with Search Based Software Engineering (SBSE). Much of cloud software engineering involves problems of optimisation: performance, allocation, assignment and the dynamic balancing of resources to achieve pragmatic trade-offs between many competing technical and business objectives. SBSE is concerned with the application of computational search and optimisation to solve precisely these kinds of software engineering challenges. Interest in both cloud computing and SBSE has grown rapidly in the past five years, yet there has been little work on SBSE as a means of addressing cloud computing challenges. Like many computationally demanding activities, SBSE has the potential to benefit from the cloud; ‘SBSE in the cloud’. However, this paper focuses, instead, of the ways in which SBSE can benefit cloud computing. It thus develops the theme of ‘SBSE for the cloud’, formulating cloud computing challenges in ways that can be addressed using SBSE

    Evaluating Performance of Web Applications in (Cloud) Virtualized Environments

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    Web applications usually involve a number of different software libraries and tools (usually referred to as frameworks) each carrying out specific task/s and generating the corresponding overhead. In this paper, we show how to evaluate and even find out several configuration performance characteristics by using virtualized environments which are now used in data centers and cloud environments. We use specific and simple web software architectures as proof of concept, and explain several experiments that show performance issues not always expected from a conceptual point of view. We also explain that adding software libraries and tools also generate performance analysis complexities. We also shown that as an application is shown to scale, the problems to identify performance details and bottlenecks also scale, and the performance analysis also requires deeper levels of details.Instituto de Investigación en Informátic
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