On the Efficiency of Querying and Storing RDF Documents

2011 ◽  
pp. 354-385
Author(s):  
Maria-Esther Vidal ◽  
Amadís Martínez ◽  
Edna Ruckhaus ◽  
Tomas Lampo ◽  
Javier Sierra
Keyword(s):  
Query Processing ◽  
Execution Time ◽  
Time Complexity ◽  
Low Cost ◽  
Data Access ◽  
Optimization Techniques ◽  
Experimental Results ◽  
Access Time ◽  
Alternative Representation ◽  
Rdf Data

In the context of the Semantic Web, different approaches have been defined to represent RDF documents, and the selected representation affects storage and time complexity of the RDF data recovery and query processing tasks. This chapter addresses the problem of efficiently querying and storing RDF documents, and presents an alternative representation of RDF data, Bhyper, which is based on hypergraphs. Additionally, access and optimization techniques to efficiently execute queries with low cost, are defined on top of this hypergraph based representation. The chapter’s authors have empirically studied the performance of the Bhyper based techniques, and their experimental results show that the proposed hypergraph based formalization reduces the RDF data access time as well as the space needed to store the Bhyper structures, while the query execution time of state-the-of-art RDF engines can be sped up by up to two orders of magnitude.

scholarly journals Automatic Synthesis of Smart Table Constraints by Abstraction of Table Constraints

2017 ◽  
Author(s):  
Baudouin Le Charlier ◽  
Minh Thanh Khong ◽  
Christophe Lecoutre ◽  
Yves Deville
Keyword(s):  
Simple Form ◽  
Execution Time ◽  
Time Complexity ◽  
State Of The Art ◽  
Experimental Results ◽  
Global Constraints ◽  
Automatic Synthesis ◽  
Compression Efficiency ◽  
Filtering Algorithms ◽  
Input Table

The smart table constraint represents a powerful modeling tool that has been recently introduced. This constraint allows the user to represent compactly a number of well-known (global) constraints and more generally any arbitrarily structured constraints, especially when disjunction is at stake. In many problems, some constraints are given under the basic and simple form of tables explicitly listing the allowed combinations of values. In this paper, we propose an algorithm to convert automatically any (ordinary) table into a compact smart table. Its theoretical time complexity is shown to be quadratic in the size of the input table. Experimental results demonstrate its compression efficiency on many constraint cases while showing its reasonable execution time. It is then shown that using filtering algorithms on the resulting smart table is more efficient than using state of the art filtering algorithms on the initial table.

scholarly journals Index and Materialized View Selection in Data Warehouses

2009 ◽  
pp. 693-700 ◽  
Author(s):  
Kamel Aouiche ◽  
Jérôme Darmont
Keyword(s):  
Response Time ◽  
Performance Optimization ◽  
Data Access ◽  
Original Data ◽  
Optimization Techniques ◽  
Access Time ◽  
Materialized Views ◽  
Storage Space ◽  
Data Warehouses ◽  
Query Response Time

Database management systems (DBMSs) require an administrator whose principal tasks are data management, both at the logical and physical levels, as well as performance optimization. With the wide development of databases and data warehouses, minimizing the administration function is crucial. This function includes the selection of suitable physical structures to improve system performance. View materialization and indexing are presumably some of the most effective optimization techniques adopted in relational implementations of data warehouses. Materialized views are physical structures that improve data access time by precomputing intermediary results. Therefore, end-user queries can be efficiently processed through data stored in views and do not need to access the original data. Indexes are also physical structures that allow direct data access. They avoid sequential scans and thereby reduce query response time. Nevertheless, these solutions require additional storage space and entail maintenance overhead. The issue is then to select an appropriate configuration of materialized views and indexes that minimizes both query response time and maintenance cost given a limited storage space. This problem is NP hard (Gupta & Mumick, 2005).

scholarly journals Spiking Neural Network-Based Near-Sensor Computing for Damage Detection in Structural Health Monitoring

2021 ◽  
Vol 13 (8) ◽  
pp. 219
Author(s):  
Francesco Barchi ◽  
Luca Zanatta ◽  
Emanuele Parisi ◽  
Alessio Burrello ◽  
Davide Brunelli ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Damage Detection ◽  
Execution Time ◽  
Sensor Node ◽  
Data Transfer ◽  
Low Cost ◽  
Access Time ◽  
Virtual Sensors ◽  
The Impact ◽  
Spi Interface

In this work, we present an innovative approach for damage detection of infrastructures on-edge devices, exploiting a brain-inspired algorithm. The proposed solution exploits recurrent spiking neural networks (LSNNs), which are emerging for their theoretical energy efficiency and compactness, to recognise damage conditions by processing data from low-cost accelerometers (MEMS) directly on the sensor node. We focus on designing an efficient coding of MEMS data to optimise SNN execution on a low-power microcontroller. We characterised and profiled LSNN performance and energy consumption on a hardware prototype sensor node equipped with an STM32 embedded microcontroller and a digital MEMS accelerometer. We used a hardware-in-the-loop environment with virtual sensors generating data on an SPI interface connected to the physical microcontroller to evaluate the system with a data stream from a real viaduct. We exploited this environment also to study the impact of different on-sensor encoding techniques, mimicking a bio-inspired sensor able to generate events instead of accelerations. Obtained results show that the proposed optimised embedded LSNN (eLSNN), when using a spike-based input encoding technique, achieves 54% lower execution time with respect to a naive LSNN algorithm implementation present in the state-of-the-art. The optimised eLSNN requires around 47 kCycles, which is comparable with the data transfer cost from the SPI interface. However, the spike-based encoding technique requires considerably larger input vectors to get the same classification accuracy, resulting in a longer pre-processing and sensor access time. Overall the event-based encoding techniques leads to a longer execution time (1.49×) but similar energy consumption. Moving this coding on the sensor can remove this limitation leading to an overall more energy-efficient monitoring system.

Investigation of Orientation Estimation of Multiple IMUs

2020 ◽  
pp. 1-9
Author(s):  
Simone A. Ludwig
Keyword(s):  
Execution Time ◽  
Parallel Implementation ◽  
Low Cost ◽  
Research Work ◽  
Ground Truth ◽  
Experimental Results ◽  
Euler Angles ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Measurement Units

Inertial Measurement Units (IMUs) were first applied to aircraft navigation and large devices in the 1930s. At that time their application was restricted because of constraints such as size, cost, and power consumption. In recent years, however, Micro-electromechanical (MEMS) IMUs were introduced with very favorable features such as low cost, compactness, and low processing power. One of the disadvantages of these low cost IMU sensors is that the accuracy is lower compared to high-end sensors. However, past experimental results have shown that redundant Magnetic and Inertial Measurement Units (MIMUs) improve navigation performance such as for unmanned air vehicles. Even though past simulation and experimental results demonstrated that redundant sensors improve the navigation performance, however, none of the current research work offers information as to how many sensors are required in order to meet a certain accuracy. This paper evaluates different numbers of sensor configurations of an MIMU sensor array using a simulation environment. Differently rotated MIMU sensors are incrementally added and the Madgwick filter is used to estimate the Euler angles of foot mounted MIMU data. The evaluation measure used is the root mean square error (RMSE) based on the Euler angles as compared to the ground truth. During the experiments it was noticed that the execution time with increasing number of sensors increases exponentially, and thus, the parallelization of the code was designed and implemented, and run on a multi-core machine. Thus, the speedup of the parallel implementation was evaluated. The findings using the parallel version with 16 sensors are that the execution time is less than twice the execution time of having only 1 sensor and 24 times less than using the sequential version with the added benefit of a 26% increase in accuracy.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

Control Cloud Data Access Privilge Anonymity with Attributed Based Encryption

2017 ◽  
Vol 7 (8) ◽  
pp. 279
Author(s):  
P. Sudheer ◽  
T. Lakshmi Surekha
Keyword(s):  
Data Privacy ◽  
Low Cost ◽  
Data Access ◽  
Privacy Concerns ◽  
Cloud Data ◽  
Computing Paradigm ◽  
Attribute Based Encryption ◽  
Data Content ◽  
Identity Privacy ◽  
Cloud Servers

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been to secure the cloud storage. Data content privacy. A semi anonymous privilege control scheme AnonyControl to address not only the data privacy. But also the user identity privacy. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semi anonymity. The  Anonymity –F which fully prevent the identity leakage and achieve the full anonymity.

scholarly journals Decreasing the Miss Rate and Eliminating the Performance Penalty of a Data Filter Cache

2021 ◽  
Vol 18 (3) ◽  
pp. 1-22
Author(s):  
Michael Stokes ◽  
David Whalley ◽  
Soner Onder
Keyword(s):  
Energy Efficient ◽  
Data Access ◽  
Performance Degradation ◽  
Access Time ◽  
Data Cache ◽  
Energy Usage ◽  
Single Cycle ◽  
Performance Penalty

While data filter caches (DFCs) have been shown to be effective at reducing data access energy, they have not been adopted in processors due to the associated performance penalty caused by high DFC miss rates. In this article, we present a design that both decreases the DFC miss rate and completely eliminates the DFC performance penalty even for a level-one data cache (L1 DC) with a single cycle access time. First, we show that a DFC that lazily fills each word in a DFC line from an L1 DC only when the word is referenced is more energy-efficient than eagerly filling the entire DFC line. For a 512B DFC, we are able to eliminate loads of words into the DFC that are never referenced before being evicted, which occurred for about 75% of the words in 32B lines. Second, we demonstrate that a lazily word filled DFC line can effectively share and pack data words from multiple L1 DC lines to lower the DFC miss rate. For a 512B DFC, we completely avoid accessing the L1 DC for loads about 23% of the time and avoid a fully associative L1 DC access for loads 50% of the time, where the DFC only requires about 2.5% of the size of the L1 DC. Finally, we present a method that completely eliminates the DFC performance penalty by speculatively performing DFC tag checks early and only accessing DFC data when a hit is guaranteed. For a 512B DFC, we improve data access energy usage for the DTLB and L1 DC by 33% with no performance degradation.

scholarly journals Lightweight Blockchain Processing. Case Study: Scanned Document Tracking on Tezos Blockchain

2021 ◽  
Vol 11 (15) ◽  
pp. 7169
Author(s):  
Mohamed Allouche ◽  
Tarek Frikha ◽  
Mihai Mitrea ◽  
Gérard Memmi ◽  
Faten Chaabane
Keyword(s):  
Load Balancing ◽  
Relative Error ◽  
Execution Time ◽  
General Purpose ◽  
Experimental Results ◽  
Raspberry Pi ◽  
Embedded Platform ◽  
Memory Resources ◽  
Processing Solution

To bridge the current gap between the Blockchain expectancies and their intensive computation constraints, the present paper advances a lightweight processing solution, based on a load-balancing architecture, compatible with the lightweight/embedding processing paradigms. In this way, the execution of complex operations is securely delegated to an off-chain general-purpose computing machine while the intimate Blockchain operations are kept on-chain. The illustrations correspond to an on-chain Tezos configuration and to a multiprocessor ARM embedded platform (integrated into a Raspberry Pi). The performances are assessed in terms of security, execution time, and CPU consumption when achieving a visual document fingerprint task. It is thus demonstrated that the advanced solution makes it possible for a computing intensive application to be deployed under severely constrained computation and memory resources, as set by a Raspberry Pi 3. The experimental results show that up to nine Tezos nodes can be deployed on a single Raspberry Pi 3 and that the limitation is not derived from the memory but from the computation resources. The execution time with a limited number of fingerprints is 40% higher than using a classical PC solution (value computed with 95% relative error lower than 5%).

A Low-Cost Hexa Platform for Efficient Force Control Systems Using Industrial Manipulators

2009 ◽  
Vol 147-149 ◽  
pp. 1-6 ◽  
Author(s):  
Rafal Osypiuk ◽  
Torsten Kröger
Keyword(s):  
Control Systems ◽  
Force Control ◽  
Execution Time ◽  
Low Cost ◽  
Degree Of Freedom ◽  
Industrial Manipulators ◽  
Control Concept ◽  
Six Dof ◽  
Parallel Platform ◽  
Six Degree Of Freedom

This contribution presents a new force control concept for industrial six-degree of freedom (DOF) manipulators, which uses a Hexa platform that provides an active environmental stiffness for all six DOFs. The paper focuses on the Hexa platform and is split into two essential parts: (i) parallel platform construction, and (ii) application of force control with industrial manipulators using a six-DOF environmental stiffness. This mechatronic solution almost gives one hundred percent robustness for stiffness changes in the environment, what guaranties a significant shortening of execution time.

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