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Ardalan Kangarlou

dblp:40/7892 · DBLP profile ↗
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7ranked-venue papers
4as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 6 · 3 first-authorSecurity and privacy · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
5 papers
Cloud and datacenter computing · 62% Storage systems · 27% Distributed systems · 12%
Computer networks
3 papers
Transport protocols and congestion control · 87% Network measurement and analytics · 13%

Topics — the 13 heaviest of 14, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
virtualization
0.432013
Protocol Responsibility Offloading to Improve TCP Throughput in Virtualized Environments · ACM Trans. Comput. Syst. 2013
vSlicer: latency-aware virtual machine scheduling via differentiated-frequency CPU slicing · HPDC 2012
vSnoop: Improving TCP Throughput in Virtualized Environments via Acknowledgement Offload · SC 2010
Storage systems
file systems
0.212015
Chronicle: Capture and Analysis of NFS Workloads at Line Rate · FAST 2015
Storage systems › file systems › distributed file system
network file system
0.212015
Chronicle: Capture and Analysis of NFS Workloads at Line Rate · FAST 2015
Transport protocols and congestion control › transport protocol implementation
congestion control offloading
0.212013
Protocol Responsibility Offloading to Improve TCP Throughput in Virtualized Environments · ACM Trans. Comput. Syst. 2013
Transport protocols and congestion control
TCP congestion control
0.212013
Protocol Responsibility Offloading to Improve TCP Throughput in Virtualized Environments · ACM Trans. Comput. Syst. 2013
Cloud and datacenter computing › virtualization
virtual machine networking
0.212013
Protocol Responsibility Offloading to Improve TCP Throughput in Virtualized Environments · ACM Trans. Comput. Syst. 2013
Cloud and datacenter computing
cluster resource management and scheduling
0.112012
vSlicer: latency-aware virtual machine scheduling via differentiated-frequency CPU slicing · HPDC 2012
Distributed systems › distributed algorithms
distributed snapshot
0.112012
VNsnap: Taking Snapshots of Virtual Networked Infrastructures in the Cloud · IEEE Trans. Serv. Comput. 2012
Cloud and datacenter computing › virtualization › virtual machine management
virtual machine scheduling
0.112012
vSlicer: latency-aware virtual machine scheduling via differentiated-frequency CPU slicing · HPDC 2012
Transport protocols and congestion control
TCP
0.112010
vSnoop: Improving TCP Throughput in Virtualized Environments via Acknowledgement Offload · SC 2010
Cloud and datacenter computing › virtualization › virtual machine management
virtual machine consolidation
0.122013
Protocol Responsibility Offloading to Improve TCP Throughput in Virtualized Environments · ACM Trans. Comput. Syst. 2013
vSnoop: Improving TCP Throughput in Virtualized Environments via Acknowledgement Offload · SC 2010
Distributed systems › fault tolerance
checkpointing
0.012012
VNsnap: Taking Snapshots of Virtual Networked Infrastructures in the Cloud · IEEE Trans. Serv. Comput. 2012
Cloud and datacenter computing › cloud service models
infrastructure as a service
0.012012
VNsnap: Taking Snapshots of Virtual Networked Infrastructures in the Cloud · IEEE Trans. Serv. Comput. 2012

Methods — techniques the papers use, named apart from their topics

workload characterization · 0.4acknowledgement offload · 0.2micro time slice scheduling · 0.1distributed snapshot · 0.1checkpointing · 0.1CPU slicing · 0.1
YearPublicationVenuePosition
2015 Chronicle: Capture and Analysis of NFS Workloads at Line Rate
Ardalan Kangarlou, Sandip Shete, John D. Strunk
FAST1
2013 Protocol Responsibility Offloading to Improve TCP Throughput in Virtualized Environments
abstract
Virtualization is a key technology that powers cloud computing platforms such as Amazon EC2. Virtual machine (VM) consolidation, where multiple VMs share a physical host, has seen rapid adoption in practice, with increasingly large numbers of VMs per machine and per CPU core. Our investigations, however, suggest that the increasing degree of VM consolidation has serious negative effects on the VMs’ TCP performance. As multiple VMs share a given CPU, the scheduling latencies, which can be in the order of tens of milliseconds, substantially increase the typically submillisecond round-trip times (RTTs) for TCP connections in a datacenter, causing significant degradation in throughput. In this article, we propose a lightweight solution, called vPRO, that (a) offloads the VM’s TCP congestion control function to the driver domain to improve TCP transmit performance; and (b) offloads TCP acknowledgment functionality to the driver domain to improve the TCP receive performance. Our evaluation of a vPRO prototype on Xen suggests that vPRO substantially improves TCP receive and transmit throughputs with minimal per-packet CPU overhead. We further show that the higher TCP throughput leads to improvement in application-level performance, via experiments with Apache Olio, a Web 2.0 cloud application, and Intel MPI benchmark.
Sahan Gamage, Ramana Rao Kompella, Dongyan Xu, Ardalan Kangarlou
ACM Trans. Comput. Syst.4
2012 vSlicer: latency-aware virtual machine scheduling via differentiated-frequency CPU slicing
abstract
Recent advances in virtualization technologies have made it feasible to host multiple virtual machines (VMs) in the same physical host and even the same CPU core, with fair share of the physical resources among the VMs. However, as more VMs share the same core/CPU, the CPU access latency experienced by each VM increases substantially, which translates into longer I/O processing latency perceived by I/O-bound applications. To mitigate such impact while retaining the benefit of CPU sharing, we introduce a new class of VMs called latency-sensitive VMs (LSVMs), which achieve better performance for I/O-bound applications while maintaining the same resource share (and thus cost) as other CPU-sharing VMs. LSVMs are enabled by vSlicer, a hypervisor-level technique that schedules each LSVM more frequently but with a smaller micro time slice. vSlicer enables more timely processing of I/O events by LSVMs, without violating the CPU share fairness among all sharing VMs. Our evaluation of a vSlicer prototype in Xen shows that vSlicer substantially reduces network packet round-trip times and jitter and improves application-level performance. For example, vSlicer doubles both the connection rate and request processing throughput of an Apache web server; reduces a VoIP server's upstream jitter by 62%; and shortens the execution times of Intel MPI benchmark programs by half or more.
Cong Xu 0010, Sahan Gamage, Pawan N. Rao, Ardalan Kangarlou, Ramana Rao Kompella, Dongyan Xu
HPDC4
2012 VNsnap: Taking Snapshots of Virtual Networked Infrastructures in the Cloud
abstract
A virtual networked infrastructure (VNI) consists of virtual machines (VMs) connected by a virtual network. Created for individual users on a shared cloud infrastructure, VNIs reflect the concept of "Infrastructure as a Service” (IaaS) as part of the emerging cloud computing paradigm. The ability to take snapshots of an entire VNI-including images of the VMs with their execution, communication, and storage states-yields a unique approach to reliability as a VNI snapshot can be used to restore the operation of the entire virtual infrastructure. We present VNsnap, a system that takes distributed snapshots of VNIs. Unlike many existing distributed snapshot/checkpointing solutions, VNsnap does not require any modifications to the applications, libraries, or (guest) operating systems (OSs) running in the VMs. Furthermore, by performing much of the snapshot operation concurrently with the VNI's normal operation, VNsnap incurs only seconds of downtime. We have implemented VNsnap on top of Xen. Our experiments with real-world parallel and distributed applications demonstrate VNsnap's effectiveness and efficiency.
Ardalan Kangarlou, Patrick Eugster, Dongyan Xu
IEEE Trans. Serv. Comput.1
2011 Opportunistic flooding to improve TCP transmit performance in virtualized clouds
abstract
Virtualization is a key technology that powers cloud computing platforms such as Amazon EC2. Virtual machine (VM) consolidation, where multiple VMs share a physical host, has seen rapid adoption in practice with increasingly large number of VMs per machine and per CPU core. Our investigations, however, suggest that the increasing degree of VM consolidation has serious negative effects on the VMs' TCP transport performance. As multiple VMs share a given CPU, the scheduling latencies, which can be in the order of tens of milliseconds, substantially increase the typically sub-millisecond round-trip times (RTTs) for TCP connections in a datacenter, causing significant degradation in throughput. In this paper, we propose a light-weight solution called vFlood that (a) allows a TCP sender VM to opportunistically flood the driver domain in the same host, and (b) offloads the VM's TCP congestion control function to the driver domain in order to mask the effects of VM consolidation. Our evaluation of a vFlood prototype on Xen suggests that vFlood substantially improves TCP transmit throughput with minimal per-packet CPU overhead. Further, our application-level evaluation using Apache Olio, a web 2.0 cloud application, indicates a 33% improvement in the number of operations per second.
Sahan Gamage, Ardalan Kangarlou, Ramana Rao Kompella, Dongyan Xu
SoCC2
2010 vSnoop: Improving TCP Throughput in Virtualized Environments via Acknowledgement Offload
abstract
Virtual machine (VM) consolidation has become a common practice in clouds, Grids, and datacenters. While this practice leads to higher CPU utilization, we observe its negative impact on the TCP throughput of the consolidated VMs: As more VMs share the same core/CPU, the CPU scheduling latency for each VM increases significantly. Such increase leads to slower progress of TCP transmissions to the VMs. To address this problem, we propose an approach called vSnoop, where the driver domain of a host acknowledges TCP packets on behalf of the guest VMs - whenever it is safe to do so. Our evaluation of a Xen-based prototype indicates that vSnoop constantly achieves TCP throughput improvement for VMs (of orders of magnitude in some scenarios). We further show that the higher TCP throughput leads to improvement in application- level performance, via experiments with a two-tier online auction application and two suites of MPI benchmarks.
Ardalan Kangarlou, Sahan Gamage, Ramana Rao Kompella, Dongyan Xu
SC1
2009 VNsnap: Taking snapshots of virtual networked environments with minimal downtime
abstract
A virtual networked environment (VNE) consists of virtual machines (VMs) connected by a virtual network. It has been adopted to create ldquovirtual infrastructuresrdquo for individual users on a shared cloud computing infrastructure. The ability to take snapshots of an entire VNE - including images of the VMs with their execution, communication and storage states - yields a unique approach to reliability as a snapshot can restore the operation of an entire virtual infrastructure. We present VNsnap, a system that takes distributed snapshots of VNEs. Unlike existing distributed snapshot/checkpointing solutions, VNsnap does not require any modifications to the applications, libraries, or (guest) operating systems running in the VMs. Furthermore, VNsnap incurs only seconds of downtime as much of the snapshot operation takes place concurrently with the VNE's normal operation. We have implemented VNsnap on top of Xen. Our experiments with real-world parallel and distributed applications demonstrate VNsnap's effectiveness and efficiency.
Ardalan Kangarlou, Patrick Eugster, Dongyan Xu
DSN1