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  • 1. Conejero, Javier
    et al.
    Caminero, Blanca
    Carrion, Carmen
    Tomas, Luis
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    From volunteer to trustable computing: Providing QoS-aware scheduling mechanisms for multi-grid computing environments2014In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 34, p. 76-93Article in journal (Refereed)
    Abstract [en]

    The exploitation of service oriented technologies, such as Grid computing, is being boosted by the current service oriented economy trend, leading to a growing need of Quality of Service (QoS) mechanisms. However, Grid computing was created to provide vast amounts of computational power but in a best effort way. Providing QoS guarantees is therefore a very difficult and complex task due to the distributed and heterogeneous nature of their resources, specially the volunteer computing resources (e.g., desktop resources). The scope of this paper is to empower an integrated multi QoS support suitable for Grid Computing environments made of either dedicated and volunteer resources, even taking advantage of that fact. The QoS is provided through SLAs by exploiting different available scheduling mechanisms in a coordinated way, and applying appropriate resource usage optimization techniques. It is based on the differentiated use of reservations and scheduling in advance techniques, enhanced with the integration of rescheduling techniques that improve the allocation decisions already made, achieving a higher resource utilization and still ensuring the agreed QoS. As a result, our proposal enhances best-effort Grid environments by providing QoS aware scheduling capabilities. This proposal has been validated by means of a set of experiments performed in a real Grid testbed. Results show how the proposed framework effectively harnesses the specific capabilities of the underlying resources to provide every user with the desired QoS level, while, at the same time, optimizing the resources' usage. (C) 2013 Elsevier B.V. All rights reserved.

  • 2.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Henriksson, Daniel
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Distributed usage logging for federated grids2010In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 26, no 8, p. 1215-1225Article in journal (Refereed)
    Abstract [en]

    We present a non-intrusive solution to the increasingly important problem of shared logging for overlapping and federated Grid environments. The solution addresses three usage scenarios of hierarchical Grids, mutual cross-Grid resource utilization, and federated Cloud computing infrastructures. The approach is evaluated by extending the existing SweGrid Accounting System (SGAS) with a light-weight component that makes the system applicable to a wide range of usage scenarios. The proposed architecture is characterized by its simplicity, flexibility, and generality, and the new key component by its non-intrusiveness, flexibility, and ability to manage high load. We present requirements derived from three usage scenarios, and also include an in-depth description of the architecture and design, as well as the implementation and performance evaluation of a new component written for use with SGAS. We conclude from a performance evaluation that the sharing of usage data is not likely to be a limiting performance factor even in large-scale Grid scenarios.

  • 3.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Three fundamental dimensions of scientific workflow interoperability: model of computation, language, and execution environment2010In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 26, no 2, p. 245-256Article in journal (Refereed)
    Abstract [en]

    We investigate interoperability aspects of scientific workflow systems and argue that the workflow execution environment, the model of computation (MoC), and the workflow language form three dimensions that must be considered depending on the type of interoperability sought: at the activity, sub-workflow, or workflow levels. With a focus on the problems that affect interoperability, we illustrate how these issues are tackled by current scientific workflows as well as how similar problems have been addressed in related areas. Our long-term objective is to achieve (logical) interoperability between workflow systems operating under different MoCs, using distinct language features, and sharing activities running on different execution environments.

  • 4.
    Elmroth, Erik
    et al.
    Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N). Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions2008In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 24, no 6, p. 585-593Article in journal (Refereed)
    Abstract [en]

    We present algorithms, methods, and software for a Grid resource manager, that performs resource brokering and job scheduling in production Grids. This decentralized broker selects computational resources based on actual job requirements, job characteristics, and information provided by the resources, with the aim to minimize the total time to delivery for the individual application. The total time to delivery includes the time for program execution, batch queue waiting, and transfer of executable and input/output data to and from the resource. The main features of the resource broker include two alternative approaches to advance reservations, resource selection algorithms based on computer benchmark results and network performance predictions, and a basic adaptation facility. The broker is implemented as a built-in component of a job submission client for the NorduGrid/ARC middleware.

  • 5. Farokhi, Soodeh
    et al.
    Jamshidi, Pooyan
    Lakew, Ewnetu Bayuh
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Brandic, Ivona
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    A hybrid cloud controller for vertical memory elasticity: a control-theoretic approach2016In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 65, p. 57-72Article in journal (Refereed)
    Abstract [en]

    Web-facing applications are expected to provide certain performance guarantees despite dynamic and continuous workload changes. As a result, application owners are using cloud computing as it offers the ability to dynamically provision computing resources (e.g., memory, CPU) in response to changes in workload demands to meet performance targets and eliminates upfront costs. Horizontal, vertical, and the combination of the two are the possible dimensions that cloud application can be scaled in terms of the allocated resources. In vertical elasticity as the focus of this work, the size of virtual machines (VMs) can be adjusted in terms of allocated computing resources according to the runtime workload. A commonly used vertical resource elasticity approach is realized by deciding based on resource utilization, named capacity-based. While a new trend is to use the application performance as a decision making criterion, and such an approach is named performance-based. This paper discusses these two approaches and proposes a novel hybrid elasticity approach that takes into account both the application performance and the resource utilization to leverage the benefits of both approaches. The proposed approach is used in realizing vertical elasticity of memory (named as vertical memory elasticity), where the allocated memory of the VM is auto-scaled at runtime. To this aim, we use control theory to synthesize a feedback controller that meets the application performance constraints by auto-scaling the allocated memory, i.e., applying vertical memory elasticity. Different from the existing vertical resource elasticity approaches, the novelty of our work lies in utilizing both the memory utilization and application response time as decision making criteria. To verify the resource efficiency and the ability of the controller in handling unexpected workloads, we have implemented the controller on top of the Xen hypervisor and performed a series of experiments using the RUBBoS interactive benchmark application, under synthetic and real workloads including Wikipedia and FIFA. The results reveal that the hybrid controller meets the application performance target with better performance stability (i.e., lower standard deviation of response time), while achieving a high memory utilization (close to 83%), and allocating less memory compared to all other baseline controllers.

  • 6. Ferrer, Ana Juan
    et al.
    Hernandez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Aley-Eldin, Ahmed
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Zsigri, Csilla
    Sirvent, Rauel
    Guitart, Jordi
    Badia, Rosa M.
    Djemame, Karim
    Ziegler, Wolfgang
    Dimitrakos, Theo
    Nair, Srijith K.
    Kousiouris, George
    Konstanteli, Kleopatra
    Varvarigou, Theodora
    Hudzia, Benoit
    Kipp, Alexander
    Wesner, Stefan
    Corrales, Marcelo
    Forgo, Nikolaus
    Sharif, Tabassum
    Sheridan, Craig
    OPTIMIS: A holistic approach to cloud service provisioning2012In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 28, no 1, p. 66-77Article in journal (Refereed)
    Abstract [en]

    We present fundamental challenges for scalable and dependable service platforms and architectures that enable flexible and dynamic provisioning of cloud services. Our findings are incorporated in a toolkit targeting the cloud service and infrastructure providers. The innovations behind the toolkit are aimed at optimizing the whole service life cycle, including service construction, deployment, and operation, on a basis of aspects such as trust, risk, eco-efficiency and cost. Notably, adaptive self-preservation is crucial to meet predicted and unforeseen changes in resource requirements. By addressing the whole service life cycle, taking into account several cloud architectures, and by taking a holistic approach to sustainable service provisioning, the toolkit aims to provide a foundation for a reliable, sustainable, and trustful cloud computing industry.

  • 7. Katsaros, Gregory
    et al.
    Subirats, Josep
    Fito, J. Oriol
    Guitart, Jordi
    Gilet, Pierre
    Espling, Daniel
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    A service framework for energy-aware monitoring and VM management in Clouds2013In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 29, no 8, p. 2077-2091Article in journal (Refereed)
    Abstract [en]

    The monitoring of QoS parameters in Services Computing as well as in Clouds has been a functionality provided by all contemporary systems. As the optimization of energy consumption becomes a major concern for system designers and administrators, it can be considered as another QoS metric to be monitored. In this paper, we present a service framework that allows us to monitor the energy consumption of a Cloud infrastructure, calculate its energy efficiency, and evaluate the gathered data in order to put in place an effective virtual machine (VM) management. In that context, a simulation scenario of an eco-driven VM placement policy resulted in a 14% improvement of the infrastructure's energy efficiency. In total, the proposed approaches and implementations have been validated against a testbed, producing very promising results regarding the prospect of energy efficiency as an important quality factor in Clouds. (C) 2012 Elsevier B.V. All rights reserved.

  • 8.
    Krzywda, Jakub
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Ali-Eldin, Ahmed
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Carlson, Trevor E.
    Department of Information Technology, Uppsala University, SE-751 05 Uppsala, Sweden.
    Östberg, Per-Olov
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Power-performance tradeoffs in data center servers: DVFS, CPUpinning, horizontal, and vertical scaling2018In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 81, p. 114-128Article in journal (Refereed)
    Abstract [en]

    Dynamic Voltage and Frequency Scaling (DVFS), CPU pinning, horizontal, and vertical scaling, are four techniques that have been proposed as actuators to control the performance and energy consumption on data center servers. This work investigates the utility of these four actuators, and quantifies the power-performance tradeoffs associated with them. Using replicas of the German Wikipedia running on our local testbed, we perform a set of experiments to quantify the influence of DVFS, vertical and horizontal scaling, and CPU pinning on end-to-end response time (average and tail), throughput, and power consumption with different workloads. Results of the experiments show that DVFS rarely reduces the power consumption of underloaded servers by more than 5%, but it can be used to limit the maximal power consumption of a saturated server by up to 20% (at a cost of performance degradation). CPU pinning reduces the power consumption of underloaded server (by up to 7%) at the cost of performance degradation, which can be limited by choosing an appropriate CPU pinning scheme. Horizontal and vertical scaling improves both the average and tail response time, but the improvement is not proportional to the amount of resources added. The load balancing strategy has a big impact on the tail response time of horizontally scaled applications.

  • 9.
    Sedaghat, Mina
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hernández-Rodriguez, Francisco
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Decentralized cloud datacenter reconsolidation through emergent and topology-aware behavior2016In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 56, p. 51-63Article in journal (Refereed)
    Abstract [en]

    Consolidation of multiple applications on a single Physical Machine (PM) within acloud data center can increase utilization, minimize energy consumption, and reduceoperational costs. However, these benefits comes at the cost of increasing the complex-ity of the scheduling problem.In this paper, we present a topology-aware resource management framework. Aspart of this framework, we introduce a Reconsolidating PlaceMent scheduler (RPM)that provides and maintains durable allocations with low maintenance costs for datacenters with dynamic workloads. We focus on workloads featuring both short-livedbatch jobs and latency-sensitive services such as interactive web applications. Thescheduler assigns resources to Virtual Machines (VMs) and maintains packing effi-ciency while taking into account migration costs, topological constraints, and the riskof resource contention, as well as the variability of the background load and its com-plementarity to the new VM.We evaluate the model by simulating a data center with over 65000 PMs, structuredas a three-level multi-rooted tree topology. We investigate trade-offs between factorsthat affect the durability and operational cost of maintaining a near-optimal packing.The results show that the proposed scheduler can scale to the number of PMs in thesimulation and maintain efficient utilization with low migration costs.

  • 10.
    Tordsson, Johan
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Montero, Ruben S.
    Universidad Complutense de Madrid.
    Moreno-Vozmediano, Rafael
    Universidad Complutense de Madrid.
    Llorente, Ignacio M.
    Universidad Complutense de Madrid.
    Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers2012In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 28, no 2, p. 358-367Article in journal (Refereed)
    Abstract [en]

    In the past few years, we have witnessed the proliferation of a heterogeneous ecosystem of cloud providers, each one with a different infrastructure offer and pricing policy. We explore this heterogeneity in a novel cloud brokering approach that optimizes placement of virtual infrastructures across multiple clouds and also abstracts the deployment and management of infrastructure components in these clouds. The feasibility of our approach is evaluated in a high throughput computing cluster case study. Experimental results confirm that multi-cloud deployment provides better performance and lower costs compared to the usage of a single cloud only. 

  • 11. Tärneberg, William
    et al.
    Mehta, Amardeep
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Wadbro, Eddie
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Tordsson, Johan
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Eker, Johan
    Kihl, Maria
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Dynamic application placement in the Mobile Cloud Network2017In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 70, p. 163-177Article in journal (Refereed)
    Abstract [en]

    To meet the challenges of consistent performance, low communication latency, and a high degree of user mobility, cloud and Telecom infrastructure vendors and operators foresee a Mobile Cloud Network that incorporates public cloud infrastructures with cloud augmented Telecom nodes in forthcoming mobile access networks. A Mobile Cloud Network is composed of distributed cost- and capacityheterogeneous resources that host applications that in turn are subject to a spatially and quantitatively rapidly changing demand. Such an infrastructure requires a holistic management approach that ensures that the resident applications’ performance requirements are met while sustainably supported by the underlying infrastructure. The contribution of this paper is three-fold. Firstly, this paper contributes with a model that captures the cost- and capacity-heterogeneity of a Mobile Cloud Network infrastructure. The model bridges the Mobile Edge Computing and Distributed Cloud paradigms by modelling multiple tiers of resources across the network and serves not just mobile devices but any client beyond and within the network. A set of resource management challenges is presented based on this model. Secondly, an algorithm that holistically and optimally solves these challenges is proposed. The algorithm is formulated as an application placement method that incorporates aspects of network link capacity, desired user latency and user mobility, as well as data centre resource utilisation and server provisioning costs. Thirdly, to address scalability, a tractable locally optimal algorithm is presented. The evaluation demonstrates that the placement algorithm significantly improves latency, resource utilisation skewness while minimising the operational cost of the system. Additionally, the proposed model and evaluation method demonstrate the viability of dynamic resource management of the Mobile Cloud Network and the need for accommodating rapidly mobile demand in a holistic manner.

  • 12.
    Östberg, Per-Olov
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    GJMF - a composable service-oriented Grid job management framework2013In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 29, no 1, p. 144-157Article in journal (Refereed)
    Abstract [en]

    We investigate best practices for Grid software design and development, and propose a composable, loosely coupled Service-Oriented Architecture for Grid job management. The architecture focuses on providing a transparent Grid access model for concurrent use of multiple Grid middlewares and aims to decouple Grid applications from Grid middlewares and infrastructure. The notion of an ecosystem of Grid infrastructure components is extended, and Grid job management software design is discussed in this context. Non- intrusive integration models and abstraction of Grid middleware function- ality through hierarchical aggregation of autonomous Grid job management services are emphasized, and service composition techniques facilitating this process are explored. A proof-of-concept implementation of the architecture is presented along with a discussion of architecture implementation details and trade-offs introduced by the service composition techniques used.

  • 13.
    Östberg, Per-Olov
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Espling, Daniel
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Elmroth, Erik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Decentralized scalable fairshare scheduling2013In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 29, no 1, p. 130-143Article in journal (Refereed)
    Abstract [en]

    This work addresses Grid fairshare allocation policy enforcement and presents Aequus, a decentralized system for Grid-wide fairshare job prioritization. The main idea of fairshare scheduling is to prioritize users with regard to predefined resource allocation quotas. The presented system builds on three contributions: a flexible tree-based policy model that allows delegation of policy definition, a job prioritization algorithm based on local enforcement of distributed fairshare policies, and a decentralized architecture for non-intrusive integration with existing scheduling systems. The system supports organization of users in virtual organizations and divides usage policies into local and global policy components that are defined by resource owners and virtual organizations. The architecture realization is presented in detail along with an evaluation of the system behavior in an emulated environment. In the evaluation, convergence noise types (mechanisms counteracting policy allocation convergence) are characterized and quantified, and the system is demonstrated to meet scheduling objectives and perform scalably under realistic operating conditions.

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