Improved QoS at the Edge Using Serverless Computing to Deploy Virtual Network Functions

Chaudhry, Saqib Rasool; Palade, Andrei; Kazmi, Aqeel; Clarke, Siobhán

doi:10.1109/jiot.2020.3011057

Cited by 36 publications

(8 citation statements)

References 36 publications

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“…Applications can be built up using a set of dependent or independent functions invoked by a single service call or an event. The idea of using functions as service instances emerges from serverless computing [139], [145]- [147], also known as function-as-a-service (FaaS) [53]. The objective is to provide a cloud computing model for stateless and event-driven applications, where application functions will be executed when necessary without consistent execution of the entire application [148], [149].…”

Section: E: Functionmentioning

confidence: 99%

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

et al. 2022

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The advent of new cloud-based applications such as mixed reality, online gaming, autonomous driving, and healthcare has introduced infrastructure management challenges to the underlying service network. Multi-access edge computing (MEC) extends the cloud computing paradigm and leverages servers near end-users at the network edge to provide a cloud-like environment. The optimum placement of services on edge servers plays a crucial role in the performance of such service-based applications. Dynamic service placement problem addresses the adaptive configuration of application services at edge servers to facilitate end-users and those devices that need to offload computation tasks. While reported approaches in the literature shed light on this problem from a particular perspective, a panoramic study of this problem reveals the research gaps in the big picture. This paper introduces the dynamic service placement problem and outline its relations with other problems such as task scheduling, resource management, and caching at the edge. We also present a systematic literature review of existing dynamic service placement methods for MEC environments from networking, middleware, applications, and evaluation perspectives. In the first step, we review different MEC architectures and their enabling technologies from a networking point of view. We also introduce different cache deployment solutions in network architectures and discuss their design considerations. The second step investigates dynamic service placement methods from a middleware viewpoint. We review different service packaging technologies and discuss their trade-offs. We also survey the methods and identify eight research directions that researchers follow. Our study categorises the research objectives into six main classes, proposing a taxonomy of design objectives for the dynamic service placement problem. We also investigate the reported methods and devise a solutions taxonomy comprising six criteria. In the third step, we concentrate on the application layer and introduce the applications that can take advantage of dynamic service placement. The fourth step investigates evaluation environments used to validate the solutions, including simulators and testbeds. We introduce real-world datasets such as edge server locations, mobility traces, and service requests used to evaluate the methods. We compile a list of open issues and challenges categorised by various viewpoints in the last step.

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Section: E: Functionmentioning

confidence: 99%

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

et al. 2022

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“…Edge computing, sometimes called fog computing [22,[28][29][30] can be defined as the data computation that is deployed and fulfilled on edge nodes rather than on the cloud. The main types of edge computing tasks have been machine learning and deep learning [31], augmented reality with object recognition [32,33] and network virtualization [34,35]. Some computations such as deep learning and augmented reality are computationally expensive i.e.…”

Section: A Edge Nodes and Edge Computingmentioning

confidence: 99%

“…The virtualization of network functions has been enhanced with the use of containers. The authors in [35] present an approach to launch virtual network functions on demand on edge nodes. Container-based network functions can be used to quickly re-establish lost network service by uploading the network functions as containerized applications.…”

Section: Container Applications In Edge Computingmentioning

confidence: 99%

Container Placement and Migration in Edge Computing: Concept and Scheduling Models

Oleghe

2021

IEEE Access

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Containers are a form of software virtualization, rapidly becoming the de facto way of providing edge computing services. Research on container-based edge computing is plentiful, and this has been buoyed by the increasing demand for single digit, milliseconds latency computations. A container scheduler is part of the architecture that is used to manage and orchestrate multiple container-based applications on heterogenous computing nodes. The scheduler decides how incoming computing requests are allocated to containers, which edge nodes the containers are placed on, and where already deployed containers are migrated to. This paper aims to clarify the concept of container placement and migration in edge servers and the scheduling models that have been developed for this purpose. The study illuminates the frameworks and algorithms upon which the scheduling models are built. To convert the problem to one that can be solved using an algorithm, the container placement problem in mostly abstracted using multi-objective optimization models or graph network models. The scheduling algorithms are predominantly heuristic-based algorithms, which are able to arrive at sub-optimal solutions very quickly. There is paucity of container scheduling models that consider distributed edge computing tasks. Research in decentralized scheduling systems is gaining momentum and the future outlook is in scheduling containers for mobile edge nodes.

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“…Aditya et al [41] present a set of general requirements that a cloud computing service must satisfy to effectively host SDN-and NFV-based services. Chaudhry et al [58] present an approach to improve QoS on the edge by employing virtual network functions using serverless computing.…”

Section: Interesting Use Casesmentioning

confidence: 99%

SoK: Function-As-A-Service: From An Application Developer’s Perspective

Raza¹,

Matta²,

Akhtar³

et al. 2021

Journal of Systems Research

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Serverless computing is a fast-moving, highly active research area. As a growing number of practitioners start using serverless and new researchers explore advancing this domain, well-written systemization of knowledge (SoK) articles like this paper are priceless to the community. The authors of this paper have done a great job providing clear categorization and insightful descriptions of various aspects of serverless systems as perceived by developers. At parts, the way the authors connected different dots provides new insights even to the experts in the field. I am glad to see the publication of such a valuable contribution as the inaugurating article in the Serverless Area of Journal of Systems Research.

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Improved QoS at the Edge Using Serverless Computing to Deploy Virtual Network Functions

Cited by 36 publications

References 36 publications

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

Dynamic Service Placement in Multi-Access Edge Computing: A Systematic Literature Review

Container Placement and Migration in Edge Computing: Concept and Scheduling Models

SoK: Function-As-A-Service: From An Application Developer’s Perspective

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