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distributed Sensor Fusion for Activity Detection in Smart Buildings 1

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11th international conference on Internet and distributed computing Systems (IDCS)

作者： Papatsimpa, C. Linnartz, J. P. M. G. Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands Signify Eindhoven Netherlands

ISBN: (数字)9783030027384

ISBN: (纸本)9783030027384;9783030027377

Modern building systems often utilize multiple, physically separated sensors (sometimes of different type) to better detect occupancy. Such systems typically rely on a central processor where global data fusion takes place. However, such centralized architectures give rise to problems with communication and computational bottlenecks and are susceptible to total system failure should the central facility fail. there are significant advantages in distributing operations over multiple processing nodes. In the wake of this need, this paper addresses the problem of presence detection in a building by employing a decentralized sensing architecture. We focus on a network of radar sensor nodes, each with its own processing facility. Each node runs a hidden Markov model algorithm to provide a local estimate of the occupancy state and share it via wireless links. We introduce a distributed fusion algorithm that optimally combines the information generated by local nodes, having access to their private information, and recovers exactly the global estimation. System performance is evaluated in real world conditions, where sensor errors and communication may not exactly follow idealized model assumptions.

关键词： Internet of things (IoT) Smart buildings Energy efficiency Sensor fusion

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Towards a Reference Architecture for Swarm Intelligence-Based Internet of things 1

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10th international conference on Internet and distributed computing Systems (IDCS)

作者： Zedadra, Ouarda Savaglio, Claudio Jouandeau, Nicolas Guerrieri, Antonio Seridi, Hamid Fortino, Giancarlo 8 May 1945 Univ LabSTIC POB 401 Guelma 24000 Algeria Univ Calabria DIMES Via P BucciCubo 41c I-87036 Arcavacata Di Rende Italy Paris 8 Univ LIASD F-93526 St Denis Reunion France CNR Natl Res Council Italy Inst High Performance Comp & Networking ICAR Via P Bucci 7-11C I-87036 Arcavacata Di Rende CS Italy

ISBN: (数字)9783319977959

ISBN: (纸本)9783319977942;9783319977959

the Internet of things (IoT) represents the global network which interconnects digital and physical entities. It aims at providing objects with intelligence that allows them to perceive, decide and cooperate with other objects, machines, systems and even humans to enable a whole new class of applications and services. Agent-Based computing paradigm has been exploited to deal with the IoT system development. Many research works focus on making objects able to think by themselves thus imitating human brain. Swarm intelligence-based systems provide decentralized, self-organized and robust systems with consideration of coordination frameworks. We explore in this paper the exploitation of swarm intelligence-based features in IoT-based systems. therefore, we present a reference swarm-based architectural model that enables cooperation among devices in IoT systems.

关键词： Internet of things

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Exploiting the SEM Framework for Modeling Smart Cities 1

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10th international conference on Internet and distributed computing Systems (IDCS)

作者： Cicirelli, Franco Fortino, Giancarlo Guerrieri, Antonio Mercuri, Alessandro Spezzano, Giandomenico Vinci, Andrea CNR Natl Res Council Italy Inst High Performance Comp & Networking ICAR Via P Bucci 7-11C I-87036 Arcavacata Di Rende CS Italy Univ Calabria Dipartimento Ingn Informat Modellist Elettron & S I-87036 Arcavacata Di Rende CS Italy

ISBN: (数字)9783319977959

ISBN: (纸本)9783319977942;9783319977959

Smart Cities are smart environments extending over a wide geographical area having the aim of improving the quality of life of the citizens and optimizing the management of city resources. Despite the paramount interest towards these systems, there is a lack of approaches for their design. the Smart Environment Metamodel (SEM) is a framework which is well suited for the development of smart environments in general, and Smart Cities in particular. SEM allows the design of such systems by offering two different perspective focusing on functional and data requirements. this paper aims at showing the effectiveness of SEM by exploiting the framework for the design of a case study referring to a realized Smart City application developed in the city of Cosenza, Italy.

关键词： Smart Cities Internet of things Modeling Implementation Meta-modeling Smart Street Cosenza

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distributed Hybrid Cloud Management Platform Based On Rule Engine

Distributed Hybrid Cloud Management Platform Based On Rule E...

引用

IEEE international conference on Cloud computing

作者： Peng Xu Jingwei Su Zhongbao Zhang Science and Technology on Communication Networks Laboratory Shijiazhuang China State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

In the past few years, there has been a rapid growth in cloud computing, especially IaaS. It's a trend to use hybrid clouds that incorporate components of private and public clouds in order to achieve lower cost, higher availability and better security. Enterprises could get the benefits from it, including high elasticity, efficiency, flexibility, etc. In the meantime, they are faced with a set of challenges in cloud management. However, previous researches have primarily focused on single cloud platform, with lack of efficient management of hybrid clouds. To bridge this gap, in this paper, we propose a distributed hybrid cloud management platform based on rule engine. We design a succinct rule model to define rules and events. Combined with a distributed and reliable architecture, the demands of batch processing, automatic operation could be met, which make it more flexible and efficient to manage cloud resources from multiple IaaS cloud providers.

关键词： Hybrid Cloud Rule Engine IaaS Management

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Dynamic Framework for Reconfiguring computing Resources in the Inter-cloud and Its Application to Genome Analysis Workflows 1

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11th international conference on Internet and distributed computing Systems (IDCS)

作者： Tanjo, Tomoya Sun, Jingtao Saga, Kazushige Takefusa, Atsuko Aida, Kento Natl Inst Informat Tokyo 1018430 Japan

ISBN: (数字)9783030027384

ISBN: (纸本)9783030027384;9783030027377

this paper proposes a framework that dynamically reconfigures an application environment by adding and removing computing resources during runtime. the main idea is that the conditions for the resources used for reconfiguration can be translated into constraints on specifications, such as the number of cores, memory size, and resource location. Our framework consists of two subsystems: an application scheduler, which determines the constraints on specifications for each application, and a resource allocator, which finds resources that satisfy the constraints established by the application scheduler. this structure enables us to apply various reconfiguration strategies by replacing the application scheduler, and also enables us to investigate new allocation strategies for the resource allocator. As an example of the proposed framework, we developed a reconfiguration module for Galaxy, a workflow manager used in the bioinformatics field. Galaxy can act as an application scheduler by interacting with the reconfiguration module and Galaxy users can take advantage of our reconfiguration framework while using their own interface. the application scheduler applies an embedded strategy to decide when reconfiguration is invoked, whereas it can apply different reconfiguration algorithms to determine constraints on specifications by replacing algorithm modules for reconfiguration. We also describe a scheme for collecting resource metrics, such as CPU usage and memory usage, for use by the reconfiguration algorithms. Finally we conducted preliminary experiments to show the reconfiguration during runtime is necessary because the prediction of resource requirements may fail even if the algorithm uses previous execution records.

关键词： Cloud computing Virtual Cloud Provider Runtime reconfiguration Bioinformatics Workflow analysis Galaxy

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11th international conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2017

11th International Conference on Complex, Intelligent, and S...

引用

11th international conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2017

ISBN: (纸本)9783319615653

the proceedings contain 98 papers. the special focus in this conference is on Complex, Intelligent, and Software Intensive Systems. the topics include: Performance evaluation of a vegetable recognition system using caffe and chainer;energy-efficient quorum selection algorithm for distributed object-based systems;energy-aware dynamic migration of virtual machines in a server cluster;an energy-efficient migration algorithm of virtual machines in server clusters;using the web of data in semantic sensor networks;a communication method for wireless mesh networks suitable to IoT communication environment;influences of ILS localizer signal over complicated terrain;monitoring health of large scale software systems using drift detection techniques;an efficient scheduling of electrical appliance in micro grid based on heuristic techniques;personal data in cyber systems security;performance measurement of energy management controller using heuristic techniques;managing energy in smart homes using binary particle swarm optimization;single hop selection based forwarding in WDFAD-DBR for under water wireless sensor networks;a framework for ranking of software design patterns;real-time body gestures recognition using training set constrained reduction;towards better population sizing for differential evolution through active population analysis with complex network;conveying audience emotions through humanoid robot gestures to an orchestra during a live musical exhibition;security infrastructure for service oriented architectures at the tactical edge;an application using a BLE beacon model combined with fully autonomous wheelchair control and enriching remote control applications with fog computing.

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Developing Agent-Based Smart Objects for IoT Edge computing: Mobile Crowdsensing Use Case 11th

Developing Agent-Based Smart Objects for IoT Edge Computing:...

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11th international conference on Internet and distributed computing Systems (IDCS)

作者： Leppanen, Teemu Savaglio, Claudio Loven, Lauri Russo, Wilma Di Fatta, Giuseppe Riekki, Jukka Fortino, Giancarlo Univ Oulu Ctr Ubiquitous Comp Oulu Finland Univ Calabria Dept Informat Modelling Elect & Syst Arcavacata Di Rende Italy Univ Reading Dept Comp Sci Reading Berks England

ISBN: (纸本)9783030027384;9783030027377

Software agents have been exploited to handle the inherent dynamicity in the Internet of things (IoT) systems, as agents are capable of autonomous, reactive and proactive operation in response to changes in their local environment. Agents, operating at the network edge, enable leveraging cloud resources into the proximity of the user devices. However, poor interoperability with the existing IoT systems and the lack of a systematic methodology for IoT system development with the agent paradigm have hindered the utilization of software agent technologies in IoT. In this paper, we describe the development process and the system architecture of a mobile crowdsensing service, provided by an agent-based smart object that comprises agents in both edge and user devices. Mobile crowdsensing is an example of such an application that relies on large-scale participatory sensor networks, where participants have active roles in producing information about their environment with their smartphones. this scheme introduces challenges in handling dynamic opportunistic resource availability, due to mobility and unpredicted actions of the participants. We present how ACOSO-Meth (Agent-oriented Cooperative Smart Object-Methodology) guidelines the development process systematically from the analysis to the actual agent-based implementation of a crowdsensing service. the implementation is done with the ROAgent framework that utilizes resource-oriented architecture and REST principles to integrate agent-based smart objects seamlessly with the programmable Web.

关键词： Smart object Edge computing Internet of things Agent-based computing Programmable web

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distributed In Situ Processing of Big Raster Data in the Cloud 11th

引用

11th international Andrei P. Ershov Informatics conference on Perspectives of System Informatics (PSI)

作者： Zalipynis, Ramon Antonio Rodriges Natl Res Univ Higher Sch Econ Moscow Russia

ISBN: (纸本)9783319743134;9783319743127

A raster is the primary data type in Earth science, geology, remote sensing and other fields with tremendous growth of data volumes. An array DBMS is an option to tackle big raster data processing. However, raster data are traditionally stored in files, not in databases. Command line tools have long being developed to process raster files. Most tools are feature-rich and free but optimized for a single machine. this paper proposes new techniques for distributed processing of raster data directly in diverse file formats by delegating considerable portions of work to such tools. An N-dimensional array data model is proposed to maintain independence from the files and the tools. Also, a new scheme named GROUP-APPLY-FINALLY is presented to universally express the majority of raster data processing operations and streamline their distributed execution. New approaches make it possible to provide a rich collection of raster operations at scale and outperform SciDB over 410x on average on climate reanalysis data. SciDB is the only freely available distributed array DBMS to date. Experiments were carried out on 8- and 16-node clusters in Microsoft Azure Cloud.

关键词： Big raster data Climate reanalysis distributed systems Cloud computing SciDB Array DBMS In situ NetCDF operators

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Performance, Resilience, and Security in Moving Data from the Fog to the Cloud: the DYNAMO Transfer Framework Approach 1

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11th international conference on Internet and distributed computing Systems (IDCS)

作者： Montella, Raffaele Di Luccio, Diana Kosta, Sokol Giunta, Giulio Foster, Ian Univ Napoli Parthenope Dept Sci & Technol Naples Italy Ctr Robust Decisionmaking Climate & Energy Policy Chicago IL 60637 USA Univ Chicago Dept Comp Sci Chicago IL 60637 USA Aalborg Univ Dept Elect Syst CMI Aalborg Denmark

ISBN: (数字)9783030027384

ISBN: (纸本)9783030027384;9783030027377

the data crowdsourcing paradigm applied in coastal and marine monitoring and management has been developed only recently due to the challenges of the marine environment. the pervasive internet of things technology is contributing to increase the number of connected instrumented devices available for data crowd-sourcing. A main issue in the fog/edge/cloud paradigm is that collected data need to be moved from tiny low power devices to cloud resources in order to be processed. this paper is about the DYNAMO data transfer framework enabling the data transfer feature in a internet of floating things scenario. the proposed framework is our solution to mitigate the effects of extreme and delay tolerant environments.

关键词： Edge Fog Cloud computing Internet of floating things Data crowdsourcing

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An Analysis on Use of Deep Learning and Lexical-Semantic Based Sentiment Analysis Method on Twitter Data to Understand the Demographic Trend of Telemedicine

An Analysis on Use of Deep Learning and Lexical-Semantic Bas...

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international conference on Knowledge and Systems Engineering

作者： Harshvadan Talpada Malka N. Halgamuge Nguyen Tran Quoc Vinh School of Computing and Mathematics Charles Sturt University Melbourne Victoria Australia Dep. of Electrical and Electronic Engineering The University of Melbourne Victoria Australia Faculty of Information Technology The University of Da Nang - University of Science and Education Vietnam

Technology has turned into a fundamental piece of everybody's life. Social media technology is already used widely by the public to speak out once mind openly. this data can be leveraged to have a better understanding of the current state of decision making. However, Twitter data is highly unstructured. Sentiment analysis can be applied to such health-related data to extract useful information regarding public opinion. the aim of the research is to understand (i) the correlation between Deep Learning versus lexical and semantic-based sentiment prediction methods, (ii) the sentiment prediction accuracy of these methods on manually annotated sentiment dataset (iii) domain-specific knowledge on accuracy of the sentiment prediction methods, and (iv) to utilize Twitter-based sentiment to understand the influence of telemedicine in regards to heart attack and epilepsy. Four sentiment prediction methods are utilized for the research;Lexical and Semantic-based (Valence Aware Dictionary and Sentiment Reasoner (VADER) and TextBlob) and Deep Learning based (Long Short Term Memory (LSTM) and sentiment model from Stanford CoreNLP). the dataset that we retrieved consists of 1.84 million old health-related tweets. Our finding suggests that lexical and semantic-based methods for sentiment prediction offer better accuracy than Deep Learning methods;when a large enough and evenly distributed training dataset is not available. We observed that domain-specific knowledge affects the prediction accuracy of sentiment, mainly when the target text contains more domain-specific words. Sentiment prediction on Twitter data can be utilized to understand the demographic distribution of sentiment. In our case, we observed that telemedicine has a high number of positive sentiment. It is still in its infancy and has not spread to a broader demographic.

关键词： Training Machine learning Telemedicine Twitter Sentiment analysis Prediction methods

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