Showing papers on "Service-level agreement published in 2011"

SMICloud: A Framework for Comparing and Ranking Cloud Services

Abstract: With the growth of Cloud Computing, more and more companies are offering different cloud services. From the customer's point of view, it is always difficult to decide whose services they should use, based on users' requirements. Currently there is no software framework which can automatically index cloud providers based on their needs. In this work, we propose a framework and a mechanism, which measure the quality and prioritize Cloud services. Such framework can make significant impact and will create healthy competition among Cloud providers to satisfy their Service Level Agreement (SLA) and improve their Quality of Services (QoS).

Multi-dimensional SLA-Based Resource Allocation for Multi-tier Cloud Computing Systems

Abstract: With increasing demand for computing and memory, distributed computing systems have attracted a lot of attention. Resource allocation is one of the most important challenges in the distributed systems specially when the clients have Service Level Agreements (SLAs) and the total profit in the system depends on how the system can meet these SLAs. In this paper, an SLA-based resource allocation problem for multi-tier applications in the cloud computing is considered. An upper bound on the total profit is provided and an algorithm based on force-directed search is proposed to solve the problem. The processing, memory requirement, and communication resources are considered as three dimensions in which optimization is performed. Simulation results demonstrate the effectiveness of the proposed heuristic algorithm.

SLA-oriented resource provisioning for cloud computing: Challenges, architecture, and solutions

Abstract: 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 market-based 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

Resource management for cloud computing platforms

Abstract: A system for managing allocation of resources based on service level agreements between application owners and cloud operators. Under some service level agreements, the cloud operator may have responsibility for managing allocation of resources to the software application and may manage the allocation such that the software application executes within an agreed performance level. Operating a cloud computing platform according to such a service level agreement may alleviate for the application owners the complexities of managing allocation of resources and may provide greater flexibility to cloud operators in managing their cloud computing platforms.

Cloud Computing: Security Issues and Research Challenges

Abstract: Cloud computing is an architecture for providing computing service via the internet on demand and pay per use access to a pool of shared resources namely networks, storage, servers, services and applications, without physically acquiring them. So it saves managing cost and time for organizations. Many industries, such as banking, healthcare and education are moving towards the cloud due to the efficiency of services provided by the pay-per-use pattern based on the resources such as processing power used, transactions carried out, bandwidth consumed, data transferred, or storage space occupied etc. Cloud computing is a completely internet dependent technology where client data is stored and maintain in the data center of a cloud provider like Google, Amazon, Salesforce.som and Microsoft etc. Limited control over the data may incur various security issues and threats which include data leakage, insecure interface, sharing of resources, data availability and inside attacks. There are various research challenges also there for adopting cloud computing such as well managed service level agreement (SLA), privacy, interoperability and reliability. This research paper outlines what cloud computing is, the various cloud models and the main security risks and issues that are currently present within the cloud computing industry. This research paper also analyzes the key research and challenges that presents in cloud computing and offers best practices to service providers as well as enterprises hoping to leverage cloud service to improve their bottom line in this severe economic climate.

A game theoretic formulation of the service provisioning problem in cloud systems

Abstract: Cloud computing is an emerging paradigm which allows the on-demand delivering of software, hardware, and data as services. As cloud-based services are more numerous and dynamic, the development of efficient service provisioning policies become increasingly challenging. Game theoretic approaches have shown to gain a thorough analytical understanding of the service provisioning problem.In this paper we take the perspective of Software as a Service (SaaS) providers which host their applications at an Infrastructure as a Service (IaaS) provider. Each SaaS needs to comply with quality of service requirements, specified in Service Level Agreement (SLA) contracts with the end-users, which determine the revenues and penalties on the basis of the achieved performance level. SaaS providers want to maximize their revenues from SLAs, while minimizing the cost of use of resources supplied by the IaaS provider. Moreover, SaaS providers compete and bid for the use of infrastructural resources. On the other hand, the IaaS wants to maximize the revenues obtained providing virtualized resources. In this paper we model the service provisioning problem as a Generalized Nash game, and we propose an efficient algorithm for the run time management and allocation of IaaS resources to competing SaaSs.

Data integrity proofs in cloud storage

Abstract: Cloud computing has been envisioned as the de-facto solution to the rising storage costs of IT Enterprises. With the high costs of data storage devices as well as the rapid rate at which data is being generated it proves costly for enterprises or individual users to frequently update their hardware. Apart from reduction in storage costs data outsourcing to the cloud also helps in reducing the maintenance. Cloud storage moves the user's data to large data centers, which are remotely located, on which user does not have any control. However, this unique feature of the cloud poses many new security challenges which need to be clearly understood and resolved. One of the important concerns that need to be addressed is to assure the customer of the integrity i.e. correctness of his data in the cloud. As the data is physically not accessible to the user the cloud should provide a way for the user to check if the integrity of his data is maintained or is compromised. In this paper we provide a scheme which gives a proof of data integrity in the cloud which the customer can employ to check the correctness of his data in the cloud. This proof can be agreed upon by both the cloud and the customer and can be incorporated in the Service level agreement (SLA). This scheme ensures that the storage at the client side is minimal which will be beneficial for thin clients.

A Survey of Pricing Schemes in Wireless Networks

Abstract: The expansion of new technologies is expected to offer economic growth in the wired and wireless technological networking environment, while at the same time, it will offer a wide variety of services and give the possibility for utilizing technologies for the benefit of many subscribers. The Pricing Schemes are designed to offer profitable business to the Wireless Service Providers (WSPs), as well as, to create favorable services for the mobile subscribers and eventually to get charged according to their services usage. In this paper, the Pricing Schemes are classified, based on their ability to adapt to the needs of the WSPs and their subscribers during the entire service period, into Static-based Pricing and Dynamic-based Pricing Schemes. The Pricing Schemes are also analyzed in detail and are further classified according to the factors involved in the price calculation of a service, i.e. the Service Level Agreement (SLA), the subscription type, the negotiation capabilities between WSPs and their subscribers, the network capacity, the available bandwidth and frequency spectrum, the network hops, and the Base Stations (BSs). The affected elements by the pricing network are also discussed, together with the performance evaluation of the presented pricing schemes.

SLA-based resource provisioning for heterogeneous workloads in a virtualized cloud datacenter

Abstract: Efficient provisioning of resources is a challenging problem in cloud computing environments due to its dynamic nature and the need for supporting heterogeneous applications with different performance requirements. Currently, cloud datacenter providers either do not offer any performance guarantee or prefer static VM allocation over dynamic, which lead to inefficient utilization of resources. Earlier solutions, concentrating on a single type of SLAs (Service Level Agreements) or resource usage patterns of applications, are not suitable for cloud computing environments. In this paper, we tackle the resource allocation problem within a datacenter that runs different type of application workloads, particularly non-interactive and transactional applications. We propose admission control and scheduling mechanism which not only maximizes the resource utilization and profit, but also ensures the SLA requirements of users. In our experimental study, the proposed mechanism has shown to provide substantial improvement over static server consolidation and reduces SLA Violations.

Cloud federations in contrail

Abstract: Cloud computing infrastructures support dynamical and flexible access to computational, network and storage resources. To date, several disjoint industrial and academic technologies provide infrastructure level access to Clouds. Especially for industrial platforms, the evolution of de-facto standards goes together with worries about user lock-in to a platform. The Contrail project [6] proposes a federated and integrated approach to Clouds. In this work we present and motivate the architecture of Contrail federations. Contrail's goal is to minimize the burden on the user and increase the efficiency in using Cloud platforms by performing both a vertical and a horizontal integration. To this end, Contrail federations play a key role, allowing users to exploit resources belonging to different cloud providers, regardless of the kind of technology of the providers and with a homogeneous, secure interface. Vertical integration is achieved by developing both the Infrastructure- and the Platform-as-a-Service levels within the project. A third key point is the adoption of a fully open-source approach toward technology and standards. Beside supporting user authentication and applications deployment, Contrail federations aim at providing extended SLA management functionalities, by integrating the SLA management approach of SLA@SOI project in the federation architecture.

An Adaptive and Intelligent SLA Negotiation System for Web Services

Abstract: The effective use of services to compose business processes in services computing demands that the Quality of Services (QoS) meet consumers' expectations. Automated web-based negotiation of Service Level Agreements (SLA) can help define the QoS requirements of critical service-based processes. We propose a novel trusted Negotiation Broker (NB) framework that performs adaptive and intelligent bilateral bargaining of SLAs between a service provider and a service consumer based on each party's high-level business requirements. We define mathematical models to map business-level requirements to low-level parameters of the decision function, which obscures the complexity of the system from the parties. We also define an algorithm for adapting the decision functions during an ongoing negotiation to comply with an opponent's offers or with updated consumer preferences. The NB uses intelligent agents to conduct the negotiation locally by selecting the most appropriate time-based decision functions. The negotiation outcomes are validated by extensive experimental study for Exponential, Polynomial, and Sigmoid time-based decision functions using simulations on our prototype framework. Results are compared in terms of a total utility value of the negotiating parties to demonstrate the efficiency of our proposed approach.

Load-Balancing Tactics in Cloud

Abstract: Cloud computing enables shared servers to provide resources, software and data for collaborative services on demand with high interoperability and scalability. However, there are a number of technical challenges that need to be tackled before these benefits can be fully realized, which include system reliability, resource provisioning, and efficient resources consuming, etc. Among them, load-balancing is a necessary mechanism to increase the service level agreement (SLA) and better uses of the resources. Unfortunately, serversi¦ capability varies much in practice and is not easy to record in ordered positions in a server farm, which will causes non resource-aware load-balancing algorithms to distribute workloads evenly. We discuss this issue and show why such algorithms doni¦t fit the cloud computing environment and then present a feasible resource-aware load-balancing mechanism by using existing proven technologies to meet higher SLA and the return of investment as well.

SLA-aware placement of multi-virtual machine elastic services in compute clouds

Abstract: Elastic services comprise multiple virtualized resources that can be added and deleted on demand to match variability in the workload. A Service owner profiles the service to determine its most appropriate sizing under different workload conditions. This variable sizing is formalized through a service level agreement (SLA) between the service owner and the cloud provider. The Cloud provider obtains maximum benefit when it succeeds to fully allocate the resource set demanded by the elastic service subject to its SLA. Failure to do so may result in SLA breach and financial losses to the provider. We define a novel combinatorial optimization problem called elastic services placement problem (ESPP) to maximize the provider's benefit from SLA compliant placement. We observe that ESPP extends the generalized assignment problem (GAP), which is a well studied combinatorial optimization problem. However, ESPP turns out to be considerably harder to solve as it does not admit a constant factor approximation. We show that using a simple transformation, ESPP can be presented as a multi-unit combinatorial auction. We further present a column generation method to obtain near optimal solutions for ESPP for large data centers where exact solutions cannot be obtained in a reasonable amount of time using a direct integer programming formulation. We demonstrate the feasibility of our approach through an extensive simulation study. Our results show that we are capable of consistently obtaining good solutions in a time efficient manner. Moreover, if one is willing to trade precision to gain in computation time, our method allows to explicitly manage this tradeoff.

SLA-Aware Application Deployment and Resource Allocation in Clouds

Abstract: Provisioning resources as a service in a scalable on-demand manner is a basic feature in Cloud computing technology. Service provisioning in Clouds is based on Service Level Agreements (SLAs) representing a contract signed between the customer and the service provider stating the terms of the agreement including non-functional requirements of the service specified as Quality of Service (QoS), obligations, and penalties in case of agreement violations. On the one hand SLA violation should be prevented to avoid costly penalties and on the other hand providers have to efficiently utilize resources to minimize cost for the service provisioning. Thus, scheduling strategies considering multiple SLA parameters and efficient allocation of resources are necessary. Recent work considers various strategies with single SLA parameters. However, those approaches are limited to simple workflows and single task applications. Scheduling and deploying service requests considering multiple SLA parameters such as amount of CPU required, network bandwidth, memory and storage are still open research challenges. In this paper, we present a novel scheduling heuristic considering multiple SLA parameters for deploying applications in Clouds. We discuss in details the heuristic design and implementation and finally present detailed evaluations as a proof of concept emphasizing the performance of our approach.

Method and system for efficient deployment of web applications in a multi-datacenter system

Abstract: A system for computing an optimal deployment of at least one web application in a multi-datacenter system comprising a collector for collecting performance measurements with regard to a web application executed in the multi-datacenter system and grouping the performance measurements according to locations of a plurality of clients accessing the web application; a data repository for maintaining at least a performance table including at least the performance measurements grouped according to the plurality of client locations and a service level agreement (SLA) guaranteed to clients in the plurality of client locations; and an analyzer for processing at least information stored in the performance table for generating a recommendation on an optimal deployment of the web application in at least one combination of datacenters in the multi-datacenter system by computing an expected SLA that can be guaranteed to the clients in each combination of datacenters.

A Business Model for Cloud Computing Based on a Separate Encryption and Decryption Service

Abstract: Enterprises usually store data in internal storage and install firewalls to protect against intruders to access the data. They also standardize data access procedures to prevent insiders to disclose the information without permission. In cloud computing, the data will be stored in storage provided by service providers. Service providers must have a viable way to protect their clients' data, especially to prevent the data from disclosure by unauthorized insiders. Storing the data in encrypted form is a common method of information privacy protection. If a cloud system is responsible for both tasks on storage and encryption/decryption of data, the system administrators may simultaneously obtain encrypted data and decryption keys. This allows them to access information without authorization and thus poses a risk to information privacy. This study proposes a business model for cloud computing based on the concept of separating the encryption and decryption service from the storage service. Furthermore, the party responsible for the data storage system must not store data in plaintext, and the party responsible for data encryption and decryption must delete all data upon the computation on encryption or decryption is complete. A CRM (Customer Relationship Management) service is described in this paper as an example to illustrate the proposed business model. The exemplary service utilizes three cloud systems, including an encryption and decryption system, a storage system, and a CRM application system. One service provider operates the encryption and decryption system while other providers operate the storage and application systems, according to the core concept of the proposed business model. This paper further includes suggestions for a multi-party Service- Level Agreement (SLA) suitable for use in the proposed business model.

Economical and Robust Provisioning of N-Tier Cloud Workloads: A Multi-level Control Approach

Abstract: Resource provisioning for N-tier web applications in Clouds is non-trivial due to at least two reasons. First, there is an inherent optimization conflict between cost of resources and Service Level Agreement (SLA) compliance. Second, the resource demands of the multiple tiers can be different from each other, and varying along with the time. Resources have to be allocated to multiple (virtual) containers to minimize the total amount of resources while meeting the end-to-end performance requirements for the application. In this paper we address these two challenges through the combination of the resource controllers on both application and container levels. On the application level, a decision maker (i.e., an adaptive feedback controller) determines the total budget of the resources that are required for the application to meet SLA requirements as the workload varies. On the container level, a second controller partitions the total resource budget among the components of the applications to optimize the application performance (i.e., to minimize the round trip time). We evaluated our method with three different workload models -- open, closed, and semi-open -- that were implemented in the RUBiS web application benchmark. Our evaluation indicates two major advantages of our method in comparison to previous approaches. First, fewer resources are provisioned to the applications to achieve the same performance. Second, our approach is robust enough to address various types of workloads with time-varying resource demand without reconfiguration.

Power Aware Load Balancing for Cloud Computing

Abstract: With the increased use of local cloud computing architectures, organizations are becoming aware of wasted power consumed by unutilized resources. In this paper, we present a load balancing approach to IaaS cloud architectures that is power aware. Since the cloud architecture implemented by local organizations tends to be heterogeneous, we take this into account in our design. Our Power Aware Load Balancing algorithm, PALB, maintains the state of all compute nodes, and based on utilization percentages, decides the number of compute nodes that should be operating. We show that our solution provides adequate availability to compute node resources while decreasing the overall power consumed by the local cloud by 70% - 97% compared to using load balancing techniques that are not power aware. Cloud computing architectures are becoming a dominant contender in the distributed systems paradigm. Using this architecture, customers are given access to resources provided by a cloud vendor as described in their Service Level Agreement (SLA). Clouds use virtualization technology in distributed data centers to allocate resources to customers as they need them. Generally, clouds are deployed to customers giving them three levels of access: Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS). The jobs can differ greatly from customer to customer. Each commercial vendor has a targeted customer and specific markets they wish to saturate. Local cloud implementations are becoming popular due to the fact that many organizations are reluctant to move their data to a commercialized cloud vendor. There are debates on whether moving data to the public cloud would benefit small organizations. Beyond the question of benefit to the organizations utilizing public clouds, there are also issues with trust, security and legality. Some organizations may not trust a third party with their information and/or software. Other organizations may not be comfortable allowing a third party to be responsible for the security of the cloud.

Maximizing Profit in Cloud Computing System via Resource Allocation

Abstract: With increasing demand for high performance computing and data storage, distributed computing systems have attracted a lot of attention. Resource allocation is one of the most important challenges in the distributed systems specially when the clients have some Service Level Agreements (SLAs) and the total profit in the system depends on how the system can meet these SLAs. In this paper, an SLA-based resource allocation problem for cloud computing is considered and a distributed solution to this problem is presented. The processing, data storage, and communication resources are considered as three dimensions in which optimizations are performed. Simulation results demonstrate that the proposed heuristic algorithm is robust (produces high quality solutions independent of the initial solution provided) and produces solutions very close to the "optimum" (best solution found by Monte Carlo simulation).

Enacting SLAs in clouds using rules

Abstract: The emergence of Cloud Computing raises the question of dynamically allocating resources of physical (PM) and virtual machines (VM) in an on-demand and autonomic way. Yet, using Cloud Computing infrastructures efficiently requires fulfilling three partially contradicting goals: first, achieving low violation rates of Service Level Agreements (SLA) that define non-functional goals between the Cloud provider and the customer; second, achieving high resource utilization; and third achieving the first two issues by as few time- and energy consuming reallocation actions as possible. To achieve these goals we propose a novel approach with escalation levels to divide all possible actions into five levels. These levels range from changing the configuration of VMs over migrating them to other PMs to outsourcing applications to other Cloud providers. In this paper we focus on changing the resource configuration of VMs in terms of storage, memory, CPU power and bandwidth, and propose a knowledge management approach using rules with threat thresholds to tackle this problem. Simulation reveals major improvements as compared to recent related work considering SLA violations, resource utilization and action efficiency, as well as time performance.

ArA: Adaptive resource allocation for cloud computing environments under bursty workloads

Abstract: Cloud computing nowadays becomes quite popular among a community of cloud users by offering a variety of resources. However, burstiness in user demands often dramatically degrades the application performance. In order to satisfy peak user demands and meet Service Level Agreement (SLA), efficient resource allocation schemes are highly demanded in the cloud. However, we find that conventional load balancers unfortunately neglect cases of bursty arrivals and thus experience significant performance degradation. Motivated by this problem, we propose new burstiness-aware algorithms to balance bursty workloads across all computing sites, and thus to improve overall system performance. We present a smart load balancer, which leverages the knowledge of burstiness to predict the changes in user demands and on-the-fly shifts between the schemes that are “greedy” (i.e., always select the best site) and “random” (i.e., randomly select one) based on the predicted information. Both simulation and real experimental results show that this new load balancer can adapt quickly to the changes in user demands and thus improve performance by making a smart site selection for cloud users under both bursty and non-bursty workloads.

A genetic model for pricing in cloud computing markets

Abstract: 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. Depending on the status of the demand, the provider is able to offer higher or lower prices for maximising its profit. It is difficult to establish a profitable pricing function in competitive markets, because there are several factors that can influence in the prices. This paper deals with the problem of offering competitive prices in the negotiation of services in Cloud Computing markets. A Genetic Algorithms approach is proposed, in which a naive pricing function evolves to a pricing function that offers suitable prices in function of the system status. Its results are compared with other pricing strategies, demonstrating its validity.

Towards Profitable Virtual Machine Placement in the Data Center

Abstract: Motivated by the limit on the power usage effectiveness (PUE) of the data centers, the potential benefit of the consolidation, and the impetus of achieving maximum return on investment (ROI) on the cloud computing market, we investigate VM placement in the data center, formulate a multi-level generalized assignment problem (MGAP) for maximizing the profit under the service level agreement and the power budget constraint based on the model of a virtualized data center, and solve it with a first-fit heuristic. Numerical simulations show that the first-fit heuristic is effective in solving the large-scale instances of the MGAP with the sampled simulation setups.

Server operational cost optimization for cloud computing service providers over a time horizon

Abstract: Service providers are migrating to on-demand cloud computing services to unburden the task of managing infrastructure, while cloud computing providers expand the number of servers in their data centers because of the increase in load. With this growing need, their energy consumption increases significantly. Conserving energy and reducing the operational cost while satisfying the service level agreement (SLA) becomes important in order to reduce both carbon emissions and the budget for cloud computing providers. On the other hand, the aggregated demands for different services are dynamic over a time horizon. We present a multi-time period optimization model for saving the operational cost by combining two factors: 1)Dynamic Voltage/Frequency Scaling (DVFS), 2)turning servers on/off over a time horizon. We show the impact of the granularity of the duration of the time slots and frequency options on optimal solutions. A parametric study on varying cost of turning servers on/off and power consumption is also presented.

SLA-tree: a framework for efficiently supporting SLA-based decisions in cloud computing

Abstract: As cloud computing becomes increasingly important in database systems, many new challenges and opportunities have arisen. One challenge is that in cloud computing, business profit plays a central role. Hence, it is very important for a cloud service provider to quickly make profit-oriented decisions. In this paper, we propose a novel data structure, called SLA-tree, to efficiently support profit-oriented decision making. SLA-tree is built on two pieces of information: (1) a set of buffered queries waiting to be executed, which represents the scheduled events that will happen in the near future, and (2) a service level agreement (SLA) for each query, which indicates the different profits for the query for varying query response times. By constructing the SLA-tree, we efficiently support the answering of certain profit-oriented "what if" questions. Answers to these questions in turn can be applied to different profit-oriented decisions in cloud computing such as profit-aware scheduling, dispatching, and capacity planning. Extensive experimental results based on both synthetic and real-world data demonstrate the effectiveness and efficiency of our SLA-tree framework.

A Reference Architecture for Multi-Level SLA Management

Abstract: Service-orientation is the core paradigm for organising business interactions and modern IT architectures. At the business level, service industries are becoming the dominating sector in which solutions are flexibly composed out of networked services. At the IT level, the paradigms of Service-Oriented Architecture and cloud computing realise service-orientation for both software and infrastructure services. Service composition across different layers is a major advantage of this paradigm. Service Level Agreements (SLAs) are a common approach to specifying the exact conditions under which services are to be delivered, and thus are a prerequisite for supporting the flexible trading of services. However, typical SLAs are only specified at a single layer and do not provide insight into metrics or parameters at the various lower layers of the service stack. Thus they do not allow service providers to manage their service stack optimally. In this chapter, we present a reference architecture for a multi-level SLA management framework. We discuss fundamental concepts of the framework and detail its main architectural components and interactions.

Ant Colony Optimization Based Service Flow Scheduling with Various QoS Requirements in Cloud Computing

Abstract: There are a mass of researches on the issue of scheduling in cloud computing, most of them, however, are bout workflow and job scheduling. There are fewer researches on service flow scheduling. Here we propose a model of service flow scheduling with various quality of service (QoS) requirements in cloud computing firstly, then we adopt the use of an ant colony optimization (ACO) algorithm to optimize service flow scheduling. In our model, we use default rate to describe the radio of cloud service provider breaking service level agreement (SLA), and also introduce an SLA monitoring module to monitor the running state of cloud services.

SLA-aware Resource Management for Application Service Providers in the Cloud

Abstract: In the today Internet of Services, one of the challenges of Application Service Providers (ASPs) is to fulfill the QoS requirements stated in the Service Level Agreements (SLAs) established with different consumers and to minimize the investment and management costs. Cloud computing is the promising solution for ASPs that increasingly demand for an elastic infrastructure. In this paper, we formulate the ASP resource management as an optimization problem and propose both reactive and proactive heuristic policies that approximate the optimal solution. The proposed policies leverage on information about the system performance history and can be applied at runtime because of their reduced computational time. Our experimental results show that some heuristics based on prediction approximate the exact knowledge of the workload.

Multi-tenant database management for sla profit maximization

Abstract: Systems and methods are disclosed to consolidate workload on cloud-based computers by co-locating one or more high-penalty tenants on one or more cloud-based servers; reducing service level agreement (SLA) violations by over-provisioning the cloud-based server; and maximizing an SLA profit.