Reliable capacity provisioning for distributed cloud/edge/fog computing applications

@article{stberg2017ReliableCP,
  title={Reliable capacity provisioning for distributed cloud/edge/fog computing applications},
  author={Per-Olov {\"O}stberg and James Byrne and Paolo Casari and Philip Eardley and Antonio Fern{\'a}ndez and Johan Forsman and John M. Kennedy and Thang Le Duc and Manuel Noya Marino and Radhika Loomba and Miguel Angel L{\'o}pez Pe{\~n}a and Jose Lopez Veiga and Theo Lynn and Vincenzo Mancuso and Sergej Svorobej and Anders Torneus and Stefan Wesner and Peter Willis and J{\"o}rg Domaschka},
  journal={2017 European Conference on Networks and Communications (EuCNC)},
  year={2017},
  pages={1-6}
}
The REliable CApacity Provisioning and enhanced remediation for distributed cloud applications (RECAP) project aims to advance cloud and edge computing technology, to develop mechanisms for reliable capacity provisioning, and to make application placement, infrastructure management, and capacity provisioning autonomous, predictable and optimized. This paper presents the RECAP vision for an integrated edge-cloud architecture, discusses the scientific foundation of the project, and outlines plans… 

Figures from this paper

RECAP (Reliable Capacity Provisioning and Enhanced Remediation for Distributed Cloud Applications): The Simulation Approach

TLDR
The outcomes of the project will pave the way for a radically novel concept in the provision of cloud services, where services are instantiated and provisioned close to the users that actually need them by self-configurable cloud computing systems.

Application, Workload, and Infrastructure Models for Virtualized Content Delivery Networks Deployed in Edge Computing Environments

TLDR
It has been shown that leveraging edge resources for the deployment of caches of content greatly benefits CDNs, and the models are described from an edge computing perspective and intended to be integrated in network topology aware application orchestration and resource management systems.

Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing

TLDR
This article investigates the problem of reliable resource provisioning in joint edge-cloud environments, and surveys technologies, mechanisms, and methods that can be used to improve the reliability of distributed applications in diverse and heterogeneous network environments.

Next Generation Cloud Architectures

TLDR
The need for heterogeneous resources integration in resource provisioning and the necessity to find the golden ratio between the cloud, fog and edge for optimal user experience are discussed.

Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

TLDR
An overview of challenges posed by fog and edge computing in relation to simulation is provided and simulation frameworks used extensively in the modelling of cloud computing environments are used extensively.

1 Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing : A Survey

TLDR
This paper investigates the problem of reliable resource provisioning in joint edge-cloud environments and surveys technologies, mechanisms, and methods that can be used to improve the reliability of distributed applications in diverse and heterogeneous network environments.

Mobile Services Meet Distributed Cloud: Benefits, Applications, and Challenges

TLDR
Distributed cloud can prove itself to bring many benefits for mobile service such as reducing network latency, as well as computational and network overhead at the central cloud.

Orchestration in Fog Computing: A Comprehensive Survey

TLDR
A generic architecture of fog orchestration is presented, created from the consolidation of the analyzed proposals, bringing to light the essential functionalities addressed in the literature.

Hierarchical Capacity Provisioning for Fog Computing

TLDR
This work considers a two-tier network architecture consisting of shallow and deep cloudlets and explores the benefits of hierarchical capacity provisioning based on queuing analysis and models two different network scenarios in which the network delay between the two tiers is negligible.

Energy Minimized Federated Fog Computing over Passive Optical Networks

TLDR
A federated fog computing architecture where multiple distributed fog cells collaborate in serving users is proposed and an increase in processing capacity and a reduction in the power consumption is shown by up to 26% compared to a Non-Federated fogs computing architecture.
...

References

SHOWING 1-10 OF 32 REFERENCES

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

TLDR
The CACTOS approach to cloud infrastructure automation and optimization is presented, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers.

Dynamic Topology Orchestration for Distributed Cloud-Based Applications

TLDR
The viability and benefits of this architectural approach are compared against simpler strategies, to establish technical and business cases for the associated engineering effort.

Cloudsim: simulator for cloud computing infrastructure and modeling

Virtual Machine Provisioning Based on Analytical Performance and QoS in Cloud Computing Environments

TLDR
A provisioning technique that automatically adapts to workload changes related to applications for facilitating the adaptive management of system and offering end-users guaranteed Quality of Services (QoS) in large, autonomous, and highly dynamic environments is presented.

Q-clouds: managing performance interference effects for QoS-aware clouds

TLDR
Q-Clouds, a QoS-aware control framework that tunes resource allocations to mitigate performance interference effects, is developed, which uses online feedback to build a multi-input multi-output (MIMO) model that captures performance interference interactions, and uses it to perform closed loop resource management.

Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures

TLDR
Mistral is presented, a holistic controller framework that optimizes power consumption, performance benefits, and the transient costs incurred by various adaptations and the controller itself to maximize overall utility.

Performance Modelling and Simulation of Three-Tier Applications in Cloud and Multi-Cloud Environments

TLDR
An analytical performance model of 3-tier applications in Cloud and Multi-Cloud environments that takes into account the performance of the persistent storage and the heterogeneity of cloud data centres in terms of Virtual Machine (VM) performance is proposed.

SLA-based Optimization of Power and Migration Cost in Cloud Computing

TLDR
An efficient heuristic algorithm based on convex optimization and dynamic programming is presented to solve the resource allocation problem of cloud computing system while meeting the specified client-level SLAs in a probabilistic sense.

The CloudMIG Approach: Model-Based Migration of Software Systems to Cloud-Optimized Applications

TLDR
This work aims at supporting SaaS providers to semi-automatically migrate existing enterprise software systems to scalable and resource-efficient PaaS and IaaS-based applications and introduces the Cloud Suitability and Alignment (CSA) hierarchy.

Service workload patterns for Qos-driven cloud resource management

TLDR
This work proposes a prediction technique that combines a workload pattern mining approach with a traditional collaborative filtering solution to meet the accuracy and efficiency requirements of a continuous approach to cloud performance management.