This work has addressed the issue of Virtual Machine Management in IaaS-type data centres from four different directions and made contributions in each. First, we explored a variety of First Fit heuristics applied to the VM Relocation problem and determined that a single policy will not be able to satisfy all management goals or perform consistently under different data centre conditions. Second, we worked on pursuing multiple management goals with equal intensity, which we achieved by dynamically switching management strategies according to data centre state. Third, we designed a hierarchical management system that, by virtue of being organized to match the topology of the data centre network, could greatly reduce network overhead. Fourth, we developed management strategies to handle multi-VM applications with placement constraints and still achieve high levels of resource utilization and SLA achievement.
[1] “RightScale 2014 state of the cloud report,” RightScale, Inc., 2014.
[2] “Cisco global cloud index: Forecast and methodology, 2012-2017,” White Paper, Cisco, 2012.
[3] N. Bobroff, A. Kochut, and K. Beaty, “Dynamic placement of virtual machines for manag- ing sla violations,” inIM Proceedings, 2007 IEEE/IFIP Int. Symp. on, 2007, pp. 119–128. [4] D. Gmach, J. Rolia, L. Cherkasova, G. Belrose, T. Turicchi, and A. Kemper, “An integrated approach to resource pool management: Policies, efficiency and quality metrics,” in 38th Annual IEEE/IFIP Int. Conf. on Dependable Systems and Networks (DSN), June 2008. [5] A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for
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DCSim
The scale of data centres providing Cloud services continues to increase, with thousands to tens-of-thousands of servers to manage. This presents a unique challenge to researchers de- veloping methods and algorithms for management, as the scale of the target environment pre- cludes the use of a physical testbed. As such, simulation is commonly used for the evaluation of management techniques. Simulation also helps researchers quickly evaluate data centre management algorithms and techniques at a speed and scale not possible with a real imple- mentation.
DCSim (Data Centre Simulator) [2, 3] is a simulation tool for simulating a virtualized data centre operating as an Infrastructure as a Service (IaaS) cloud. To support our research and to provide tools that other researchers can leverage in their work, we have developed DCSim. Its features include event handling and message passing, mechanisms for event callbacks and sequencing, new components to simplify the creation of management systems and to model the communication between them, and a more complete model of the structure of a data centre including racks and clusters. We also introduce classes to help streamline the creation of new experiments, new output options and metrics, and a visualization tool to help provide a new perspective on the behaviour of data centre management methods and systems. Finally, we continue to focus on providing an extensible platform for researchers to extend and adapt to suit their own work.
The remainder of this chapter is organized as follows: Section A.1 presents related work in data centre simulation, Section A.2 describes the architecture, core features and new additions to DCSim, Section A.3 gives some detail on how to configure and run experiments with DC- Sim, Section A.4 provides an evaluation of the simulator through a demonstration of its use, and Section A.5 presents some conclusions and future work.
0This chapter is based on work published in [1].
A.1
Related Work
There are a small set of existing simulation tools available, each with their own strengths, weaknesses, and target environments. GreenCloud [4] is designed to evaluate the energy costs of operating a data centre. It is a packet-level simulator built as an extension to Ns-2 [5], and provides a detailed model of communication hardware and power consumption of each element of the data centre. It does not, however, include modelling of virtualization. MDCSim [6] is designed to simulate a large-scale data centre running a three-tiered web application. It fo- cuses only on evaluating the configuration of each tier, measuring both power and performance metrics. As with GreenCloud, it does not consider virtualization. Furthermore, it is built on a commercial product and is not publicly available.
GDCSim (Green Data Centre Simulator) [7] aims to help researchers fine-tune the inter- actions between management systems and the physical layout of the data centre, including thermal and cooling interactions with workload placement. This tool does not consider multi- ple tenants of the data centre, nor does it consider virtualization.
CloudSim [8] simulates a virtualized data centre, with multiple clients operating VMs. However, it implements an HPC-style workload, withCloudlets(jobs) submitted by users to VMs for processing. It can be manipulated to simulate an interactive, continuous workload such as a web server [9], but it lacks a real model of such an application. An extension of CloudSim, NetworkCloudSim [10], considers communication costs between VMs performing parallel computations, but again focuses on HPC-style workloads rather than interactive work- loads. Additionally, our work on DCSim adds data centre organization components such as racks and clusters not present in CloudSim.
SimWare [11] targets the modelling of data centre cooling and power costs, including the impact of server fan power consumption as related to the temperature of the data centre, and air travel time from CRACs to servers. Their simulated client workload is based on traces of HPC systems, rather than interactive applications.
DCSim [2, 3] models a virtualized data centre providing IaaS to multiple tenants, with a focus on transactional, continuous workloads, and models such an application using a basic queuing model. It can model replicated VMs sharing incoming workload, as well as dependen- cies between VMs that are part of a multi-tiered application. It also provides metrics to gauge SLA achievement, power consumption, and other performance metrics that serve to evaluate a data centre management approach or system. Furthermore, DCSim is designed to be easily extended, implementing new features and functionality.
Figure A.1: Data Centre Model