Model-based self-adaptive resource allocation in virtualized environments

Abstract

The adoption of virtualization and Cloud Computing technologies promises a number of benefits such as increased flexibility, better energy efficiency and lower operating costs for IT systems. However, highly variable workloads make it challenging to provide quality-of-service guarantees while at the same time ensuring efficient resource utilization. To avoid violations of service-level agreements (SLAs) or inefficient resource usage, resource allocations have to be adapted continuously during operation to reflect changes in application workloads. In this paper, we present a novel approach to self-adaptive resource allocation in virtualized environments based on online architecture-level performance models. We present a detailed case study of a representative enterprise application, the new SPECjEnterprise2010 benchmark, deployed in a virtualized cluster environment. The case study serves as a proof-of-concept demonstrating the effectiveness and practical applicability of our approach.

Remediating Overload in Over-Subscribed Computing Environments

“…Other related work includes workload prediction techniques that are leveraged to proactively prevent or reactively remediate overload [2][8] [10][14] [18], as well as dynamic resource management in over-subscribed Cloud [15][16] [19]. These techniques can be applied with our method as a complement in remediating overload.…”

Self-managing SLA compliance in cloud architectures

“…Huber et al [16] proposed a self-adaptive resource allocation method based on online architecture-level performance models with the goal of avoiding violations of SLAs and ensuring efficient resource usage. Their method takes into consideration cloud dynamics triggered by variation in application workload, however, ours takes into account dynamics triggered by resource and network failures.…”

Providing Dependability and Performance in the Cloud: Case Studies

“…In this section we present results of our case study on self-adaptive resource management in virtualized environments [23]. To avoid violations of service-level agreements (SLAs) or inefficient resource usage, capacity management has to be adopted continuously during system operation.…”

“…However, for this case study we extracted the entire benchmark application, i.e., including supplier domain, dealer domain, web tier and the asynchronous communication between the three domains. For reasons of brevity, the reader is referred to [23] for a detailed description of the PCM model instance.…”