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  • 1.
    Elmroth, Erik
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hernandez, Francisco
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ali-Eldin, Ahmed
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Sedaghat, Mina
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Li, Wubin
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Self-management Challenges for Multi-cloud Architectures (Invited Paper)2011Ingår i: TOWARDS A SERVICE-BASED INTERNET, Berlin: Springer, 2011, Vol. 6994, s. 38-49Konferensbidrag (Refereegranskat)
    Abstract [en]

    Addressing the management challenges for a multitude of distributed cloud architectures, we focus on the three complementary cloud management problems of predictive elasticity, admission control, and placement (or scheduling) of virtual machines. As these problems are intrinsically intertwined we also propose an approach to optimize the overall system behavior by policy-tuning for the tools handling each of them. Moreover, in order to facilitate the execution of some of the management decisions, we also propose new algorithms for live migration of virtual machines with very high workload and/or over low-bandwidth networks, using techniques such as caching, compression, and prioritization of memory pages.

  • 2.
    Elmroth, Erik
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hernández, Francisco
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ali-Eldin, Ahmed
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Sedaghat, Mina
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Li, Wubin
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Self-management challenges for multi-cloud architectures2011Ingår i: Towards a Service-Based Internet: 4th European Conference, ServiceWave 2011, Poznan, Poland, October 26-28, 2011. Proceedings / [ed] Witold Abramowicz, Ignacio M. Llorente, Mike Surridge, Andrea Zisman and Julien Vayssière, Springer Berlin/Heidelberg, 2011, s. 38-49Konferensbidrag (Refereegranskat)
    Abstract [en]

    Addressing the management challenges for a multitude of distributed cloud architectures, we focus on the three complementary cloud management problems of predictive elasticity, admission control, and placement (or scheduling) of virtual machines. As these problems are intrinsically intertwined we also propose an approach to optimize the overall system behavior by policy-tuning for the tools handling each of them. Moreover, in order to facilitate the execution of some of the management decisions, we also propose new algorithms for live migration of virtual machines with very high workload and/or over low-bandwidth networks, using techniques such as caching, compression, and prioritization of memory pages.

  • 3. Karakostas, Vasileios
    et al.
    Goumas, Georgios
    Bayuh Lakew, Ewnetu
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Gerangelos, Stefanos
    Kolberg, Simon
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nikas, Konstantinos
    Psomadakis, Stratos
    Siakavaras, Dimitrios
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Koziris, Nectarios
    Efficient Resource Management for Data Centers: The ACTiCLOUD Approach2018Ingår i: 2018 International conference on embedded computer systems: architectures, modeling, and simulation (SAMOS XVIII) / [ed] Mudge T., Pnevmatikatos D.N., Association for Computing Machinery (ACM), 2018, s. 244-246Konferensbidrag (Refereegranskat)
    Abstract [en]

    Despite their proliferation as a dominant computing paradigm, cloud computing systems lack effective mechanisms to manage their vast resources efficiently. Resources are stranded and fragmented, limiting cloud applicability only to classes of applications that pose moderate resource demands. In addition, the need for reduced cost through consolidation introduces performance interference, as multiple VMs are co-located on the same nodes. To avoid such issues, current providers follow a rather conservative approach regarding resource management that leads to significant underutilization. ACTiCLOUD is a three-year Horizon 2020 project that aims at creating a novel cloud architecture that breaks existing scale-up and share-nothing barriers and enables the holistic management of physical resources, at both local and distributed cloud site levels. This extended abstract provides a brief overview of the resource management part of ACTiCLOUD, focusing on the design principles and the components.

  • 4. Kyriazis, Dimosthenis
    et al.
    Anagnostopoulos, Vasileios
    Arcangeli, Andrea
    Gilbert, David
    Kalogeras, Dimitrios
    Kat, Ronen
    Klein, Cristian
    Umeå universitet.
    Kokkinos, Panagiotis
    Kuperman, Yossi
    Nider, Joel
    Svärd, Petter
    Umeå universitet.
    Tomas, Luis
    Umeå universitet.
    Varvarigos, Emmanuel
    Varvarigou, Theodora
    High performance fault-tolerance for clouds2015Ingår i: 2015 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATION (ISCC), Larnaca, Cyprus, July 6-9, 2015, IEEE , 2015, s. 251-257Konferensbidrag (Refereegranskat)
    Abstract [en]

    Cloud computing and virtualized infrastructures are currently the baseline environments for the provision of services in different application domains. While the number of service consumers increasingly grows, service providers aim at exploiting infrastructures that enable non-disruptive service provisioning, thus minimizing or even eliminating downtime. Nonetheless, to achieve the latter current approaches are either application-specific or cost inefficient, requiring the use of dedicated hardware. In this paper we present the reference architecture of a fault-tolerance scheme, which not only enhances cloud environments with the aforementioned capabilities but also achieves high-performance as required by mission critical every day applications. To realize the proposed approach, a new paradigm for memory and I/O externalization and consolidation is introduced, while current implementation references are also provided.

  • 5.
    Li, Wubin
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    REST-Based SOA Application in the Cloud: A Text Correction Service Case Study2010Ingår i: Services (SERVICES 2010): 2010 6th World Congress on, IEEE Computer Society, 2010, s. 84-90Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we present a REST-based SOA system, Set It Right (SIR), where people can get feedback on and help with short texts. The rapid development of the SIR system, enabled by designing it as a set of services, and also leveraging commercially offered services, illustrates the strength of the SOA paradigm. Finally, we evaluate the Cloud Computing techniques and infrastructures used to deploy the system and how cloud technology can help shorten the time to market and lower the initial costs.

  • 6.
    Li, Wubin
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    A General Approach to Service Deployment in Cloud Environments2012Ingår i: Cloud and Green Computing (CGC 2012): 2012 Second International Conference on, IEEE Computer Society, 2012, s. 17-24Konferensbidrag (Refereegranskat)
    Abstract [en]

    The cloud computing landscape has recently developed into a spectrum of cloud architectures, leading to a broad range of management tools for similar operations but specialized for certain deployment scenarios. This both hinders the efficient reuse of algorithmic innovations within cloud management operations and increases the heterogeneity between different management systems. Our overarching goal is to overcome these problems by developing tools general enough to support the full range of popular architectures. In this contribution, we analyze commonalities in recently proposed cloud models (private clouds, multi-clouds, bursted clouds, federated clouds, etc.), and demonstrate how a key management functionality - service deployment - can be uniformly performed in all of these by a carefully designed system. The design of our service deployment framework is validated through a demonstration of how it can be used to deploy services, perform bursting and brokering, as well as mediate a cloud federation in the context of the OPTIMIS Toolkit.

  • 7.
    Li, Wubin
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Cost-Optimal Cloud Service Placement under Dynamic Pricing Schemes2013Ingår i: 6th IEEE/ACM International Conference on Utility and Cloud Computing, IEEE Computer Society, 2013, s. 187-194Konferensbidrag (Refereegranskat)
    Abstract [en]

    Until now, most research on cloud service placement has focused on static pricing scenarios, where cloud providers offer fixed prices for their resources. However, with the recent trend of dynamic pricing of cloud resources, where the price of a compute resource can vary depending on the free capacity and load of the provider, new placement algorithms are needed. In this paper, we investigate service placement in dynamic pricing scenarios by evaluating a set of placement algorithms, tuned for dynamic pricing. The algorithms range from simple heuristics to combinatorial optimization solutions. The studied algorithms are evaluated by deploying a set of services across multiple providers. Finally, we analyse the strengths and weaknesses of the algorithms considered. The evaluation suggests that exhaustive search based approach is good at finding optimal solutions for service placement under dynamic pricing schemes, but the execution times are usually long. In contrast, greedy approaches perform surprisingly well with fast execution times and acceptable solutions, and thus can be a suitable compromise considering the tradeoffs between quality of solution and execution time.

  • 8.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dynamic Cloud Resource Management: Scheduling, Migration and Server Disaggregation2014Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    A key aspect of cloud computing is the promise of infinite, scalable resources, and that cloud services should scale up and down on demand. This thesis investigates methods for dynamic resource allocation and management of services in cloud datacenters, introducing new approaches as well as improvements to established technologies.Virtualization is a key technology for cloud computing as it allows several operating system instances to run on the same Physical Machine, PM, and cloud services normally consists of a number of Virtual Machines, VMs, that are hosted on PMs. In this thesis, a novel virtualization approach is presented. Instead of running each PM isolated, resources from multiple PMs in the datacenter are disaggregated and exposed to the VMs as pools of CPU, I/O and memory resources. VMs are provisioned by using the right amount of resources from each pool, thereby enabling both larger VMs than any single PM can host as well as VMs with tailor-made specifications for their application. Another important aspect of virtualization is live migration of VMs, which is the concept moving VMs between PMs without interruption in service. Live migration allows for better PM utilization and is also useful for administrative purposes. In the thesis, two improvements to the standard live migration algorithm are presented, delta compression and page transfer reordering. The improvements can reduce migration downtime, i.e., the time that the VM is unavailable, as well as the total migration time. Postcopy migration, where the VM is resumed on the destination before the memory content is transferred is also studied. Both userspace and in-kernel postcopy algorithms are evaluated in an in-depth study of live migration principles and performance.Efficient mapping of VMs onto PMs is a key problem for cloud providers as PM utilization directly impacts revenue. When services are accepted into a datacenter, a decision is made on which PM should host the service VMs. This thesis presents a general approach for service scheduling that allows for the same scheduling software to be used across multiple cloud architectures. A number of scheduling algorithms to optimize objectives like revenue or utilization are also studied. Finally, an approach for continuous datacenter consolidation is presented. As VM workloads fluctuate and server availability varies any initial mapping is bound to become suboptimal over time. The continuous datacenter consolidation approach adjusts this VM-to-PM mapping during operation based on combinations of management actions, like suspending/resuming PMs, live migrating VMs, and suspending/resuming VMs. Proof-of-concept software and a set of algorithms that allows cloud providers to continuously optimize their server resources are presented in the thesis.

  • 9.
    Svärd, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Live VM Migration: Principles and Performance2012Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Virtualization is a key technology for cloud computing as it allows several operating system instances to run on the same machine, enhances resource manageability and enables flexible definition of billing units. Virtualization works by adding a software layer, a hypervisor, on top of the hardware platform. Virtual Machines, \emph{VMs}, are run on top of the hypervisor, which provisions hardwares resources to the VM guests. In addition to enabling higher utilization of hardware resources, the ability to move VMs from one host to another is an important feature.

    Live migration is the concept of migrating a VM while it is running and responding to requests. Since VMs can be re-located while running, live migration allows for better hardware utilization. This is because placement of services can be performed dynamically and not only when the are started. Live migration is also a useful tool for administrative purposes. If a server needs to be taken off-line for maintenance reasons, it can be cleared of services by live migrating these to other hosts.

    This thesis investigates the principles behind live migration. The common live migration approaches in use today are evaluated and common objectives are presented as well as challenges that have to be overcome in order to implement an ideal live migration algorithm. The performance of common live migration approaches is also evaluated and it is found that even though live migration is supported by most hypervisors, it has drawbacks which makes the technique hard to use in certain situations. Migrating CPU and/or memory intensive VMs or migrating VMs over low-bandwidth links is a problem regardless of which approach that is used. To tackle this problem, two improvements to live migration are proposed and evaluated, delta compression and dynamic page transfer reordering. Both improvements demonstrate better performance than the standard algorithm when migrating CPU and/or memory intensive VMs and migrating over low bandwidth links. Finally, recommendations are made on which live migration approach to use depending on the scenario and also what improvements to the standard live migration algorithms should be used and when.

  • 10.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hudzia, Benoit
    SAP (UK) Limited, Belfast, United Kingdom.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Evaluation of delta compression techniques for efficient live migration of large virtual machines2011Ingår i: The 2011 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE 2011), New York, NY: ACM Press, 2011, s. 111-120Konferensbidrag (Refereegranskat)
    Abstract [en]

    Despite the widespread support for live migration of Virtual Machines (VMs) in current hypervisors, these have significant shortcomings when it comes to migration of certain types of VMs. More specifically, with existing algorithms, there is a high risk of service interruption when migrating VMs with high workloads and/or over low-bandwidth networks. In these cases, VM memory pages are dirtied faster than they can be transferred over the network, which leads to extended migration downtime. In this contribution, we study the application of delta compression during the transfer of memory pages in order to increase migration throughput and thus reduce downtime. The delta compression live migration algorithm is implemented as a modification to the KVM hypervisor. Its performance is evaluated by migrating VMs running different type of workloads and the evaluation demonstrates a significant decrease in migration downtime in all test cases. In a benchmark scenario the downtime is reduced by a factor of 100. In another scenario a streaming video server is live migrated with no perceivable downtime to the clients while the picture is frozen for eight seconds using standard approaches. Finally, in an enterprise application scenario, the delta compression algorithm successfully live migrates a very large system that fails after migration using the standard algorithm. Finally, we discuss some general effects of delta compression on live migration and analyze when it is beneficial to use this technique.

  • 11.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hudzia, Benoit
    SAP Research Belfast.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hecatonchire: Enabling Multi-Host Virtual Machines by Resource Aggregation and Pooling2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Vertical elasticity, or scale-up of individual virtual ma- chines is hard to perform in today’s cloud environments due to limitations in the amount of hardware resources available in single servers. We propose a novel approach that allows aggregation of memory, compute and I/O resources from multiple physical machines in resource pools which in turn are used to seamlessly provision vir- tual machines with the right amount of resources. We present our architecture and highlight key functionality such as transparent and resilient memory aggregation and fast live migration. Our approach is validated by a demonstration using benchmarks and a real-world big- data application. Performance results indicate a very low overhead in using aggregated memory as well as a sig- nificant improvement in live migration performance.

  • 12.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hudzia, Benoit
    Stratoscale, Belfast, UK.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hecatonchire: Towards Multi-Host Virtual Machines by Server Disaggregation2014Ingår i: EuroPar 2014: 20:th International Conference on Parallell Processing / [ed] Luis Lopes, Springer, 2014, s. 519-529Konferensbidrag (Refereegranskat)
    Abstract [en]

    Horizontal elasticity through scale-out is the current dogma for scaling cloud applications but requires a particular application architecture. Vertical elasticity is transparent to applications but less used as scale-up is limited by the size of a single physical server. In this paper, we propose a novel approach, server disaggregation, that aggregates memory, compute and I/O resources from multiple physical machines in resource pools. From these pools, virtual machines can be seamlessly provisioned with the right amount of resources for each application and more resources can be added to vertically scale a virtual machine as needed, regardless of the bound of any single physical machine. We present our proposed architecture and implement key functionality such as transparent memory scale-out and cloud management integration. Our approach is validated by a demonstration using benchmarks and a real-world big-data application and results indicate a low overhead in using memory scale-out in both test cases.

  • 13.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hudzia, Benoit
    SAP Research CEC Belfast.
    Walsh, Steve
    SAP Research CEC Belfast.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Principles and performance characteristics of algorithms for live VM migration2015Ingår i: ACM SIGOPS Operating Systems Review, Vol. 49, nr 1, s. 142-155Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Since first demonstrated by Clark et al. in 2005, live migration of virtual machines has both become a standard feature of hypervisors and created an active field of research. However, the rich ongoing research in live migration focusmainly on performance improvements to well-known techniques, most of them being variations of the Clark approach. In order to advance live migration beyond incremental performance improvements, it is important to gain a deeper understanding of the live migration problem itself and its underlying principles.

    To address this issue, this contribution takes a step back and investigates the essential characteristics of live migration. The paper identifies five fundamental properties of live migration and uses these to investigate, categorize, and compare three approaches to live migration: precopy, postcopy and hybrid. The evaluated algorithms include well-known techniques derived from that of Clark as well as novel RDMA in-kernel approaches. Our analysis of the fundamental properties of the algorithms is validated by a set of experiments. In these, we migrate virtual machines with large memory sizes hosting workloads with high page dirtying rates to expose differences and limitations of the different approaches. Finally, we provide guidelines for which approach to use in different scenarios.

  • 14.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Li, Wubin
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Wadbro, Eddie
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Continuous Datacenter Consolidation2014Rapport (Refereegranskat)
    Abstract [en]

    Efficient mapping of Virtual Machines (VMs) onto physical servers is a key problem for cloud infrastructure providers as hardware utilization directly im- pacts revenue. Today, this mapping is commonly only performed when new VMs are created, but as VM workloads fluctuate and server availability varies, any ini- tial mapping is bound to become suboptimal over time. We introduce a set of heuristic methods for continuous optimization of the VM-to-server mapping based on combina- tions of fundamental management actions, namely suspending and resuming physical machines, migrating VMs, and suspending and resuming VMs. Using these methods cloud infrastructure providers can continuously optimize their server resources regard- less of the predictability of the workload. To verify that our approach is applicable in real-world scenarios, we build a proof-of-concept datacenter management system that implements the proposed algorithms. The feasibility of our approach is evaluated through a combination of simulations and real experiments where our system provi- sions a workload of benchmark applications. Our results indicate that the proposed algorithms are feasible, that the combined management approach achieves the best results, and that the VM suspend and resume mechanism has the largest impact. 

  • 15.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Li, Wubin
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Wadbro, Eddie
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Continuous Datacenter Consolidation2015Ingår i: 2015 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2015, s. 387-396Konferensbidrag (Refereegranskat)
    Abstract [en]

    Efficient mapping of Virtual Machines (VMs) onto physical servers is a key problem for cloud infrastructure providers as hardware utilization directly impacts profit. Today, this mapping is commonly only performed when new VMs are created, but as VM workloads fluctuate and server availability varies, any initial mapping is bound to become suboptimal over time. We introduce a set of heuristic methods for continuous optimization of the VM-to-server mapping based on combinations of fundamental management actions, namely suspending and resuming physical machines, migrating VMs, and suspending and resuming VMs. By using these methods, cloud infrastructure providers can continuously optimize their server resources regardless of the predictability of the workload. To verify that our approach is applicable in real-world scenarios, we build a proof-of-concept datacenter management system that implements the proposed algorithms. The feasibility of our approach is evaluated through a combination of simulations and real experiments where our system provisions a workload of benchmark applications. Our results indicate that the proposed algorithms are feasible, that the combined management approach achieves the best results, and that the VM suspend and resume mechanism has the largest impact on provider profit.

  • 16.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    The Noble art of Live MigrationManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    Although a mature technique and an important feature of virtualization, live VM migration still suffers from performance and robustness issues, limiting its usefulness. This is particularly true if the migration technique is not appropriately selected for the usage scenario. In this contribution, we define requirements for live migration and discuss some of the challenges that arise in meeting these. We investigate, categorize, and compare current approaches to live migration as well as provide guidelines for which to use in different scenarios. Our investigation is validated by a set of experiments that highlights different characteristics of these approaches. We also propose methods for hybrid live migration and an improved memory page reordering algorithm. Finally we outline the future research landscape in the area. 

  • 17.
    Svärd, Petter
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Tordsson, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Hudzia, Benoit
    SAP Research CEC Belfast, UK.
    Elmroth, Erik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    High Performance Live Migration through Dynamic Page Transfer Reordering and Compression2011Ingår i: 2011 IEEE Third International Conference on Cloud Computing Technology and Science, IEEE Computer Society, 2011, s. 542-548Konferensbidrag (Refereegranskat)
    Abstract [en]

    Although supported by many contemporary Virtual Machine (VM) hyper visors, live migration is impossible for certain applications. When migrating CPU and/or memory intensive VMs two problems occur, extended migration downtime that may cause service interruption or even failure, and prolonged total migration time that is harmful for the overall system performance as significant network resources must be allocated to migration. These problems become more severe for migration over slower networks, such as long distance migration between clouds. We approach this two-fold problem through a combination of techniques. A novel algorithm that dynamically adapts the transfer order of VM memory pages during live migration reduces the risk of re-transfers for frequently dirtied pages. As the amount of transferred data is thereby reduced, the total migration time is shortened. By combining this technique with a compression scheme that increases the migration bandwidth the migration downtime is also reduced. An evaluation by means of synthetic migration benchmarks shows that our combined approach reduces migration downtime by a factor 10 to 20, shortens total migration time by around 35%, as well as consumes between 26% and 39% less network bandwidth. The feasibility of our approach for real-life applications is demonstrated by migrating a streaming video server 31% faster while transferring 51% less data.

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