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Cross-Layer SLA Management for Cloud-hosted Big Data Analytics Applications

Xuezhi Zeng, Rajiv Ranjan, Peter Strazdins, Saurabh Kumar Garg, Lizhe Wang
2015 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing  
That is service level agreement (SLA) management to deliver strong Quality of Service (QoS) guarantees for big data analytics applications (BDAA) sharing the same underlying infrastructure, for example  ...  Although SLA and QoS are not new concepts as they originated much before the cloud computing and big data era, its importance is amplified and complexity is aggravated by the emergence of time-sensitive  ...  The extended CloudSim will then support SLA evaluation templates that incorporate details on aSLA constraints, fault injection models, workload contention models, big data processing benchmarks, and configuration  ... 
doi:10.1109/ccgrid.2015.175 dblp:conf/ccgrid/ZengRSGW15 fatcat:jl7k65uas5fajh7oegzyai2zlq

Cloud Performance Modeling with Benchmark Evaluation of Elastic Scaling Strategies

Kai Hwang, Xiaoying Bai, Yue Shi, Muyang Li, Wen-Guang Chen, Yongwei Wu
2016 IEEE Transactions on Parallel and Distributed Systems  
Cloud benchmarking results are analyzed with the efficiency, elasticity, QoS, productivity, and scalability of cloud performance.  ...  We test clouds with real-life benchmark programs and propose some new performance metrics. Our benchmark experiments are conducted mainly on IaaS cloud platforms over scaleout and scale-up workloads.  ...  and big-data analytics.  ... 
doi:10.1109/tpds.2015.2398438 fatcat:blkvz2kyuzfqpbfrlv4id2n54y

Ready for Rain? A View from SPEC Research on the Future of Cloud Metrics [article]

Nikolas Herbst, Rouven Krebs, Giorgos Oikonomou, George Kousiouris, Athanasia Evangelinou, Alexandru Iosup, Samuel Kounev
2016 arXiv   pre-print
Keywords: Cloud Computing; Metrics; Measurement; Benchmarking; Elasticity; Isolation; Performance; Service Level Objective; Availability; Operational Risk.  ...  Addressing this requirement, in this work we focus on four system properties: (i) elasticity of the cloud service, to accommodate large variations in the amount of service requested, (ii) performance isolation  ...  As a next step, we are working on an extensive review of existing cloud-relevant benchmarks and connected domains like big data, web services, and graph processing.  ... 
arXiv:1604.03470v1 fatcat:wk6zkaimubfdflynj2qbfkzzcy

Benchmarking data warehouse systems in the cloud

Rim Moussa
2013 2013 ACS International Conference on Computer Systems and Applications (AICCSA)  
Finally, we present new requirements for implementing a benchmark for data warehouse systems in the cloud.  ...  Then, we argue that TPC-H benchmark -the most prominent benchmark for decision support system, mismatches cloud rationale (scalability, elasticity, pay-per-use, fault-tolerance features) and Customer Relationship  ...  , scalability, elasticity, as well as SLAs.  ... 
doi:10.1109/aiccsa.2013.6616442 dblp:conf/aiccsa/Moussa13 fatcat:y4mcf7xk3zdjzgd473dufhpeau

Benchmarking in the Cloud: What It Should, Can, and Cannot Be [chapter]

Enno Folkerts, Alexander Alexandrov, Kai Sachs, Alexandru Iosup, Volker Markl, Cafer Tosun
2013 Lecture Notes in Computer Science  
Our driving principle is that Cloud Benchmarks must consider end-to-end performance and pricing, taking into account that services are delivered over the Internet.  ...  This requirement yields new challenges for benchmarking and requires us to revisit existing benchmarking practices in order to adopt them to the Cloud.  ...  High Workload Analytical Platform ACME Analytics is a start-up that wants to provide Big Data analytics services.  ... 
doi:10.1007/978-3-642-36727-4_12 fatcat:aiva75paozeepb3dnriuysj4vy

HPS-HDS: High Performance Scheduling for Heterogeneous Distributed Systems

Florin Pop, Alexandru Iosup, Radu Prodan
2018 Future generations computer systems  
Topics include cloud computing and big data, with applications in big science, big business, online gaming, and (upcoming) massivized education.  ...  In this special issues, the accepted papers address the advance on scheduling algorithms, energy-aware models, self-organizing resource management, dataaware service allocation, Big Data management and  ...  The problem of task scheduling and resource allocation under SLA constraints is one of the main challenges the context of heterogeneous distributed systems, because we face with the need to satisfy the  ... 
doi:10.1016/j.future.2017.09.012 fatcat:aqdguozk5jffbjxpfoecskbpv4

Quantifying Cloud Performance and Dependability

Nikolas Herbst, Cristina L. Abad, Alexandru Iosup, André Bauer, Samuel Kounev, Giorgos Oikonomou, Erwin Van Eyk, George Kousiouris, Athanasia Evangelinou, Rouven Krebs, Tim Brecht
2018 ACM Transactions on Modeling and Performance Evaluation of Computing Systems  
INTRODUCTION Cloud computing is a paradigm under which ICT services are offered on demand "as a service," where resources providing the service are dynamically adjusted to meet the needs of a varying workload  ...  Fourth, as the risks of not meeting implicit user-expectations and explicit service contracts (service level agreements, SLAs) ACM Trans. Model. Perform.  ...  As a next step, we are working on an extensive review of existing cloud-relevant benchmarks and connected domains like big data, web services and graph processing.  ... 
doi:10.1145/3236332 fatcat:ne3amvxqdra4pg25leeytv4vn4

Scale-Out vs. Scale-Up Techniques for Cloud Performance and Productivity

Kai Hwang, Yue Shi, Xiaoying Bai
2014 2014 IEEE 6th International Conference on Cloud Computing Technology and Science  
We evaluate three scaling strategies to upgrade the performance, efficiency and productivity of elastic clouds like EC2, Rackspace, etc.  ...  An elastic cloud provisions machine instances upon user demand. Auto-scaling, scale-out, scale-up, or any mixture techniques are used to reconfigure the user cluster as workload changes.  ...  big-data analytics.  ... 
doi:10.1109/cloudcom.2014.66 dblp:conf/cloudcom/HwangSB14 fatcat:fnmnjmen2ngw5c5eushwyrs2jy

SLA-Based Resource Scheduling for Big Data Analytics as a Service in Cloud Computing Environments

Yali Zhao, Rodrigo N. Calheiros, Graeme Gange, Kotagiri Ramamohanarao, Rajkumar Buyya
2015 2015 44th International Conference on Parallel Processing  
Cloud computing is a suitable platform for Big Data Analytic Applications (BDAAs) that can greatly reduce application cost by elastically provisioning resources based on user requirements and in a pay  ...  To support the AaaS platform, our research focuses on efficiently scheduling Cloud resources for BDAAs to satisfy Quality of Service (QoS) requirements of budget and deadline for data analytic requests  ...  ACKNOWLEDGMENTS We thank Mohsen Amini Salehi, Yun Yang, Satish Srirama, and all the members at the CLOUDS Lab for their valuable comments and suggestions to improve the work.  ... 
doi:10.1109/icpp.2015.60 dblp:conf/icpp/ZhaoCGRB15 fatcat:li2zx7bw7za3rf7xbk7wz4hr7y

SLA-Aware Provisioning and Scheduling of Cloud Resources for Big Data Analytics

Mohammed Alrokayan, Amir Vahid Dastjerdi, Rajkumar Buyya
2014 2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)  
provisioning that can both lead to SLA or budget constraint violations.  ...  However, to make Cloud hosted Big Data analytics available to wider range of enterprises, we have to carefully capture their preferences in terms of budget and service level objectives.  ...  To pave the way for organizations to adopt Cloud-hosted Big Data analytics, we have to carefully consider their preferences in terms of budget and service level objectives through provisioning and scheduling  ... 
doi:10.1109/ccem.2014.7015497 fatcat:srkuumu3crcwnot23ivkhkhqwy

Software-Defined Multi-Cloud Computing: A Vision, Architectural Elements, and Future Directions [article]

Rajkumar Buyya, Jungmin Son
2018 arXiv   pre-print
of the resources in Cloud data centers.  ...  Cloud providers run multiple data centers in various locations to manage and provision the Cloud resources to their customers.  ...  New benchmarks can be proposed to measure performance criteria such as VNFs' throughput, time to deploy, and migration impacts on SLAs.  ... 
arXiv:1805.10780v1 fatcat:43qvxxtsavh2vfiywdgagkbrq4

Multi-Criteria Virtual Machine Placement in Cloud Computing Environments: A literature Review [article]

Wissal Attaoui, Essaid Sabir
2018 arXiv   pre-print
It allows a high level of flexibility as Virtual Machines (VMs) run elastically workloads on physical machines in data centers.  ...  , Service Level Agreement, and incurred cost.  ...  These constraint are expressed in the SLA between the customer and the cloud provider.  ... 
arXiv:1802.05113v1 fatcat:faiazufoq5fphmdd4qefdh5aje

Cross-Layer Multi-Cloud Real-Time Application QoS Monitoring and Benchmarking As-a-Service Framework

Khalid Alhamazani, Rajiv Ranjan, Prem Prakash Jayaraman, Karan Mitra, Fethi Rabhi, Dimitrios Georgakopoulos, Lizhe Wang
2015 IEEE Transactions on Cloud Computing  
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  ...  Such applications hosted on single or multiple cloud provider platforms have diverse characteristics requiring extensive monitoring and benchmarking mechanisms to ensure run-time Quality of Service (QoS  ...  Big Data Analytics Application Scenario Such a burst of input data is hard to estimate or predict.  ... 
doi:10.1109/tcc.2015.2441715 fatcat:ixlxbede3rglnh7emtmhnhtg6q

Experiences in building a mOSAIC of clouds

Dana Petcu, Beniamino Martino, Salvatore Venticinque, Massimiliano Rak, Tamás Máhr, Gorka Lopez, Fabrice Brito, Roberto Cossu, Miha Stopar, Svatopluk Šperka, Vlado Stankovski
2013 Journal of Cloud Computing: Advances, Systems and Applications  
The diversity of Cloud computing services is challenging the application developers as various and non-standard interfaces are provided for these services.  ...  Few middleware solutions were developed until now to support the design, deployment and execution of service-independent applications as well as the management of resources from multiple Clouds.  ...  Particular attention was given in mOSAIC to the data services as part of the proof-of-concept applications which are dealing with big data (static and streaming).  ... 
doi:10.1186/2192-113x-2-12 fatcat:q4fd7ccswrgdrdn77spx2phluq

Cloud Elasticity: A Survey [chapter]

Athanasios Naskos, Anastasios Gounaris, Spyros Sioutas
2016 Lecture Notes in Computer Science  
Cloud elasticity is a unique feature of cloud environments, which allows for the on demand (de-)provisioning or reconfiguration of the resources of cloud deployments.  ...  The efficient handling of cloud elasticity is a challenge that attracts the interest of the research community. This work constitutes a survey of research efforts towards this direction.  ...  on top of the cloud infrastructure (Service Provider (SP)).  ... 
doi:10.1007/978-3-319-29919-8_12 fatcat:saqa4reabfajhk6zikgvgf2tee
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