Resolving the intractability of the 'warehouseman's problem' using temporary storage space and other constraints

2002 ◽  
Author(s):  
R. Sharma ◽  
J. Aloimonos
Keyword(s):  
Storage Space ◽  
Temporary Storage

scholarly journals A Novel Massive Deployment Solution Based on the Peer-to-Peer Protocol

2019 ◽  
Vol 9 (2) ◽  
pp. 296 ◽  
Author(s):  
Steven J. H. Shiau ◽  
Yu-Chiang Huang ◽  
Ching-Hsuan Yen ◽  
Yu-Chin Tsai ◽  
Chen-Kai Sun ◽  
...  
Keyword(s):  
File System ◽  
File Systems ◽  
Peer To Peer ◽  
Superior Performance ◽  
The Novel ◽  
Storage Space ◽  
Improve Performance ◽  
Temporary Storage ◽  
P2p File Sharing ◽  
System Versus

: The BitTorrent (BT) is a peer-to-peer (P2P) file sharing protocol that was developed approximately 20 years ago, is becoming increasingly popular, and has been widely accepted. The BT-based mass deployment system can be used to improve performance and scalability that cannot be achieved by the unicasting, broadcasting, and multicasting protocols. However, when the BT-based system is applied in massive deployments, a major issue related to insufficient temporary storage space to store the whole system image before deploying needs to be resolved. Such problems arose because the system is deployed to the disk space, meaning that it cannot be used for temporary storage. Therefore, a novel BT-based solution that can remove the limitations caused by the insufficient temporary storage issue is proposed. The BT-based mass deployment system was designed by using the file system blocks transferring (FSBT) mechanism. The receiver of the FSBT mechanism can obtain the blocks of the file system from other peers. Then, those blocks will be written directly to raw disks or partitions. The sender of the FSBT mechanism can read the blocks of file systems directly from raw disks or partitions. Then, the blocks can be sent to other peers. This approach solves the insufficient temporary storage issue. The novel BT-based mass deployment system was tested and verified for the configuration consisting of at most 32 personal computers (PCs). To demonstrate the achievable performance of the novel BT-based system, comparisons were made between the novel program and the traditional multicast solutions, as well as other solutions for mass deployment. The proposed BT solution can be much faster than the multicast solution when deploying 11 machines or more. The experimental results demonstrated the feasibility and superior performance of the proposed system. Furthermore, performance comparisons of the proposed BT-based mass deployment system versus other solutions demonstrated the feasibility and efficiency of the proposed solution. In the future, the BT parameters can be further optimized, and the simultaneous read and write features can be implemented to improve the deployment performance. In addition, the BT-based mass deployment system can serve as the basis for the development of other mass deployment systems.

Indirect measurements in micro-space with the EM

1995 ◽  
Vol 53 ◽  
pp. 598-599
Author(s):  
Sterling P. Newberry
Keyword(s):  
Electron Microscope ◽  
Standard Model ◽  
Particle Physics ◽  
Information Storage ◽  
Storage Space ◽  
Indirect Measurements ◽  
Storage And Retrieval ◽  
Adequate Information ◽  
Compelling Reason ◽  
The Standard Model

At the 1958 meeting of our society, then known as EMSA, the author introduced the concept of microspace and suggested its use to provide adequate information storage space and the use of electron microscope techniques to provide storage and retrieval access. At this current meeting of MSA, he wishes to suggest an additional use of the power of the electron microscope.The author has been contemplating this new use for some time and would have suggested it in the EMSA fiftieth year commemorative volume, but for page limitations. There is compelling reason to put forth this suggestion today because problems have arisen in the “Standard Model” of particle physics and funds are being greatly reduced just as we need higher energy machines to resolve these problems. Therefore, any techniques which complement or augment what we can accomplish during this austerity period with the machines at hand is worth exploring.

PERANCANGAN DAN IMPLEMENTASI ALGORITMA ELIAS GAMMA CODE UNTUK MENGKOMPRESI RECORD DATABASE PADA APLIKASI RANGKUMAN PENGETAHUAN UMUM LENGKAP

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Hikka Sartika ◽  
Taronisokhi Zebua
Keyword(s):  
Compression Ratio ◽  
General Public ◽  
Storage Capacity ◽  
Storage Space ◽  
File Size ◽  
Compression Technique ◽  
Code Algorithm ◽  
Database File ◽  
Large File

Storage space required by an application is one of the problems on smartphones. This problem can result in a waste of storage space because not all smartphones have a very large storage capacity. One application that has a large file size is the RPUL application and this application is widely accessed by students and the general public. Large file size is what often causes this application can not run effectively on smartphones. One solution that can be used to solve this problem is to compress the application file, so that the size of the storage space needed in the smartphone is much smaller. This study describes how the application of the elias gamma code algorithm as one of the compression technique algorithms to compress the RPUL application database file. This is done so that the RPUL application can run effectively on a smartphone after it is installed. Based on trials conducted on 64 bit of text as samples in this research it was found that compression based on the elias gamma code algorithm is able to compress text from a database file with a ratio of compression is 2 bits, compression ratio is 50% with a redundancy is 50%. Keywords: Compression, RPUL, Smartphone, Elias Gamma Code

IMPLEMENTASI ALGORITMA LEVENSTEIN DALAM MENGKOMPRESI TEKS PADA APLIKASI RANGKUMAN PENGETAHUAN ALAM LENGKAP

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Winda Winda ◽  
Taronisokhi Zebua
Keyword(s):  
Compression Ratio ◽  
Mobile Application ◽  
Storage Space ◽  
Compression Technique ◽  
The Public ◽  
Natural Knowledge ◽  
Database Size ◽  
Text Database

The size of the data that is owned by an application today is very influential on the amount of space in the memory needed one of which is a mobile-based application. One mobile application that is widely used by students and the public at this time is the Complete Natural Knowledge Summary (Rangkuman Pengetahuan Alam Lengkap or RPAL) application. The RPAL application requires a large amount of material storage space in the mobile memory after it has been installed, so it can cause this application to be ineffective (slow). Compression of data can be used as a solution to reduce the size of the data so as to minimize the need for space in memory. The levestein algorithm is a compression technique algorithm that can be used to compress material stored in the RPAL application database, so that the database size is small. This study describes how to compress the RPAL application database records, so as to minimize the space needed on memory. Based on tests conducted on 128 characters of data (200 bits), the compression results obtained of 136 bits (17 characters) with a compression ratio is 68% and redundancy is 32%.Keywords: compression, levestein, aplication, RPAL, text, database, mobile

Design and Implementation of Low Energy Wireless Network Nodes based on Hardware Compression Acceleration

2019 ◽  
Vol 12 ◽  
Author(s):  
Hui Yang ◽  
Anand Nayyar
Keyword(s):  
Energy Consumption ◽  
Data Compression ◽  
Energy Saving ◽  
Optimization Design ◽  
Hardware Acceleration ◽  
Transmission Efficiency ◽  
General Purpose ◽  
Storage Space ◽  
General Purpose Processor ◽  
Compression Time

: In the fast development of information, the information data is increasing in geometric multiples, and the speed of information transmission and storage space are required to be higher. In order to reduce the use of storage space and further improve the transmission efficiency of data, data need to be compressed. processing. In the process of data compression, it is very important to ensure the lossless nature of data, and lossless data compression algorithms appear. The gradual optimization design of the algorithm can often achieve the energy-saving optimization of data compression. Similarly, The effect of energy saving can also be obtained by improving the hardware structure of node. In this paper, a new structure is designed for sensor node, which adopts hardware acceleration, and the data compression module is separated from the node microprocessor.On the basis of the ASIC design of the algorithm, by introducing hardware acceleration, the energy consumption of the compressed data was successfully reduced, and the proportion of energy consumption and compression time saved by the general-purpose processor was as high as 98.4 % and 95.8 %, respectively. It greatly reduces the compression time and energy consumption.

scholarly journals Remote Sensing Image Retrieval with Gabor-CA-ResNet and Split-Based Deep Feature Transform Network

2021 ◽  
Vol 13 (5) ◽  
pp. 869
Author(s):  
Zheng Zhuo ◽  
Zhong Zhou
Keyword(s):  
Remote Sensing ◽  
Image Retrieval ◽  
State Of The Art ◽  
Remote Sensing Image ◽  
Storage Space ◽  
Remote Sensing Images ◽  
Retrieval Method ◽  
Organization Management ◽  
Deep Feature ◽  
Feature Transform

In recent years, the amount of remote sensing imagery data has increased exponentially. The ability to quickly and effectively find the required images from massive remote sensing archives is the key to the organization, management, and sharing of remote sensing image information. This paper proposes a high-resolution remote sensing image retrieval method with Gabor-CA-ResNet and a split-based deep feature transform network. The main contributions include two points. (1) For the complex texture, diverse scales, and special viewing angles of remote sensing images, A Gabor-CA-ResNet network taking ResNet as the backbone network is proposed by using Gabor to represent the spatial-frequency structure of images, channel attention (CA) mechanism to obtain stronger representative and discriminative deep features. (2) A split-based deep feature transform network is designed to divide the features extracted by the Gabor-CA-ResNet network into several segments and transform them separately for reducing the dimensionality and the storage space of deep features significantly. The experimental results on UCM, WHU-RS, RSSCN7, and AID datasets show that, compared with the state-of-the-art methods, our method can obtain competitive performance, especially for remote sensing images with rare targets and complex textures.

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