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1. Multi-tenant network acceleration scheme for OpenStack

   https://doi.org/10.1109/UIC-ATC.2017.8397577  

   Phan, Linh Paul; Liu, Kaikai (August 2017, The IEEE Smart City Innovations 2017 (IEEE SCI 2017))

   Cloud visualization and multi-tenant networking provide Infrastructure as a Service (IaaS) provider a new and innovative way to offer the on-demand services to their customers, such as the easy provisioning of new applications and the better resource efficiency and scalability. However, existing data-intensive applications require more powerful processor and computing power, as well as a high bandwidth, low latency and consistent networking service. In order to boost the performance of computing and networking services, as well as reduce the overhead of the software virtualization, we propose a new data center network design based on OpenStack, which is a promising cloud operating system solution. Specifically, we map the OpenStack networking services to the hardware switch, and perform hardware-accelerated L2 switch and L3 routing to solve the software limitations, as well as achieve the software-like scalability and flexibility. We designed our prototype system via the Arista Software-Defined-Networking (SDN) switch, and evaluated the performance improvement in terms of the bandwidth and delay using various tools. Our experimental results demonstrate that our datacenter networking solution achieves higher bandwidth, lower latency, and lower CPU utilization of the host server. 

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2. HYPER: A Hybrid High-Performance Framework for Network Function Virtualization

   https://doi.org/10.1109/JSAC.2017.2760438  

   Sun, Chen; Bi, Jun; Zheng, Zhilong; Hu, Hongxin (October 2017, IEEE Journal on Selected Areas in Communications)

   Network function virtualization (NFV) offers the potential for both enhancing service delivery flexibility and reducing overall costs by virtualizing network functions that are traditionally implemented in dedicated hardware. However, the flexibility of NFV comes with considerable compromises since virtual machine carried functions could introduce significant performance overhead. In this paper, we present a novel high-performance framework called HYPER, which combines programmable hardware infrastructure and traditional software infrastructure in NFV to achieve both high performance and flexibility for supporting virtualized network functions (VNFs). In HYPER, we design a mediator layer to hide underlying infrastructure heterogeneity from the NFV orchestrator to simplify VNF management. In addition, we design a SLA-aware service chaining algorithm in HYPER to leverage the benefits of the hybrid infrastructure to fulfill both functional and performance requirements from service subscribers (or tenants). To optimize resource utilization efficiency, we also introduce a performance-aware VNF placement algorithm in HYPER, which accommodates both resource and performance requirements in placing VNFs. We implement HYPER in a testbed based on OpenStack and ONetCard. Experimental results show that HYPER reduces the forwarding latency of a service chain by 40% to 67% compared with data plane development kit -based implementation, while maintaining the flexibility of VNF management. 

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3. Towards an Adaptive Multi-Modal Traffic Analytics Framework at the Edge

   https://doi.org/10.1109/PERCOMW.2019.8730577  

   Pettet, Geoffrey; Sahoo, Saroj; Dubey, Abhishek (March 2019, 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops))

   The Internet of Things (IoT) requires distributed, large scale data collection via geographically distributed devices. While IoT devices typically send data to the cloud for processing, this is problematic for bandwidth constrained applications. Fog and edge computing (processing data near where it is gathered, and sending only results to the cloud) has become more popular, as it lowers network overhead and latency. Edge computing often uses devices with low computational capacity, therefore service frameworks and middleware are needed to efficiently compose services. While many frameworks use a top-down perspective, quality of service is an emergent property of the entire system and often requires a bottom up approach. We define services as multi-modal, allowing resource and performance tradeoffs. Different modes can be composed to meet an application's high level goal, which is modeled as a function. We examine a case study for counting vehicle traffic through intersections in Nashville. We apply object detection and tracking to video of the intersection, which must be performed at the edge due to privacy and bandwidth constraints. We explore the hardware and software architectures, and identify the various modes. This paper lays the foundation to formulate the online optimization problem presented by the system which makes tradeoffs between the quantity of services and their quality constrained by available resources. 

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4. Jetstream2: Accelerating cloud computing via Jetstream

   https://doi.org/10.1145/3437359.3465565  

   Hancock, David Y.; Fischer, Jeremy; Lowe, John Michael; Snapp-Childs, Winona; Pierce, Marlon; Marru, Suresh; Coulter, J. Eric; Vaughn, Matthew; Beck, Brian; Merchant, Nirav; et al (July 2021, Proceedings of the 2021 Practice & Experience in Advanced Research Computing (PEARC) Conference)

   null (Ed.)

   Jetstream2 will be a category I production cloud resource that is part of the National Science Foundation’s Innovative HPC Program. The project’s aim is to accelerate science and engineering by providing “on-demand” programmable infrastructure built around a core system at Indiana University and four regional sites. Jetstream2 is an evolution of the Jetstream platform, which functions primarily as an Infrastructure-as-a-Service cloud. The lessons learned in cloud architecture, distributed storage, and container orchestration have inspired changes in both hardware and software for Jetstream2. These lessons have wide implications as institutions converge HPC and cloud technology while building on prior work when deploying their own cloud environments. Jetstream2’s next-generation hardware, robust open-source software, and enhanced virtualization will provide a significant platform to further cloud adoption within the US research and education communities. 

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5. Enhancing P4-Based Network Emulation Fidelity Through a Lightweight Virtual Time System and Application Evaluation

   https://doi.org/10.1145/3725530  

   Chen, Gong; Hu, Zheng; Qu, Yanfeng; Jin, Dong (April 2025, ACM Transactions on Modeling and Computer Simulation)

   P4 serves as a programming language for configuring flexible and programmable network data planes, facilitating the development of custom protocols and programmable switches, and driving innovation in software-defined networking and network function virtualization. While the Linux container based network emulator, Mininet, coupled with the BMv2 software P4 switch, is widely used for rapid prototyping of P4-based applications, BMv2’s diminished performance raises fidelity concerns under high traffic and large network scenarios. In this paper, we introduce a lightweight virtual time system integrated into Mininet with BMv2 to enhance fidelity and scalability. By applying a time dilation factor (TDF) to interactions between containers and the physical machine, we optimize the emulated P4 network’s perceived speed from the application processes’ perspective. System evaluation demonstrates accurate emulation of significantly larger networks under high loads with minimal system overhead. We showcase our system’s utility through two network applications: an emulation of a TCP SYN flood attack and an ECMP load balancer. Evaluating against a production-grade software switch, Open vSwitch, and a physical testbed, we highlight the virtual time system’s improvement in temporal fidelity despite the observed performance degradation in BMv2 software switches. 

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