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Biologically-inspired Network "Memory" for Smarter Networking

Biologically-inspired Network "Memory" for Smarter Networkin...

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8th ieee international conference on Collaborative computing: Networking, Applications and Worksharing (CollaborateCom)

作者： Mokhtar, Bassem Eltoweissy, Mohamed Virginia Tech Bradley Dept Elect & Comp Engn Blacksburg VA 24061 USA Egypt Japan Univ Sci & Technol Dept Comp Sci & Engn Alexandria Egypt Virginia Tech ECE Dept Blacksburg VA USA Univ Arizona Tucson AZ 85721 USA

ISBN: (纸本)9781467327404;9781467327404

Emerging technologies such as the Internet of things generate huge amounts of network traffic and data which lead to significant challenges in a) ensuring availability of resources on-demand, b) recognizing emergent and abnormal behavior, and c) making effective decisions for efficient network operations. Network traffic data exhibit spatiotemporal patterns. Learning and maintaining the currently elusive rich semantics based on analyzing such patterns would help in mitigating those challenges. In this paper, we propose the concept of a network "memory" (or NetMem) to support smarter data-driven network operations as a foundational component of next generation networks. NetMem will enable networking objects to understand autonomously, at real-time, on-demand, and at low cost semantics with different levels of granularity and related to various network elements. Guided by the fact that human activities exhibit spatiotemporal data patterns;and the human memory extracts and maintains semantics to enable accordingly learning and predicting new things, we design NetMem to mimic functionalities of that memory. NetMem provides capabilities for semantics management through uniquely integrating data virtualization for homogenizing massive data originating from heterogeneous sources, cloud-like scalable storage, associative rule learning to recognize data patterns, and hidden Markov models for reasoning and extracting semantics clarifying normal/abnormal behavior. NetMem provides associative access to data patterns and relevant derived semantics to enable enhancements in early anomaly detection, more accurate behavior prediction and satisfying QoS requirements with better utilization of resources. We evaluate NetMem using simulation. Preliminary results demonstrate the positive impact of NetMem on various network management operations.

关键词： Network Semantics Data Virtualization Cloud Data Storage distributed systems Bio-inspired Design

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Virtual cluster tree based distributed data classification strategy using locally linear embedding in wireless sensor network

Virtual cluster tree based distributed data classification s...

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8th international conference on Intelligent computing Technology, ICIC 2012

作者： Song, Xin Wang, Cuirong Wang, Cong Hu, Xi School of Information Science and Engineering Northeastern University 110819 Shenyang China Key Laboratory of Complex System and Intelligence Science Institute of Automation Chinese Academy of Sciences 100190 Beijing China

ISBN: (纸本)9783642315879

With recent advances in wireless communication and low cost, low power sensors are enabling the deployment of large-scale and collaborative wireless sensor network (WSN), which performs different tasks using the subsets formation of sensor on specific requirement of event monitoring. For implementing the differentiated monitoring task of the heterogeneous sensor network in the same geographical region, efficient classification of the various sensed data becomes a critical task due to stringent constraint on network resources, frequent link and indeterminate variations in sensor readings. In this paper, we present a virtual cluster tree based distributed data classification strategy using locally linear embedding (LLE). the strategy can realize the structure representation of original sensed data by LLE to meet the classification for forming the virtual cluster tree of the various monitoring task. the theoretical analysis and experimental results show that the proposed strategy can effectively reduce the energy consumption using LLE based classifier. © 2012 Springer-Verlag.

关键词： Wireless sensor networks

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Time-aware Data Spaces-A key computing Unit in the Edge-to-Cloud Continuum 8

Time-aware Data Spaces-A key Computing Unit in the Edge-to-C...

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8th international conference on Future Internet of things and Cloud, FiCloud 2021

作者： Zeiner, Herwig Unterberger, Roland DIGITAL-Institute for Information and Communication Technologies JOANNEUM RESEARCH Forschungsgesellschaft MbH Graz Austria

ISBN: (纸本)9781665425742

Digital transformation requires new views and strategies for edge computing for Industrial Internet of things applications. In this work, we elaborate the importance of time-aware data spaces as a conceptual entity for a digital and scaleable approach in a data-driven world. this work introduces these small data spaces deployed and distributed through edge analytic boxes. the concept time-aware data space is more suitable than single sensors for this type of application. It is particularly suitable in the edge-to-cloud continuum to build robust solutions and allow a new view on these types of applications. Moreover, we use this approach in a production environment. the requirements are a suitable application area for our time-aware data spaces. they can be used to monitor the environment, the machines or the production processes. Such an approach can also be integrated into other existing solutions with reasonable efforts. © 2021 ieee.

关键词： Digital transformation distributed databases systems engineering and theory Software Production facilities sensors Complexity theory

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Gas Recognition Under sensor Drift by Using Deep Learning 1

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8th international conference on Intelligent systems and Knowledge Engineering (ISKE)

作者： Hu, Xiaonan Liu, Qihe Cai, Hongbin Li, Fan Univ Elect Sci & Technol China Sch Comp Sci & Engn Digital Media Technol Key Lab Sichuan Prov Chengdu 611731 Peoples R China

ISBN: (数字)9783642549274

ISBN: (纸本)9783642549274;9783642549267

Machine olfaction is an intelligent system that combines cross-sensitivity chemical sensor array and an effective pattern recognition algorithm for the detection, identification, or quantification of various odors. Data collected by the sensor array are multivariate time-series signals with complex structure, and these signals become more difficult to analyze due to sensor drift. In this work, we focus on improving the classification performance under sensor drift by using the deep learning method, which is popular among these years. Compared with other methods, our method can effectively tackle sensor drift by automatically extracting features, thus not only removing the complexity of designing the hand-made features, but also making it pervasive for a variety of application in machine olfaction. Our experimental results show that the deep learning method can learn the features that are more robust to drift than the original input and achieves high classification accuracy.

关键词： sensor drift Deep learning Machine olfaction

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SpecTextor: End-to-End Attention-based Mechanism for Dense Text Generation in Sports Journalism 8

SpecTextor: End-to-End Attention-based Mechanism for Dense T...

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8th ieee international conference on Smart computing (SMARTCOMP)

作者： Ghosh, Indrajeet Ivler, Matthew Ramamurthy, Sreenivasan Ramasamy Roy, Nirmalya Univ Maryland Baltimore Cty Mobile Pervas & Sensor Comp Lab Baltimore MD 21228 USA Univ Maryland Baltimore Cty Ctr Real Time Distributed Sensing & Auton Cards Baltimore MD 21228 USA Univ Maryland Baltimore Cty Dept Informat Syst Baltimore MD 21228 USA Pomona Coll Dept Comp Sci Claremont CA 91711 USA

ISBN: (纸本)9781665481526

Language-guided smart systems can help to design next-generation human-machine interactive applications. the dense text description is one of the research areas where systems learn the semantic knowledge and visual features of each video frame and map them to describe the video's most relevant subjects and events. In this paper, we consider untrimmed sports videos as our case study. Generating dense descriptions in the sports domain to supplement journalistic works without relying on commentators and experts requires more investigation. Motivated by this, we propose an end-to-end automated text-generator, SpecTextor, that learns the semantic features from untrimmed videos of sports games and generates associated descriptive texts. the proposed approach considers the video as a sequence of frames and sequentially generates words. After splitting videos into frames, we use a pre-trained VGG-16 model for feature extraction and encoding the video frames. With these encoded frames, we posit a Long Short-Term Memory (LSTM) based attention-decoder pipeline that leverages soft-attention mechanism to map the semantic features with relevant textual descriptions to generate the explanation of the game. Because developing a comprehensive description of the game warrants training on a set of dense time-stamped captions, we leverage two available public datasets: ActivityNet Captions and Microsoft Video Description. In addition, we utilized two different decoding algorithms: beam search and greedy search and computed two evaluation metrics: BLEU and METEOR scores.

关键词： Sports Journalism Semantic Knowledge LSTM Soft-Attention Mechanism Beam Search Greedy Search Human-Machine Interactive Applications

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A dynamic and distributed addressing and routing protocol for wireless sensor networks

A dynamic and distributed addressing and routing protocol fo...

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8th Annual international conference on Mobile and Ubiquitous systems: computing, Networking and Services, MobiQuitous 2011

作者： Sánchez López, Tomás Huerta-Canepa, Gonzalo EADS UK Innovation Works Newport NP10 8FZ United Kingdom Korean Advanced Institute of Science and Technology Daejeon 305-701 Korea Republic of

ISBN: (纸本)9783642309724

Wireless sensor Networks (WSNs) have traditionally had static topologies that require little or no maintenance from their addressing mechanisms. New research directions have introduced additional scenarios where WSNs should adapt to the environment and network conditions. this shift in requirements also means that the addressing schemes should evolve dynamically, providing a distributed and lightweight way of assigning addresses to the sensor nodes. In addition, the routing protocols, which drive the information exchange within the network, must leverage the addressing properties in order to function efficiently. In this paper, we present Sequence Chain (SC) as a lightweight tree-based addressing mechanism for Wireless sensor Networks. SC offers distributed and dynamic address allocation together with optimized tree routing. We compare our work with the de-facto industry standard, ZigBee, and show how SC improves the formation of addressing trees and yields up to three and a half times shorter multi-hop routes. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

关键词： Routing protocols

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Data Fault Detection Using Multi-label Classification in sensor Network 1

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8th international conference on Intelligent systems and Knowledge Engineering (ISKE)

作者： Zhang, Zhenhai Li, Shining Li, Zhigang Northwestern Polytech Univ Sch Comp Sci Xian 710072 Peoples R China

ISBN: (数字)9783642549274

ISBN: (纸本)9783642549274;9783642549267

Detection of data fault is a hit point in sensor network in recent years and multiple data faults may occur at the same time. However the existing detection methods can only detect one type of data fault at the same time. To solve this problem, the detection of data fault is model as multi-label classification task, where an instance may belong to more than one label. We firstly break down the sensor data into instances using sliding window and then employ feature extraction methods to extract data features from instances. After this we associate each instance with corresponding data fault labels. A comparative experimental evaluation of five multi-label classification algorithms is conducted on aforementioned multi-label dataset using a variety of evaluation measures. Experimental results and their analysis show preliminarily that: (1) LP outperforms other classification algorithms on all evaluation measures since it takes the correlation of multiple data fault labels into account in detection of data fault;(2) outlier is the easiest data fault to detect and high noise is the hardest data fault to detect.

关键词： Algorithms Classification Fault detection sensor network Multi-label classification

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Concept of designing the wireless sensor networks based on ant intelligence

Concept of designing the wireless sensor networks based on a...

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ieee international Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications

作者： Vasyl Yatskiv Nataliya Yatskiv Anatoliy Sachenko Orest Volynskyy Ternopil National Economic University Ternopil Ukraine

Implementation of WSN based on the proposed concept will simplify the process of recovery and scaling of network and improve network survivability due to the backup of important segments of distributed processor.

关键词： Wireless sensor networks Particle swarm optimization Wireless communication Optimization Redundancy Heuristic algorithms Ant colony optimization

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Anonymity Networks and Access to Information During Conflicts: Towards a distributed Network Organisation 8

Anonymity Networks and Access to Information During Conflict...

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8th international conference on Cyber Conflict - Cyber Power (CyCon)

作者： Palmieri, Paolo Bournemouth Univ Dept Comp & Informat Poole BH12 5BB Dorset England

ISBN: (纸本)9781538623787;9781538623794

Access to information is crucial during conflicts and other critical events such as population uprisings. An increasing number of social interactions happen in the cyberspace, while information exchanges at the infrastructural level (monitoring systems, sensor networks, etc.) are now also based on Internet and wireless links rather than ad hoc, isolated wired networks. However, the nature of the Internet allows powerful hostile actors to block, censor, or redirect communication to and from specific Internet services, through a number of available techniques. Anonymity networks such as Tor provide a way to circumvent traditional strategies for restricting access to online resources, and make communication harder to trace and identify. Tor, in particular, has been successfully used in past crises to evade censorship and Internet blockades (Egypt in 2011, and Iran in 2012). Anonymity networks can provide essential communication tools during conflicts, allowing information exchanges to be concealed from external observers, anonymised, and made resilient to imposed traffic controls and geographical restrictions. However, the design of networks such as Tor makes them vulnerable to large-scale denial of service attacks, as shown by the DDoS targeted at Tor hidden services in March 2015. In this paper, we analyse the structural weaknesses of Tor with regard to denial of service attacks, and propose a number of modifications to the structure of the Tor network aimed at improving its resilience to a large coordinated offensive run by a hostile actor in a conflict scenario. In particular, we introduce novel mechanisms that allow relay information to be propagated in a distributed and peer-to-peer manner. this eliminates the need for directory services, and allows the deployment of Tor-like networks in hostile environments, where centralised control is impossible. the proposed improvements concern the network organisation, but preserve the underlying onion routing mechanism tha

关键词： Tor anonymous networks peer-to-peer denial of service DDoS

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A High-Speed sensor Resources Allocation Method for distributed WSN

A High-Speed Sensor Resources Allocation Method for Distribu...

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ieee international conference on Service-Oriented computing and Applications (SOCA)

作者： Takanobu Otsuka Takuma Inamoto Yoshitaka Torii Takayuki Ito Nagoya Institute of Technology Japan

As a promising application in WSN, there is an anomaly detection using the sensor information. In the anomaly detection, to the acquired sensor information based on the abnormality of the water quality in rivers, detects weather anomalies as familiar, it is to report to the user. Further, in the WSN, the problem sensor price and power consumption, it is difficult to provide all sensors required for anomaly detection in all nodes. therefore, it is required to share the expensive sensors in the network. We propose an autonomous distributed WSN systems sharing a limited sensor resources at high speed between the nodes, with improved anomaly detection rate by the node in the WSN.

关键词： Wireless sensor networks Spread spectrum communication Computers Tides Resource management Power demand Temperature sensors

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