Fault-Tolerant Covering Problems in Metric Spaces
In this article, we study some fault-tolerant covering problems in metric spaces. In the metric multi-cover problem (MMC), we are given two point sets Y (servers) and X (clients) in an arbitrary metric space ( X ∪ Y , d ) , a positive integer k that represents the coverage demand of each client, and...
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Veröffentlicht in: | Algorithmica 2021-02, Vol.83 (2), p.413-446 |
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description | In this article, we study some fault-tolerant covering problems in metric spaces. In the metric multi-cover problem (MMC), we are given two point sets
Y
(servers) and
X
(clients) in an arbitrary metric space
(
X
∪
Y
,
d
)
, a positive integer
k
that represents the coverage demand of each client, and a constant
α
≥
1
. Each server can host a single ball of arbitrary radius centered on it. Each client
x
∈
X
needs to be covered by at least
k
such balls centered on servers. The objective function that we wish to minimize is the sum of the
α
-th powers of the radii of the balls. We also study some non-trivial generalizations of the MMC, such as (a) the
non-uniform MMC
, where we allow client-specific demands, and (b) the
t
-
MMC
, where we require the number of open servers to be at most some given integer
t
. We present the first constant approximations for these fault-tolerant covering problems. Our algorithms are based on the following paradigm: for each of the three problems, we present an efficient algorithm that reduces the problem to several instances of the corresponding 1-covering problem, where the coverage demand of each client is 1. The reductions preserve optimality up to a multiplicative constant factor. Applying known constant factor approximation algorithms for 1-covering, we obtain our results for the MMC and these generalizations. |
doi_str_mv | 10.1007/s00453-020-00762-y |
format | Article |
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Y
(servers) and
X
(clients) in an arbitrary metric space
(
X
∪
Y
,
d
)
, a positive integer
k
that represents the coverage demand of each client, and a constant
α
≥
1
. Each server can host a single ball of arbitrary radius centered on it. Each client
x
∈
X
needs to be covered by at least
k
such balls centered on servers. The objective function that we wish to minimize is the sum of the
α
-th powers of the radii of the balls. We also study some non-trivial generalizations of the MMC, such as (a) the
non-uniform MMC
, where we allow client-specific demands, and (b) the
t
-
MMC
, where we require the number of open servers to be at most some given integer
t
. We present the first constant approximations for these fault-tolerant covering problems. Our algorithms are based on the following paradigm: for each of the three problems, we present an efficient algorithm that reduces the problem to several instances of the corresponding 1-covering problem, where the coverage demand of each client is 1. The reductions preserve optimality up to a multiplicative constant factor. Applying known constant factor approximation algorithms for 1-covering, we obtain our results for the MMC and these generalizations.</description><identifier>ISSN: 0178-4617</identifier><identifier>EISSN: 1432-0541</identifier><identifier>DOI: 10.1007/s00453-020-00762-y</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithm Analysis and Problem Complexity ; Algorithms ; Computer Science ; Computer Systems Organization and Communication Networks ; Data Structures and Information Theory ; Fault tolerance ; Integers ; Mathematics of Computing ; Metric space ; Servers ; Theory of Computation</subject><ispartof>Algorithmica, 2021-02, Vol.83 (2), p.413-446</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020</rights><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-2d30dceb091285dd60fbfbde9e62c095ba8abea9c6707622356adb9e0565dbd93</citedby><cites>FETCH-LOGICAL-c319t-2d30dceb091285dd60fbfbde9e62c095ba8abea9c6707622356adb9e0565dbd93</cites><orcidid>0000-0002-0184-5932</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00453-020-00762-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00453-020-00762-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Bhowmick, Santanu</creatorcontrib><creatorcontrib>Inamdar, Tanmay</creatorcontrib><creatorcontrib>Varadarajan, Kasturi</creatorcontrib><title>Fault-Tolerant Covering Problems in Metric Spaces</title><title>Algorithmica</title><addtitle>Algorithmica</addtitle><description>In this article, we study some fault-tolerant covering problems in metric spaces. In the metric multi-cover problem (MMC), we are given two point sets
Y
(servers) and
X
(clients) in an arbitrary metric space
(
X
∪
Y
,
d
)
, a positive integer
k
that represents the coverage demand of each client, and a constant
α
≥
1
. Each server can host a single ball of arbitrary radius centered on it. Each client
x
∈
X
needs to be covered by at least
k
such balls centered on servers. The objective function that we wish to minimize is the sum of the
α
-th powers of the radii of the balls. We also study some non-trivial generalizations of the MMC, such as (a) the
non-uniform MMC
, where we allow client-specific demands, and (b) the
t
-
MMC
, where we require the number of open servers to be at most some given integer
t
. We present the first constant approximations for these fault-tolerant covering problems. Our algorithms are based on the following paradigm: for each of the three problems, we present an efficient algorithm that reduces the problem to several instances of the corresponding 1-covering problem, where the coverage demand of each client is 1. The reductions preserve optimality up to a multiplicative constant factor. Applying known constant factor approximation algorithms for 1-covering, we obtain our results for the MMC and these generalizations.</description><subject>Algorithm Analysis and Problem Complexity</subject><subject>Algorithms</subject><subject>Computer Science</subject><subject>Computer Systems Organization and Communication Networks</subject><subject>Data Structures and Information Theory</subject><subject>Fault tolerance</subject><subject>Integers</subject><subject>Mathematics of Computing</subject><subject>Metric space</subject><subject>Servers</subject><subject>Theory of Computation</subject><issn>0178-4617</issn><issn>1432-0541</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE9LxDAQxYMouK5-AU8Fz9FJ0qTNURbXFVYUXM8hf6bSpdvWpCvst7drBW-ehoH33sz7EXLN4JYBFHcJIJeCAgc6rorTwwmZsVxwCjJnp2QGrChprlhxTi5S2gIwXmg1I2xp981AN12D0bZDtui-MNbtR_YaO9fgLmV1mz3jEGufvfXWY7okZ5VtEl79zjl5Xz5sFiu6fnl8WtyvqRdMD5QHAcGjA814KUNQULnKBdSouActnS2tQ6u9Ko4PcyGVDU4jSCWDC1rMyc2U28fuc49pMNtuH9vxpOG5FoyVUMhRxSeVj11KESvTx3pn48EwMEc0ZkJjRjTmB405jCYxmVJ_7IrxL_of1zf7cmaQ</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Bhowmick, Santanu</creator><creator>Inamdar, Tanmay</creator><creator>Varadarajan, Kasturi</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-0184-5932</orcidid></search><sort><creationdate>20210201</creationdate><title>Fault-Tolerant Covering Problems in Metric Spaces</title><author>Bhowmick, Santanu ; Inamdar, Tanmay ; Varadarajan, Kasturi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-2d30dceb091285dd60fbfbde9e62c095ba8abea9c6707622356adb9e0565dbd93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithm Analysis and Problem Complexity</topic><topic>Algorithms</topic><topic>Computer Science</topic><topic>Computer Systems Organization and Communication Networks</topic><topic>Data Structures and Information Theory</topic><topic>Fault tolerance</topic><topic>Integers</topic><topic>Mathematics of Computing</topic><topic>Metric space</topic><topic>Servers</topic><topic>Theory of Computation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bhowmick, Santanu</creatorcontrib><creatorcontrib>Inamdar, Tanmay</creatorcontrib><creatorcontrib>Varadarajan, Kasturi</creatorcontrib><collection>CrossRef</collection><jtitle>Algorithmica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bhowmick, Santanu</au><au>Inamdar, Tanmay</au><au>Varadarajan, Kasturi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fault-Tolerant Covering Problems in Metric Spaces</atitle><jtitle>Algorithmica</jtitle><stitle>Algorithmica</stitle><date>2021-02-01</date><risdate>2021</risdate><volume>83</volume><issue>2</issue><spage>413</spage><epage>446</epage><pages>413-446</pages><issn>0178-4617</issn><eissn>1432-0541</eissn><abstract>In this article, we study some fault-tolerant covering problems in metric spaces. In the metric multi-cover problem (MMC), we are given two point sets
Y
(servers) and
X
(clients) in an arbitrary metric space
(
X
∪
Y
,
d
)
, a positive integer
k
that represents the coverage demand of each client, and a constant
α
≥
1
. Each server can host a single ball of arbitrary radius centered on it. Each client
x
∈
X
needs to be covered by at least
k
such balls centered on servers. The objective function that we wish to minimize is the sum of the
α
-th powers of the radii of the balls. We also study some non-trivial generalizations of the MMC, such as (a) the
non-uniform MMC
, where we allow client-specific demands, and (b) the
t
-
MMC
, where we require the number of open servers to be at most some given integer
t
. We present the first constant approximations for these fault-tolerant covering problems. Our algorithms are based on the following paradigm: for each of the three problems, we present an efficient algorithm that reduces the problem to several instances of the corresponding 1-covering problem, where the coverage demand of each client is 1. The reductions preserve optimality up to a multiplicative constant factor. Applying known constant factor approximation algorithms for 1-covering, we obtain our results for the MMC and these generalizations.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s00453-020-00762-y</doi><tpages>34</tpages><orcidid>https://orcid.org/0000-0002-0184-5932</orcidid></addata></record> |
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subjects | Algorithm Analysis and Problem Complexity Algorithms Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Fault tolerance Integers Mathematics of Computing Metric space Servers Theory of Computation |
title | Fault-Tolerant Covering Problems in Metric Spaces |
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