Le Taureau: Deconstructing the Serverless Landscape &amp; A Look Forward

Khandelwal, Anurag; Kejariwal, Arun; Ramasamy, Karthikeyan

doi:10.1145/3318464.3383130

Cited by 13 publications

(8 citation statements)

References 27 publications

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“…led to the widespread adoption of the Function as a Service (FaaS) programming model, where the application does not run as a whole process, but rather it is split into shortlived stateless tasks that can be executed by different workers without a tight coordination [17]. It is expected that serverless computing will become widespread in the future [20]. The seamless adoption of a FaaS paradigm in an edge system would allow to re-use applications, on both the provider's and the user's side, which were designed originally for serverless computing and are growing significantly in number and importance [26].…”

Section: Introductionmentioning

confidence: 99%

A Decentralized Framework for Serverless Edge Computing in the Internet of Things

Cicconetti

Conti

Passarella

2021

IEEE Trans. Netw. Serv. Manage.

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Serverless computing is becoming widely adopted among cloud providers, thus making increasingly popular the Function-as-a-Service (FaaS) programming model, where the developers realize services by packaging sequences of stateless function calls. The current technologies are very well suited to data centers, but cannot provide equally good performance in decentralized environments, such as edge computing systems, which are expected to be typical for Internet of Things (IoT) applications. In this paper, we fill this gap by proposing a framework for efficient dispatching of stateless tasks to in-network executors so as to minimize the response times while exhibiting short-and long-term fairness, also leveraging information from a virtualized network infrastructure when available. Our solution is shown to be simple enough to be installed on devices with limited computational capabilities, such as IoT gateways, especially when using a hierarchical forwarding extension. We evaluate the proposed platform by means of extensive emulation experiments with a prototype implementation in realistic conditions. The results show that it is able to smoothly adapt to the mobility of clients and to the variations of their service request patterns, while coping promptly with network congestion.

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Section: Introductionmentioning

confidence: 99%

A Decentralized Framework for Serverless Edge Computing in the Internet of Things

Cicconetti

Conti

Passarella

2021

IEEE Trans. Netw. Serv. Manage.

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“…In addition, quantum-based processing elements have rapidly emerged in recent times and cloud service providers have started to ofer such quantum processing capabilities as part of their cloud services as well [110]. However, none of the serverless platforms from these providers ofer access to hardware accelerators at the moment [71]. As a result, research focus has been increasingly directed towards expanding the FaaS service oferings by adding access to hardware accelerators.…”

Section: Runtime Resource Limitationsmentioning

confidence: 99%

A Holistic View on Resource Management in Serverless Computing Environments: Taxonomy and Future Directions

2022

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Serverless computing has emerged as an attractive deployment option for cloud applications in recent times. The unique features of this computing model include rapid auto-scaling, strong isolation, fine-grained billing options and access to a massive service ecosystem which autonomously handles resource management decisions. This model is increasingly being explored for deployments in geographically distributed edge and fog computing networks as well, due to these characteristics. Effective management of computing resources has always gained a lot of attention among researchers. The need to automate the entire process of resource provisioning, allocation, scheduling, monitoring and scaling, has resulted in the need for specialized focus on resource management under the serverless model. In this article, we identify the major aspects covering the broader concept of resource management in serverless environments and propose a taxonomy of elements which influence these aspects, encompassing characteristics of system design, workload attributes and stakeholder expectations. We take a holistic view on serverless environments deployed across edge, fog and cloud computing networks. We also analyse existing works discussing aspects of serverless resource management using this taxonomy. This article further identifies gaps in literature and highlights future research directions for improving capabilities of this computing model.

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“…Supporting stateful applications is one of the key research challenges identified in the position paper [4] for serverless computing in the cloud. A datastore for edge computing with consistent replicas has been also proposed in [23], which reconciles only the data that are relevant to a given session for performance reasons.…”

Section: Related Workmentioning

confidence: 99%

“…For the purpose of evaluating the performance of protocols and algorithms in controlled and repeatable conditions, we have also implemented so-called ecomputers, which emulate serverless platforms with a given configuration, in terms of computation speed, memory, number of containers, etc. ServerlessOnEdge uses Google's gRPC 4 for communication among clients, e-routers, and e-computers. The interested reader can find further details on ServerlessOnEdge in [21].…”

Section: A Implementationmentioning

confidence: 99%

“…FaaS is very well suited to many Internet of Things (IoT) applications of practical interest for what concerns the programming model (functional event-based), an efficient utilization of resources (both at device-and edge node-level) and the promises of high scalability. The latter stems from symbiosis with a serverless computing framework, where functions are invoked in containers that are orchestrated in a highly flexible virtualization infrastructure [4]. Results have demonstrated that serverless is more suitable than a microservice architecture for unpredictable requests accompanied by a large size of the response, due to the scaling agility [5].…”

Section: Introductionmentioning

confidence: 99%

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FaaS Execution Models for Edge Applications

Cicconetti¹,

Conti²,

Passarella³

2021

Preprint

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In this paper, we address the problem of supporting stateful workflows following a Function-as-a-Service (FaaS) model in edge networks. In particular we focus on the problem of data transfer, which can be a performance bottleneck due to the limited speed of communication links in some edge scenarios and we propose three different schemes: a pure FaaS implementation, StateProp, i.e., propagation of the application state throughout the entire chain of functions, and StateLocal, i.e., a solution where the state is kept local to the workers that run functions and retrieved only as needed. We then extend the proposed schemes to the more general case of applications modeled as Directed Acyclic Graphs (DAGs), which cover a broad range of practical applications, e.g., in the Internet of Things (IoT) area. Our contribution is validated via a prototype implementation. Experiments in emulated conditions show that applying the data locality principle reduces significantly the volume of network traffic required and improves the end-to-end delay performance, especially with local caching on edge nodes and low link speeds.

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Le Taureau: Deconstructing the Serverless Landscape & A Look Forward

Cited by 13 publications

References 27 publications

A Decentralized Framework for Serverless Edge Computing in the Internet of Things

A Decentralized Framework for Serverless Edge Computing in the Internet of Things

A Holistic View on Resource Management in Serverless Computing Environments: Taxonomy and Future Directions

FaaS Execution Models for Edge Applications

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