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Conference

European Symposium on Algorithms 

About: European Symposium on Algorithms is an academic conference. The conference publishes majorly in the area(s): Approximation algorithm & Time complexity. Over the lifetime, 2413 publications have been published by the conference receiving 43898 citations.


Papers
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Book ChapterDOI
17 Sep 2002
TL;DR: In this article, the authors consider a router on the Internet analyzing the statistical properties of a TCP/IP packet stream and present an algorithm that deterministically finds (in particular) all categories having a frequency above 1/(m+1) using m counters, which is best possible in the worst case.
Abstract: We consider a router on the Internet analyzing the statistical properties of a TCP/IP packet stream. A fundamental difficulty with measuring traffic behavior on the Internet is that there is simply too much data to be recorded for later analysis, on the order of gigabytes a second. As a result, network routers can collect only relatively few statistics about the data. The central problem addressed here is to use the limited memory of routers to determine essential features of the network traffic stream. A particularly difficult and representative subproblem is to determine the top k categories to which the most packets belong, for a desired value of k and for a given notion of categorization such as the destination IP address.We present an algorithm that deterministically finds (in particular) all categories having a frequency above 1/(m+1) using m counters, which we prove is best possible in the worst case. We also present a sampling-based algorithm for the case that packet categories follow an arbitrary distribution, but their order over time is permuted uniformly at random. Under this model, our algorithm identifies flows above a frequency threshold of roughly 1/?nm with high probability, where m is the number of counters and n is the number of packets observed. This guarantee is not far off from the ideal of identifying all flows (probability 1/n), and we prove that it is best possible up to a logarithmic factor. We show that the algorithm ranks the identified flows according to frequency within any desired constant factor of accuracy.

532 citations

Book ChapterDOI
25 Sep 1996
TL;DR: This work focuses on the question of finding a connected dominating set of minimum size, where the graph induced by vertices in the dominating set is required to be connected.
Abstract: The dominating set problem in graphs asks for a minimum size subset of vertices with the following property: each vertex is required to either be in the dominating set, or adjacent to at least one node in the dominating set. We focus on the question of finding a connected dominating set of minimum size, where the graph induced by vertices in the dominating set is required to be connected. This problem arises in network testing, as well as in wireless communication.

458 citations

Book ChapterDOI
08 Oct 2007
TL;DR: A (1 - 1/e)-competitive (optimal) algorithm is designed for the online ad-auctions problem, which is based on a clean primal-dual approach, matching the competitive factor obtained in Mehta et al.
Abstract: We study the online ad-auctions problem introduced by Mehta et al. [15]. We design a (1 - 1/e)-competitive (optimal) algorithm for the problem, which is based on a clean primal-dual approach, matching the competitive factor obtained in [15]. Our basic algorithm along with its analysis are very simple. Our results are based on a unified approach developed earlier for the design of online algorithms [7,8]. In particular, the analysis uses weak duality rather than a tailor made (i.e., problem specific) potential function. We show that this approach is useful for analyzing other classical online algorithms such as ski rental and the TCP-acknowledgement problem. We are confident that the primal-dual method will prove useful in other online scenarios as well. The primal-dual approach enables us to extend our basic ad-auctions algorithm in a straight forward manner to scenarios in which additional information is available, yielding improved worst case competitive factors. In particular, a scenario in which additional stochastic information is available to the algorithm, a scenario in which the number of interested buyers in each product is bounded by some small number d, and a general risk management framework.

372 citations

Book ChapterDOI
03 Oct 2005
TL;DR: A new speedup technique for route planning that exploits the hierarchy inherent in real world road networks and preprocesses the eight digit number of nodes needed for maps of the USA or Western Europe in a few hours using linear space.
Abstract: We present a new speedup technique for route planning that exploits the hierarchy inherent in real world road networks. Our algorithm preprocesses the eight digit number of nodes needed for maps of the USA or Western Europe in a few hours using linear space. Shortest (i.e. fastest) path queries then take around eight milliseconds to produce exact shortest paths. This is about 2 000 times faster than using Dijkstra’s algorithm.

372 citations

Book ChapterDOI
11 Sep 2006
TL;DR: A simple hashing-based alternative based on d- left hashing called a d-left CBF (dlCBF), which offers the same functionality as a CBF, but uses less space, generally saving a factor of two or more.
Abstract: A counting Bloom filter (CBF) generalizes a Bloom filter data structure so as to allow membership queries on a set that can be changing dynamically via insertions and deletions. As with a Bloom filter, a CBF obtains space savings by allowing false positives. We provide a simple hashing-based alternative based on d-left hashing called a d-left CBF (dlCBF). The dlCBF offers the same functionality as a CBF, but uses less space, generally saving a factor of two or more. We describe the construction of dlCBFs, provide an analysis, and demonstrate their effectiveness experimentally.

346 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202142
202095
2019111
2018101
201780
2016102