K
Kamesh Munagala
Researcher at Duke University
Publications - 166
Citations - 6750
Kamesh Munagala is an academic researcher from Duke University. The author has contributed to research in topics: Approximation algorithm & Common value auction. The author has an hindex of 44, co-authored 157 publications receiving 6192 citations. Previous affiliations of Kamesh Munagala include Cornell University & Stanford University.
Papers
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Journal ArticleDOI
Local Search Heuristics for k -Median and Facility Location Problems
TL;DR: This work analyzes local search heuristics for the metric k-median and facility location problems and shows that local search with swaps has a locality gap of 5 and introduces a new local search operation which opens one or more copies of a facility and drops zero or more facilities.
Proceedings ArticleDOI
Local search heuristic for k-median and facility location problems
TL;DR: This paper analyzes local search heuristics for the k-median and facility location problems and proves that without this stretch, the problem becomes NP-Hard to approximate.
Proceedings ArticleDOI
Adaptive ordering of pipelined stream filters
TL;DR: This work considers the problem of pipelined filters, where a continuous stream of tuples is processed by a set of commutative filters, and identifies a three-way tradeoff among provable convergence to good orderings, run-time overhead, and speed of adaptivity.
Proceedings ArticleDOI
Operator placement for in-network stream query processing
TL;DR: This paper addresses in-network processing for queries involving possibly expensive conjunctive filters, and joins, and considers the problem of placing operators along the nodes of the hierarchy so that the overall cost of computation and data transmission is minimized.
Proceedings ArticleDOI
Query optimization over web services
TL;DR: This paper tackles a first basic WSMS problem: query optimization for Select-Project-Join queries spanning multiple web services, and gives an algorithm for determining the optimal granularity of data "chunks" to be used for each web service call.