The challenge of computing in a highly dynamic environment: We are rapidly approaching the era of dynamicity and of the highly unpredictable. A great variety of modern networked systems are highly dynamic both in space and time. Theory will continue sitting at the center of progress in our science and its necessity toward our understanding of dynamic networks is already evident. Many traditional approaches and measures for static networks are not adequate for dynamic networks. There is already strong evidence that there is room for the development of a rich theory. Despite the considerable recent progress discussed in this article, we do not yet really know how to compute in highly dynamic environments.
%0 Journal Article
%1 MichailSpirakis18cacm
%A Michail, Othon
%A Spirakis, Paul G.
%D 2018
%J Communications of the ACM
%K 01821 acm paper network application system adaptive software theory
%N 2
%P 72--81
%R 10.1145/3156693
%T Elements of the Theory of Dynamic Networks
%V 61
%X The challenge of computing in a highly dynamic environment: We are rapidly approaching the era of dynamicity and of the highly unpredictable. A great variety of modern networked systems are highly dynamic both in space and time. Theory will continue sitting at the center of progress in our science and its necessity toward our understanding of dynamic networks is already evident. Many traditional approaches and measures for static networks are not adequate for dynamic networks. There is already strong evidence that there is room for the development of a rich theory. Despite the considerable recent progress discussed in this article, we do not yet really know how to compute in highly dynamic environments.
@article{MichailSpirakis18cacm,
abstract = {The challenge of computing in a highly dynamic environment: We are rapidly approaching the era of dynamicity and of the highly unpredictable. A great variety of modern networked systems are highly dynamic both in space and time. Theory will continue sitting at the center of progress in our science and its necessity toward our understanding of dynamic networks is already evident. Many traditional approaches and measures for static networks are not adequate for dynamic networks. There is already strong evidence that there is room for the development of a rich theory. Despite the considerable recent progress discussed in this article, we do not yet really know how to compute in highly dynamic environments.},
added-at = {2018-01-26T15:00:49.000+0100},
author = {Michail, Othon and Spirakis, Paul G.},
biburl = {https://www.bibsonomy.org/bibtex/2a11e7b5ac6f27d995601da066bc2bf2b/flint63},
doi = {10.1145/3156693},
file = {ACM Digital Library:2018/MichailSpirakis18cacm.pdf:PDF},
groups = {public},
interhash = {ad14e8970be49cd0ee08e240a58b8cd2},
intrahash = {a11e7b5ac6f27d995601da066bc2bf2b},
issn = {0001-0782},
journal = {Communications of the ACM},
keywords = {01821 acm paper network application system adaptive software theory},
month = {#feb#},
number = 2,
pages = {72--81},
timestamp = {2018-04-16T12:08:02.000+0200},
title = {Elements of the Theory of Dynamic Networks},
username = {flint63},
volume = 61,
year = 2018
}