Adaptive Buffer Tuning for Data Intensive Algebraic Operations

2010 ◽  
pp. 149-155
Keyword(s):  
Data Intensive ◽  
Buffer Tuning ◽  
Algebraic Operations

CSO Modelling Considering Moving Storms and Tipping Bucket Gauge Failures

2007 ◽  
Vol 2 (1) ◽  
Author(s):  
M. Hochedlinger ◽  
W. Sprung ◽  
H. Kainz ◽  
K. König
Keyword(s):  
Hydrological Models ◽  
Rain Intensity ◽  
Hydrodynamic Models ◽  
Data Intensive ◽  
Storm Flow ◽  
Cell Velocity ◽  
Combined Sewer ◽  
Moving Direction ◽  
The Difference

The simulation of combined sewer overflow volumes and loads is important for the assessment of the overflow and overflow load to the receiving water to predict the hydraulic or the pollution impact. Hydrodynamic models are very data-intensive and time-consuming for long-term quality modelling. Hence, for long-term modelling, hydrological models are used to predict the storm flow in a fast way. However, in most cases, a constant rain intensity is used as load for the simulation, but in practice even for small catchments rain occurs in rain cells, which are not constant over the whole catchment area. This paper presents the results of quality modelling considering moving storms depending on the rain cell velocity and its moving direction. Additionally, tipping bucket gauge failures and different corrections are also taken into account. The results evidence the importance of these considerations for precipitation due the effects on overflow load and show the difference up to 28% of corrected and uncorrected data and of moving rain cells instead of constant raining intensities.

Enhancing the use of Object Based Contents Addressable Storage

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Simab Hasan Rizvi
Keyword(s):  
File System ◽  
Application Performance ◽  
Shared Storage ◽  
Data Intensive ◽  
Network Bandwidth ◽  
Storage Performance ◽  
Efficient Management ◽  
Object Based ◽  
Data Volume ◽  
Potential Benefits

In Today's age of Tetra Scale computing, the application has become more data intensive than ever. The increased data volume from applications, in now tackling larger and larger problems, and has fuelled the need for efficient management of this data. In this paper, a technique called Content Addressable Storage or CAS, for managing large volume of data is evaluated. This evaluation focuses on the benefits and demerits of using CAS it focuses, i) improved application performance via lockless and lightweight synchronization ofaccess to shared storage data, ii) improved cache performance, iii) increase in storage capacity and, iv) increase network bandwidth. The presented design of a CAS-Based file store significantly improves the storage performance that provides lightweight lock less user defined consistency semantics. As a result, this file system shows a 28% increase in read bandwidth and 13% increase in write bandwidth, over a popular file system in common use. In this paper the potential benefits of using CAS for a virtual machine are estimated. The study also explains mobility application for active use and public deployment.

scholarly journals Bloom Filter-Based Parallel Architecture for Accelerating Equi-Join Operation on FPGA

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1778
Author(s):  
Binhao He ◽  
Meiting Xue ◽  
Shubiao Liu ◽  
Wei Luo
Keyword(s):  
Relational Databases ◽  
Parallel Architecture ◽  
Operation Time ◽  
Bloom Filter ◽  
Search Tree ◽  
Binary Search Tree ◽  
Maximum Acceleration ◽  
Data Intensive ◽  
Match Rate ◽  
Field Programmable

As one of the most important operations in relational databases, the join is data-intensive and time-consuming. Thus, offloading this operation using field-programmable gate arrays (FPGAs) has attracted much interest and has been broadly researched in recent years. However, the available SRAM-based join architectures are often resource-intensive, power-consuming, or low-throughput. Besides, a lower match rate does not lead to a shorter operation time. To address these issues, a Bloom filter (BF)-based parallel join architecture is presented in this paper. This architecture first leverages the BF to discard the tuples that are not in the join result and classifies the remaining tuples into different channels. Second, a binary search tree is used to reduce the number of comparisons. The proposed method was implemented on a Xilinx FPGA, and the experimental results show that under a match rate of 50%, our architecture achieved a high join throughput of 145.8 million tuples per second and a maximum acceleration factor of 2.3 compared to the existing SRAM-based join architectures.

Closed Sets of Boolean Terms in Relational Databases

1991 ◽  
Vol 14 (3) ◽  
pp. 367-385
Author(s):  
Andrzej Jankowski ◽  
Zbigniew Michalewicz
Keyword(s):  
Computational Complexity ◽  
Incomplete Information ◽  
Relational Databases ◽  
The Other ◽  
New Approach ◽  
Closed Sets ◽  
Null Value ◽  
Algebraic Operations

A number of approaches have been taken to represent compound, structured values in relational databases. We review a few such approaches and discuss a new approach, in which every set is represented as a Boolean term. We show that this approach generalizes the other approaches, leading to more flexible representation. Boolean term representation seems to be appropriate in handling incomplete information: this approach generalizes some other approaches (e.g. null value mark, null variables, etc). We consider definitions of algebraic operations on such sets, like join, union, selection, etc. Moreover, we introduce a measure of computational complexity of these operations.

scholarly journals A State-of-the-Art Analysis of Obstacle Avoidance Methods from the Perspective of an Agricultural Sprayer UAV’s Operation Scenario

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1069
Author(s):  
Shibbir Ahmed ◽  
Baijing Qiu ◽  
Fiaz Ahmad ◽  
Chun-Wei Kong ◽  
Huang Xin
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
State Of The Art ◽  
Obstacle Detection ◽  
Crop Monitoring ◽  
Data Intensive ◽  
Structural Details ◽  
Dynamic Operating ◽  
New Generation ◽  
The Internet Of Things

Over the last decade, Unmanned Aerial Vehicles (UAVs), also known as drones, have been broadly utilized in various agricultural fields, such as crop management, crop monitoring, seed sowing, and pesticide spraying. Nonetheless, autonomy is still a crucial limitation faced by the Internet of Things (IoT) UAV systems, especially when used as sprayer UAVs, where data needs to be captured and preprocessed for robust real-time obstacle detection and collision avoidance. Moreover, because of the objective and operational difference between general UAVs and sprayer UAVs, not every obstacle detection and collision avoidance method will be sufficient for sprayer UAVs. In this regard, this article seeks to review the most relevant developments on all correlated branches of the obstacle avoidance scenarios for agricultural sprayer UAVs, including a UAV sprayer’s structural details. Furthermore, the most relevant open challenges for current UAV sprayer solutions are enumerated, thus paving the way for future researchers to define a roadmap for devising new-generation, affordable autonomous sprayer UAV solutions. Agricultural UAV sprayers require data-intensive algorithms for the processing of the images acquired, and expertise in the field of autonomous flight is usually needed. The present study concludes that UAV sprayers are still facing obstacle detection challenges due to their dynamic operating and loading conditions.

scholarly journals Data diaries: A situated approach to the study of data

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172199603
Author(s):  
Nathaniel Tkacz ◽  
Mário Henrique da Mata Martins ◽  
João Porto de Albuquerque ◽  
Flávio Horita ◽  
Giovanni Dolif Neto
Keyword(s):  
Natural Hazards ◽  
Empirical Analysis ◽  
Ways Of Knowing ◽  
Data Intensive ◽  
Related Data ◽  
Data Practices ◽  
National Centre ◽  
The Creation ◽  
Situated Approach

This article adapts the ethnographic medium of the diary to develop a method for studying data and related data practices. The article focuses on the creation of one data diary, developed iteratively over three years in the context of a national centre for monitoring disasters and natural hazards in Brazil (Cemaden). We describe four points of focus involved in the creation of a data diary – spaces, interfaces, types and situations – before reflecting on the value of this method. We suggest data diaries (1) are able to capture the informal dimension of data-intensive organisations; (2) enable empirical analysis of the specific ways that data intervene in the unfolding of situations; and (3) as a document, data diaries can foster interdisciplinary and inter-expert dialogue by bridging different ways of knowing data.

Sign in / Sign up

Export Citation Format

Share Document