Balancing push and pull for data broadcast

Author:

Acharya Swarup1,Franklin Michael2,Zdonik Stanley1

Affiliation:

1. Brown University

2. University of Maryland

Abstract

The increasing ability to interconnect computers through internet-working, wireless networks, high-bandwidth satellite, and cable networks has spawned a new class of information-centered applications based on data dissemination . These applications employ broadcast to deliver data to very large client populations. We have proposed the Broadcast Disks paradigm [Zdon94, Acha95b] for organizing the contents of a data broadcast program and for managing client resources in response to such a program. Our previous work on Broadcast Disks focused exclusively on the “push-based” approach, where data is sent out on the broadcast channel according to a periodic schedule, in anticipation of client requests. In this paper, we study how to augment the push-only model with a “pull-based” approach of using a backchannel to allow clients to send explicit requests for data to the server. We analyze the scalability and performance of a broadcast-based system that integrates push and pull and study the impact of this integration on both the steady state and warm-up performance of clients. Our results show that a client backchannel can provide significant performance improvement in the broadcast environment, but that unconstrained use of the backchannel can result in scalability problems due to server saturation. We propose and investigate a set of three techniques that can delay the onset of saturation and thus, enhance the performance and scalability of the system.

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems,Software

Cited by 43 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Novel Method of Smart Communication using PSoC for Wireless Push System;2020 International Conference on Emerging Smart Computing and Informatics (ESCI);2020-03

2. A Broadcasting Scheme for Transaction Processing in a Wireless Environment;Handling Priority Inversion in Time-Constrained Distributed Databases;2020

3. Studying the multilevel impact of cohesion versus structural holes in knowledge networks on adaptation to IT‐enabled patient‐care practices;Information Systems Journal;2019-04-12

4. Content-Aware D2D Caching for Reducing Visiting Latency in Virtualized Cellular Networks;KSII Transactions on Internet and Information Systems;2019-02-28

5. A Novel Technique for Data Push in Mobile Clients Using Sequential Regression Algorithm;International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018;2018-12-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3