Special interest messaging: A Comparison of IGM Approaches
(2007) In Computer Journal 53(1). p.50-68- Abstract
- Hundreds of technical, special interest Internet weblogs are already generating thousands of niche articles worldwide, and many institutions are starting to create internal blogs for team collaboration. As this style of communication becomes more pervasive in the lives of employees and researchers, the difficulty of finding relevant information only grows with the number of authors and articles. To reduce the load, we propose using implicit group messaging (IGM) to automatically deliver relevant content to readers grouped by shared characteristics or interests. In this paper, we outline a context-aware application suited to special interest messaging and describe three alternative delivery models including our peer-to-peer (P2P) design... (More)
- Hundreds of technical, special interest Internet weblogs are already generating thousands of niche articles worldwide, and many institutions are starting to create internal blogs for team collaboration. As this style of communication becomes more pervasive in the lives of employees and researchers, the difficulty of finding relevant information only grows with the number of authors and articles. To reduce the load, we propose using implicit group messaging (IGM) to automatically deliver relevant content to readers grouped by shared characteristics or interests. In this paper, we outline a context-aware application suited to special interest messaging and describe three alternative delivery models including our peer-to-peer (P2P) design called SPICE and a broker-based design. We investigate the advantages and disadvantages of each approach through detailed simulations driven by realistic data and actual national/global network topologies. We find that although a broker-based design is generally the most network efficient and lowest latency, a structured P2P system can offer exceptionally low and fair loading across peers and network links without relying on specialized broker nodes. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3173093
- author
- Cutting, Daniel ; Quigley, Aaron and Landfeldt, Björn LU
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Computer Journal
- volume
- 53
- issue
- 1
- pages
- 50 - 68
- publisher
- Oxford University Press
- external identifiers
-
- scopus:77749258177
- ISSN
- 1460-2067
- DOI
- 10.1093/comjnl/bxm076
- language
- English
- LU publication?
- no
- id
- c79d82d7-b662-44ed-be98-9feedb9cb296 (old id 3173093)
- date added to LUP
- 2016-04-01 11:34:34
- date last changed
- 2022-01-26 07:15:02
@article{c79d82d7-b662-44ed-be98-9feedb9cb296,
abstract = {{Hundreds of technical, special interest Internet weblogs are already generating thousands of niche articles worldwide, and many institutions are starting to create internal blogs for team collaboration. As this style of communication becomes more pervasive in the lives of employees and researchers, the difficulty of finding relevant information only grows with the number of authors and articles. To reduce the load, we propose using implicit group messaging (IGM) to automatically deliver relevant content to readers grouped by shared characteristics or interests. In this paper, we outline a context-aware application suited to special interest messaging and describe three alternative delivery models including our peer-to-peer (P2P) design called SPICE and a broker-based design. We investigate the advantages and disadvantages of each approach through detailed simulations driven by realistic data and actual national/global network topologies. We find that although a broker-based design is generally the most network efficient and lowest latency, a structured P2P system can offer exceptionally low and fair loading across peers and network links without relying on specialized broker nodes.}},
author = {{Cutting, Daniel and Quigley, Aaron and Landfeldt, Björn}},
issn = {{1460-2067}},
language = {{eng}},
number = {{1}},
pages = {{50--68}},
publisher = {{Oxford University Press}},
series = {{Computer Journal}},
title = {{Special interest messaging: A Comparison of IGM Approaches}},
url = {{http://dx.doi.org/10.1093/comjnl/bxm076}},
doi = {{10.1093/comjnl/bxm076}},
volume = {{53}},
year = {{2007}},
}