pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems

Abstract

Abstract. Workload placement on servers has been traditionally driven by mainly performance objectives. In this work, we investigate the design, implementation, and evaluation of a power-aware application placement controller in the context of an environment with heterogeneous virtualized server clusters. The placement component of the application management middleware takes into account the power and migration costs in addition to the performance benefit while placing the application containers on the physical servers. The contribution of this work is two-fold: first, we present multiple ways to capture the cost-aware application placement problem that may be applied to various settings. For each formulation, we provide details on the kind of information required to solve the problems, the model assumptions, and the practicality of the assumptions on real servers. In the second part of our study, we present the pMapper architecture and placement algorithms to solve one practical formulation of the problem: minimizing power subject to a fixed performance requirement. We present comprehensive theoretical and experimental evidence to establish the efficacy of pMapper.

Energy Efficient Resource Management in Virtualized Cloud Data Centers

“…Verma et al [17] have formulated the problem of dynamic placement of applications in virtualized heterogeneous systems as continuous optimization: at each time frame the placement of VMs is optimized to minimize power consumption and maximize performance. The authors have applied a heuristic for bin packing problem with variable bin sizes and costs.…”

Strategies for Increased Energy Awareness in Cloud Federations

“…This solution is able to dynamically consolidate the workload of a software and hardware heterogeneous large-scale cluster composed of resources using the virtualization. Also, IBM has proposed pMapper [15], which is a power-aware application placement controller in the context of an environment with heterogeneous virtualized server clusters. The placement component of the application management middleware takes into account the power and migration costs in addition to the performance benefit while placing the application containers on the physical servers.…”

Geographical Load Balancing for Online Service Applications in Distributed Datacenters

“…Datacenter, VM and SLA modeling, and resource management solutions inside a datacenter are extensively discussed in the previous work, cf. [12,13,14,15,16,17,18]. In this section, a review of the most relevant work to the GLB problem is provided.…”