Cloud Service Broker Research Articles

Are Cloud Service Brokers (CSBs) Still Relevant?

Cloud Service Brokers (CSBs) rose in importance due to the diverse number of public and private cloud providers, and the need to manage the consumption of those services within an enterprise. As you can see in Figure 1, CSBs sit between the service consumers, which is typically an application, and the cloud service provider. CSBs provide the following services.

A performance brokerage for heterogeneous clouds

The trading of virtual machines, storage and other Cloud Computing resources on commodity exchanges has generated considerable interest from both academia and the financial services market. With multiple sellers providing appropriately equivalent virtual machines they become fungible, offering the opportunity for users to swap instances from one seller with instances from another when required, easing concerns over vendor lock-in, availability and provider failure. However, heterogeneity in the hardware from which they are provisioned is likely inevitable, given heterogeneity already found on a number of Public Clouds, where it results in performance variation across instances of the same type, and consequently variation in Cloud costs at the same price. To address this problem we propose a Cloud Service Broker (CSB) that acquires and re-sells instances on the basis of their current performance. The service reduces performance risk for users, but comes at a cost. We determine the average markup the CSB must add to the base instance price to cover the costs of operating a pool capable of satisfying a given proportion of requests. We show how increases in heterogeneity on the underlying commodity exchange lead to lower costs for the CSB, and that the largest degree of heterogeneity we consider, on the basis of real-world findings, leads to the best outcome: an average markup of just 12% on the buy price from the exchange will satisfy 95% of requests. This creates opportunities for CSB profitability to be explored on the basis of selling performance-assured instances at prices that will account for this markup

A MAS-Based Cloud Service Brokering System to Respond Security Needs of Cloud Customers

Cloud computing is becoming a key factor in computer science and an important technology for many organizations to deliver different types of services. The companies which provide services to customers are called as cloud service providers. The cloud users (CUs) increase and require secure, reliable and trustworthy cloud service providers (CSPs) from the market. So, it’s a challenge for a new customer to choose the highly secure provider. This paper presents a cloud service brokering system in order to analyze and rank the secured cloud service provider among the available providers list. This model uses an autonomous and flexible agent in multi-agent system (MASs) that have an intelligent behavior and suitable tools for helping the brokering system to assess the security risks for the group of cloud providers which make decision of the more secured provider and justify the business needs of users in terms of security and reliability.

Research challenges in legal-rule and QoS-aware cloud service brokerage

The ICT industry and specifically critical sectors, such as healthcare, transportation, energy and government, require as mandatory the compliance of ICT systems and services with legislation and regulation, as well as with standards. In the era of cloud computing, this compliance management issue is exacerbated by the distributed nature of the system and by the limited control that customers have on the services. Today, the cloud industry is aware of this problem (as evidenced by the compliance program of many cloud service providers), and the research community is addressing the many facets of the legal-rule compliance checking and quality assurance problem.Cloud service brokerage plays an important role in legislation compliance and QoS management of cloud services. In this paper we discuss our experience in designing a legal-rule and QoS-aware cloud service broker, and we explore relate research issues. Specifically we provide three main contributions to the literature: first, we describe the detailed design architecture of the legal-rule and QoS-aware broker. Second, we discuss our design choices which rely on the state of the art solutions available in literature. We cover four main research areas: cloud broker service deployment, seamless cloud service migration, cloud service monitoring, and legal rule compliance checking. Finally, from the literature review in these research areas, we identify and discuss research challenges.

User-Centric Cloud Service Broker

computing technology has gained enormous attention due to its promising capabilities such as virtualization, elasticity and the pay-per-use paradigm. Theoretically, cloud computing can offer Everything as a Service (XaaS). Selecting suitable cloud services matching the Quality-of- Service (QoS) requirements of the user is one of the prominent problems in the literature. A considerable number of research studies attempted to address this problem from different perspectives such as service discovery, service matching and ranking (against QoS requirements of the user) in addition to QoS evaluation and monitoring. In this paper, we argue that we need to integrate all those functionalities to help the cloud service user make more informed selection decisions. Accordingly, we propose a comprehensive user- centric Cloud Service Broker (CSB). We describe the architecture of this broker and discuss how it integrates and orchestrates the different required functionalities. We also discuss different possible methods to realize and implement each of its modules and pinpoint open points of research that need to be explored further. As a proof of concept, we present an example prototype implementation of CSB and discuss a case study using this prototype to justify the advantage of the integration. Towards this goal, we propose a novel evaluation- aware matching and ranking technique that integrates cloud services evaluation results with their matching and ranking against the user QoS requirements for more informed selections of suitable cloud services by taking into consideration the credibility of the cloud service providers.

A Cloud Service Broker Based on Dynamic Game Theory for Bilateral SLA Negotiation in Cloud Environment

In recent years, with the development of cloud computing, more and more service providers appear, making the cloud computing market more open and competitive. However, it is difficult for service consumers to choose the most suitable service provider for their own, especially for the service providers to provide the best service in the negotiated price, while the service providers and the service consumers themselves can't automatically negotiate, thus in this paper, we propose a cloud service broker framework based on dynamic game theory for bilateral SLA negotiation in cloud environment, aiming for successful negotiation among participators. This paper also proposes a Nash equilibrium point and a satisfaction degree difference algorithm, aiming to find the optimal value of SLA attributes (price and bandwidth) at the minimum satisfaction degree difference among the participators. Experimental results show that the service consumers and the service providers are able to achieve the same satisfaction degree on price and bandwidth.

Virtual cloud bank: consumer-centric service recommendation process and architectural perspective for cloud service brokers

A paradigm shift from a PC-centric to a cloud computing environment has occurred because of rapid and continuous improvements in the IT environments. With the expansion of cloud computing, various types of cloud services are emerging, collectively known as XaaS (that is, "everything as a service"), including Infrastructure as a Service, Platform as a Service, and Software as a Service. Therefore, an intermediation entity known as a CSB (cloud service broker) is required that interrelates cloud service providers and cloud consumers. However, CSBs remain an active research area in industry and academia. With the diversification of cloud services and the emergence of services with similar functions, the role of the CSB to recommend cloud services that meet the requirements of various consumers has become increasingly important. In this paper, to allow CSBs to provide appropriate cloud services from consumer-centric perspectives, we propose a CSB named the virtual cloud bank that includes a process for recommending cloud services and architectural aspects. Our proposed approach can be utilized as a reference model for a consumer-centric CBS for provisioning cloud services. Therefore, if CSB developers apply and extend the proposed well-defined architectural elements and recommendation approach, this is expected to help accelerate the growth of the cloud computing market.

Efficient service selection approach for mobile devices in mobile cloud

The paper proposes optimal efficient cloud service selection scheme for mobile device through local and public cloud in hybrid cloud. The proposed model consists of non-dedicated public cloud resources and local cloud resources. At different locations, local cloud service providers maintain finite dedicated resources that can be used by mobile device users. In the proposed model, the system middleware first examines if any of the local cloud servers have sufficient idle capacity to satisfy the desired requirement of mobile application. If the mobile users' requirement cannot be handled locally, the proposed architecture must choose mobile users' jobs to burst to the remote public cloud. The decision of when to trigger a cloud burst involves monitoring the system context and workload. A cloud-based service selection optimization is proposed, which can optimize the resource utilization, cloud supplier's benefit and mobile user's QoS. The proposed optimization problem is partitioned by local cloud service selection and public cloud resource scheduling, which is implemented by the mobile device, mobile cloud service broker and cloud supplier. A cloud service selection algorithm for mobile device is proposed, which is composed of two sub-algorithms: cloud service selection optimization and cloud resource scheduling optimization. The efficiency of the cloud service selection algorithm for mobile device is tested by experiments.

Learning techniques for cloud demands aggregation in cloud service brokering

The cloud service broker (CSB) has to ensure intermediation for cloud services. Especially, it acts as an interface among customers and providers of cloud resources. The main purpose of the CSB is to pertinently aggregate different demands of customers into a global demand. The objective is to obtain a price for this global demand as low as possible from the providers. Finding the best aggregations of demands is an optimisation problem. In a competitive context between providers, this optimisation problem has to be solved taking into account partial knowledge. We model this problem as a game in which we evaluate the quality of Nash equilibria from the optimisation problem point of view. We propose to use a linear reward inaction algorithm to reach such equilibria in a partial knowledge and distributed context after proving a convergence property of the algorithm. This approach is finally experimented by numerous simulations.

Learning techniques for cloud demands aggregation in cloud service brokering

The cloud service broker (CSB) has to ensure intermediation for cloud services. Especially, it acts as an interface among customers and providers of cloud resources. The main purpose of the CSB is to pertinently aggregate different demands of customers into a global demand. The objective is to obtain a price for this global demand as low as possible from the providers. Finding the best aggregations of demands is an optimisation problem. In a competitive context between providers, this optimisation problem has to be solved taking into account partial knowledge. We model this problem as a game in which we evaluate the quality of Nash equilibria from the optimisation problem point of view. We propose to use a linear reward inaction algorithm to reach such equilibria in a partial knowledge and distributed context after proving a convergence property of the algorithm. This approach is finally experimented by numerous simulations.

MCSQAM: Service Quality Assessment Model in Mobile Cloud Services Environment

Cloud computing is high technology that extends existing IT capabilities and requirements. Recently, the cloud computing paradigm is towards mobile with advances of mobile network and personal devices. As concept of mobile cloud, the number of providers rapidly increases for various mobile cloud services. Despite development of cloud computing, most service providers used their own policies to deliver their services to user. In other words, quality criteria for mobile cloud service assessment are not clearly established yet. To solve the problem, there were some researches that proposed models for service quality assessment. However, they did not consider various metrics to assess service quality. Although existing research considers various metrics, they did not consider newly generated Service Level Agreement. In this paper, to solve the problem, we proposed a mobile cloud service assessment model called mCSQAM and verify our model through few case researches. To apply the mobile cloud, proposed assessment model is transformed from ISO/IEC 9126 which is an international standard for software quality assessment. mCSQAM can provide service quality assessment and determine raking of the service. Furthermore, if Cloud Service Broker includes mCSQAM, appropriate services can be recommended for service users using user and service conditions.

Cross-cutting 기반의 클라우드 서비스 품질 메트릭 및 SLA 명세 기법

클라우드 서비스가 증가하고 다양해짐에 따라 클라우드 서비스 사용자들의 요구사항을 만족하는 가장 적절한 서비스를 찾아주는 클라우드 서비스 브로커(CSB) 기술이 나타났다. CSB를 통해 클라우드 서비스가 사용되는 것을 촉진시키기 위해서는 서비스 수준 협약(SLA) 기반의 협상 과정을 통해 사용자들의 요구사항에 맞는 품질 수준을 보장하는 것이 중요하다. 그러나 클라우드 서비스 유형 별로 품질수준을 표현하는 측정 기준과 척도, 계산 방식이 서로 상이하다. 따라서 클라우드 서비스의 품질에 대한 가변성을 분석하고, 분석된 품질 수준을 보장 및 개선하기 위한 SLA 모델이 필요하다. 본 논문에서는 cross-cutting 개념을 적용하여 클라우드 서비스의 유형 별 품질 메트릭을 분석하고 사용자와 제공자 간의 품질 수준에 대한 협상을 담당하는 VSLA(Variable SLA) 메타모델을 제안한다.

PuLSaR: preference-based cloud service selection for cloud service brokers

Over the last few years, the vast increase of cloud service offerings that are available from heterogeneous cloud vendors, has made the evaluation and selection of desired cloud services, a cumbersome task for service consumers. In that respect, there is an increasing need for user guidance and intermediation during the service selection process but also during the cloud service consumption that should always refer to the best possible choice based on user preferences. In this paper, we discuss the Preference-based cLoud Service Recommender (PuLSaR) that uses a holistic multi-criteria decision making (MCDM) approach for offering optimisation as a brokerage service. The specification and implementation details of this proposed software mechanism are thoroughly discussed while the background method used is summarised. Both method and brokerage service allow for the multi-objective assessment of cloud services in a unified way, taking into account precise and imprecise metrics and dealing with their fuzziness. We cope with the fuzziness of imprecise metrics in the sense that this approach deals with linguistically expressed preferences and cloud service characteristics that lack a fixed or precise value and entail a level of vagueness which can only be captured using the Zadeh’s Fuzzy Set Theory. Furthermore, this paper reports on a number of experiments that were conducted in order to measure PuLSaR’s performance and scalability.

테넌트 요구사항 기반의 클라우드 서비스 추천 방법

It is difficult to provide proper cloud services for cloud users, because the number of cloud services are increasing and the type of cloud services are diversifying. To overcome this problem, the concept of cloud service broker is presented to mediate cloud services between cloud providers and tenant. The most important role of cloud service broker is to finding cloud services that fulfill requirements of tenant. However, current existing cloud service broker conduct passive requirements analysis process with cloud service expert`s assistance. In addition, the systematic functional and non-functional requirement analysis is insufficient. Therefore, we need the new methods for requirement analysis to find nearest service that matches with requirement of tenant. In this paper, we apply pairwise comparison from AHP method to analyze requirement automatically and systematically. It calculates score of service by comparing requirement with service specification, calculating importance rate, and so on.

Governance of cloud computing: semantic aspects and cloud service brokers

This paper provides an overview of cloud governance aspects based on a representative survey of trends in the perception, assessment and adoption of cloud computing within the enterprise. The survey was conducted through a twofold research approach and combined a meta-study of existing and published empirical studies with an own empirical study within a representative group of European and international enterprises. We consider governance through the prism of adoption drivers and focus on the role of cloud brokers and cloud marketplaces more specifically, as well as the inclusion of semantic based strategies oriented to enhance the quality of service offered by cloud service brokers.

A Cloud Service Broker with Legal-Rule Compliance Checking and Quality Assurance Capabilities

Abstract The ICT industry, and specifically critical sectors such as healthcare, transportation, energy and government require as mandatory the compliance of the ICT systems and services with legislation and regulation, as well as with standards. In the era of cloud computing, and particularly in a public cloud scenario, this compliance management issue is exacerbated by the distributed nature of the system and by the limited control of the customer on the infrastructure/services. Also if the cloud industry is aware of this legislation/regulation compliance issue (e.g. the compliance program of Amazon, Google and Microsoft Azure), right now, there are nor reference architectures neither mechanisms capable to check and to assure, off-line and at run-time, that the compliance is guaranteed during the whole life cycle of a cloud service. Cloud service brokerage can play an important role in law/regulation compliance management of cloud services. In this paper we propose a broker-based solution for the management of law/regulation compliance. In the specific first we define a reference architecture for a legislation-aware cloud service broker, and second we propose an autonomic manager that integrate the MAPE-K control loop with the LegEx framework for the management of the legal compliance checking lifecycle.

Changing Demand - Evaluating Effects Using Simulation as a Service

Many industrial and commercial print service providers (PSPs) are dealing with fragmentation of high copy count, low-mix demands to low copy count, high-mix demands due to mass customization and personalization of content. To understand the true dynamics of a changing demand, a stochastic discrete event simulator such as Ptolemy, from UC Berkeley, could be a very useful tool. However, simulation usage presents a high technology and knowledge barrier to solution architects. Additionally, IT requirements such as periodic upgrade and update of software and hardware infrastructure further imperils the use of simulation for solution architects. With the advent of cloud technology and service broker architecture, both problems can be solved effectively. Solution architects can now quantify effects of these changes using simulation-as-a-service (SimaaS) without worrying about simulation and the hardware and software updates.

클라우드 서비스 중개를 위한 수리과학 모형연구

Cloud computing is fast becoming the wave of the future for both home and business computing. Because of this growing acceptance, we can expect an explosion of diverse cloud service providers in the coming years. However, the cloud is not a single entity, rather it is a set of many disconnected islands of application (SaaS), infrastructure (IaaS), and different platform (PaaS) services. Cloud brokering mechanisms are essential to transform the heterogeneous cloud market into a commodity-like service. Cloud service brokers (CSBs) are the new form of business entities to help to aggregate the scattered set of cloud services and make conveniently available to their diverse users. CSBs can reserve a certain percentage of their clients’ (users’) demand and satisfy the remaining portion in an on-demand basis. In doing so, they need to minimize cost of both reserved and on-demand instances as well as the distance of a link between the cloud service provider (CSP) and the user. The study proposes a reservation approach with a mixed integer model to optimizes the cloud service cost and quality.

클라우드 서비스 중개를 위한 가변성 기반의 서비스 명세 기법

As the prevalence of cloud computing increases, various cloud service types have emerged, such as IaaS, PaaS, and SaaS. The growth and diversification of these cloud services has also resulted in the development of technology for cloud service brokers (CSBs), which serve as intermediate cloud services that can assist cloud tenants (users) in deploying services that fit their requirements. In order to broker cloud services, CSBs require the specification of structural models in order to facilitate the analysis and search for cloud services. In this study, we propose a variability-based service analysis model (SAM) that can be used to describe various cloud services. This model is based on the concept of variability in the software product line and represents the commonality and variability of cloud services by binding variants to each variation point that exists in the specification, quality, and pricing of the services. We also propose a virtual cloud bank architecture as a CSB that serves as an intermediate to provides tenants with appropriate cloud services based on the SAM.

Dynamic cloud service selection using an adaptive learning mechanism in multi-cloud computing

Cloud service selection in a multi-cloud computing environment is receiving more and more attentions. There is an abundance of emerging cloud service resources that makes it hard for users to select the better services for their applications in a changing multi-cloud environment, especially for online real time applications. To assist users to efficiently select their preferred cloud services, a cloud service selection model adopting the cloud service brokers is given, and based on this model, a dynamic cloud service selection strategy named DCS is put forward. In the process of selecting services, each cloud service broker manages some clustered cloud services, and performs the DCS strategy whose core is an adaptive learning mechanism that comprises the incentive, forgetting and degenerate functions. The mechanism is devised to dynamically optimize the cloud service selection and to return the best service result to the user. Correspondingly, a set of dynamic cloud service selection algorithms are presented in this paper to implement our mechanism. The results of the simulation experiments show that our strategy has better overall performance and efficiency in acquiring high quality service solutions at a lower computing cost than existing relevant approaches.