42,743 research outputs found

    A practical framework for data collection in wireless sensor networks

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    Optimizing energy consumption for extending the lifetime in wireless sensor networks is of dominant importance. Groups of autonomous robots and unmanned aerial vehicles (UAVs) acting as mobile data collectors are utilized to minimize the energy expenditure of the sensor nodes by approaching the sensors and collecting their buffers via single hop communication, rather than using multihop routing to forward the buffers to the base station. This paper models the sensor network and the mobile collectors as a system-of-systems, and defines all levels and types of interactions. A practical framework that facilitates deploying heterogeneous mobiles without prior knowledge about the sensor network is presented. Realizing the framework is done through simulation experiments and tested against several performance metrics.<br /

    MAGDA: A Mobile Agent based Grid Architecture

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    Mobile agents mean both a technology and a programming paradigm. They allow for a flexible approach which can alleviate a number of issues present in distributed and Grid-based systems, by means of features such as migration, cloning, messaging and other provided mechanisms. In this paper we describe an architecture (MAGDA – Mobile Agent based Grid Architecture) we have designed and we are currently developing to support programming and execution of mobile agent based application upon Grid systems

    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

    Modeling the power consumption of a Wifibot and studying the role of communication cost in operation time

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    Mobile robots are becoming part of our every day living at home, work or entertainment. Due to their limited power capabilities, the development of new energy consumption models can lead to energy conservation and energy efficient designs. In this paper, we carry out a number of experiments and we focus on the motors power consumption of a specific robot called Wifibot. Based on the experimentation results, we build models for different speed and acceleration levels. We compare the motors power consumption to other robot running modes. We, also, create a simple robot network scenario and we investigate whether forwarding data through a closer node could lead to longer operation times. We assess the effect energy capacity, traveling distance and data rate on the operation time
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