<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Personal Cloud Storage Benchmarks and Comparison</style></title><secondary-title><style face="normal" font="default" size="100%">Cloud Computing, IEEE Transactions on</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Benchmark testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud computing</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Computers</style></keyword><keyword><style  face="normal" font="default" size="100%">Google</style></keyword><keyword><style  face="normal" font="default" size="100%">Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">Performance</style></keyword><keyword><style  face="normal" font="default" size="100%">Servers</style></keyword><keyword><style  face="normal" font="default" size="100%">Synchronization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><volume><style face="normal" font="default" size="100%">PP</style></volume><pages><style face="normal" font="default" size="100%">1-1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The large amount of space offered by personal cloud storage services (e.g., Dropbox and OneDrive), together with the possibility of synchronizing devices seamlessly, keep attracting customers to the cloud. Despite the high public interest, little information about system design and actual implications on performance is available when selecting a cloud storage service. Systematic benchmarks to assist in comparing services and understanding the effects of design choices are still lacking. This paper proposes a methodology to understand and benchmark personal cloud storage services. Our methodology unveils their architecture and capabilities. Moreover, by means of repeatable and customizable tests, it allows the measurement of performance metrics under different workloads. The effectiveness of the methodology is shown in a case study in which 11 services are compared under the same conditions. Our case study reveals interesting differences in design choices. Their implications are assessed in a series of benchmarks. Results show no clear winner, with all services having potential for improving performance. In some scenarios, the synchronization of the same files can take 20 times longer. In other cases, we observe a wastage of twice as much network capacity, questioning the design of some services. Our methodology and results are thus useful both as benchmarks and as guidelines for system design.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Personal Cloud Storage: Usage, Performance and Impact of Terminals </style></title><secondary-title><style face="normal" font="default" size="100%">4th IEEE International Conference on Cloud Networking (IEEE CloudNet 2015)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cloud storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Monitoring</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ieee-cloudnet.org/program.html</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Niagara Falls, Canada</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Personal cloud storage services such as Dropbox and OneDrive are popular among Internet users. They help in sharing content and backing up data by relying on the cloud to store files. The rise of mobile terminals and the presence of new providers question whether the usage of cloud storage is evolving. This knowledge is essential to understand the workload these services need to handle, their performance, and implications. In this paper we present a comprehensive characterization of personal cloud storage services. Relying on traces collected for one month in an operational network, we show that users of each service present distinct behaviors. Dropbox is now threatened by competitors, with OneDrive and Google Drive reaching large market shares. However, the popularity of the latter services seems to be driven by their integration into Windows and Android. Indeed, around 50% of their users do not produce any workload. Considering performance, providers show distinct trade-offs, with bottlenecks that hardly allow users to fully exploit their access line bandwidth. Finally, usage of cloud services is now ordinary among mobile users, thanks to the automatic backup of pictures and media files.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Sofiane Sarni</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cloud Storage Service Benchmarking: Methodologies and Experimentations</style></title><secondary-title><style face="normal" font="default" size="100%">3rd IEEE International Conference on Cloud Networking (IEEE CloudNet 2014)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amazon S3</style></keyword><keyword><style  face="normal" font="default" size="100%">Benchmarking</style></keyword><keyword><style  face="normal" font="default" size="100%">Cloud storage</style></keyword><keyword><style  face="normal" font="default" size="100%">Performance measurement</style></keyword><keyword><style  face="normal" font="default" size="100%">Web services</style></keyword><keyword><style  face="normal" font="default" size="100%">Windows Azure</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Luxembourg</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;page&quot; title=&quot;Page 1&quot;&gt;&lt;div class=&quot;layoutArea&quot;&gt;&lt;div class=&quot;column&quot;&gt;&lt;p&gt;&lt;span&gt;Data storage is one of today’s fundamental services with companies, universities and research centers having the need of storing large amounts of data every day. Cloud storage services are emerging as strong alternative to local storage, allowing customers to save costs of buying and maintaining expensive hardware. Several solutions are available on the market, the most famous being Amazon S3. However it is rather difficult to access information about each service architecture, performance, and pricing. To shed light on storage services from the customer perspective, we propose a benchmarking methodology, apply it to four popular offers (Amazon S3, Amazon Glacier, Windows Azure Blob and Rackspace Cloud Files), and compare their performance. Each service is analysed as a black box and benchmarked through crafted workloads. We take the perspective of a customer located in Europe, looking for possible service providers and the optimal data center where to deploy its applications. At last, we complement the analysis by comparing the actual and forecast costs faced when using each service. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;According to collected results, all services show eventual weaknesses related to some workload, with no all-round eligible winner, e.g., some offers providing excellent or poor performance when exchanging large or small files. For all services, it is of paramount importance to accurately select the data center to where deploy the applications, with throughput that varies by factors from 2x to 10x. The methodology (and tools implementing it) here presented is instrumental for potential customers to identify the most suitable offer for their needs.&amp;nbsp;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Idilio Drago</style></author><author><style face="normal" font="default" size="100%">Enrico Bocchi</style></author><author><style face="normal" font="default" size="100%">Marco Mellia</style></author><author><style face="normal" font="default" size="100%">Herman Slatman</style></author><author><style face="normal" font="default" size="100%">Aiko Pras</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Benchmarking Personal Cloud Storage</style></title><secondary-title><style face="normal" font="default" size="100%">Internet Measurement Conference - IMC</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Active Measurements</style></keyword><keyword><style  face="normal" font="default" size="100%">Personal Cloud Storage</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.simpleweb.org/wiki/Cloud_benchmarks</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">Barcelona (ES)</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Personal cloud storage services are data-intensive applica- tions already producing a significant share of Internet traffic. Several solutions offered by different companies attract more and more people. However, little is known about each service capabilities, architecture and – most of all – performance implications of design choices. This paper presents a methodology to study cloud storage services. We apply our methodology to compare 5 popular offers, revealing different system architectures and capabilities. The implications on performance of different designs are assessed executing a series of benchmarks. Our results show no clear winner, with all services suffering from some limitations or having potential for improvement. In some scenarios, the upload of the same file set can take seven times more, wasting twice as much capacity. Our methodology and results are useful thus as both benchmark and guideline for system design.&lt;/p&gt;</style></abstract></record></records></xml>