Xingyu Ma, Chengchen Hu, Kai Chen, Che Zhang, Hongtao Zhang, K. Zheng, Yan Chen, Xianda Sun
{"title":"Error Tolerant Address Configuration for Data Center Networks with Malfunctioning Devices","authors":"Xingyu Ma, Chengchen Hu, Kai Chen, Che Zhang, Hongtao Zhang, K. Zheng, Yan Chen, Xianda Sun","doi":"10.1109/ICDCS.2012.27","DOIUrl":null,"url":null,"abstract":"Address auto-configuration is a key problem in data center networks, where servers and switches encode topology information into their addresses for routing. A recent work DAC [2] has been introduced to address this problem. Without malfunctions, DAC can auto-configure all the devices quickly. But in case of malfunctions, DAC requires significant human efforts to correct malfunctions and it can cause substantial operation delay of the whole data center. In this paper, we further optimize address auto-configuration process even in the presence of malfunctions. Instead of waiting for all the malfunctions to be corrected, we could first configure the devices that are not involved in malfunctions and let them work first. This idea can be translated to considerable practical benefits because in most cases malfunctions in data centers only account for a very small portion. To realize the idea, we conceptually remove the malfunctions from the physical data center topology graph and mathematically convert the address configuration problem into induced sub graph isomorphism problem, which is NP-complete. We then introduce an algorithm that can solve the induced sub graph isomorphism quickly by taking advantage of data center topology characteristics and induced sub graph properties. We extensively evaluate our design on representative data center structures with various malfunction scenarios. The evaluation results demonstrate that the proposed framework and algorithm are efficient and labor-free to deal with the mapping task in the presence of error devices.","PeriodicalId":6300,"journal":{"name":"2012 IEEE 32nd International Conference on Distributed Computing Systems","volume":"1 1","pages":"708-717"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 32nd International Conference on Distributed Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCS.2012.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Address auto-configuration is a key problem in data center networks, where servers and switches encode topology information into their addresses for routing. A recent work DAC [2] has been introduced to address this problem. Without malfunctions, DAC can auto-configure all the devices quickly. But in case of malfunctions, DAC requires significant human efforts to correct malfunctions and it can cause substantial operation delay of the whole data center. In this paper, we further optimize address auto-configuration process even in the presence of malfunctions. Instead of waiting for all the malfunctions to be corrected, we could first configure the devices that are not involved in malfunctions and let them work first. This idea can be translated to considerable practical benefits because in most cases malfunctions in data centers only account for a very small portion. To realize the idea, we conceptually remove the malfunctions from the physical data center topology graph and mathematically convert the address configuration problem into induced sub graph isomorphism problem, which is NP-complete. We then introduce an algorithm that can solve the induced sub graph isomorphism quickly by taking advantage of data center topology characteristics and induced sub graph properties. We extensively evaluate our design on representative data center structures with various malfunction scenarios. The evaluation results demonstrate that the proposed framework and algorithm are efficient and labor-free to deal with the mapping task in the presence of error devices.