Optimization Approach for Resource Allocation on Cloud Computing for IoT
Combinatorial auction is a popular approach for resource allocation in cloud computing. One of the challenges in resource allocation is that QoS (Quality of Service) constraints are satisfied and provider's profit is maximized. In order to increase the profit, the penalty cost for SLA (Service...
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| Format: | Article |
| Language: | English |
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Wiley
2016-03-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2016/3479247 |
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| _version_ | 1849472809289383936 |
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| author | Yeongho Choi Yujin Lim |
| author_facet | Yeongho Choi Yujin Lim |
| author_sort | Yeongho Choi |
| collection | DOAJ |
| description | Combinatorial auction is a popular approach for resource allocation in cloud computing. One of the challenges in resource allocation is that QoS (Quality of Service) constraints are satisfied and provider's profit is maximized. In order to increase the profit, the penalty cost for SLA (Service Level Agreement) violations needs to be reduced. We consider execution time constraint as SLA constraint in combinatorial auction system. In the system, we determine winners at each bidding round according to the job's urgency based on execution time deadline, in order to efficiently allocate resources and reduce the penalty cost. To analyze the performance of our mechanism, we compare the provider's profit and success rate of job completion with conventional mechanism using real workload data. |
| format | Article |
| id | doaj-art-dae60e83cd5f44719f41d71572d8b7a8 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2016-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-dae60e83cd5f44719f41d71572d8b7a82025-08-20T03:24:25ZengWileyInternational Journal of Distributed Sensor Networks1550-14772016-03-011210.1155/2016/34792473479247Optimization Approach for Resource Allocation on Cloud Computing for IoTYeongho Choi0Yujin Lim1 Department of Computer Science, University of Suwon, San 2-2, Wau-ri, Bongdam-eup, Hwaseong, Gyeonggi-do 445-743, Republic of Korea Department of Information Technology Engineering, Sookmyung Women's University, Cheongpa-ro 47-gil 100, Yongsan-gu, Seoul 04310, Republic of KoreaCombinatorial auction is a popular approach for resource allocation in cloud computing. One of the challenges in resource allocation is that QoS (Quality of Service) constraints are satisfied and provider's profit is maximized. In order to increase the profit, the penalty cost for SLA (Service Level Agreement) violations needs to be reduced. We consider execution time constraint as SLA constraint in combinatorial auction system. In the system, we determine winners at each bidding round according to the job's urgency based on execution time deadline, in order to efficiently allocate resources and reduce the penalty cost. To analyze the performance of our mechanism, we compare the provider's profit and success rate of job completion with conventional mechanism using real workload data.https://doi.org/10.1155/2016/3479247 |
| spellingShingle | Yeongho Choi Yujin Lim Optimization Approach for Resource Allocation on Cloud Computing for IoT International Journal of Distributed Sensor Networks |
| title | Optimization Approach for Resource Allocation on Cloud Computing for IoT |
| title_full | Optimization Approach for Resource Allocation on Cloud Computing for IoT |
| title_fullStr | Optimization Approach for Resource Allocation on Cloud Computing for IoT |
| title_full_unstemmed | Optimization Approach for Resource Allocation on Cloud Computing for IoT |
| title_short | Optimization Approach for Resource Allocation on Cloud Computing for IoT |
| title_sort | optimization approach for resource allocation on cloud computing for iot |
| url | https://doi.org/10.1155/2016/3479247 |
| work_keys_str_mv | AT yeonghochoi optimizationapproachforresourceallocationoncloudcomputingforiot AT yujinlim optimizationapproachforresourceallocationoncloudcomputingforiot |