@inproceedings {7145326,
	title = {Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks},
	booktitle = {IFIP Networking Conference (IFIP Networking), 2015},
	year = {2015},
	month = {May},
	keywords = {Cellular Networks, Content Delivery Networks, Europe, Facebook, Internet, IP networks, Network Measurements, Online Social Networks, Organizations, Servers, WhatsApp},
	doi = {10.1109/IFIPNetworking.2015.7145326},
	author = {Fiadino, Pierdomenico and Casas, Pedro and Schiavone, Mirko and D{\textquoteright}Alconzo, Alessandro}
}
@article {7096995,
	title = {Personal Cloud Storage Benchmarks and Comparison},
	journal = {Cloud Computing, IEEE Transactions on},
	volume = {PP},
	year = {2015},
	pages = {1-1},
	abstract = {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.},
	keywords = {Benchmark testing, Cloud computing, Cloud storage, Computers, Google, Measurements, Performance, Servers, Synchronization},
	issn = {2168-7161},
	doi = {10.1109/TCC.2015.2427191},
	author = {Enrico Bocchi and Idilio Drago and Marco Mellia}
}
@article {6975242,
	title = {When YouTube Does not Work - Analysis of QoE-Relevant Degradation in Google CDN Traffic},
	journal = {Network and Service Management, IEEE Transactions on},
	volume = {11},
	year = {2014},
	month = {Dec},
	pages = {441-457},
	keywords = {CDN distributed services, CDN server selection strategies, client-server systems, content delivery network, Content Delivery Networks, Degradation, dynamic approach, dynamic server selection strategies, end-user QoE, end-user quality of experience, European ISP, Google, Google CDN traffic, Google server selection strategies, IP networks, iterative structured process, load reduction, QoE-relevant anomaly characterization, QoE-relevant anomaly detection, QoE-relevant anomaly diagnosis, QoE-relevant degradation, Quality of Experience, Servers, social networking (online), statistical analysis, statistical analysis methodologies, Statistical Data Analysis, telecommunication traffic, Traffic Monitoring, Videos, watching experience improvement, YouTube, YouTube flow trace collection, YouTube QoE-relevant degradation, YouTube videos},
	issn = {1932-4537},
	doi = {10.1109/TNSM.2014.2377691},
	author = {Casas, Pedro and D{\textquoteright}Alconzo, Alessandro and Fiadino, Pierdomenico and B{\"a}r, Arian and Finamore, Alessandro and Zseby, Tanja}
}
@inproceedings {Fin2012,
	title = {The need for an intelligent measurement plane: The example of time-variant CDN policies},
	booktitle = {Telecommunications Network Strategy and Planning Symposium (NETWORKS), 2012 XVth International },
	year = {2012},
	month = {10/2012},
	pages = {1 - 6 },
	abstract = {In this paper we characterize how web-based services are delivered by large organizations in today{\textquoteright}s Internet. Taking advantage oftwo week-long data sets separated in time by 10 months and reporting the web activity of more than 10,000 ADSL residential customers, we identify the services offered by large organizations like Google, Akamai and Amazon. We then compare theevolution of both policies used to serve requests, and the infrastructure they use to match the users{\textquoteright} demand. Results depict anovercrowded scenario in constant evolution. Big-players are more and more responsible for the majority of the volume and a plethora of other organizations offering similar or more specific services through different CDNs and traffic policies. Unfortunately, no standard tools and methodologies are available to capture and expose the hidden properties of this in constant evolution picture. A deeper understanding of such dynamics is however fundamental to improve the performance of current and future Internet. To this extend, we claim the need for a Internet-wide, standard, flexible and intelligent measurement plane to be added tothe current Internet infrastructure.},
	keywords = {Facebook, Google, Monitoring, Organizations, Servers, Streaming media, Throughput},
	issn = {978-1-4673-1390-2},
	doi = {http://dx.doi.org/10.1109/NETWKS.2012.6381662},
	author = {Alessandro Finamore and Vinicius Gehlen and Marco Mellia and Maurizio M Munafo{\textquoteright}}
}
