1,472 research outputs found
Notes on Cloud computing principles
This letter provides a review of fundamental distributed systems and economic
Cloud computing principles. These principles are frequently deployed in their
respective fields, but their inter-dependencies are often neglected. Given that
Cloud Computing first and foremost is a new business model, a new model to sell
computational resources, the understanding of these concepts is facilitated by
treating them in unison. Here, we review some of the most important concepts
and how they relate to each other
Resource provisioning in Science Clouds: Requirements and challenges
Cloud computing has permeated into the information technology industry in the
last few years, and it is emerging nowadays in scientific environments. Science
user communities are demanding a broad range of computing power to satisfy the
needs of high-performance applications, such as local clusters,
high-performance computing systems, and computing grids. Different workloads
are needed from different computational models, and the cloud is already
considered as a promising paradigm. The scheduling and allocation of resources
is always a challenging matter in any form of computation and clouds are not an
exception. Science applications have unique features that differentiate their
workloads, hence, their requirements have to be taken into consideration to be
fulfilled when building a Science Cloud. This paper will discuss what are the
main scheduling and resource allocation challenges for any Infrastructure as a
Service provider supporting scientific applications
Business-driven resource allocation and management for data centres in cloud computing markets
Cloud Computing markets arise as an efficient way to allocate resources for the execution of tasks and services within a set of geographically dispersed providers from different organisations. Client applications and service providers meet in a market and negotiate for the sales of services by means of the signature of a Service Level Agreement that contains the Quality of Service terms that the Cloud provider has to guarantee by managing properly its resources.
Current implementations of Cloud markets suffer from a lack of information flow between the negotiating agents, which sell the resources, and the resource managers that allocate the resources to fulfil the agreed Quality of Service. This thesis establishes an intermediate layer between the market agents and the resource managers. In consequence, agents can perform accurate negotiations by considering the status of the resources in their negotiation models, and providers can manage their resources considering both the performance and the business objectives. This thesis defines a set of policies for the negotiation and enforcement of Service Level Agreements. Such policies deal with different Business-Level Objectives: maximisation of the revenue, classification of clients, trust and reputation maximisation, and risk minimisation. This thesis demonstrates the effectiveness of such policies by means of fine-grained simulations.
A pricing model may be influenced by many parameters. The weight of such parameters within the final model is not always known, or it can change as the market environment evolves. This thesis models and evaluates how the providers can self-adapt to changing environments by means of genetic algorithms. Providers that rapidly adapt to changes in the environment achieve higher revenues than providers that do not.
Policies are usually conceived for the short term: they model the behaviour of the system by considering the current status and the expected immediate after their application. This thesis defines and evaluates a trust and reputation system that enforces providers to consider the impact of their decisions in the long term. The trust and reputation system expels providers and clients with dishonest behaviour, and providers that consider the impact of their reputation in their actions improve on the achievement of their Business-Level Objectives.
Finally, this thesis studies the risk as the effects of the uncertainty over the expected outcomes of cloud providers. The particularities of cloud appliances as a set of interconnected resources are studied, as well as how the risk is propagated through the linked nodes. Incorporating risk models helps providers differentiate Service Level Agreements according to their risk, take preventive actions in the focus of the risk, and pricing accordingly. Applying risk management raises the fulfilment rate of the Service-Level Agreements and increases the profit of the providerPostprint (published version
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
Truthful Mechanisms For Resource Allocation And Pricing In Clouds
A major challenging problem for cloud providers is designing efficient mechanisms for
Virtual Machine (VM) provisioning and allocation. Such mechanisms enable the cloud
providers to effectively utilize their available resources and obtain higher profits. Recently,
cloud providers have introduced auction-based models for VM provisioning and allocation
which allow users to submit bids for their requested VMs. We formulate the dynamic
VM provisioning and allocation problem for the auction-based model as an integer program
considering multiple types of resources. We then design truthful greedy and optimal
mechanisms for the problem such that the cloud provider provisions VMs based on the
requests of the winning users and determines their payments. We show that the proposed
mechanisms are truthful, that is, the users do not have incentives to manipulate the system
by lying about their requested bundles of VM instances and their valuations. We perform
extensive experiments using real workload traces in order to investigate the performance
of the proposed mechanisms. Our proposed mechanisms achieve promising results in terms
of revenue for the cloud provider
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