Pub Date : 2017-11-01DOI: 10.1109/SmartCloud.2017.54
Hong Zhu, Nan Xie
The airport emergency rescue evaluation is a multi-indicator, multi-level problem and indicator attributes are associated with each other, The traditional evaluation methods include Fuzzy-AHP and so on. However, the precondition of weighted arithmetic mean is assumed that each indicator is independent, There is an association between evaluation indicators. In this paper, according to the emergency rescue capability indicators, we establish hierarchical evaluation system, and use AHP to calculate the weights. Then, an improved Fuzzy Measure is proposed to solve the problem of the traditional fuzzy measure, which has non-zero real solution or Multiple solutions. Finally we evaluate the ability of airport emergency rescue by using Choquet integral. The experimental results indicate that this method makes score more reasonable.
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Pub Date : 1900-01-01DOI: 10.1109/SmartCloud.2019.00019
K. Jayasena, S. ThisarasingheB.
Task scheduling in fog computing is tackled with the use of different kinds of algorithms in general but this paper implements a meta-heuristic based approach. Fog computing is increasingly being adopted because it reduces latency and improves performance. Compared to the cloud data centers that are resource enriched , fog nodes don't have the same luxury and hence with the additional constraint of coordinating a distributed network, task scheduling in Fog Computing is not a trivial task. Since we only have limited capacity in the system, we use meta heuristic algorithms which guarantee a solution to the optimization problem posed here. Here the main research problem was to minimize the energy used in a fog environment.
{"title":"Optimized task scheduling on fog computing environment using meta heuristic algorithms","authors":"K. Jayasena, S. ThisarasingheB.","doi":"10.1109/SmartCloud.2019.00019","DOIUrl":"https://doi.org/10.1109/SmartCloud.2019.00019","url":null,"abstract":"Task scheduling in fog computing is tackled with the use of different kinds of algorithms in general but this paper implements a meta-heuristic based approach. Fog computing is increasingly being adopted because it reduces latency and improves performance. Compared to the cloud data centers that are resource enriched , fog nodes don't have the same luxury and hence with the additional constraint of coordinating a distributed network, task scheduling in Fog Computing is not a trivial task. Since we only have limited capacity in the system, we use meta heuristic algorithms which guarantee a solution to the optimization problem posed here. Here the main research problem was to minimize the energy used in a fog environment.","PeriodicalId":208283,"journal":{"name":"International Conference on Smart Cloud","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123048788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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