SageShift: Managing SLAs for highly consolidated cloud

Sukwong, Orathai; Sangpetch, Akkarit; Kim, Hyong S.

doi:10.1109/infcom.2012.6195591

Cited by 24 publications

(14 citation statements)

References 11 publications

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“…In many related studies, 100 requests per second (or even lower numbers) are chosen (see e.g. [4], [12]). As we focus on higher loads, we have chosen 100 Hr/s as the lowest call frequency.…”

Section: Experimental Planningmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Data Routing Decisions for Compliant Data Handling in Service-and Cloud-Based Architectures: A Performance Analysis

Amiri

Krieger

Zdun

et al. 2019

2019 IEEE International Conference on Services Computing (SCC)

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In many service-based applications, decisions about data routing need to be made at runtime, for instance to ensure compliant data handling. Different service-and cloudbased architectures to make dynamic data routing decisions exist including central entities, multiple dedicated dynamic router services, or using a sidecar for each involved service. These architectures differ in various quality attributes including complexity, understandability, and changeability of the decision logic. Choosing the wrong architecture for decision-making at runtime may severely impact the performance of the software system. In this paper, we have evaluated the performance of three representative approaches for processing compliance rules concerned with data routing in service-and cloud-based architectures. The results show that distributed approaches for dynamic data routing have a better performance compared to centralized solutions. On the other hand, centralized solutions are easier to understand and change, but this strongly depends on the domain problem.

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Section: Experimental Planningmentioning

confidence: 99%

“…Our experimental setup is influenced by the named related work, a broader study of related experimental setups (e.g. [4], [12], [6]), and our own experiences in building microservice and cloud systems as outlined above.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Data Routing Decisions for Compliant Data Handling in Service-and Cloud-Based Architectures: A Performance Analysis

Amiri

Krieger

Zdun

et al. 2019

2019 IEEE International Conference on Services Computing (SCC)

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“…SageShift [38] targets the hosting of web services, and uses SLAs to make admission control of new VMs (Sage) based on the expected rate of co-arrival requests. In addition, it presents an extension to an hypervisor scheduler (Shift) to control the order of execution of colocated VMs, and minimize the risk of failing to meet the negotiated response time.…”

Section: Related Workmentioning

confidence: 99%

Partial Utility-Driven Scheduling for Flexible SLA and Pricing Arbitration in Clouds

Simão

Veiga

2016

IEEE Trans. Cloud Comput.

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Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads' execution time is also improved, by incorporating an SLA-based redistribution of their VM's computational power.

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“…In most of the research work VM consolidation [1], [10], [11] is regarded as a bin-packing problem to map VMs onto PMs with minimal number of PM used. Comprehensive studies on VM packing problems are conducted in [12] and [13].…”

Section: Related Workmentioning

confidence: 99%

“…Then we get Equation (10) from the recursive relation of θ(t) in Equation (8). Using the fact that O(t) and I(t) are mutually independent we have Equation (11), and from the distribution of O(t) and I(t) in Equation (7) we have Equation (12). Let P = [p ij ] denote the matrix of one-step transition probabilities which can be calculated by Equation (12) with given p on and p of f values.…”

Section: B Resource Reservation For a Single Pmmentioning

confidence: 99%

Burstiness-aware Server Consolidation via Queuing Theory Approach in a Computing Cloud

Luo

Qian

2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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Burstiness is a common pattern of virtual machines (VMs)'s workload in production data centers, where spikes usually occur aperiodically with low frequency and last shortly. Since virtualization technology enables elastic resource provisioning in a computing cloud, the bursty workloads could be handled effectively through dynamically scaling up/down. However, to cut back energy consumption, VMs are usually highly consolidated with the minimum number of physical machines (PMs) used. In this case, to meet the runtime expanding demands of the resources (spikes), some VMs have to be migrated to other idle PMs, which is costly and causes performance degradation potentially. In this paper, we investigate the elastic resource provisioning problem and propose a novel VM consolidation mechanism with resource reservation which takes burstiness into consideration as well as energy consumption. We model the resource requirement pattern as the popular ON-OFF Markov chain to represent burstiness, based on which a reservation strategy via queuing theory approach is given for each PM. Next we present a complete VM consolidation scheme with resource reservation within reasonable time complexity. The experiment result show that our algorithms improve the consolidation ratio by up to 45% with large spike size and around 30% with normal spike size compared to those provisioning for peak workload, and a better balance of performance and energy consumption is achieved in comparison with other commonly used consolidation algorithms.

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SageShift: Managing SLAs for highly consolidated cloud

Cited by 24 publications

References 11 publications

Dynamic Data Routing Decisions for Compliant Data Handling in Service-and Cloud-Based Architectures: A Performance Analysis

Dynamic Data Routing Decisions for Compliant Data Handling in Service-and Cloud-Based Architectures: A Performance Analysis

Partial Utility-Driven Scheduling for Flexible SLA and Pricing Arbitration in Clouds

Burstiness-aware Server Consolidation via Queuing Theory Approach in a Computing Cloud

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