Overload Control Mechanisms for Web Servers

Iyer, Ravi; Tewari, Vijay; Kant, Krishna

doi:10.1007/978-1-4471-0705-7_13

Cited by 39 publications

(25 citation statements)

References 3 publications

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“…A common way to achieve efficient overload control in traditional distributed systems is to use admission control mechanisms [7,20]. In grids, however, instead of dropping or rejecting tasks, it may be sufficient to delay the submission of some of the tasks, in the expectation that the sites which to dispatch them will become less overloaded at a later time.…”

Section: Task Throttlingmentioning

confidence: 99%

Performance analysis of dynamic workflow scheduling in multicluster grids

Sonmez

Yigitbasi

Abrishami

et al. 2010

Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

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Scientists increasingly rely on the execution of workflows in grids to obtain results from complex mixtures of applications. However, the inherently dynamic nature of grid workflow scheduling, stemming from the unavailability of scheduling information and from resource contention among the (multiple) workflows and the non-workflow system load, may lead to poor or unpredictable performance. In this paper we present a comprehensive and realistic investigation of the performance of a wide range of dynamic workflow scheduling policies in multicluster grids. We first introduce a taxonomy of grid workflow scheduling policies that is based on the amount of dynamic information used in the scheduling process, and map to this taxonomy seven such policies across the full spectrum of information use. Then, we analyze the performance of these scheduling policies through simulations and experiments in a real multicluster grid. We find that there is no single grid workflow scheduling policy with good performance across all the investigated scenarios. We also find from our real system experiments that with demanding workloads, the limitations of the head-nodes of the grid clusters may lead to performance loss not expected from the simulation results. We show that task throttling, that is, limiting the per-workflow number of tasks dispatched to the system, prevents the head-nodes from becoming overloaded while largely preserving performance, at least for communication-intensive workflows.

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Section: Task Throttlingmentioning

confidence: 99%

Performance analysis of dynamic workflow scheduling in multicluster grids

Sonmez

Yigitbasi

Abrishami

et al. 2010

Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

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“…The determination of these rate limits, however, is not dynamic but is delegated to the administrator. Iyer et al [Iyer et al 2000] propose a system based on two mechanisms-using thresholds on the connection queue length to decide when to start dropping new connection requests and sending feedback to the proxy during overloads which would cause it to restrict the traffic being forwarded to the server. However, they do not address how these thresholds may be determined online.…”

Section: Slas and Adaptive Qos Degradationmentioning

confidence: 99%

Agile dynamic provisioning of multi-tier Internet applications

Urgaonkar

Shenoy

Chandra

et al. 2008

ACM Trans. Auton. Adapt. Syst.

342

292

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-Dynamic capacity provisioning is a useful technique for handling the multi-time-scale variations seen in Internet workloads. In this paper, we propose a novel dynamic provisioning technique for multi-tier Internet applications that employs (i) a flexible queuing model to determine how much resources to allocate to each tier of the application, and (ii) a combination of predictive and reactive methods that determine when to provision these resources, both at large and small time scales. We propose a novel data center architecture based on virtual machine monitors to reduce provisioning overheads. Our experiments on a forty-machine Xen/Linux-based hosting platform demonstrate the responsiveness of our technique in handling dynamic workloads. In one scenario where a flash crowd caused the workload of a three-tier application to double, our technique was able to double the application capacity within five minutes, thus maintaining response time targets. Our technique also reduced the overhead of switching servers across applications from several minutes to less than a second, while meeting the performance targets of residual sessions.

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“…Realizing any meaningful usage/cost gains for the power infrastructure may require setting the provisioning parameters (e.g., p and δ introduced in the previous section) high enough to make the likelihood of budget violations non-negligible. Furthermore, hard-to-predict workload changes (such as an overload experienced by an e-commerce site [Iyer 2000]) may also render budget violations more likely than predicted using application profiles. These concerns necessitate mechanisms within a data center that can completely avert such episodes.…”

Section: Enforcement Of Soft Fusesmentioning

confidence: 99%

Statistical profiling-based techniques for effective power provisioning in data centers

Govindan

Choi

Urgaonkar

et al. 2009

Proceedings of the 4th ACM European Conference on Computer Systems

126

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Current capacity planning practices based on heavy over-provisioning of power infrastructure hurt (i) the operational costs of data centers as well as (ii) the computational work they can support. We explore a combination of statistical multiplexing techniques to improve the utilization of the power hierarchy within a data center. At the highest level of the power hierarchy, we employ controlled underprovisioning and over-booking of power needs of hosted workloads. At the lower levels, we introduce the novel notion of soft fuses to flexibly distribute provisioned power among hosted workloads based on their needs. Our techniques are built upon a measurement-driven profiling and prediction framework to characterize key statistical properties of the power needs of hosted workloads and their aggregates. We characterize the gains in terms of the amount of computational work (CPU cycles) per provisioned unit of powerComputation per Provisioned Watt (CPW). Our technique is able to double the CPW offered by a Power Distribution Unit (PDU) running the e-commerce benchmark TPC-W compared to conventional provisioning practices. Over-booking the PDU by 10% based on tails of power profiles yields a further improvement of 20%. Reactive techniques implemented on our Xen VMM-based servers dynamically modulate CPU DVFS states to ensure power draw below the limits imposed by soft fuses. Finally, information captured in our profiles also provide ways of controlling application performance degradation despite overbooking. The 95 th percentile of TPC-W session response time only grew from 1.59 sec to 1.78 sec-a degradation of 12%.

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Overload Control Mechanisms for Web Servers

Cited by 39 publications

References 3 publications

Performance analysis of dynamic workflow scheduling in multicluster grids

Performance analysis of dynamic workflow scheduling in multicluster grids

Agile dynamic provisioning of multi-tier Internet applications

Statistical profiling-based techniques for effective power provisioning in data centers

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