An Empirical Analysis of a Large-scale Mobile Cloud Storage Service

Li, Zhenyu; Wang, Xiaohui; Huang, Ningjing; Kâafar, Mohamed Ali; Li, Zhenhua; Zhou, Jianer; Xie, Gaogang; Steenkiste, Peter

doi:10.1145/2987443.2987465

Cited by 25 publications

(15 citation statements)

References 19 publications

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“…At the individual mobile service level, several works have studied specific applications in depth. Investigations have focused on services such as adaptive-bit-rate video streaming by over-the-top providers [12], Facebook and WhatsApp [15], or cloud storage [22]. These studies address the network-level performance of the examined services, and do not provide insights in terms of the geographical diversity of their usage.…”

Section: Related Workmentioning

confidence: 99%

“…input: C, set of geographical areas, i.e., communes input: A, adjacency matrix of areas in C input: N K 1 , N K 2 target number of clusters in phases I and II . The dissimilarity matrix is also updated, by removing the weighted diversity values associated to the two merged areas, and computing and adding to D the weighted diversities between the newly created cluster J and all adjacent (merged) regions in the current K (line [21][22][23][24][25][26].…”

Section: Phase Imentioning

confidence: 99%

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Urban Vibes and Rural Charms: Analysis of Geographic Diversity in Mobile Service Usage at National Scale

Singh

Fiore

Marina

et al. 2019

The World Wide Web Conference

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We investigate spatial patterns in mobile service consumption that emerge at national scale. Our investigation focuses on a representative case study, i.e., France, where we find that: (i) the demand for popular mobile services is fairly uniform across the whole country, and only a reduced set of peculiar services (mainly operating system updates and long-lived video streaming) yields geographic diversity; (ii) even for such distinguishing services, the spatial heterogeneity of demands is limited, and a small set of consumption behaviors is sufficient to characterize most of the mobile service usage across the country; (iii) the spatial distribution of these behaviors correlates well with the urbanization level, ultimately suggesting that the adoption of geographically-diverse mobile applications is linked to a dichotomy of cities and rural areas. We derive our results through the analysis of substantial measurement data collected by a major mobile network operator, leveraging an approach rooted in information theory that can be readily applied to other scenarios.

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Section: Related Workmentioning

confidence: 99%

Section: Phase Imentioning

confidence: 99%

Urban Vibes and Rural Charms: Analysis of Geographic Diversity in Mobile Service Usage at National Scale

Singh

Fiore

Marina

et al. 2019

The World Wide Web Conference

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“…Supporting large file upload and retrieval is crucial for the mobile cloud storage services, as file sizes are trending larger and mobile users access or share files of large size [8], [9]. Practical large object services are, however, only available for PC clients and not for mobile apps.…”

Section: Related Workmentioning

confidence: 99%

“…Recently a large number of research efforts have been conducted on enterprise cloud storage services and personal cloud storage services. The investigations from [8] attempted to find out mobile user access behavior in a large-scale mobile cloud storage with a a dataset of 350 million HTTP request logs. The study observed the trend of using the cloud storage for large file sharing, with the average volume as large as about 70 MB, in multiple sessions for retrieving one file.…”

Section: Introductionmentioning

confidence: 99%

NetMob: A Mobile Application Development Framework with Enhanced Large Objects Access for Mobile Cloud Storage Service

Faniband¹,

Ishak²,

Sidi³

et al. 2019

IJACSA

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Mobile enterprise applications are primarily developed for existing backend enterprise systems and some usage scenarios require storing of large files on the mobile devices.These files range from large PDFs to media files in various formats (MPEG videos).These files needs to be used offline , sometimes updated and shared among users. Present work studied different Mobile Backend as a service (M)BaaS platforms to understand techniques use to handle large file and found that many are either missing the feature or does not handle performance issues for large files. In this paper, we are proposing, NetMob, a mobile synchronization platform that allows resource-limited mobile devices to access large objects from the cloud. This framework is mainly focused on large file handling and has support for both table and objects data models that can be tuned for three consistency semantics, resembling strong, causal and eventual consistency. Experimental results conducted using representative workloads showed that NetMob can handle large files access with the size ranging from 100MB upto 1GB and is able to reduce sync time with object chunking in our experiment settings.

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“…Furthermore, our experiments show that this problem cannot be fundamentally addressed by employing parallelism techniques, i.e., by increasing the number of sync threads N thread (detailed in §3. 7).…”

Section: Introductionmentioning

confidence: 99%

On the Synchronization Bottleneck of OpenStack Swift-Like Cloud Storage Systems

Ruan

Titcheu

Zhai

et al. 2018

IEEE Trans. Parallel Distrib. Syst.

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As one type of the most popular cloud storage services, OpenStack Swift and its follow-up systems replicate each object across multiple storage nodes and leverage object sync protocols to achieve high reliability and eventual consistency. The performance of object sync protocols heavily relies on two key parameters: r (number of replicas for each object) and n (number of objects hosted by each storage node). In existing tutorials and demos, the configurations are usually r = 3 and n < 1000 by default, and the sync process seems to perform well. However, we discover in data-intensive scenarios, e.g., when r > 3 and n 1000, the sync process is significantly delayed and produces massive network overhead, referred to as the sync bottleneck problem. By reviewing the source code of OpenStack Swift, we find that its object sync protocol utilizes a fairly simple and network-intensive approach to check the consistency among replicas of objects. Hence in a sync round, the number of exchanged hash values per node is Θ(n × r). To tackle the problem, we propose a lightweight and practical object sync protocol, LightSync, which not only remarkably reduces the sync overhead, but also preserves high reliability and eventual consistency. LightSync derives this capability from three novel building blocks: 1) Hashing of Hashes, which aggregates all the h hash values of each data partition into a single but representative hash value with the Merkle tree; 2) Circular Hash Checking, which checks the consistency of different partition replicas by only sending the aggregated hash value to the clockwise neighbor; and 3) Failed Neighbor Handling, which properly detects and handles node failures with moderate overhead to effectively strengthen the robustness of LightSync. The design of LightSync offers provable guarantee on reducing the per-node network overhead from Θ(n × r) to Θ(n h). Furthermore, we have implemented LightSync as an open-source patch and adopted it to OpenStack Swift, thus reducing the sync delay by up to 879× and the network overhead by up to 47.5×.

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An Empirical Analysis of a Large-scale Mobile Cloud Storage Service

Cited by 25 publications

References 19 publications

Urban Vibes and Rural Charms: Analysis of Geographic Diversity in Mobile Service Usage at National Scale

Urban Vibes and Rural Charms: Analysis of Geographic Diversity in Mobile Service Usage at National Scale

NetMob: A Mobile Application Development Framework with Enhanced Large Objects Access for Mobile Cloud Storage Service

On the Synchronization Bottleneck of OpenStack Swift-Like Cloud Storage Systems

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