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A performance comparison of energy conservation between idle mode and power down mode for microcontroller in wireless mobile node

A performance comparison of energy conservation between idle...

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7th Annual International Conference on Electrical Engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON 2010

作者： Krongtripop, T. Department of Computer Engineering Faculty of Engineering and Architecture Rajamangala University of Technology Isan Nakhonratchasima Muang Nakhonratchasima 30000 Thailand

ISBN: (纸本)9789746724913

In the regular of wireless network, conserving energy is important to extending the lifetime of mobile nodes and network. The goal of this paper is investigated the comparison of energy conservation between idle mode and power down mode based on the microcontroller. The LWM-433H wireless module is applied with the microcontroller. The operation of idle mode and power down mode are controlling the energy supply while the data transmission only. Based on experiment, the data transmission of wireless node is every 5 minutes, 15 minutes and 30 minutes at the transmission range is 65 meters. The time of each transmission successfully at 0.33 seconds that the frame size is 10 bytes, the battery is 12V2.6Ah. The result shows that the energy conservation of microcontroller in power down mode is more than idle mode by up to 14.59 percents, 14.64 percents and 14.65 percents, respectively. In addition, the battery lifetime in mobile node is 89.55 hours, 89.62 hours and 89.64 hours. The result can be explained, the power down mode that is stop the operation of an oscillator circuit while the idle mode closes the internal clock signal only. The result may be applied for some mobile application and support working with lifetime such as wireless mobile node, etc.

关键词： Energy conservation

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SSA, SVD, QR-cp, and RBF model reduction

引用

2002 International Conference on Artificial Neural Networks, ICANN 2002

作者： Salmerón, Moisés Ortega, Julio García Puntonet, Carlos Prieto, Alberto Rojas, Ignacio Department of Computer Architecture and Computer Technology University of Granada E.T.S. Ingeniería Informática Campus Aynadamar s/n E-18071 Granada Spain

ISBN: (纸本)9783540440741

We propose an application of SVD model reduction to the class of RBF neural models for improving performance in contexts such as on-line prediction of time series. The SVD is coupled with QR-cp factorization. It has been found that such a coupling leads to more precise extraction of the relevant information, even when using it in an heuristic way. Singular Spectrum Analysis (SSA) and its relation to our method is also mentioned. We analize performance of the proposed on-line algorithm using a 'benchmark' chaotic time series and a difficult-to-predict, dynamically changing series. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Time series

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HDCat: Effectively identifying hot data in large-Scale I/O streams with enhanced temporal locality 15th

HDCat: Effectively identifying hot data in large-Scale I/O s...

引用

15th International Conference on Algorithms and architectures for Parallel Processing, ICA3PP 2015

作者： Chen, Jiahao Deng, Yuhui Huang, Zhan Department of Computer Science Jinan University Guangzhou510632 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783319271217

Hot data is very important for optimizing modern computer systems. For example, the identified hot data can be employed to extend the lifespan of flash memory. However, it is very challenging to effectively identify hot data with low memory consumption and low runtime overhead. This paper proposes a Hot Data Catcher (HDCat) which can effectively identify hot data in large-scale I/O streams by leveraging enhanced temporal locality. HDCat only maintains a hot data queue and a candidate hot data queue to record the data access pattern by tracking limited data set, thus effectively reducing the memory consumption. Furthermore, HDCat adopts a D-bit counter and a recency-bit to leverage both the frequency and recency contained in the data stream. Additionally, HDCat can significantly reduce the conversion between hot data and cold data. Real traces are used to evaluate the proposed approach. Experimental results demonstrate that HDCat significantly outperforms the state-of-the-art Multi-hash algorithm and the two-level LRU algorithm. © Springer International Publishing Switzerland 2015.

关键词： Hash functions

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New architectures for modulo 2N - 1 Adders

New architectures for modulo 2N - 1 Adders

引用

12th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2005

作者： Dimitrakopoulos, G. Nikolos, D.G. Vergos, H.T. Nikolos, D. Efstathiou, C. Technology and Computer Architecture Lab Computer Engineering and Informatics Dept. University of Patras 26500 Patras Greece Informatics Department ATEI of Athens 12210 Egaleo Athens Greece

ISBN: (纸本)9789972611001

Two architectures for parallel-prefix modulo 2n - 1 adders are presented in this paper. For large wordlengths we introduce the sparse modulo 2n - 1 adders that achieve significant reduction of the wiring complexity without imposing any delay penalty. Then, the Ling-carry formulation of modulo 2n - 1 addition is presented. Ling modulo adders save one logic level of implementation and provide high-speed solutions for smaller adder widths, where wiring complexity is small. The performance of the proposed adders has been validated with static CMOS implementations. In all examined cases, the proposed designs achieve significant savings in both area and delay compared to previously published architectures.

关键词： Adders

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Designing a power-aware replication strategy for storage clusters

Designing a power-aware replication strategy for storage clu...

引用

2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013

作者： Zhang, Lingwei Deng, Yuhui Department of Computer Science Jinan University Guangzhou 510632 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769550466

The exponential data growth is presenting challenges to traditional storage systems. Component-based cluster storage systems, due to their high scalability, are becoming the architecture of next generation storage systems. Cluster storage systems often use data replication to ensure high availability, fault tolerance, and load balance. However, this kind of data replication not only consumes a large amount of storage resources, but also generates more energy consumption. This paper presents a power-aware data replication strategy by leveraging data access behavior. This strategy uses 80/20 rule (80% of the data accesses often go to 20% of the storage space) to replicate only a small amount of frequently accessed data. Furthermore, the storage nodes are divided into a hot node set and a cold node set. Hot nodes, which store a small amount of hot data copies, are always in an active state to guarantee the QoS of the system. The cold nodes which store a large number of infrequently accessed cold data, are placed in a low power state, thus reducing the energy consumption of the cluster storage system. The experimental results show that the proposed strategy can effectively reduce the resource and energy consumption of the system, while ensuring the system performance. © 2013 IEEE.

关键词： Energy utilization

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MV-Sketch: A Fast and Compact Invertible Sketch for Heavy Flow Detection in Network Data Streams

MV-Sketch: A Fast and Compact Invertible Sketch for Heavy Fl...

引用

2019 IEEE Conference on computer Communications, INFOCOM 2019

作者： Tang, Lu Huang, Qun Lee, Patrick P. C. Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong State Key Lab of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781728105154

Fast detection of heavy flows (e.g., heavy hitters and heavy changers) in massive network traffic is challenging due to the stringent requirements of fast packet processing and limited resource availability. Invertible sketches are summary data structures that can recover heavy flows with small memory footprints and bounded errors, yet existing invertible sketches incur high memory access overhead that leads to performance degradation. We present MV-Sketch, a fast and compact invertible sketch that supports heavy flow detection with small and static memory allocation. MV-Sketch tracks candidate heavy flows inside the sketch data structure via the idea of majority voting, such that it incurs small memory access overhead in both update and query operations, while achieving high detection accuracy. We present theoretical analysis on the memory usage, performance, and accuracy of MV-Sketch. Trace-driven evaluation shows that MV-Sketch achieves higher accuracy than existing invertible sketches, with up to 3.38 × throughput gain. We also show how to boost the performance of MV-Sketch with SIMD instructions. © 2019 IEEE.

关键词： Data structures

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Exploring the Use of WebAssembly in HPC 23

Exploring the Use of WebAssembly in HPC

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28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, PPoPP 2023

作者： Chadha, Mohak Krueger, Nils John, Jophin Jindal, Anshul Gerndt, Michael Benedict, Shajulin Computer Architecture and Parallel Systems Technische Universität München Germany Department of Computer Science and Engg. Indian and Institute of Information Technology Kottayam Kerala India

ISBN: (纸本)9798400700156

Containerization approaches based on namespaces offered by the Linux kernel have seen an increasing popularity in the HPC community both as a means to isolate applications and as a format to package and distribute them. However, their adoption and usage in HPC systems faces several challenges. These include difficulties in unprivileged running and building of scientific application container images directly on HPC resources, increasing heterogeneity of HPC architectures, and access to specialized networking libraries available only on HPC systems. These challenges of container-based HPC application development closely align with the several advantages that a new universal intermediate binary format called WebAssembly (Wasm) has to offer. These include a lightweight userspace isolation mechanism and portability across operating systems and processor architectures. In this paper, we explore the usage of Wasm as a distribution format for MPI-based HPC applications. To this end, we present MPIWasm, a novel Wasm embedder for MPI-based HPC applications that enables high-performance execution of Wasm code, has low-overhead for MPI calls, and supports high-performance networking interconnects present on HPC systems. We evaluate the performance and overhead of MPIWasm on a production HPC system and AWS Graviton2 nodes using standardized HPC benchmarks. Results from our experiments demonstrate that MPIWasm delivers competitive native application performance across all scenarios. Moreover, we observe that Wasm binaries are 139.5x smaller on average as compared to the statically-linked binaries for the different standardized benchmarks. © 2023 ACM.

关键词： Containers

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A Comparative Study on Deep Learning Models for Stock Price Prediction 5

A Comparative Study on Deep Learning Models for Stock Price ...

引用

5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： He, Zhexin Zhang, Huan Por, Lip Yee Chongqing College of Architecture and Technology Chongqing401331 China Chongqing Academy of Science and Technology Chongqing401123 China Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9781643685243

With the advancement of deep learning technology, researchers have begun employing deep neural network models such as LSTM, MLP, CNN, and GRU to tackle nonlinear prediction problems in stock markets. This study harnesses these deep learning models, including LSTM, MLP, CNN, and GRU, to investigate the nonlinear forecasting of stock market price indices. The experiment selects globally representative stock indices and, through analyzing short-term, mid-term, and long-term data, discovers that the GRU model demonstrates exceptional performance in both prediction accuracy and generalization capabilities. To further enhance precision, the research constructs a filtering ensemble decision-making system based on multiple GRU models. This strategy reduces the error by at least 0.3% in medium to long-term predictions, significantly outperforming a single standalone GRU model. Consequently, the GRU-filtered ensemble decision model has been empirically proven as an effective tool for predicting stock indices, not only broadening the methods available for stock market prediction but also deepening the understanding and application of the generalization abilities of deep learning models within financial markets. © 2024 The Authors.

关键词： Long short-term memory

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Creation of a database including a set of biological features related to protein sequences and their corresponding alignment

Creation of a database including a set of biological feature...

引用

27th IEEE International Symposium on computer-Based Medical Systems, CBMS 2014

作者： Ortuño, F. Pomares, H. Rojas, I. Valenzuela, O. Department of Computer Architecture and Technology University of Granada 18071-Granade Spain Department of Applied Mathematics University of Granada 18071-Granade Spain

ISBN: (纸本)9781479944354

There are currently several biological databases related to proteins depending on the information we are interested to extract. Therefore, since a heterogeneous set of features will be needed (domains, structures, ontology terms, etc), several quite different databases should be consulted. The handling of different databases can become difficult, as each database could provide a different nomenclature for the same proteins. Anyway, these databases usually provides some mapping tools in order to determine the correspondence among the different nomenclatures used for the same protein. The main goal of this paper is to provide a biological database including a huge amount of protein information in order to be used for different purposes in bioinformatics. This database will be designed as a flexible and extensible tool and it could be extended and updated when new proteins are annotated or the included ones are modified. © 2014 IEEE.

关键词： Database systems

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Graph Data Management 1

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丛书名： Data-Centric Systems and Applications

1000年

作者： George Fletcher Jan Hidders Josep Lluís Larriba-Pey

ISBN: (数字)9783319961934

ISBN: (纸本)9783319961927;9783030071516

This book presents a comprehensive overview of fundamental issues and recent advances in graph data management. Its aim is to provide beginning researchers in the area of graph data management, or in fields that require graph data management, an overview of the latest developments in this area, both in applied and in fundamental subdomains.;The topics covered range from a general introduction to graph data management, to more specialized topics like graph visualization, flexible queries of graph data, parallel processing, and benchmarking. The book will help researchers put their work in perspective and show them which types of tools, techniques and technologies are available, which ones could best suit their needs, and where there are still open issues and future research directions.;The chapters are contributed by leading experts in the relevant areas, presenting a coherent overview of the state of the art in the field. Readers should have a basic knowledge of data management techniques as they are taught in computer science MSc programs.

关键词： Database Management Math Applications in computer Science System Performance and Evaluation Models and Principles

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