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Primal-dual approximation algorithms for metric facility location and k-median problems
- Journal of the ACM
, 1999
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The Online Median Problem
- In Proceedings of the 41st Annual IEEE Symposium on Foundations of Computer Science
, 2000
"... We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the online median problem. Whereas the k-median problem involves optimizing the simultaneous placement of k facilities, the online median problem imposes the following additional constraints: the facilities ar ..."
Abstract
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Cited by 69 (2 self)
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We introduce a natural variant of the (metric uncapacitated) k-median problem that we call the online median problem. Whereas the k-median problem involves optimizing the simultaneous placement of k facilities, the online median problem imposes the following additional constraints: the facilities are placed one at a time; a facility cannot be moved once it is placed, and the total number of facilities to be placed, k, is not known in advance. The objective of an online median algorithm is to minimize the competitive ratio, that is, the worst-case ratio of the cost of an online placement to that of an optimal offline placement. Our main result is a linear-time constant-competitive algorithm for the online median problem. In addition, we present a related, though substantially simpler, linear-time constant-factor approximation algorithm for the (metric uncapacitated) facility location problem. The latter algorithm is similar in spirit to the recent primal-dual-based facility location algorithm of Jain and Vazirani, but our approach is more elementary and yields an improved running time.
The Facility Location Problem with General Cost Functions
- Networks
, 2002
"... In this paper we introduce a generalized version of the facility location problem in which the facility cost is a function of the number of clients assigned to the facility. We focus on the case of concave facility cost functions. We observe that this problem can be reduced to the uncapacitated faci ..."
Abstract
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Cited by 19 (4 self)
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In this paper we introduce a generalized version of the facility location problem in which the facility cost is a function of the number of clients assigned to the facility. We focus on the case of concave facility cost functions. We observe that this problem can be reduced to the uncapacitated facility location problem. We analyze a natural greedy algorithm for this problem and show that its approximation factor is at most 1.861. We also consider several generalizations and variants of this problem.
Gamps: Compressing multi sensor data by grouping and amplitude scaling
- In: ACM SIGMOD. (2009
"... We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within a given maximum (L∞) error ε. The problem arises naturally in applications that need to collect large amounts of data fr ..."
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Cited by 12 (0 self)
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We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within a given maximum (L∞) error ε. The problem arises naturally in applications that need to collect large amounts of data from multiple concurrent sources, such as sensors, servers and network routers, and archive them over a long period of time for offline data mining. We present GAMPS, a general framework that addresses this problem by combining several novel techniques. First, it dynamically groups multiple signals together so that signals within each group are correlated and can be maximally compressed jointly. Second, it appropriately scales the amplitudes of different signals within a group and compresses them within the maximum allowed reconstruction error bound. Our schemes are polynomial time O(α, β) approximation schemes, meaning that the maximum (L∞) error is at most αε and it uses at most β times the optimal memory. Finally, GAMPS maintains an index so that various queries can be issued directly on compressed data. Our experiments on several real-world sensor datasets show that GAMPS significantly reduces space without compromising the quality of search and query. Categories and Subject Descriptors
The adoption of electronic data interchange: a model and practical tool for managers. Decision Support Systems
, 2000
"... Despite the benefits of standards-based Electronic Data Interchange (EDI) modes of communication, only a small percentage of organizations have adopted even a single form of EDI. Organizations are often unable to assess the benefits resulting from the adoption of EDI due to the complexity of operati ..."
Abstract
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Cited by 9 (1 self)
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Despite the benefits of standards-based Electronic Data Interchange (EDI) modes of communication, only a small percentage of organizations have adopted even a single form of EDI. Organizations are often unable to assess the benefits resulting from the adoption of EDI due to the complexity of operational issues. This paper develops a model and decision support tool for identifying if EDI adoption is cost effective. In contrast to previous research, the model presented allows for the simultaneous adoption of multiple modes of communication. This tool is used to predict the appropriateness of EDI adoption with greater than 85 % accuracy.
Parallelization of the scatter search for the p-median problem
- Parallel Computing
, 2003
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Placement of Nodes in an Adaptive Distributed Multimedia Server
- In Proceedings of the 10th International Euro-Par Conference, 2004
"... Partial support of the EC Centre of Excellence programme (No. ICA1-CT-2000-70025) and ..."
Abstract
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Cited by 1 (1 self)
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Partial support of the EC Centre of Excellence programme (No. ICA1-CT-2000-70025) and

