A Process for Clouds Services Procurement Based on Model and QoS

Hélder Pereira Borges 1,2

José Neuman de Souza 2

Computer Science Federal Institute of Maranhão - IFMA

São Luís, Brasil 2 Federal University of Ceará - UFC

Fortaleza, Brasil helderpb@hotmail.com

Bruno Schulze 3Antonio Roberto Mury 3

Computer Science 3 National Laboratory for Scientific Computing - LNCC

Petrópolis, Brasil bruno.schulze@gmail.com

Abstract - A relevant challenge for cloud computing is related to quality control of the services available. Cloud providers sometimes just deliver services, but do not clearly define quality of services guarantees. In addition, each provider uses a particular process to provide services. In this way, aiming to define a service procurement process to clouds, this paper proposes an approach based on a cloud environment model, considering service quality preservation.

The proposed process will use an environment model containing all relevant information to create a virtual workspace, taking into account requirements of hardware and software and quality parameters, all of them specified by users.From this model, it will be possible to automatically provide platform and infrastructure as a service.

The agreement negotiation happens during the service acquisition process from automated agents, creating the services and monitoring their quality attributes, generating an environment less error-prone, increasing the customer level satisfaction.

Index Terms - Cloud Computing; Models; Service Procurement; SLA; QoS.

I. INTRODUCTION

A fact commonly observed in the cloud computing context is the lack of a standard procedure for services request that takes into account the user requirements. Each providerdefines how this process should happen, usually just based on its convenience, not necessarily considering the real user's needs. The National Science Foundation - NSF, confirms this reality through the program Strategic Technology for Cyber Infrastructure (STCI), which calls initiatives with proposals to standardize and automate access to cloud services. Within this perspective, this work defines a process based on users' requirements for services procurement and presents a systemassociated with clouds that has the objective of to create automatically personalized services and to ensure their quality.This project is called GerNU.

The main artifact in this structure is a virtual environment model, containing all information required for a service to be available. After the model creation, there are three perspectives that can be taken: 1. The cloud provider develops a mechanism for mapping this virtual environment model to its own virtual structure. This is not a promising perspectivedue external dependence. 2. Add to proposed system a mapping mechanism, to one or more specific kinds of virtual images usually used by cloud providers. It creates small

dependencies that must be negotiated between the provider and the system, representing a real possibility. 3. From the model, the proposed system, should automatically and dynamically creates and delivers services to users. This is our future work.

The paper scope will be restricted to the second option. So,after the acquisition service process definition we developed amechanism that maps the environment model created during the service specification to the structure used by the middleware Neblina [6]. In other words, the user will specify exactly their requirements (hardware, software and quality of service), GerNU creates a virtual image that is sent to Neblina that provides the service. In this way, this work will describe a process to hire cloud services and will assess its operation.

Section 2 presents the main topics related to this work and some related works. In section 3 is depicted the GerNU and its procurement process. Section 4 presents a case study and evaluation. Finally in section 5, closing remarks and future work.

II. RELATED WORKS

As far as was possible to research, it wasn't possible identify in the scientific literature works that are similar to the general context of this proposal. Thus, we described works related to some challenges in the cloud context and that encouraged the policies adopted in this proposal, as QoS parameters, SLA and models, all them aiming to improve the cloud services.

A. Cloud Computing Cloud computing is a paradigm that proposes an

abstraction in providing computing resources, so that they are available as services. One of the reasons for clouds success is that its features can be used in the business and academic context, being its efficiency verified through applications in real problems.

The use of specialized companies to provide computing resources represents to basic idea of cloud computing. In this context, the resources supply is abstracted from the user and the management and maintenance become the responsibility of specialists. Moreover, the resources provision must be done in several layers, representing a specific kind of resources provided as a service (Infrastructure - IaaS, Platform - PaaS or

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Software - SaaS). These abstractions hide the infrastructure complexity [3].

Another important feature is the payment based on resource utilization [12]. Clouds represent a scalability scenario unprecedented, providing services, resources, processes and infrastructure and improving flexibility to information technology structures. Furthermore, decreasing the business cost through on-demand services.

Patterns are described in [5] as one way to document architectural principles and to make good solutions to recurring cloud challenges.

This work was developed in the context of cloud computing, considering that the cloud structure is maintained by a large resources set that support on demand services. Thus, an approach to assist the cloud management and service quality monitoring is very important, as well as a process definition to service procurement that merges the negotiation of SLA guarantees during the services procurement [1], and how it serves as a basis for resource allocation, verification and assurance of this guarantees.

B. Quality of Service Parameters (QoS) Normally proposals for resource provisioning have been

based on best effort policies, they do the possible to meet the user's request, but do not taking into account the QoS. In work [4] is depicted this problem, presenting a proposal focused on QoS aspects, describing how to deliver Service Level Agreement (SLA) based on guarantees for QoS.

Virtualization is used by providers to host independent services on their servers, this practice introduces interference in the physical machine performance, reflecting in the virtual machines, fact that may significantly affect the QoS requirements [8].

A method for allocating resources for cloud services, considering processing, memory, network speed, reliability and throughput is shown in work [9], where are presented algorithms for data partitioning, allowing data parallel transfer.Moreover, approaches that evaluate and rank components areimportant for selection and identification of components with high/low performance [15].

One purpose of this work is to define quality parameters relevant to the clouds context. These parameters must correctly identify the QoS and monitoring regularly theserequirements, setting a good level of trust between provider and user.

C. Service Level Agreement - SLA The QoS parameters must be described in an SLA, as well

as their values. They should be adequate to meet the clients’ requests. Furthermore, the services must be accompanied by precise definitions of their proposals and use conditions. The SLAs warranty terms, normally, are not explicitly related toperformance metrics or configuration parameters, making it difficult for providers to monitor the process. This lack of connection between SLAs parameters and metrics is a major obstacle to management, considering planning, forecasting or reconfiguration process [2].

The SLA should clearly specify a threshold that must be met to each requirement and penalties should be explained for case of failure. Although there wasn't great complexity in managing an SLA with few services, it becomes complex when it is necessary to meet SLAs for thousands of applications that use shared resources [13].

The article [14] describes the need for mechanisms to make the negotiation process more interactive and automated. This automation involves the definition of standard protocols that serve to check the contract requirements and to define the operating parameters of available resources.

This work uses SLA in order to define the user and provider responsibilities, allowing the agreements verification during the services execution, making the SLA be more efficient and reliable.

D. Model Driven Approach Models are widely used in the computational context,

being possible to perceive several benefits, such as standardization, information exchange, mapping between different structures, among others. Models can be used to automate complex processes in the cloud computing environment. Furthermore, using mechanisms to import and to export the components of model structure, it's possible to add flexibility to the process. This fact allows that a work environment can be migrated from one provider to another, enabling users to choose between the service providers, that one that will provide the best service. Models utilization raises the system abstraction level, favoring the planning and understanding during systems development, furthermore, removing technological advances effects [7], [12].

The work [10] considers that the development of software-dependent technology is not viable in the long term, taking into account the rapid emergence of new technologies. The article describes an approach for cloud services development that is specific technologies independent, using MDA (Model Driven Architecture).

The model-driven approach becomes relevant in this work because they may contain several types of information, such as user data, specification of hardware/software, among others. These information will be used to create the virtual environment and to monitor the QoS.

E. Summary GerNU, take into account the relevance of standardization

in cloud context, intends to define procedures for managing clouds that consider the users requirements, bringing benefits to provider and constumer. Considering the importance of using suitable quality parameters for clouds and the need to ensure the QoS, GerNU initially presents quality parameters based on the dependability concept. Regarding SLA, one goal for GerNU is automate the most of the negotiation process, making it simple and intuitive, reducing human intervention and speeding up the service delivery process to the user, making more effective the SLA use. GerNU adopts a model driven approach, using models to create structures that are technology independents and can be manipulated from their

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models, intending that all system activities should happen around of them.

III. PROPOSED APPROACH - GERNUThis project presents a proposal for managing clouds.

Users can connect and request services based on the SLA specifications. The GerNU’s goal is to meet these requests efficiently, providing the necessary information about the resources to support these services and transparently createsthe virtual environment through virtualization. Its scope is still limited, but intends to provide solutions to three major challenges, described below. Figure 1 shows the generic problem scenario addressed in this paper.

1. Service Procurement Standardization - A fact noted in the cloud context is that there is not a standard service acquisition procedure taking into account the user requirements. Each provider defines how this process should happen, considering just its particular policies. Noting this fact, we propose a process acquisition to cloud services.

Fig. 1. Problem Scenario

2. Service Delivery Automation - Distributed and heterogeneous cloud environment has a number of complex tasks for services provision. Automatic services instantiation allows minimal or no human intervention. This automation accelerates and adds quality for services provision process, making the execution of these procedures with lower error rate.

3. QoS Management - The user's need not finish when he has an available service. Specific metrics are necessary to evaluate the QoS. Available services must be within the quality parameters required by the user, so it is necessary to identify relevant parameters for clouds and to perform their

monitoring, assessing whether these parameters are between acceptable thresholds.

This section has the objective to present briefly the GerNU system, its process of procurement service and main features.

A. Proposed Process This work defines a requisition process for cloud services,

it is model-based and considers QoS, aiming to ensure the SLA guarantees. This process is operationalized from a virtual environment model. Moreover, from this model it is possible to import and to export services between providers, mapping the model to the provider’s specific structure.

The activities specified by process were designed to meet the users' needs, related to hardware and software, unlike the usual imposition of prefabricated virtual images made by the providers. Furthermore, to manage its resources efficiently, the provider must specify exactly which parameters can be supported by its infrastructure. Figure 2 shows the proposed process, followed by activities description.

Fig. 2. Proposed Process

Requirements Specification - The purpose of this activity is to allow the user to specify his exact requirements for hardware (CPU, memory, storage, others) and software (operating system and applications), necessary to its virtual environment. In addition, the user must to specify the quality attributes, which he wants to hire. This is a flexible creating process, for personalized services that takes into account the available resources, aiming to ensure the SLA.

Registration - The user should create an account in the provider to hire a service. It’s necessary personal information, as email, credit card number and others. This account will be used to access the services and to contacts, charges and reimbursements.

Negotiation - This activity aims to enable negotiation of hardware requirements, quality attributes and service values, being possible negotiate a greater or lesser amount of these items. It is an interactive activity and should be as automated as possible.

Dynamic Configuration - The virtual environment must represent exactly the requirements specified by the user, so this activity is responsible for creating in real-time the virtual structure that will support the user's personalized service. This is a complex task considering the heterogeneous cloud computing environment.

Service Providing - This activity is related to the effective service delivery to the user, being necessary a management of services access to preserve the user’s data.

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Service Monitoring - After the service be available to the user, it is started the quality parameters monitoring, to ensure the agreed SLA with an efficient service.

From the activities proposed by this process, considering that the relevant information for each activity will be structured on an environment model, it's possible to automatically instantiate the services and ensure their quality.Other great advantage of this process is the flexibility related to service specification

B. Proposed Scenario The scenario depicted in Figure 3 was developed to

provide an environment in which the user specifies their needs, negotiate the terms of services guarantees, as well as their values in simplified way, and then dynamically and automatically have the service available in the cloud.

Fig. 3.Proposed Scenario

This scenario consists of four phases, in which the customer interacts in the first and the second specifying his intentions, while the third and fourth phases are controlled by automated processes, and they are related to service implementation, to ensure the SLA and the monitoring. The purpose of these phases and how they attend the proposed process is described below and their relation can be seen in the Figure 4.

Fig. 4. Scenario attending the Process

The first process's activity is related to requirements specification. This phase is developed during the GerNU's Specification Phase. It represents the definition about the kind of service, choosing between IaaS and PaaS. Moreover, must be specified the hardware requirements and QoS attributes. For each specification, the system provides three hardware (cpu, memory, storage, among others) configurations (minimal, flexible and robust) as well as the associated fees.

Still it's possible make a definition with specific hardware values. All these specifications are chosen through simple selections in a GerNU's graphical interface, making the procedure simpler and faster.

The process's registration and negotiation activities are contemplated in the GerNU through Negotiation Phase. This phase starts from user's account creation. Following, an SLA will be generated by system, specifying terms and guarantees for the service, providing the attributes for the quality parameters. These information will serve as a starting point for the negotiation process.

The Implementation Phase was designed to meet the activities related to dynamic configuration and to provide the service. This phase works from an automatic process started to create a virtual machine in accordance with requirements agreed in the SLA. It considers the hardware requirement, operating system and the applications specified by user, in order to provide an adequate performance to preserve the QoS attributes. The entire process occurs dynamically and in real time, because there are not prefabricated images in the GerNU's environment.

The activity defined by pattern to ensure the QoS is met through the Monitoring Phase. It starts when the user's service is available. If there is QoS degradation, the cloud's administrator is warned and the environment model should be updated to meet the customer expectations in accordance with the SLA specifications. This update is made by system agents that control the GerNU’s functionalities.

C. Environment Model After the negotiation phase, considering that an agreement

was established, an environment model is generated, containing all information about hardware, software and QoSto provide the agreed service, based on information extracted from the SLA. In GerNU, the environment model contains three major kinds of information items, but it structure allows the addition of others information, given flexibility to this approach. All model’s information are described in XML (Extensible Markup Language) format. Following, a brief description:

a) Infrastructure: describe information about the hardware and software specification that are available on the platform. This information is collected during the specification phase, where the user selects software structure and will be informed of the minimum requirements.

b) Administration: composed by the information collected during the first stage of the negotiation and are related to the user's data. To make effective the service requisition or to negotiate the requirements or values, the user should make his registration.

c) Quality: describes the SLA guarantees, related to QoS parameters, in according with specification required by user. This information is collected during the second stage of negotiation phase and represents the target attributes during the monitoring phase, being extremely important to ensure that the terms of the SLA are met.

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D. Automatic Instantiation In the GerNU, there are not images previously configured,

they are created at runtime to meet the specific user requirements related to hardware and software. In this way, a Preboot eXecution Environment (PXE) provides a standard for performing remote boot, allowing a physical or virtual machine, to perform its initialization and the installation of an operating system over the network, being all necessary files loaded to boot from a FTP service.

Usually, a PXE server is used to simultaneously install the same operating system distribution on multiple machines across the network, for example, when there are 1000 machines that need a specific operating system installed, the manual process consumes large amount of time, but using a PXE server, it is only necessary to connect all the machines on the network and power them on to automatically starts the installation.

To attend the GerNU necessities, the PXE approach was modified to meet the dynamic profile of the cloud activities, and it is used as a mechanism for custom installation, which starting from the user's specifications, defining the operating system dynamically and also what applications will be used to construct the image that will be worn by the virtualizer to provide services. The PXE configuration files in the GerNU's environment, starts predetermining an installation directory for the operating systems (OS) available in the system's repository, containing the files for boot and installation. Just adding a new directory, others OS will be available.

E. Preserving QoS GerNU defined quality parameters for IaaS considering the

dependability concept. From this concept, the parameters have been adapted to suit the cloud characteristics, being relevant in the QoS evaluation. Following, we described the initial quality criteria adopted, with the tables I, II, III and IV specifying the parameters for each one.

Availability: is related to how much time the service should be available for customer use, without interruption. It's relevant attribute that should have a big impact in the user’s purposes.

TABLE I. AVAILABILITY

Ref Attribute Description0 Unadopted No guarantees.1 50% The service will be available at least

50% of the contacted time. 2 70% The service will be available at least

70% of the contacted time.3 100% Assurance that the service will

always be available.

Backup Policy: covers the concept of security (safety) and integrity referred by dependability [8]. Thus, this attribute provides guarantees against intrusion, disasters and undue modifications. It aims to ensure that user information will be preserved, both related to their infrastructure as their business data.

TABLE II. BACKUP POLICY

Ref Attribute Description0 Unadopted No guarantees.1 No Access Backup without audit.2 Access Backup audited by user.3 User Domain Mechanisms for backup available,

but under the user responsibility.

Monitoring of Virtual Environment: relates to the identification of workload levels in the virtual machines. Aims to map the use level of allocated resources to the client. It is observed that, even without the SLA violations, may be occurring overloads or waste of resources, facts that are bad for both the client and the provider, and then the user may be warned to change his specification.

TABLE III. MONITORING OF VIRTUAL ENVIRONMENT

Ref Attribute Description0 Unadopted No guarantees.1 Monitored Reporting.

Variability: considers that, the use of virtualization and resource sharing may present significant loss of performance, thus this attribute is used to ensure variation limits in service performance.

TABLE IV. VARIABILITY

Ref Attribute Description0 Unadopted No guarantees.1 76 - 100 % Assurance the variation rate.2 51 - 75 % Assurance the variation rate.3 26 - 50 % Assurance the variation rate.

Each cloud provider must correctly identify which kind of parameter and what attributes may guarantee. The provider is responsible to endorse the provision of mechanisms for each kind of attribute offered.

IV. CASE STUDY This is an initial GerNU assessment and its objective is to

verify if the process of creation and delivery of services occurs correctly. In this moment, aspects of negotiation and monitoring are not been contemplated. To evaluate the proposal was used a middleware for cloud computing calledNeblina [6]. It is focused on usability, able to configure and monitor resources, store files, generate dedicated virtualizedwork environments, since platforms until virtual clusters, allowing them to be accessed remotely, easily and intuitively through a web interface. Neblina was used because, considering the accompaniment of its development, obtaining detailed information about the features of its cloud environment can be done in an easier way. In the Neblina perspective, the GerNU should contribute to the consolidation of the infrastructure that is being created.

The validation of the above proposal was achieved fromseveral simulations, where users utilize the system to make a service specification and negotiate the SLA, being extract the environment model to provide the service. All simulations

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performed in the test environment were successful. The service was provided correctly, validating the proposed approach. Figure 5 displays the Neblina’s screen showing an available service specified in GerNU. The average time needed to service provision was 4,5 minutes, reasonable time to create a virtual machine from scratch.

Figure 5. Available Service

Our preliminary positive results using a dedicated middleware, which has not the purpose of exchanging services, imply that in a generic middleware will also be possible. In the future, tests will be performed with othersmiddlewares, to compare the procedures and the results achieved.

V. CONCLUSION

Considering the lack of service procurement process forclouds that take into account user‘s requirements, this work proposes a system associated with cloud, in order to set a process for service request. This process is based on models and quality of services and was implemented through GerNUsystem. The GerNU's aim is to allow that an user defines hisspecific needs related to service, ensuring the quality of it. GerNU uses a model containing all virtual environment specifications. In its structure are present definitions about hardware infrastructure, operating system, applications and quality parameters. These definitions are made by the user.

The environment model becomes the most important artifact in the system. Activities as monitoring and updating happen based on it. Changes in the virtual environment occur firstly in the model and subsequently are reflected in the service. Moreover, the use of this model approach could be a valuable tool to map virtualized structures in any provider, allowing portability between different virtual environments.

Tests to create a service from GerNU were carried out successfully, the model was correctly mapped and the service was provided using a private cloud middleware called Neblina.

Currently, policies of monitoring are being specified, considering quality attributes already defined, moreover, a automatic and dynamic mechanism for creation and deliveryof virtual environments, by GerNU is being developed.

ACKNOWLEDGMENT

This article is based on work partially supported by the Funding Agency of Maranhão State (FAPEMA), BD-00526/09.

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