10,221 research outputs found
SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions
Cloud computing systems promise to offer subscription-oriented,
enterprise-quality computing services to users worldwide. With the increased
demand for delivering services to a large number of users, they need to offer
differentiated services to users and meet their quality expectations. Existing
resource management systems in data centers are yet to support Service Level
Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to
realize cloud computing and utility computing. In addition, no work has been
done to collectively incorporate customer-driven service management,
computational risk management, and autonomic resource management into a
market-based resource management system to target the rapidly changing
enterprise requirements of Cloud computing. This paper presents vision,
challenges, and architectural elements of SLA-oriented resource management. The
proposed architecture supports integration of marketbased provisioning policies
and virtualisation technologies for flexible allocation of resources to
applications. The performance results obtained from our working prototype
system shows the feasibility and effectiveness of SLA-based resource
provisioning in Clouds.Comment: 10 pages, 7 figures, Conference Keynote Paper: 2011 IEEE
International Conference on Cloud and Service Computing (CSC 2011, IEEE
Press, USA), Hong Kong, China, December 12-14, 201
Engineering a QoS Provider Mechanism for Edge Computing with Deep Reinforcement Learning
With the development of new system solutions that integrate traditional cloud
computing with the edge/fog computing paradigm, dynamic optimization of service
execution has become a challenge due to the edge computing resources being more
distributed and dynamic. How to optimize the execution to provide Quality of
Service (QoS) in edge computing depends on both the system architecture and the
resource allocation algorithms in place. We design and develop a QoS provider
mechanism, as an integral component of a fog-to-cloud system, to work in
dynamic scenarios by using deep reinforcement learning. We choose reinforcement
learning since it is particularly well suited for solving problems in dynamic
and adaptive environments where the decision process needs to be frequently
updated. We specifically use a Deep Q-learning algorithm that optimizes QoS by
identifying and blocking devices that potentially cause service disruption due
to dynamicity. We compare the reinforcement learning based solution with
state-of-the-art heuristics that use telemetry data, and analyze pros and cons
InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services
Cloud computing providers have setup several data centers at different
geographical locations over the Internet in order to optimally serve needs of
their customers around the world. However, existing systems do not support
mechanisms and policies for dynamically coordinating load distribution among
different Cloud-based data centers in order to determine optimal location for
hosting application services to achieve reasonable QoS levels. Further, the
Cloud computing providers are unable to predict geographic distribution of
users consuming their services, hence the load coordination must happen
automatically, and distribution of services must change in response to changes
in the load. To counter this problem, we advocate creation of federated Cloud
computing environment (InterCloud) that facilitates just-in-time,
opportunistic, and scalable provisioning of application services, consistently
achieving QoS targets under variable workload, resource and network conditions.
The overall goal is to create a computing environment that supports dynamic
expansion or contraction of capabilities (VMs, services, storage, and database)
for handling sudden variations in service demands.
This paper presents vision, challenges, and architectural elements of
InterCloud for utility-oriented federation of Cloud computing environments. The
proposed InterCloud environment supports scaling of applications across
multiple vendor clouds. We have validated our approach by conducting a set of
rigorous performance evaluation study using the CloudSim toolkit. The results
demonstrate that federated Cloud computing model has immense potential as it
offers significant performance gains as regards to response time and cost
saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape
QoSatAr: a cross-layer architecture for E2E QoS provisioning over DVB-S2 broadband satellite systems
This article presents QoSatAr, a cross-layer architecture developed to provide end-to-end quality of service (QoS) guarantees for Internet protocol (IP) traffic over the Digital Video Broadcasting-Second generation (DVB-S2) satellite systems. The architecture design is based on a cross-layer optimization between the physical layer and the network layer to provide QoS provisioning based on the bandwidth availability present in the DVB-S2 satellite channel. Our design is developed at the satellite-independent layers, being in compliance with the ETSI-BSM-QoS standards. The architecture is set up inside the gateway, it includes a Re-Queuing Mechanism (RQM) to enhance the goodput of the EF and AF traffic classes and an adaptive IP scheduler to guarantee the high-priority traffic classes taking into account the channel conditions affected by rain events. One of the most important aspect of the architecture design is that QoSatAr is able to guarantee the QoS requirements for specific traffic flows considering a single parameter: the bandwidth availability which is set at the physical layer (considering adaptive code and modulation adaptation) and sent to the network layer by means of a cross-layer optimization. The architecture has been evaluated using the NS-2 simulator. In this article, we present evaluation metrics, extensive simulations results and conclusions about the performance of the proposed QoSatAr when it is evaluated over a DVB-S2 satellite scenario. The key results show that the implementation of this architecture enables to keep control of the satellite system load while guaranteeing the QoS levels for the high-priority traffic classes even when bandwidth variations due to rain events are experienced. Moreover, using the RQM mechanism the user’s quality of experience is improved while keeping lower delay and jitter values for the high-priority traffic classes. In particular, the AF goodput is enhanced around 33% over the drop tail scheme (on average)
- …