An Optimal Relationship-Based Partitioning of Large Datasets

Capko, Darko; Erdeljan, Aleksandar; Popović, Miroslav; Svenda, Goran

doi:10.1007/978-3-642-15576-5_42

Cited by 3 publications

(5 citation statements)

References 3 publications

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“…In other words, relations between elements depend on input values, i.e. when a potential connection is activated two elements become neighbours [3] .…”

Section: Fig 1 Connectivity Modelmentioning

confidence: 99%

“…The optimal partitioning can be done in two complementary ways: 1) initially -before starting the system and 2) dynamically -while the system works (online) [3]. The dynamic repartitioning is applied while the system is working (on line) -triggered by changes in inputs (that affects the calculations) or periodically if the processor load is imbalanced [6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Repartitioning of Large Data Model in Distribution Management Systems

Capko¹,

Erdeljan²,

Svenda³

et al. 2012

ElAEE

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“…In other words, relations between elements depend on input values, i.e. when a potential connection is activated two elements become neighbours [3] .…”

Section: Fig 1 Connectivity Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Repartitioning of Large Data Model in Distribution Management Systems

Capko¹,

Erdeljan²,

Svenda³

et al. 2012

ElAEE

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“…In our studies [5,6,12], evolutionary algorithms are used for the initial partitioning. This allows the use of somewhat slower algorithms since it is done prior to startup.…”

Section: Related Workmentioning

confidence: 99%

“…This paper compares hybrid GA with previously used GA [5,12] and PSO [6,12] algorithms for initial graph partitioning.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Genetic Algorithm for Partitioning of Data Model in Distribution Management Systems

Capko¹,

Erdeljan²,

Vukmirovic³

et al. 2011

ITC

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In this paper, we propose a Hybrid Genetic Algorithm for data model partitioning of power distribution network. Analytical functions are the core of Distribution Management Systems (DMSs). Efficient calculation of the functions is of the utmost importance for the DMS users; the necessary preconditions for the efficient calculation are optimal load balancing of processors and data model partitioning among processors. The proposed algorithm is applied to different real models of power distribution systems. It obtains better results than classical evolutionary algorithms (Genetic Algorithm and Particle Swarm Optimization). The Hybrid Genetic Algorithm also achieves better results than multilevel algorithm (METIS) in cases of small graphs.

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“…Therefore, graph edges represent open switches between elements from different roots. The weight of the vertex is determined by the calculation complexity of the corresponding root and the weight of edge are defined as the number of open switches between the corresponding roots [6].…”

Section: Introductionmentioning

confidence: 99%

Distributed PSO Algorithm for Data Model Partitioning in Power Distribution Systems

Erdeljan

Capko

Vukmirovic

et al. 2014

Journal of Applied Research and Technology

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This paper presents a method for data model partitioning of power distribution network. Modern Distribution Management Systems which utilize multiprocessor systems for efficient processing of large data model are considered. The data model partitioning is carried out for parallelization of analytical power calculations. The proposed algorithms (Particle Swarm Optimization (PSO) and distributed PSO algorithms) are applied on data model describing large power distribution network. The experimental results of PSO and distributed PSO algorithms are presented. Distributed PSO algorithm achieves significantly better results than the basic PSO algorithm.

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An Optimal Relationship-Based Partitioning of Large Datasets

Cited by 3 publications

References 3 publications

Dynamic Repartitioning of Large Data Model in Distribution Management Systems

Dynamic Repartitioning of Large Data Model in Distribution Management Systems

A Hybrid Genetic Algorithm for Partitioning of Data Model in Distribution Management Systems

Distributed PSO Algorithm for Data Model Partitioning in Power Distribution Systems

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