Relevant bibliographies by topics / Data Node

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data Node'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Data Node"

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Roby, M. Fadhli, Aryuanto Soetedjo, and Irmalia Suryani Faradisa. "Pengembangan Sistem Monitoring Kualitas Air pada IPAL Tirtarona Tlogomas Kota Malang menggunakan IoT Berbasis LoRa." Prosiding SENIATI 6, no. 1 (2022): 33–41. http://dx.doi.org/10.36040/seniati.v6i1.4839.

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IPAL (Instalasi pembuangan air limbah) merupakan sebuah struktur bangunan, yang bertujuan untuk mengurangi sebuah pencemaran yang terkandung pada air limbah, peneliti sebelumnya merancang alat monitoring dengan beberapa sensor yaitu diantaranya sensor pH, DO, Turbidity dan DS18B20 terhadap webserver menggunakan modem GSM pada setiap alat yang terdiri dari 4 (empat) node ,hal ini membuat kurangnya efisiensi penggunaan konsumsi daya yang tinggi serta stabilitas pengiriman data, oleh sebab itu dilakukan pengembangan alat monitoring sebelumnya dengan pemanfaatan modul LoRa SX1278, sistem ini memil
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Kanwal, Samira, Zeshan Iqbal, Aun Irtaza, Muhammad Sajid, Sohaib Manzoor, and Nouman Ali. "Head Node Selection Algorithm in Cloud Computing Data Center." Mathematical Problems in Engineering 2021 (July 24, 2021): 1–12. http://dx.doi.org/10.1155/2021/3418483.

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Cloud computing provides multiple services such as computational services, data processing, and resource sharing through multiple nodes. These nodes collaborate for all prementioned services in the data center through the head/leader node. This head node is responsible for reliability, higher performance, latency, and deadlock handling and enables the user to access cost-effective computational services. However, the optimal head nodes’ selection is a challenging problem due to consideration of resources such as memory, CPU-MIPS, and bandwidth. The existing methods are monolithic, as they sele
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Ganesh, P., G. B. S. R. Naidu, Korla Swaroopa, et al. "Implementation of Hidden Node Detection Scheme for Self-Organization of Data Packet." Wireless Communications and Mobile Computing 2022 (March 26, 2022): 1–9. http://dx.doi.org/10.1155/2022/1332373.

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The mobile nodes are infrequent movement in nature; therefore, its packet transmission is also infrequent. Packet overload occurred for routing process, and data are lossed by receiver node, since hackers hide the normal routing node. Basically, the hidden node problem is created based on the malicious nodes that are planned to hide the vital relay node in the specific routing path. The packet transmission loss occurred for routing; so, it minimizes the packet delivery ratio and network lifetime. Then, proposed enhanced self-organization of data packet (EAOD) mechanism is planned to aggregate
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Ali Ahammed G.F, Reshman Banu, Masthan Ali A. H,. "Energy Aware Hierarchal Data Aggregation and Trust Based Data Integrity Verification for WSN." Psychology and Education Journal 58, no. 1 (2021): 5637–43. http://dx.doi.org/10.17762/pae.v58i1.2185.

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Currently the demand of wireless sensor networks has gained huge attraction due to its wide range of applications. Generally, these nodes are equipped with limited power resource and deployed in harsh environment where replacing these resources is a tedious task. Due to these issues, minimizing the energy consumption is a prime task to prolong the network lifetime. To overcome the challenging issue of data aggregation we introduced a novel combined mechanism which performs clustering and trust computing process to improve the data aggregation. According to this scheme, we arrange the nodes as
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Zhou, Xin Lian, and Jian Bo Xu. "The Research of Data Gathering Protocol for Mobile Sensor Networks." Advanced Materials Research 216 (March 2011): 621–24. http://dx.doi.org/10.4028/www.scientific.net/amr.216.621.

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This paper first proposed an energy-efficient distributed clustering technology for mobile sensor nodes and sink node mobility, select the higher residual energy and the nearest node from fixed nodes as cluster heads responsible for collecting sensed data, and all the fixed nodes form routing backbone to forward data, both can save energy and avoid cluster head away. Then, proposed a cross-layer scheduling mechanism to avoid the impact of mobile node and meet expectations cluster coverage. With energy-efficient clustering technology, efficient network topology control technology and mobile sin
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Reddi, Sivaranjani. "Privacy Preserving Data Mining Using Time Series Data Aggregation." International Journal of Strategic Information Technology and Applications 8, no. 4 (2017): 1–15. http://dx.doi.org/10.4018/ijsita.2017100101.

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This article proposes a mechanism to provide privacy to mined results by assuming that the data is distributed across many nodes. The first objective includes mining the query results by the node in a cluster, communicating it to the cluster head, aggregating the data collected from all the cluster nodes and then communicating it to the group controller. The second objective is to incorporate privacy at each level of the clusters node: cluster head and the group controller level. The final objective is to provide a dynamic network feature, where the nodes can join or leave the distributed netw
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R, Jayamma. "Improving The Performances of WSN Using Data Scheduler and Hierarchical Tree." Journal of Computational Science and Intelligent Technologies 2, no. 2 (2021): 7–16. http://dx.doi.org/10.53409/mnaa/jcsit/2202.

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Users of data-intensive implementation needs intelligent services and schedulers that will provide models and strategies to optimize their data transfer jobs. Normally sensor nodes are connected to consecutive sensor nodes depending on frequent transmission. To enhance end-to-end data flow parallelism for throughput optimization in high speed WSNs. The major objective is to maximize the WSNs throughput, minimizing the model overhead, avoiding disputation among users and using minimum number of end-system resources. Data packets are broadcasted from sender node to target node. Though, all nodes
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Sujatha, J., and K. Meena. "A vibrant data placement approach for map reduce in diverse environments." International Journal of Engineering & Technology 7, no. 2.4 (2018): 20. http://dx.doi.org/10.14419/ijet.v7i2.4.10034.

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Map reduce assumes that the computing capacity is same for each node in a cluster. Each node is assigned to the same load in homogeneous environment, hence it fully use the resources in the cluster. In such a cluster, there is likely to be various specifications of PCs or servers, which causes the abilities of the nodes to differ. If such a heterogeneous environment still uses the original Hadoop strategy that distributes data blocks into each node equally and the load is also evenly distributed to each node, then the overall performance of Hadoop may be reduced. The majorreasonis thatdifferent
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Meghanathan, Natarajan. "A Generic Algorithm to Determine Maximum Bottleneck Node Weight-based Data Gathering Trees for Wireless Sensor Networks." Network Protocols and Algorithms 7, no. 3 (2015): 18. http://dx.doi.org/10.5296/npa.v7i3.7961.

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We propose a generic algorithm to determine maximum bottleneck node weight-based data gathering (MaxBNW-DG) trees for wireless sensor networks (WSNs) and compare the performance of the MaxBNW-DG trees with those of maximum and minimum link weight-based data gathering trees (MaxLW-DG and MinLW-DG trees). Assuming each node in a WSN graph has a weight, the bottleneck weight for the path from a node u to the root node of the DG tree is the minimum of the node weights on the path (inclusive of the weights of the end nodes). The MaxBNW-DG tree algorithm determines a DG tree such that each node has
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Aikebaier, Ailixier, Tomoya Enokido, and Makoto Takizawa. "Design and Evaluation of Reliable Data Transmission Protocol in Wireless Sensor Networks." Mobile Information Systems 4, no. 3 (2008): 237–52. http://dx.doi.org/10.1155/2008/791720.

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A wireless sensor-actuator network (WSAN) is composed of sensor modes and actuator modes which are interconnected in wireless networks. A sensor node collects information on the physical world and sends a sensed value in a wireless network. Another sensor node forwards the sensed value to deliver to an actuator node. A sensor node can deliver messages with sensed values to only nearby nodes due to weak radio. Messages are forwarded by sensor nodes to an actuator node by a type of flooding protocol. A sensor mode senses an event and sends a message with the sensed value. In addition, on receipt
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Dissertations / Theses on the topic "Data Node"

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Norman, Zandra. "SGSN-MME Test Node Pool - Resources utilization for SGSN test nodes." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-143343.

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The SGSN-MME node, which is important in wireless networks, handles many users and therefore the uptime requirements for it are very high. The goal at Ericsson is to reach 99.9999% uptime for their SGSN-MME nodes and to reach this a lot of testing is required. Therefore the test process during the SGSN-MME development is both resource expensive and time consuming. To optimize both resource utilization and test runtimes a common test node pool solution for their different test tools has been proposed. During this thesis a first exploratory investigation about how to optimize such a solution was
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Sims, LT Todd E. "Wireless Sensor Node Data Gathering and Location Mapping." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/6869.

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With advances in wireless communications and miniaturization of mobile sensors, Wireless Sensor Nodes are increasingly being deployed in Ad Hoc fashions. Efficiently gathering data from the networks now becomes a larger problem. Collecting sensor data from a group of nodes deployed in an unknown arrangement in the shortest amount of time requires the collector to utilize a methodology that minimizes collection overlap. Inexpensive commercial off-the-shelf wireless routers and mobile platforms that can be utilized to fly over a field of wireless nodes and create a link connecting to and retriev
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Zimmermann, Hans-Martin. "Efficient data transport in cellular multi-hop networks." kostenfrei, 2009. http://mediatum2.ub.tum.de/node?id=668421.

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Al-Riyami, Ahmed. "Towards an adaptive solution to data privacy protection in hierarchical wireless sensor networks." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/towards-an-adaptive-solution-to-data-privacy-protection-in-hierarchical-wireless-sensor-networks(a096db2a-251c-4e9e-a4ff-8bfe4c6f1bf4).html.

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Hierarchical Wireless Sensor networks (WSNs) are becoming attractive to many applications due to their energy efficiency and scalability. However, if such networks are deployed in a privacy sensitive application context such as home utility consumption, protecting data privacy becomes an essential requirement. Our threat analysis in such networks has revealed that PPDA (Privacy Preserving Data Aggregation), NIDA (Node ID Anonymity) and ENCD (Early Node Compromise Detection) are three essential properties for protecting data privacy. The scope of this thesis is on protecting data privacy in hie
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Hadden, Ross A. "A WebSocket-based Approach to Transporting Web Application Data." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427813562.

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Xu, Huan. "Controlling false positive rate in network analysis of transcriptomic data." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin156267322069819.

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Kotari, Ravi Teja. "Node failure detection and data retrieval in wireless sensor networks." Thesis, California State University, Long Beach, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10108190.

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<p> This project presents a method for detecting node failure in a wireless sensor network. The defective node is identified using round-trip delay measurements. Data transfer from the transmitter section to the receiver section is accomplished via the ZigBee protocol. As soon as a node has been identified as defective, the node is removed from the sensor network. Information about the failed node is provided to users with registered mobile device through the Global System for Mobile (GSM) module. The proposed method has been successfully implemented and tested experimentally on a small sensor
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Dimaki, Georgia. "Dynamic node clustering in hierarchical optical data center network architectures." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/128973.

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Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, September, 2020<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 127-134).<br>During the past decade an increasing trend in the Data Center Network's traffic has been observed. This traffic is characterized mostly by many small bursty flows (mice) that last for less than few milliseconds as well as a few heavier more persistent (elephant) flows between certain number of nodes. As a result many relatively underutilized network links become momentaril
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Balasubramanian, Shyam Sundar. "Assessing the Vulnerability of DTN Data Relaying Schemes to Node Selfishness." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176381.

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The main principle behind the working of delay tolerant networks (DTN) is the mobility of the nodes along with their contact sequences for exchanging data. Nodes which are a part of the DTN network can behave selfishly due to network reservation policy, especially when constrained to energy or storage space. Several forwarding protocols exist for spreading data but our focus is on the performance of popular data relaying protocols namely epidemic routing and two hop routing protocol in a situation where nodes exhibit various degrees of selfishness. Results of an analytical model show the perfo
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Aasberg, Freddy. "HypervisorLang : Attack Simulations of the OpenStack Nova Compute Node." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-294139.

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Cloud services are growing in popularity and the global public cloud services are forecasted to increase by 17% in 2020[1]. The popularity of cloud services is due to the improved resource allocation for providers and simplicity of use for the customer. Due to the increasing popularity of cloud services and its increased use by companies, the security assessment of the services is strategically becoming more critical. Assessing the security of a cloud system can be problematic because of its complexity since the systems are composed of many different technologies. One way of simplifying the se
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Books on the topic "Data Node"

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Center, Langley Research, and United States. National Aeronautics and Space Administration., eds. Independent analysis of the space station node modal test data. National Aeronautics and Space Administration, Langley Research Center, 1997.

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Reed, Carl N. MOSS arc/node and DBMS design document: Final draft. Autometric, Inc., 1985.

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Institute, SAS, ed. SAS/CPE software for open systems: Getting started with HP OpenView network node manager data, IBM NetView for AIX data, and Cabletron systems SPECTRUM data. SAS Institute, 1996.

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Solutions, SAS Business, ed. SAS/CPE software for open systems: Getting started with HP OpenView network node manager data. SAS Business Solutions, 1996.

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K, Kokula Krishna Hari, ed. Secure Data Transmission through Trusted Node in Mantes using AODV Routing Algorithm: SATEM: ICCS 2014. Association of Scientists, Developers and Faculties, 2014.

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United States. National Aeronautics and Space Administration., ed. INDEPENDENT ANALYSIS OF THE SPACE STATION NODE MODEL TEST DATA... NASA/TM-97-206262... JAN. 26, 1998. s.n., 1999.

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Halton, Christopher H. An effectiveness study for prioritization algorithms in a communications node model for the Copernicus Tactical Data Information Exchange System (TADIXS). Naval Postgraduate School, 1997.

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French, Richard G. Submission of earth-based ring occultation observations to the NASA planetary data system rings discipline node: Technical report, period covered by report, 1 July 1992 - 30 June 1993. National Aeronautics and Space Administration, 1993.

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United States. National Aeronautics and Space Administration., ed. Submission of earth-based ring occultation observations to the NASA planetary data system rings discipline node: Technical report, period covered by report, 1 July 1992 - 30 June 1993. National Aeronautics and Space Administration, 1993.

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United States. National Aeronautics and Space Administration., ed. Submission of earth-based ring occultation observations to the NASA planetary data system rings discipline node: Technical report, period covered by report, 1 July 1992 - 30 June 1993. National Aeronautics and Space Administration, 1993.

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Book chapters on the topic "Data Node"

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Weik, Martin H. "data processing node." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_4342.

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Reardon, Joel. "Data Node Encrypted File System." In Secure Data Deletion. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28778-2_6.

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Skarmeta, Antonio, Dan Garcia Carrillo, and Alexis Olivereau. "End-Node Security." In Internet of Things Security and Data Protection. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04984-3_3.

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Bhagat, Smriti, Graham Cormode, and S. Muthukrishnan. "Node Classification in Social Networks." In Social Network Data Analytics. Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-8462-3_5.

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Lyu, Tianshu, Fei Sun, and Yan Zhang. "Node Conductance: A Scalable Node Centrality Measure on Big Networks." In Advances in Knowledge Discovery and Data Mining. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47436-2_40.

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Stokes, Alan B., Alvaro A. A. Fernandes, and Norman W. Paton. "Adapting to Node Failure in Sensor Network Query Processing." In Big Data. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39467-6_7.

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Singh, Harsh Pratap, Bhaskar Singh, and Rashmi Singh. "Different Techniques of Data Fusion in the Internet of Things (IoT)." In Intelligent Sensor Node-Based Systems. Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003372042-15.

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Zhao, Lu, Li Xiong, and Shan Xue. "Global Recursive Based Node Importance Evaluation." In Advanced Data Mining and Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49586-6_53.

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Wu, Yang, Ada Wai-Chee Fu, Cheng Long, and Zitong Chen. "LSimRank: Node Similarity in a Labeled Graph." In Web and Big Data. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60259-8_10.

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Wu, Jintao, and Youlong Yang. "Node Importance-Based Semi-supervised Nonnegative Matrix Factorization for Image Clustering." In Data Mining and Big Data. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0844-4_6.

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Conference papers on the topic "Data Node"

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Carpenter, Justin, Janet Layne, Edoardo Serra, and Alfredo Cuzzocrea. "Detecting Botnet Nodes via Structural Node Representation Learning." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671728.

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Cosar, Emre I., Maurizio Bocca, and Lasse M. Eriksson. "High Speed Portable Wireless Data Acquisition System for High Data Rate Applications." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86459.

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Communication between a sink node and a PC can constitute a bottleneck for high data rate applications of wireless sensor networks (WSNs) including, but not limited to, structural health monitoring, condition monitoring, wireless surveillance and patient health monitoring. In this paper, we evaluate four different data acquisition alternatives for data-intensive WSN applications. We will concentrate especially on optimizing UART (universal asynchronous receiver transmitter) communication in conjunction with WSN applications. Furthermore, we propose a new method for sink node to PC communicatio
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Serra, Edoardo, Mikel Joaristi, and Alfredo Cuzzocrea. "Large-scale Sparse Structural Node Representation." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9377854.

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Nguyen, Hoang H., Sergej Zerr, and Tuan-Anh Hoang. "On Node Embedding of Uncertain Networks." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378022.

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Rallapalli, Swati, Liang Ma, Mudhakar Srivatsa, et al. "SENSE: Semantically Enhanced Node Sequence Embedding." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006591.

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Lee, Kwangwon, Incheol Nam, Daesun Kim, et al. "Analysis of Write Recovery Time Degradation Caused by Adjacent Storage Node Data in DRAM." In ISTFA 2015. ASM International, 2015. http://dx.doi.org/10.31399/asm.cp.istfa2015p0234.

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Abstract As microelectronic feature sizes are scaled down, the characteristics and distribution of DRAM data retention time and write recovery time are getting worse. This degradation is due to the increases in the leakage current and resistance of the cell node and the decrease of cell capacitance in DRAM devices. As the physical distance between storage nodes decreases, node potential is increasingly affected by small potential changes in adjacent storage nodes. In this paper, we will show that the one of the most dominant contributors to failure is the adjacent storage node level, and we wi
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Jhin, Sheo Yon, Minju Jo, Taeyong Kong, Jinsung Jeon, and Noseong Park. "ACE-NODE." In KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2021. http://dx.doi.org/10.1145/3447548.3467419.

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Malita, Mihaela, and Gheorghe M. Stefan. "Map-scan node accelerator for big-data." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258342.

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Corizzo, Roberto, and Terry Slenn. "Distributed Node Classification with Graph Attention Networks." In 2022 IEEE International Conference on Big Data (Big Data). IEEE, 2022. http://dx.doi.org/10.1109/bigdata55660.2022.10020664.

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Sun, Jiarui, Mengting Gu, Chin-Chia Michael Yeh, Yujie Fan, Girish Chowdhary, and Wei Zhang. "Dynamic Graph Node Classification via Time Augmentation." In 2022 IEEE International Conference on Big Data (Big Data). IEEE, 2022. http://dx.doi.org/10.1109/bigdata55660.2022.10020941.

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Reports on the topic "Data Node"

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Hall, R. C. The Product Data Network and Distributed Data System: Node configuration. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/6024742.

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Steneker, M., and G. F. Bonham-Carter. Computer Program For Converting Arc - Node Vector Data To Raster Format. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1988. http://dx.doi.org/10.4095/130461.

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Kinser, Ryan, Mark Barkey, Timothy Rushing, et al. Computationally efficient modeling of lightweight expeditionary airfield surfacing systems at large length scales. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48266.

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Expeditionary airfield matting systems are lightweight, portable surfaces that enable the rapid deployment of infrastructure to support aircraft operations. Individual matting components are assembled via interlocking joints to construct arrays that serve as temporary aircraft operating surfaces. The paper outlines the homogenization of the AM2 portable airfield matting system and its interlocking mechanisms to permit computationally efficient analyses toward understanding mechanisms that influence the global behavior of these arrays and underlying subgrade during aircraft maneuvers. An equiva
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Tzonev. PR-396-143702-R01 Feasibility of a Petroleum Leak Detection Cable Utilizing Polymer Absorption Sensor. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010849.

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Several high-profile new pipeline projects in Canada and the USA have triggered investigation of auxiliary leak detection systems outside of the pipeline. Although external leak detection technologies have existed for decades, a comprehensive solution that is widely applicable for both new and existing pipeline deployment still does not exist. The goal of PRCI project PL-1H was to evaluate the feasibility of interconnecting multiple underground Polymer Absorption (PA) hydrocarbon sensor nodes through a single cable that provides both power and data communication inductively to each node. Insta
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Harr, C. M., J. W. Long, and T. M. Heer. Hardware Recommendations for Data Transfer Nodes. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1178387.

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Mayerhoffer, Daniel, Moritz Schulz, Simon Scheller, and Jan Schulz-Gebhard. Networks of Polarisation : A Generative Mechanism. Otto-Friedrich-Universität Bamberg, 2025. https://doi.org/10.20378/irb-108470.

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This paper presents a generative algorithm for simulating network polarisation based on attitudinal homophily, i.e., the tendency to connect to others with similar attitudes as oneself. To do so, it applies the notion of preferential attachment to node properties other than degree, aiding intuitive communication within and beyond the network science community. The algorithm works with one or more flexibly weighted attitude dimensions, heterogeneous populations. The generated networks commonly share features of real-world social networks such as (weak) small-worldiness. They can contribute to h
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Chepeliev, Maksym. GTAP-Power 10 Data Base: A Technical Note. GTAP Research Memoranda, 2019. http://dx.doi.org/10.21642/gtap.rm31.

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The purpose of this note is to document changes introduced to the GTAP-Power 10 database construction process in addition to the GTAP-Power build approach developed in Peters (2016). First, in Peters (2016) output of the electricity and heat generation sector in GTAP was split using electricity generation data only. We use heat generation volumes data to provide a more representative sectoral split and better concordance with GTAP definitions. Second, we consider data on country and year-specific shares of transformation and distribution costs in electricity tariff for 80 countries. Finally, f
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8

Fernandez, Jasmine, Michaela Bonnett, Teri Garstka, and Meaghan Kennedy. Exploring Social Care Network Structures. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/hdnz4028https://www.orangesparkleball.com/innovation-library-blog/2024/5/30/sunbelt2024-exploring-social-care-network-structures.

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This research is grounded in the theory that scale-free networks form between many organizations in a community when coordinating social care services and influential hubs in the network emerge (Barabási &amp; Réka, 1999).We explore the variability in the structures of social care networks, focusing on how the diverse needs of community members and the array of providers influence these structures. We posit that the architecture of these networks may hold the key to discerning patterns in community health and social outcomes. Our study examines the resilience of social care networks, defining
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9

Fernandez, Jasmine, Michaela Bonnett, Teri Garstka, and Meaghan Kennedy. Exploring Social Care Network Structures. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/hdnz4028.

Full text
Abstract:
This research is grounded in the theory that scale-free networks form between many organizations in a community when coordinating social care services and influential hubs in the network emerge (Barabási &amp; Réka, 1999).We explore the variability in the structures of social care networks, focusing on how the diverse needs of community members and the array of providers influence these structures. We posit that the architecture of these networks may hold the key to discerning patterns in community health and social outcomes. Our study examines the resilience of social care networks, defining
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10

Leathers, Emily, Clayton Thurmer, and Kendall Niles. Encryption for edge computing applications. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48596.

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As smart sensors and the Internet of Things (IoT) exponentially expand, there is an increased need for effective processing solutions for sensor node data located in the operational arena where it can be leveraged for immediate decision support. Current developments reveal that edge computing, where processing and storage are performed close to data generation locations, can meet this need (Ahmed and Ahmed 2016). Edge computing imparts greater flexibility than that experienced in cloud computing architectures (Khan et al. 2019). Despite these benefits, the literature highlights open security i
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