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

Using resource-level information into nonadditive negotiation models for cloud market environments

Markets arise as an efficient way of organising resources in Cloud Computing scenarios. In Cloud Computing Markets, Brokers that represent both Clients and Service Providers meet in a Market and negotiate for the sales of resources or services. This paper defends the idea that efficient negotiations require of the usage of resource-level information for increasing the accuracy of negotiated Service Level Agreements and facilitating the achievement of both performance and business goals. A negotiation model based on the maximisation of nonadditive utility functions that considers multiple objectives is defined, and its validity is demonstrated in the experiments.Postprint (published version

A non-additive negotiation model for utility computing markets

Market-based resource allocation is a promising model for dealing with the growing Utility Computing environments, such as Grid or Cloud Computing. Agents that represent both service clients and providers meet in a market to negotiate the terms of the sale of resources. Additive negotiation models are extended because they are simple, but they are not valid for negotiations whose terms are not independent between them. This paper proposes a simple non-additive model for performing negotiations and demonstrates its validity through simulation experiments.Postprint (published version

Maximising revenue in cloud computing markets by means of economically enhanced SLA management

This paper proposes a bidirectional communication between market brokers and resource managers in Cloud Computing Markets. This communication is implemented by means of an Economically Enhanced Resource Manager (EERM), that supports the negotiation process by deciding which tasks can be allocated or not, and under which economic and technical conditions. The EERM also uses the economic information that collects from market layers to manage the resources accordingly to concrete BLOs. This paper shows several Business Policies and Rules for maximizing the revenue of a Cloud Provider that sells its services and resources in a market. Their validity is demonstrated through several experiments that shown how the application of these rules can have a positive influence in the revenue and minimize the violations of Service-Level Agreements.Preprin

Using resource-level information into nonadditive negotiation models for cloud market environments

Markets arise as an efficient way of organising resources in Cloud Computing scenarios. In Cloud Computing Markets, Brokers that represent both Clients and Service Providers meet in a Market and negotiate for the sales of resources or services. This paper defends the idea that efficient negotiations require of the usage of resource-level information for increasing the accuracy of negotiated Service Level Agreements and facilitating the achievement of both performance and business goals. A negotiation model based on the maximisation of nonadditive utility functions that considers multiple objectives is defined, and its validity is demonstrated in the experiments.Postprint (published version

Rule-based SLA management for revenue maximisation in cloud computing markets

This paper introduces several Business Rules for maximising the revenue of Providers in Cloud Computing Markets. These rules apply in both negotiation and execution time, and enforce the achievement of Business-Level Objectives by establishing a bidirectional data flow between market and resource layers. The experiments demonstrate that the revenue is maximized by using both resource data when negotiating, and economic information when managing the resources.Postprint (published version

Toward business-driven risk management for cloud computing

The Cloud computing paradigm is offering an innovative and promising vision concerning the Information and Communications Technology (ICT). Notwithstanding, the use of Cloud resources, which usually are external assets to their consumers, implies risk issues that must be taken into account. In this paper, we present a Cloud computing risk management approach aware of the Business-Level Objectives (BLOs) of a given Cloud organization. More to the point, we propose an innovatory SEmi-quantitative BLO-driven Cloud Risk Assessment (SEBCRA) as its core subprocess. In addition, we present, as a use case, a Cloud Service Provider (CSP) that is able to improve the achievement of a BLO, i.e. profit maximization, by managing, assessing, and treating Cloud risks. As demonstrated in the experimentation, this provider maximizes its profit by transferring risks of provisioning its private Cloud to third-party providers of Cloud infrastructures.Postprint (published version

Risk-driven proactive fault-tolerant operation of IaaS providers

In order to improve service execution in Clouds, the management of Cloud Infrastructure has to take measures to adhere to Service Level Agreements and Business Level Objectives, from the application layer through to how services are supported at the lowest hardware levels. In this paper a risk model methodology and holistic management approach is developed specific to the operation of the Cloud Infrastructure Provider and is applied through improvements to SLA fault tolerance in Cloud Infrastructure. Risk assessments are used to analyse execution specific data from the Cloud Infrastructure and linked to a business driven holistic management component that is part of a Cloud Manager. Initial results show improved eco-efficiency, virtual machine availability and reductions in SLA failure across the whole Cloud infrastructure by applying our combined risk-based fault tolerance approach.Postprint (author’s final draft

Extended resource management using client classification and economic enhancements

Commercialization of Grid resources will become more and more important as utility computing and the deployment of Grids gains momentum. This results in the necessity to not only base Grid components on technical aspects, but also to include economical aspects in their design. This paper presents a framework that links technical and economical aspects to the management of computational resources. Economic enhancements like dynamic pricing and client classification are introduced based on a technical resource management environment and positioned within this resulting in a proposed architecture for an Economically Enhanced Resource Manager (EERM). The introduced approach is evaluated considering various economic design criteria and example scenarios.Postprint (published version

EMOTIVE: the BSC’s engine for cloud solutions

Cloud computing is strongly based on virtualization, allowing applications to be multiplexed onto a physical resource while isolated from other applications sharing that physical resource. This technology simplifies the management of e-Infrastructures, but also requires additional effort if users are to benefit from it. Cloud computing must hide its underlying complexity from users: the key is to provide users with a simple but functional interface for accessing IT resources "as a service", while allowing providers to build costeffective self-managed systems for transparently managing these resources. System developers should be also supported with simple tools that allow them to exploit the facilities of cloud infrastructures.Peer ReviewedPostprint (published version