Shared-Memory Optimizations for Inter-Virtual-Machine Communication

Ren, Yi; Liu, Ling; Zhang, Qi; Wu, Qingbo; Guan, Jianbo; Kong, Jing; Dai, Huadong; Shao, Leng−Leng

doi:10.1145/2847562

Cited by 21 publications

(7 citation statements)

References 24 publications

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“…Compared to the above interdomain communication mode, based on shared memory [6,50,51,52,53,54], Fido et al [50] implemented interdomain communication by using full page mapping. Pages are mapped to the other side, so the other side can directly read and write the corresponding page while communicating.…”

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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“…An in‐depth comparison of state‐of‐the‐art shared‐memory optimizations for inter‐VM communication is conducted in a most recent survey by Ren et al where the key issues for improving inter‐VM communication using shared memory are studied. However, it is worthwhile to note that the compared works are mostly oriented to the coresident VMs on the same physical host, which is different from Naplus , which implements a global shared memory across the VMs on different physical hosts.…”

Section: Related Workmentioning

confidence: 99%

“…In order to address this problem, some efforts have been made to improve the inter‐VM communication within the realm of virtualization . However, the existing improvements are by and large limited to the coresident VMs on the same host machine , where the message passing mechanisms are often optimized out by exploiting the shared memory in the hosts . For example, XenLoop uses shared‐memory ring buffers as an inter‐VM communication mechanism, and Fido , designed for Xen, provides a shared‐memory network and blocks devices to achieve the same purpose.…”

Section: Introductionmentioning

confidence: 99%

“…These systems often provide a limited illusion of shared memory to applications, either by supplying middleware libraries [6] or by leveraging the programming language features [7]. However, these systems are not well suited to cloud environments as the cloud resources are typically multiplexed by virtualization techniques to support a large number and scale of applications while fully utilizing the underlying physical resources.In order to address this problem, some efforts have been made to improve the inter-VM communication within the realm of virtualization [8][9][10][11]. However, the existing improvements are by and large limited to the coresident VMs on the same host machine [11,12], where the message passing mechanisms are often optimized out by exploiting the shared memory in the hosts [10,13].…”

mentioning

confidence: 99%

“…However, these systems are not well suited to cloud environments as the cloud resources are typically multiplexed by virtualization techniques to support a large number and scale of applications while fully utilizing the underlying physical resources.In order to address this problem, some efforts have been made to improve the inter-VM communication within the realm of virtualization [8][9][10][11]. However, the existing improvements are by and large limited to the coresident VMs on the same host machine [11,12], where the message passing mechanisms are often optimized out by exploiting the shared memory in the hosts [10,13]. For example, XenLoop [10] uses shared-memory ring buffers as an inter-VM communication mechanism, and Fido [8], designed for Xen, provides a shared-memory network and blocks devices to achieve the same purpose.…”

mentioning

confidence: 99%

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Naplus: a software distributed shared memory for virtual clusters in the cloud

et al. 2017

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Summary Virtual clusters (VCs) have exhibited various advantages over traditional cluster computing platforms by virtue of their extensibility, reconfigurability, and maintainability. As such, they have become a major execution environment for cloud‐based cluster applications. However, compared with traditional clusters, their distributed‐memory programming paradigm still remains largely unchanged, which implies that cluster applications cannot be efficiently deployed in VCs, especially when virtual machines (VMs) are running in different physical hosts. Recently, some efforts have been made to improve inter‐VM communication, resulting in many studies on how cluster applications could take advantages of VCs. However, most of them mainly focus on the situation that the VMs are all coresident on the same physical machine where the message passing mechanism is usually optimized away by exploiting the host's shared memory. In this paper, we present a design and implementation of Naplus, a kernel‐based virtual machine approach to the inter‐VM communications that are across different physical hosts. Naplus is based on Nahanni, a mechanism for shared‐memory communication in virtual environments. As such, it not only inherits the major merits of Nahanni with respect to flexible data structures and efficient synchronization but also achieves a shared‐memory paradigm among VMs. With Naplus, we enable the size of shared space to be maximized as large as the sum of each machine's local memory to accommodate cluster applications with large memory footprints. We prototype Naplus in a dual‐host system where an empirical study is conducted to show the effectiveness of the Naplus approach in achieving distributed shared memory for VCs in data centers. Copyright © 2017 John Wiley & Sons, Ltd.

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Privacy-Preserving SAT Solving Based on Projection-Equivalence CNF Obfuscation

Qin

Shen

2018

Cyberspace Safety and Security

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Shared-Memory Optimizations for Inter-Virtual-Machine Communication

Cited by 21 publications

References 24 publications

Interdomain I/O Optimization in Virtualized Sensor Networks

Interdomain I/O Optimization in Virtualized Sensor Networks

Naplus: a software distributed shared memory for virtual clusters in the cloud

Privacy-Preserving SAT Solving Based on Projection-Equivalence CNF Obfuscation

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