PERFORMANCE COMPARISON OF SIX EFFICIENT PURE HEURISTICS FOR SCHEDULING META-TASKS ON HETEROGENEOUS DISTRIBUTED ENVIRONMENTS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F09%3A00020941" target="_blank" >RIV/61989100:27240/09:00020941 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

PERFORMANCE COMPARISON OF SIX EFFICIENT PURE HEURISTICS FOR SCHEDULING META-TASKS ON HETEROGENEOUS DISTRIBUTED ENVIRONMENTS

Popis výsledku v původním jazyce

Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous, distributed computing systems and represents an NP-complete problem. Therefore, using meta heuristic algorithms is a suitable approach in order to cope with itsdifficulty. In many meta-heuristic. algorithms, generating individuals in the initial stop has an important effect oil the convergence behavior of the algorithm and final solutions. Using some pure heuristics for generating one or more near-optimal individuals in the initial step can improve the final solutions obtained by meta-heuristic algorithms. Pure heuristics may be used solitary for generating schedules in many real-world situations in which using the meta-heuristic methods are too difficult orinappropriate. Different criteria can be used for evaluating the efficiency of scheduling algorithms, the most important of which are makespan and flowtime. In this paper, we propose an efficient pure heuristic method and then we compare

Název v anglickém jazyce

PERFORMANCE COMPARISON OF SIX EFFICIENT PURE HEURISTICS FOR SCHEDULING META-TASKS ON HETEROGENEOUS DISTRIBUTED ENVIRONMENTS

Popis výsledku anglicky

Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous, distributed computing systems and represents an NP-complete problem. Therefore, using meta heuristic algorithms is a suitable approach in order to cope with itsdifficulty. In many meta-heuristic. algorithms, generating individuals in the initial stop has an important effect oil the convergence behavior of the algorithm and final solutions. Using some pure heuristics for generating one or more near-optimal individuals in the initial step can improve the final solutions obtained by meta-heuristic algorithms. Pure heuristics may be used solitary for generating schedules in many real-world situations in which using the meta-heuristic methods are too difficult orinappropriate. Different criteria can be used for evaluating the efficiency of scheduling algorithms, the most important of which are makespan and flowtime. In this paper, we propose an efficient pure heuristic method and then we compare

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F09%2F1494" target="_blank" >GA102/09/1494: Nové metody přenosu dat založené na turbo kódech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

NEURAL NETWORK WORLD

ISSN

1210-0552

e-ISSN

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Svazek periodika

6

Číslo periodika v rámci svazku

19

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

15

Strana od-do

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Kód UT WoS článku

000273729800003

EID výsledku v databázi Scopus

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