• Corpus ID: 232105169

Capelin: Data-Driven Capacity Procurement for Cloud Datacenters using Portfolios of Scenarios - Extended Technical Report

  title={Capelin: Data-Driven Capacity Procurement for Cloud Datacenters using Portfolios of Scenarios - Extended Technical Report},
  author={George Andreadis and Fabian Mastenbroek and Vincent van Beek and Alexandru Iosup},
Cloud datacenters provide a backbone to our digital society. Inaccurate capacity procurement for cloud datacenters can lead to significant performance degradation, denser targets for failure, and unsustainable energy consumption. Although this activity is core to improving cloud infrastructure, relatively few comprehensive approaches and support tools exist for mid-tier operators, leaving many planners with merely rule-of-thumb judgement. We derive requirements from a unique survey of experts… 

Capelin: Data-Driven Compute Capacity Procurement for Cloud Datacenters Using Portfolios of Scenarios

The proposed Capelin, a data-driven, scenario-based capacity planning system for mid-tier cloud datacenters, is implemented and open-source, and it is shown through comprehensive trace-based experiments it can aid practitioners.



The cost of a cloud: research problems in data center networks

This work examines the costs of cloud service data centers today and proposes (1) joint optimization of network and data center resources, and (2) new systems and mechanisms for geo-distributing state.

Metrics and techniques for quantifying performance isolation in cloud environments

This paper proposes three different types of novel metrics for quantifying the performance isolation of cloud-based systems and a simulation-based case study applying these metrics in the context of a Softwareas-a-Service (SaaS) scenario where different customers (tenants) share one single application instance.

Stochastic Model Driven Capacity Planning for an Infrastructure-as-a-Service Cloud

Simulated annealing, a well-known stochastic search algorithm, is used to solve two cost minimization problems to address the capacity planning in an IaaS Cloud and shows that the optimal solutions are found within reasonable time.

A CPU Contention Predictor for Business-Critical Workloads in Cloud Datacenters

This work investigates the contention in CPU resources, as CPU is allowed to be over-committed by typical SLAs, and proposes a CPU-contention predictor for the demanding business-critical workloads, which require low resource contention to deliver the required performance to customers.

An optimized capacity planning approach for virtual infrastructure exhibiting stochastic workload

The results illustrate that reserving certain amount of resources in servers for addressing variability of workloads gives better results in terms of lesser number of servers compared to packing resources based on peak workloads for the same service levels.

The Datacenter as a Computer: Designing Warehouse-Scale Machines, Third Edition

This book describes warehouse-scale computers (WSCs), the computing platforms that power cloud computing and all the great web services the authors use every day, and details the main factors influencing their design, operation, and cost structure, and the characteristics of their software base.

Statistical Characterization of Business-Critical Workloads Hosted in Cloud Datacenters

  • S. ShenV. V. BeekA. Iosup
  • Computer Science, Business
    2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
  • 2015
This study sheds light into the workload of cloud data enters hosting business-critical workloads and collects large-scale and long-term workload traces corresponding to requested and actually used resources in a distributed datacenter servicing business- critical workloads.

The OpenDC Vision: Towards Collaborative Datacenter Simulation and Exploration for Everybody

This work envisioning the exploration of various datacenter concepts and technologies, using existing and new scientific methods, enabling new education practices and topics, and leading to the creation of new software and data artifacts on OpenDC.

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.

Performance-Based Pricing in Multi-Core Geo-Distributed Cloud Computing

This paper proposes a non-linear power model that estimates power dissipation of a multi-core CPU physical machine (PM) and second a pricing model that adjusts the pricing based on the VM's CPU-boundedness characteristics and presents a cloud controller that uses these models to allocate VM and scale CPU frequencies of the physical machine.