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Cross-Layer Multi-Cloud Real-Time Application QoS Monitoring and Benchmarking As-a-Service Framework
School of Computer Science and Engineering, University of New South Wales.
CSIRO Digital Productivity, Acton.
CSIRO Digital Productivity, Acton.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
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2016 (English)In: I E E E Transactions on Cloud Computing, ISSN 2168-7161Article in journal (Refereed) Epub ahead of print
Abstract [en]

Cloud computing provides on-demand access to affordable hardware (e.g., multi-core CPUs, GPUs, disks, and networking equipment) and software (e.g., databases, application servers and data processing frameworks) platforms with features such as elasticity, pay-per-use, low upfront investment and low time to market. This has led to the proliferation of business critical applications that leverage various cloud platforms. Such applications hosted on single/multiple cloud provider platforms have diverse characteristics requiring extensive monitoring and benchmarking mechanisms to ensure run-time Quality of Service (QoS) (e.g., latency and throughput). This paper proposes, develops and validates CLAMBS—Cross-Layer Multi Cloud Application Monitoring and Benchmarking as-a-Service for efficient QoS monitoring and benchmarking of cloud applications hosted on multi-clouds environments. The major highlight of CLAMBS is its capability of monitoring and benchmarking individual application components such as databases and web servers, distributed across cloud layers (*-aaS), spread among multiple cloud providers. We validate CLAMBS using prototype implementation and extensive experimentation and show that CLAMBS efficiently monitors and benchmarks application components on multi-cloud platforms including Amazon EC2 and Microsoft Azure.

Place, publisher, year, edition, pages
Keyword [en]
Cloud Computing, Benchmarking, Cloud Monitoring, Information technology - Systems engineering
Keyword [sv]
Informationsteknik - Systemteknik
Research subject
Mobile and Pervasive Computing
URN: urn:nbn:se:ltu:diva-5655DOI: 10.1109/TCC.2015.2441715Local ID: 3d0653ee-adf9-462f-a6bc-f5dcec1c3dc3OAI: diva2:978529
Upprättat; 2016; 20150508 (karan)Available from: 2016-09-29 Created: 2016-09-29

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