Pub Date : 2013-11-01DOI: 10.1109/CloudNet.2013.6710569
Shinya Kitajima, Tetsuya Uchiumi, S. Kikuchi, Y. Matsumoto
The recent progress in computer performance and the development of virtualization technologies has led to the prevalence of cloud computing. Data center providers providing public cloud services have to install additional resources and infrastructures continuously to keep up with the increasing demands from cloud users. Since the newly installed infrastructure (e.g. servers) usually have similar structure as the existing infrastructure, the configuration settings for the existing ones can be copied and used for the new one. One of the exceptions is network setting (e.g. IP address) which must be customized for each infrastructure. However, the customization requires manual configuration, which can cause misconfigurations, resulting in communication failures in the new infrastructure. One of the promising approaches to identify the misconfigurations is to detect the differences between the communication logs recorded in the existing infrastructure and the new infrastructure being developed. In order to execute this approach, we need to identify a pair of servers that play the same role in the existing and new infrastructure so that we can verify whether or not the same functions are working properly in both of these infrastructures. In this paper, we propose a method that automatically identifies the pair of servers playing the same role by detecting the common communication patterns observed in both infrastructures. We evaluated our method in actual cloud infrastructure and confirmed that it identified 94.1% of corresponding pairs of servers correctly.
{"title":"Automatic server role identification for cloud infrastructure construction","authors":"Shinya Kitajima, Tetsuya Uchiumi, S. Kikuchi, Y. Matsumoto","doi":"10.1109/CloudNet.2013.6710569","DOIUrl":"https://doi.org/10.1109/CloudNet.2013.6710569","url":null,"abstract":"The recent progress in computer performance and the development of virtualization technologies has led to the prevalence of cloud computing. Data center providers providing public cloud services have to install additional resources and infrastructures continuously to keep up with the increasing demands from cloud users. Since the newly installed infrastructure (e.g. servers) usually have similar structure as the existing infrastructure, the configuration settings for the existing ones can be copied and used for the new one. One of the exceptions is network setting (e.g. IP address) which must be customized for each infrastructure. However, the customization requires manual configuration, which can cause misconfigurations, resulting in communication failures in the new infrastructure. One of the promising approaches to identify the misconfigurations is to detect the differences between the communication logs recorded in the existing infrastructure and the new infrastructure being developed. In order to execute this approach, we need to identify a pair of servers that play the same role in the existing and new infrastructure so that we can verify whether or not the same functions are working properly in both of these infrastructures. In this paper, we propose a method that automatically identifies the pair of servers playing the same role by detecting the common communication patterns observed in both infrastructures. We evaluated our method in actual cloud infrastructure and confirmed that it identified 94.1% of corresponding pairs of servers correctly.","PeriodicalId":262262,"journal":{"name":"2013 IEEE 2nd International Conference on Cloud Networking (CloudNet)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115698329","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}
Pub Date : 2013-11-01DOI: 10.1109/CloudNet.2013.6710573
Efstratios Rappos, Stephan Robert, R. Riedi
Distributed data center architectures have been recently developed for a more efficient and economical storage of data. In many models of distributed storage, the aim is to store the data in such a way so that the storage costs are minimized and increased redundancy requirements are maintained. However, many approaches do not fully consider issues relating to delivering the data to the end user and the associated costs that this creates. We present an integer programming optimization model for determining the optimal allocation of data components among a network of Cloud data servers in such a way that the total costs of additional storage, estimated data retrieval costs and network delay penalties is minimized. The method is suitable for periodic dynamic reconfiguration of the Cloud data servers, so that the when localized data request spikes occur the data can be moved to a closer or cheaper data server for cost reduction and increased efficiency.
{"title":"A Cloud data center optimization approach using dynamic data interchanges","authors":"Efstratios Rappos, Stephan Robert, R. Riedi","doi":"10.1109/CloudNet.2013.6710573","DOIUrl":"https://doi.org/10.1109/CloudNet.2013.6710573","url":null,"abstract":"Distributed data center architectures have been recently developed for a more efficient and economical storage of data. In many models of distributed storage, the aim is to store the data in such a way so that the storage costs are minimized and increased redundancy requirements are maintained. However, many approaches do not fully consider issues relating to delivering the data to the end user and the associated costs that this creates. We present an integer programming optimization model for determining the optimal allocation of data components among a network of Cloud data servers in such a way that the total costs of additional storage, estimated data retrieval costs and network delay penalties is minimized. The method is suitable for periodic dynamic reconfiguration of the Cloud data servers, so that the when localized data request spikes occur the data can be moved to a closer or cheaper data server for cost reduction and increased efficiency.","PeriodicalId":262262,"journal":{"name":"2013 IEEE 2nd International Conference on Cloud Networking (CloudNet)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131441587","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}
Pub Date : 1900-01-01DOI: 10.1109/CloudNet.2013.6710572
Wei-Chu Lin, Gen-Hen Liu, Kuan-Tsen Kuo, Charles H.-P. Wen
A prior layer-2 routing algorithm-D2ENDIST demonstrates advantages in throughput improvement, reroute period and failure recovery. Moreover, with the invention of software-defined networking (SDN), a revolutionary networking concept, dynamic routing protocols can embrace more flexible policy on per-flow basis. However, due to runtime complexity of dynamic routing, many issues on the practicality emerge and await to be resolved. Therefore, in this paper, we first apply D2ENDIST to a SDN architecture and compare performances between dynamic-routing and flow-control mechanisms in a OpenFlow-based cloud network. Then, the flow-migration (FM) scheme, showing a better flow-control management, can be combined with D2ENDIST, and evolved into D2ENDIST-FM. At last, experimental results demonstrate that D2ENDIST-FM enables better feasibility in real-world applications, throughput improvement, sensitivity to reroute period and reduction in failure recovery time.
{"title":"D2ENDIST-FM: Flow migration in routing of OpenFlow-based cloud networks","authors":"Wei-Chu Lin, Gen-Hen Liu, Kuan-Tsen Kuo, Charles H.-P. Wen","doi":"10.1109/CloudNet.2013.6710572","DOIUrl":"https://doi.org/10.1109/CloudNet.2013.6710572","url":null,"abstract":"A prior layer-2 routing algorithm-D2ENDIST demonstrates advantages in throughput improvement, reroute period and failure recovery. Moreover, with the invention of software-defined networking (SDN), a revolutionary networking concept, dynamic routing protocols can embrace more flexible policy on per-flow basis. However, due to runtime complexity of dynamic routing, many issues on the practicality emerge and await to be resolved. Therefore, in this paper, we first apply D2ENDIST to a SDN architecture and compare performances between dynamic-routing and flow-control mechanisms in a OpenFlow-based cloud network. Then, the flow-migration (FM) scheme, showing a better flow-control management, can be combined with D2ENDIST, and evolved into D2ENDIST-FM. At last, experimental results demonstrate that D2ENDIST-FM enables better feasibility in real-world applications, throughput improvement, sensitivity to reroute period and reduction in failure recovery time.","PeriodicalId":262262,"journal":{"name":"2013 IEEE 2nd International Conference on Cloud Networking (CloudNet)","volume":"19 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":"121657234","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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