Residency Aware Inter-VM Communication in Virtualized Cloud: Performance Measurement and Analysis

Zhang, Qi; Liu, Ling; Ren, Yi; Lee, Kisung; Tang, Yuzhe; Zhao, Xu; Zhou, Yang

doi:10.1109/cloud.2013.116

Cited by 16 publications

(6 citation statements)

References 12 publications

(26 reference statements)

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“…Disk I/O performance is vital for virtualized systems like HPC clusters or commodity servers [12,13,26,29,30,32,33,62,63]. Zeng et al [62] proposed Raccoon, a network I/O allocation framework for a workload-aware VM scheduling algorithm, to facilitate hybrid I/O workloads in virtual environments.…”

Section: Related Workmentioning

confidence: 99%

Interdomain I/O Optimization in Virtualized Sensor Networks

Jiang

Fan

Qiu

et al. 2018

Sensors

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In virtualized sensor networks, virtual machines (VMs) share the same hardware for sensing service consolidation and saving power. For those VMs that reside in the same hardware, frequent interdomain data transfers are invoked for data analytics, and sensor collaboration and actuation. Traditional ways of interdomain communications are based on virtual network interfaces of bilateral VMs for data sending and receiving. Since these network communications use TCP/IP (Transmission Control Protocol/Internet Protocol) stacks, they result in lengthy communication paths and frequent kernel interactions, which deteriorate the I/O (Input/Output) performance of involved VMs. In this paper, we propose an optimized interdomain communication approach based on shared memory to improve the interdomain communication performance of multiple VMs residing in the same sensor hardware. In our approach, the sending data are shared in memory pages maintained by the hypervisor, and the data are not transferred through the virtual network interface via a TCP/IP stack. To avoid security trapping, the shared data are mapped in the user space of each VM involved in the communication, therefore reducing tedious system calls and frequent kernel context switches. In implementation, the shared memory is created by a customized shared-device kernel module that has bidirectional event channels between both communicating VMs. For performance optimization, we use state flags in a circular buffer to reduce wait-and-notify operations and system calls during communications. Experimental results show that our proposed approach can provide five times higher throughput and 2.5 times less latency than traditional TCP/IP communication via a virtual network interface.

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Section: Related Workmentioning

confidence: 99%

Interdomain I/O Optimization in Virtualized Sensor Networks

Jiang

Fan

Qiu

et al. 2018

Sensors

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“…In particular, the task completion time for meeting "rack data locality" and "acrossrack data locality" approaches three and four times as long as that for meeting "host data locality", respectively. Data transmission between co-located VMs is often as efficient as local data access mainly because inter-VM communication within a single host is optimized by the hypervisor [18] . Hence, we consider to improve "host data locality" in order to optimize the performance of the DHCI architecture.…”

Section: Dynamic Migration Based Data Localitymentioning

confidence: 99%

Load feedback-based resource scheduling and dynamic migration-based data locality for virtual hadoop clusters in openstack-based clouds

Tao

Lin

Wang

2017

Tinshhua Sci. Technol.

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With cloud computing technology becoming more mature, it is essential to combine the big data processing tool Hadoop with the Infrastructure as a Service (IaaS) cloud platform. In this study, we first propose a new Dynamic Hadoop Cluster on IaaS (DHCI) architecture, which includes four key modules: monitoring, scheduling, Virtual Machine (VM) management, and VM migration modules. The load of both physical hostsand VMs is collected by the monitoring module and can be used to design resource scheduling and data locality solutions. Second, we present a simple load feedback-based resource scheduling scheme. The resource allocation can be avoided on overburdened physical hosts or the strong scalability of virtual cluster can be achieved by fluctuating the number of VMs. To improve the flexibility, we adopt the separated deployment of the computation and storage VMs in the DHCI architecture, which negatively impacts the data locality. Third, we reuse the method of VM migration and propose a dynamic migration-based data locality scheme using parallel computing entropy. We migrate the computation nodes to different host(s) or rack(s) where the corresponding storage nodes are deployed to satisfy the requirement of data locality. We evaluate our solutions in a realistic scenario based on OpenStack. Substantial experimental results demonstrate the effectiveness of our solutions that contribute to balance the workload and performance improvement, even under heavy-loaded cloud system conditions.

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“…From our experimental observations on existing open source shared memory based co-resident VM communication mechanism, we find that throughput or latency of data interchange turns unstable under certain circumstances and the mechanisms even fails to work in some boundary conditions [15]. Therefore, special concerns should be paid during the design of the shared memory based inter-VM communication mechanisms for co-resident VMs to ensure the stability.…”

Section: Seamless Agility and Multi-level Transparencymentioning

confidence: 99%

Residency-Aware Virtual Machine Communication Optimization: Design Choices and Techniques

Ren

Liu

Zhang

et al. 2013

2013 IEEE Sixth International Conference on Cloud Computing

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Abstract-Network I/O workloads are dominating in many data centers and cloud computing environments today. One way to improve inter Virtual Machine (VM) communication efficiency is to support co-resident VM communication by using shared memory based approaches and to resort to the traditional TCP/IP for inter-VM communications between VMs that are located on different physical hosts. Although a number of independent efforts are dedicated to improving communication efficiency between co-resident VMs, they differ from one another in terms of how the inter-VM communication optimization is carried out and where in the software stack the shared memory channel is established. In this paper, we provide an in-depth overview of the design choices and techniques for optimizing the performance of the co-resident inter-VM communication, with dual objectives. First, we describe the core design guidelines and key issues for optimizing inter-VM communication by using shared memory based mechanisms. Typical issues include choices of implementation layer in the software stack, seamless agility for VM live migration and VM dynamic deployment support, multilevel transparency. Second, we conduct a comprehensive analysis of representative state-of-the-art research efforts and implementation techniques based on the core design guidelines. We also give an analysis of future requirements in advanced features such as reliability, security and stability. The research reported in this paper not only provides the reference for developing the next generation of inter-VM communication optimization mechanisms, but also offers opportunities for both cloud infrastructure providers and cloud service consumers to improve inter-VM communication efficiency in virtualized platforms.

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Residency Aware Inter-VM Communication in Virtualized Cloud: Performance Measurement and Analysis

Abstract: Abstract-A known problem for virtualized cloud data centers is the inter-VM communication inefficiency for data transfer between

Cited by 16 publications

References 12 publications

Interdomain I/O Optimization in Virtualized Sensor Networks

Interdomain I/O Optimization in Virtualized Sensor Networks

Load feedback-based resource scheduling and dynamic migration-based data locality for virtual hadoop clusters in openstack-based clouds

Residency-Aware Virtual Machine Communication Optimization: Design Choices and Techniques

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