scholarly journals TCP Using Adaptive FEC to Improve Throughput Performance in High-Latency Environments

2019 ◽  
Vol E102.B (3) ◽  
pp. 537-544 ◽  
Author(s):  
Yurino SATO ◽  
Hiroyuki KOGA ◽  
Takeshi IKENAGA
Keyword(s):  
Throughput Performance ◽  
Adaptive Fec

Measured Downlink Throughput Performance of MBWA System in Urban Area

2013 ◽  
Vol E96.B (1) ◽  
pp. 329-334 ◽  
Author(s):  
Suguru KAMEDA ◽  
Hiroshi OGUMA ◽  
Noboru IZUKA ◽  
Yasuyoshi ASANO ◽  
Yoshiharu YAMAZAKI ◽  
...  
Keyword(s):  
Urban Area ◽  
Throughput Performance ◽  
Downlink Throughput

Throughput Performance Prediction Approach for Wi-Fi Site Surveys

2021 ◽  
Author(s):  
Akihiro Tatsuta ◽  
Yasunori Shimazaki ◽  
Teppei Emura ◽  
Takuya Asada ◽  
Taichi Hamabe
Keyword(s):  
Performance Prediction ◽  
Throughput Performance ◽  
Prediction Approach

scholarly journals Kilogram scale throughput performance of the KATRIN tritium handling system

2021 ◽  
Vol 170 ◽  
pp. 112507
Author(s):  
Michael Sturm ◽  
Florian Priester ◽  
Marco Röllig ◽  
Carsten Röttele ◽  
Alexander Marsteller ◽  
...  
Keyword(s):  
Throughput Performance ◽  
Handling System

scholarly journals CacheInspector

2021 ◽  
Vol 18 (3) ◽  
pp. 1-25
Author(s):  
Weijia Song ◽  
Christina Delimitrou ◽  
Zhiming Shen ◽  
Robbert Van Renesse ◽  
Hakim Weatherspoon ◽  
...  
Keyword(s):  
Virtual Machines ◽  
Controlled Environment ◽  
Shared Resources ◽  
Throughput Performance ◽  
Shared Caches ◽  
Output Quality ◽  
Cloud Providers ◽  
Cloud Users ◽  
Service Cloud ◽  
Critical Aspects

Infrastructure-as-a-Service cloud providers sell virtual machines that are only specified in terms of number of CPU cores, amount of memory, and I/O throughput. Performance-critical aspects such as cache sizes and memory latency are missing or reported in ways that make them hard to compare across cloud providers. It is difficult for users to adapt their application’s behavior to the available resources. In this work, we aim to increase the visibility that cloud users have into shared resources on public clouds. Specifically, we present CacheInspector , a lightweight runtime that determines the performance and allocated capacity of shared caches on multi-tenant public clouds. We validate CacheInspector ’s accuracy in a controlled environment, and use it to study the characteristics and variability of cache resources in the cloud, across time, instances, availability regions, and cloud providers. We show that CacheInspector ’s output allows cloud users to tailor their application’s behavior, including their output quality, to avoid suboptimal performance when resources are scarce.

scholarly journals Reconfigurable Binary Neural Network Accelerator with Adaptive Parallelism Scheme

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 230
Author(s):  
Jaechan Cho ◽  
Yongchul Jung ◽  
Seongjoo Lee ◽  
Yunho Jung
Keyword(s):  
Neural Networks ◽  
High Throughput ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
Throughput Performance ◽  
Adaptive Parallelism ◽  
Sensor Applications ◽  
Binary Neural Network ◽  
Target Layer ◽  
Network Topologies

Binary neural networks (BNNs) have attracted significant interest for the implementation of deep neural networks (DNNs) on resource-constrained edge devices, and various BNN accelerator architectures have been proposed to achieve higher efficiency. BNN accelerators can be divided into two categories: streaming and layer accelerators. Although streaming accelerators designed for a specific BNN network topology provide high throughput, they are infeasible for various sensor applications in edge AI because of their complexity and inflexibility. In contrast, layer accelerators with reasonable resources can support various network topologies, but they operate with the same parallelism for all the layers of the BNN, which degrades throughput performance at certain layers. To overcome this problem, we propose a BNN accelerator with adaptive parallelism that offers high throughput performance in all layers. The proposed accelerator analyzes target layer parameters and operates with optimal parallelism using reasonable resources. In addition, this architecture is able to fully compute all types of BNN layers thanks to its reconfigurability, and it can achieve a higher area–speed efficiency than existing accelerators. In performance evaluation using state-of-the-art BNN topologies, the designed BNN accelerator achieved an area–speed efficiency 9.69 times higher than previous FPGA implementations and 24% higher than existing VLSI implementations for BNNs.

Modeling of assembly systems with complex structures for throughput analysis during transients

2019 ◽  
Vol 39 (2) ◽  
pp. 262-271
Author(s):  
Yukan Hou ◽  
Yuan Li ◽  
Yuntian Ge ◽  
Jie Zhang ◽  
Shoushan Jiang
Keyword(s):  
Steady State ◽  
Fixed Point Theory ◽  
Point Theory ◽  
Assembly Systems ◽  
Complex Structures ◽  
Throughput Performance ◽  
Throughput Analysis ◽  
Content Type ◽  
Serial Production Lines ◽  
Transient And Steady State

Purpose The purpose of this paper is to present an analytical method for throughput analysis of assembly systems with complex structures during transients. Design/methodology/approach Among the existing studies on the performance evaluation of assembly systems, most focus on the system performance in steady state. Inspired by the transient analysis of serial production lines, the state transition matrix is derived considering the characteristics of merging structure in assembly systems. The system behavior during transients is described by an ergodic Markov chain, with the states being the occupancy of all buffers. The dynamic model for the throughput analysis is solved using the fixed-point theory. Findings This method can be used to predict and evaluate the throughput performance of assembly systems in both transient and steady state. By comparing the model calculation results with the simulation results, this method is proved to be accurate. Originality/value This proposed modeling method can depict the throughput performance of assembly systems in both transient and steady state, whereas most exiting methods can be used for only steady-state analysis. In addition, this method shows the potential for the analysis of complex structured assembly systems owing to the low computational complexity.

Throughput performance under primary user emulation attack in cognitive radio networks

2017 ◽  
Vol 30 (18) ◽  
pp. e3371 ◽  
Author(s):  
Kuldeep Yadav ◽  
Binod Prasad ◽  
Abhijit Bhowmick ◽  
Sanjay Dhar Roy ◽  
Sumit Kundu
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Primary User ◽  
Radio Networks ◽  
Throughput Performance ◽  
Primary User Emulation Attack ◽  
Primary User Emulation
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