Approximation Algorithms for the k-center Problem: An Experimental Evaluation

Mihelič, Jurij; Robič, Borut

doi:10.1007/978-3-642-55537-4_60

Cited by 12 publications

(8 citation statements)

References 5 publications

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“…In this heuristic [6,7], we solve a series of dominating set and apply a parametric pruning [17,18,19] technique to calculate our centers. This technique is also known as the elimination heuristic.…”

Section: The Dominating Set Heuristicmentioning

confidence: 99%

Examining Heuristics for the K-Centers Problem

Shetty¹,

Mukherjee²,

Senthilkumar³

2018

IJET

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In this paper, we discuss and analyze the heuristics existing to solve the K-Center problem. The K-Center problem is used in various practical scenarios such as facility location, load-balancing, ATM mapping, Cloud Server Selection, or even data clustering and image classification. Specifically, we examine a standard Greedy algorithm with an approximation factor of 2, the clustering algorithm introduced by Gonzales in 1985, and the Dominating Set Algorithm(commonly referred to as the elimination heuristic) devised by Jurij Mihelič and Borut Robič. We also propose a new heuristic to solve the specified problem using Tree-Independent Dual-Trees devised by Ryan R. Curtin.

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Section: The Dominating Set Heuristicmentioning

confidence: 99%

Examining Heuristics for the K-Centers Problem

Shetty¹,

Mukherjee²,

Senthilkumar³

2018

IJET

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“…It formulates the scenario where a known number (k) of service facilities are to be deployed in the network so that they are "close to every client". The problem itself is NP-complete but can be approximated within a factor of 2 [37,38]. The root node selection problem in MCTS can be formulated as a 1-center problem [39].…”

Section: Root Node Selection For Mctsmentioning

confidence: 99%

Network-Wide Time Synchronization in Multi-Channel Wireless Sensor Networks

Nieminen¹,

Qian²,

Jäntti³

2011

WSN

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Recent advances in wireless sensor technology have enabled simultaneous exploitation of multiple channels in wireless sensor systems. In this paper, a novel time synchronization algorithm is proposed for multi- channel Wireless Sensor Networks (WSNs) called Multi-Channel Time Synchronization (MCTS) protocol. Time synchronization is critical for many WSN applications and enables efficient communications between sensor nodes along with intelligent spectrum access. Contrary to many existing protocols that do not exploit multi-channel communications, the protocol takes advantage of potential multiple channels and distributes the synchronization of different nodes to distinct channels and thus, reduces the convergence time of synchronization processes significantly

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“…Another related implementation that has been recently posted on the web for solving the k-center problem is by Jurij Mihelic [40]. This implementation solves the k-center problem on graphs by reducing it to the dominating set problem.…”

Section: Definition (K-clustering)mentioning

confidence: 99%