Latency-Sensitive Edge/Cloud Serverless Dynamic Deployment Over Telemetry-Based Packet-Optical Network

Pelle, István; Paolucci, F.; Sonkoly, Balázs; Cugini, F.

doi:10.1109/jsac.2021.3064655

“…Such flat K8s network, also called Pod network, does not account for network constraints in terms of limited bandwidth or bounded latency. For this reason, deploying K8s in edge computing environments over metro optical infrastructures to serve latency/QoS-critical applications (e.g., [2,3]) requires a specifically designed and comprehensive framework. In particular, specific workflows are needed to efficiently interface K8s with various components such as Software Defined Networking (SDN) controller, Service Level Agreement (SLA) broker, and Telemetry Collector.…”

Section: Overviewmentioning

confidence: 99%

“…The testbed encompasses: edge computing resources (three DELL nodes equipped with GPU acceleration), disaggregated metro optical network resources (ROADMs, 100G transponders, etc. [3]), and P4-based network switches (either physical and emulated switches). The demo will show dynamic K8s orchestration exploiting provisioning and adaptation of network resources efficiently coordinated by the proposed framework.…”

Section: Demo Implementationmentioning

confidence: 99%

Kubernetes Orchestration in SDN-based Edge Network Infrastructure

Giorgetti

¹

,

Scano

²

,

Chamanara

³

et al. 2022

Optical Fiber Communication Conference (OFC) 2022

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“…We employ the optical edge network as the substrate (or physical) network, where edge servers are connected via fiber links [14], [25]- [27]. The optical edge network (OEN) is denoted by OEN 𝕜, 𝑁, 𝐿 , where OEN is 𝕜-edge-connected, while 𝑁 and 𝐿 represent the set of nodes and bidirectional fiber links, respectively.…”

Section: A Optical Edge Network (Oen)mentioning

confidence: 99%

“…Based on [14], [25]- [27], OEN can be composed of a main ring and multiple sub-rings with dense connectivity, and we employ three network structures to perform our evaluations, (1) 2-D n-Torus network, (2) 4-degree n-ring network, and (3) 𝕜edge-connected random network (𝕜 4). According to [34], the size of a 2-D n-Torus network is 𝑛 .…”

Section: A Simulation Settingsmentioning

confidence: 99%

Service Function Chaining with Deterministic Fault Tolerance in Optical Edge Networks

Zheng¹,

Shen²,

Li³

et al. 2021

Preprint

0

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In the upcoming 5G-and-beyond era, ultra-reliable low-latency communication (URLLC) services will be ubiquitous in edge networks. To improve network performance and quality of service (QoS), URLLC services could be delivered via a sequence of software-based network functions, also known as service function chains (SFCs). Towards reliable SFC delivery, it is imperative to incorporate deterministic fault tolerance during SFC deployment. However, deploying an SFC with deterministic fault tolerance is challenging because the protection mechanism needs to consider protection against physical/virtual network failures and hardware/software failures jointly. Against multiple and diverse failures, this work investigates how to effectively deliver an SFC in optical edge networks with deterministic fault tolerance while minimizing wavelength resource consumption. We introduce a protection augmented graph, called k-connected service function slices layered graph (KC-SLG), protecting against k-1 fiber link failures and k-1 server failures. We formulate a novel problem called deterministic-fault-tolerant SFC embedding and propose an effective algorithm, called most candidate first SF slices layered graph embedding (MCF-SE). MCF-SE employs two proposed techniques: k-connected network slicing (KC-NS) and k-connected function slicing (KC-FS). Through thorough mathematical proof, we show that KC-NS is 2-approximate. For KC-FS, we demonstrate that k = 3 provides the best cost-efficiency. Our experimental results also show that the proposed MCF-SE achieves deterministic-fault-tolerant service delivery and performs better than the schemes directly extended from existing work regarding survivability and average cost-efficiency.

show abstract

“…Based on [14], [25]- [27], OEN can be composed of a main ring and multiple sub-rings with dense connectivity, and we employ three network structures to perform our evaluations, (1) 2-D n-Torus network, (2) 4-degree n-ring network, and (3) 𝕜edge-connected random network (𝕜 4). According to [34], the size of a 2-D n-Torus network is 𝑛 .…”

Section: A Simulation Settingsmentioning

confidence: 99%

Service Function Chaining with Deterministic Fault Tolerance in Optical Edge Networks

Zheng¹,

Shen²,

Li³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

In the upcoming 5G-and-beyond era, ultra-reliable low-latency communication (URLLC) services will be ubiquitous in edge networks. To improve network performance and quality of service (QoS), URLLC services could be delivered via a sequence of software-based network functions, also known as service function chains (SFCs). Towards reliable SFC delivery, it is imperative to incorporate deterministic fault tolerance during SFC deployment. However, deploying an SFC with deterministic fault tolerance is challenging because the protection mechanism needs to consider protection against physical/virtual network failures and hardware/software failures jointly. Against multiple and diverse failures, this work investigates how to effectively deliver an SFC in optical edge networks with deterministic fault tolerance while minimizing wavelength resource consumption. We introduce a protection augmented graph, called k-connected service function slices layered graph (KC-SLG), protecting against k-1 fiber link failures and k-1 server failures. We formulate a novel problem called deterministic-fault-tolerant SFC embedding and propose an effective algorithm, called most candidate first SF slices layered graph embedding (MCF-SE). MCF-SE employs two proposed techniques: k-connected network slicing (KC-NS) and k-connected function slicing (KC-FS). Through thorough mathematical proof, we show that KC-NS is 2-approximate. For KC-FS, we demonstrate that k = 3 provides the best cost-efficiency. Our experimental results also show that the proposed MCF-SE achieves deterministic-fault-tolerant service delivery and performs better than the schemes directly extended from existing work regarding survivability and average cost-efficiency.

show abstract

Latency-Sensitive Edge/Cloud Serverless Dynamic Deployment Over Telemetry-Based Packet-Optical Network

Cited by 33 publications

References 21 publications

Kubernetes Orchestration in SDN-based Edge Network Infrastructure

Kubernetes Orchestration in SDN-based Edge Network Infrastructure

Service Function Chaining with Deterministic Fault Tolerance in Optical Edge Networks

Service Function Chaining with Deterministic Fault Tolerance in Optical Edge Networks

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