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检索条件"任意字段=3rd International Symposium on Information Processing in Sensor Networks"

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Cell Search Time Performance Using Same Frequency Spectrum for Heterogeneous networks Including Indoor Small Cells 12

Cell Search Time Performance Using Same Frequency Spectrum f...

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IEEE 12th international symposium on Autonomous Decentralized Systems (ISADS)

作者： Noguchi, Naoki Sawahashi, Mamoru Nagata, Satoshi Tokyo City Univ Dept Informat & Commun Engn Setagaya Ku 1-28-1 Tamadutsumi Tokyo 1588557 Japan NTT DOCOMO Inc Res Labs Yokosuka Kanagawa 2398536 Japan

ISBN: (纸本)9781479982615

This paper presents the initial cell search time performance based on Long Term Evolution (LTE) synchronization signals employing the same frequency spectrum for heterogeneous networks including indoor small cells. We assume the indoor small cell models in hot zone buildings that are specified in the 3rd Generation Partnership Project (3GPP) technical report. System-level simulation results show that in both the sparse and dense scenarios employing the same frequency spectrum for the heterogeneous networks, the influence of co-channel interference particularly from a macrocell to indoor small cells on the initial cell search time is not large except for the case when a small cell cluster is placed very close to the macrocell site. We also show that the indoor small cell deployment is effective in achieving fast cell search times as well as achieving higher cell throughput for heterogeneous networks where high volume traffic occurs in the indoor hot zone building.

关键词： cell search LTE synchronization signal heterogeneous networks indoor small cell

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3rd international Conference on Communications, Signal processing, and Systems, CSPS 2014

3rd International Conference on Communications, Signal Proce...

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3rd international Conference on Communications, Signal processing and Systems, CSPS 2014

ISBN: (纸本)9783319089904

The proceedings contain 110 papers. The special focus in this conference is on Cognitive Radio System, Short Range Wireless Network, Radar Signal processing, Mobile networks and Wireless Communication. The topics include: Cognitive radio interference modeling and application on fading channels;robust localization with the mobility of SUS for cognitive radio networks;a primary user localization method in cognitive radio networks;management mechanism of key leakage avoidance in hybrid zigbee network;a spectral efficient cognitive radio resource management method for low-energy cognitive networks;an efficient authenticated key exchange protocol for wireless body area network;a simulation study on performance influencing factors;on the security of wireless sensor networks via compressive sensing;home area network security in smart grid;an improved grouping spectrum allocation algorithm in cognitive radio;monitoring and controlling packets transmission improvement based on the physical depth in the zigbee networks;an improved routing discovery algorithm based on the relative position information in the zigbee networks;optimal multiple kernel local discriminant embedding for SAR ATR;cubature Kalman filter based on strong tracking;nonlinear radar tracking data filtering with unscented kalman filter;human detection through wall using information theory;a feature fusion-based visual attention method for target detection in SAR images;sub-dictionary based joint sparse representation for multi-aspect SAR automatic target recognition and sequential loud test for genuine and dummy warhead identification using MIMO radar.

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Encryption and hash based security in Internet of Things 3

Encryption and hash based security in Internet of Things

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3rd international Conference on Signal processing, Communication and Networking, ICSCN 2015

作者： Vinayaga Sundaram, B. Ramnath, M. Prasanth, M. Varsha Sundaram, J. Department of Information Technology Madras Institute of Technology Anna University Chennai India

ISBN: (纸本)9781467368230

The Internet of Things (IoT) promises to be the next big revolution of the World Wide Web. It has a very wide range of applications, ranging from smart cities, smart homes, monitoring radiation levels in nuclear plants, animal tracking, health surveillance and a lot more. When nodes in wireless sensor networks are monitored through internet it becomes a part of Internet of Things. This brings in a lot of concerns related to security, privacy, standardization, power management. This paper aims at enhancing security in smart home systems. Devices like thermostat, air conditioners, doors and lighting systems are connected with each other and the internet through the internet of things technologies. Encryption and hash algorithms are proposed in this paper through which devices in the IoT can securely send messages between them. Encryption algorithm is used to ensure confidentiality as the attackers cannot interpret the cipher text that is sent. In order to ensure integrity (cipher text is not changed) hash algorithm is used. © 2015 IEEE.

关键词： Internet of things

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Improving WSNs Sleep Scheduling Mechanism with SDN-like Architecture 14

Improving WSNs Sleep Scheduling Mechanism with SDN-like Arch...

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14th IEEE/ACM international Conference on information processing in sensor networks (IPSN)

作者： Wang, Yanwen Chen, Hainan Wu, Xiaoling Shu, Lei Chinese Acad Sci Guangzhou Inst Adv Technol 1121 Haibin Rd Guangzhou Guangdong Peoples R China Guangdong Univ Petrochem Technol Guangdong Prov Key Lab Petrochem Equipment Fault Maoming Peoples R China

ISBN: (纸本)9781450334754

We propose a SDN-like architecture based WSN and improve the existing EC-CKN Sleep Scheduling mechanism to implement more efficient energy management. A SDN-like architecture is adopted instead of traditional WSN architecture and EC-CKN algorithm is applied as the fundamental algorithm. This paper presents the design, implementation and evaluation of the proposed SDN-ECCKN on the WSN with SDN-like architecture.

关键词： SDN-like architecture WSN EC-CKN SDN-ECCKN Sleep Scheduling

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A Pareto Survivor Function Based Cluster Head Selection Mechanism (PSFCHSM) to Mitigate Selfish Nodes in Wireless sensor networks 3rd

A Pareto Survivor Function Based Cluster Head Selection Mech...

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3rd international symposium on Security in Computing and Communications (SSCC)

作者： Rajarajeswari, P. L. Karthikeyan, N. K. Sri Krishna Coll Technol Dept Comp Sci & Engn Coimbatore 641042 Tamil Nadu India Sri Krishna Coll Engn & Technol Dept Informat Technol Coimbatore 641008 Tamil Nadu India

ISBN: (纸本)9783319229157;9783319229140

In Wireless sensor networks (WSNs), co-operation among sensor nodes plays a significant role for reliable data delivery by prolonging the lifetime of the network. Taking this aspect into account, a Pareto Survivor Function based Cluster Head Selection Mechanism (PSFCHSM) is proposed for electing the new cluster head under selfish attack. In this approach, the detection of selfish attack is achieved through a conditional probabilistic approach which monitors events that purely depends only on the continuous network parameters. The proposed strategy not only identifies the selfish attack in sensor networks but also elects a new sensor node as a rehabilitative Cluster Head (CH) based on Pareto Survivor Function (PSF). The preeminence of the proposed approach is evaluated through evaluation parameters like Packet Delivery Ratio (PDR), Energy Consumption Rate and Throughput by varying the number of sensor nodes and the transmission range. Further, the incorporation of this conditional survivability co-efficient mechanism detects and mitigates selfish nodes at a rapid rate of 32 % than the benchmark mechanisms like Fuzzy Ant Colony Optimization Routing (FACOR) and Genetic Algorithm Inspired Routing Protocol (GROUP) considered for comparison. The proposed approach not only isolates the selfish nodes that causes Denial of Service (DoS) attack but also reduces the cost incurred in communication. Furthermore, the simulation results show that PSFCHSM outperforms GROUP and FACOR by enhancing the network lifetime by 28 %.

关键词： Selfish nodes Conditional survivability co-efficient Pareto Survivor Function (PSF) FACOR GROUP Node lifetime

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Wearable sensor Grid Architecture For Body Posture And Surface Detection And Rehabilitation 14

Wearable Sensor Grid Architecture For Body Posture And Surfa...

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14th IEEE/ACM international Conference on information processing in sensor networks (IPSN)

作者： Hermanis, Atis Cacurs, Ricards Nesenbergs, Krisjanis Greitans, Modris Syundyukov, Emil Selavo, Leo Inst Elect & Comp Sci LV-1006 Riga Latvia

ISBN: (纸本)9781450334754

We propose a hybrid architecture of wired and wireless sensors for smart fabric with applications including body dynamics and shape monitoring and patient rehabilitation. Our system is capable of acquiring data from up to 200 on-body sensors with 50Hz sampling rate using conventional low-cost hardware. The sensing and data processing is done in real time and the results available on a smaptphone, tablet or pc in 3D visual form or as alerts. The user experience of the demo will include trying out smart clothing that is enabled with the shape sensing fabric and observing the body shape dynamics on-screen in real time.

关键词： Patient rehabilitation

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Exploring Recurrent Neural networks to Detect Named Entities from Biomedical Text 1

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14th China National Conference on Computational Linguistics (CCL) / 3rd international symposium on Natural Language processing Based on Naturally Annotated Big Data (NLP-NABD)

作者： Li, Lishuang Jin, Liuke Huang, Degen Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Liaoning Peoples R China

ISBN: (数字)9783319258164

ISBN: (纸本)9783319258164;9783319258157

Biomedical named entity recognition (bio-NER) is a crucial and basic step in many biomedical information extraction tasks. However, traditional NER systems are mainly based on complex hand-designed features which are derived from various linguistic analyses and maybe only adapted to specified area. In this paper, we construct Recurrent Neural Network to identify entity names with word embeddings input rather than hand-designed features. Our contributions mainly include three aspects: (1) we adapt a deep learning architecture Recurrent Neural Network (RNN) to entity names recognition;(2) based on the original RNNs such as Elman-type and Jordan-type model, an improved RNN model is proposed;(3) considering that both past and future dependencies are important information, we combine bidirectional recurrent neural networks based on information entropy at the top layer. The experiments conducted on the BioCreative II GM data set demonstrate RNN models outperform CRF and deep neural networks (DNN), furthermore, the improved RNN model performs better than two original RNN models and the combined method is effective.

关键词： Bio-NER Recurrent neural network Word embeddings Bidirectional information entropy

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Improving Link Prediction in Social networks by User Comments and Sentiment Lexicon 1

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14th China National Conference on Computational Linguistics (CCL) / 3rd international symposium on Natural Language processing Based on Naturally Annotated Big Data (NLP-NABD)

作者： Liu, Feng Liu, Bingquan Sun, Chengjie Liu, Ming Wang, Xiaolong Harbin Inst Technol Sch Comp Sci & Technol Harbin 150006 Peoples R China

ISBN: (数字)9783319258164

ISBN: (纸本)9783319258164;9783319258157

In some online Social Network Services, users are allowed to label their relationship with others, which can be represented as links with signed values. The link prediction problem is to estimate the values of unknown links by the information from the social network. A lot of similarity based metrics and machine learning based methods are proposed. Most of these methods are based on the network topological and node states. In this paper, by considering the information from user comment and sentiment lexicon, our methods improved the performances of link prediction for both similarity based metrics and machine learning based methods.

关键词： Link prediction Social networks Link network structure User comments Sentiment lexicon

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Reducing Multi-Hop Calibration Errors in Large-Scale Mobile sensor networks 14

Reducing Multi-Hop Calibration Errors in Large-Scale Mobile ...

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14th IEEE/ACM international Conference on information processing in sensor networks (IPSN)

作者： Saukh, Olga Hasenfratz, David Thiele, Lothar Swiss Fed Inst Technol Comp Engn & Networks Lab Zurich Switzerland

ISBN: (纸本)9781450334754

Frequent sensor calibration is essential in sensor networks with low-cost sensors. We exploit the fact that temporally and spatially close measurements of different sensors measuring the same phenomenon are similar. Hence, when calibrating a sensor, we adjust its calibration parameters to minimize the differences between co-located measurements of previously calibrated sensors. In turn, freshly calibrated sensors can now be used to calibrate other sensors in the network, referred to as multi-hop calibration. We are the first to study multi-hop calibration with respect to a reference signal (micro-calibration) in detail. We show that ordinary least squares regression-commonly used to calibrate noisy sensors-suffers from significant error accumulation over multiple hops. In this paper, we propose a novel multi-hop calibration algorithm using geometric mean regression, which (i) highly reduces error propagation in the network, (ii) distinctly outperforms ordinary least squares in the multi-hop scenario, and (iii) requires considerably fewer ground truth measurements compared to existing network calibration algorithms. The proposed algorithm is especially valuable when calibrating large networks of heterogeneous sensors with different noise characteristics. We provide theoretical justifications for our claims. Then, we conduct a detailed analysis with artificial data to study calibration accuracy under various settings and to identify different error sources. Finally, we use our algorithm to accurately calibrate 13 million temperature, ground ozone (O-3), and carbon monoxide (CO) measurements gathered by our mobile air pollution monitoring network.

关键词： Calibration

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Influence of on-Device Measurement Analysis on Energy Efficiency in Machine-to-Machine Systems

Influence of on-Device Measurement Analysis on Energy Effici...

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3rd international Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on Computer Science and information Systems (FedCSIS)

作者： Skocir, Pavle Kusek, Mario Jezic, Gordan Univ Zagreb Fac Elect Engn & Comp Dept Telecommun Unska 3 HR-10000 Zagreb Croatia

ISBN: (纸本)9788360810668

Machine-to-Machine Communication (M2M) enables communication between heterogeneous devices without human intervention. It is considered to be a key enabler technology for the concept of Internet of Things (IoT) and Cyber Physical Systems (CPS). With M2M's integration with Wireless sensor networks (WSN), information from different kinds sensors can be obtained. In order to discover useful knowledge from sensor data, various data mining techniques need to be applied. Due to the development of microprocessors on end devices in M2M system which collect data from sensors, data processing can also be executed on those devices. However, since end devices are often battery powered, energy consumption when running those algorithms needs to be taken into account. In this paper we implement an algorithm in M2M system, on Libelium Waspmote devices, which detects temperature plummeting in an indoor space. Afterwards, energy consumption of Waspmote devices is analyzed for two cases: when algorithm is executed on-device and when algorithm is executed on gateway or on back-end system.

关键词： Internet of Things mobile communication wireless sensor networks CPS M2M integration M2M system WSN Waspmote devices back end system cyber physical systems data mining techniques energy efficiency human intervention indoor space key enabler technology machine-to-machine communication machine-to-machine systems microprocessors ondevice measurement analysis sensor data temperature plummeting Data mining Energy consumption Logic gates Temperature measurement Temperature sensors Wireless sensor networks

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