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LaSS: Running Latency Sensitive Serverless Computations at the Edge

Authors:

Ahmed Ali-Eldin,

Prashant ShenoyAuthors Info & Claims

HPDC '21: Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing

Pages 239 - 251

https://doi.org/10.1145/3431379.3460646

Published: 21 June 2021 Publication History

Abstract

Serverless computing has emerged as a new paradigm for running short-lived computations in the cloud. Due to its ability to handle IoT workloads, there has been considerable interest in running serverless functions at the edge. However, the constrained nature of the edge and the latency sensitive nature of workloads result in many challenges for serverless platforms. In this paper, we present LaSS, a platform that uses model-driven approaches for running latency-sensitive serverless computations on edge resources. LaSS uses principled queuing-based methods to determine an appropriate allocation for each hosted function and auto-scales the allocated resources in response to workload dynamics. LaSS uses a fair-share allocation approach to guarantee a minimum of allocated resources to each function in the presence of overload. In addition, it utilizes resource reclamation methods based on container deflation and termination to reassign resources from over-provisioned functions to under-provisioned ones. We implement a prototype of our approach on an OpenWhisk serverless edge cluster and conduct a detailed experimental evaluation. Our results show that LaSS can accurately predict the resources needed for serverless functions in the presence of highly dynamic workloads, and reprovision container capacity within hundreds of milliseconds while maintaining fair share allocation guarantees.

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Cited By

Shahid UAhmed GSiddiqui SShuja JBalogun A(2024)Latency-Sensitive Function Placement among Heterogeneous Nodes in Serverless ComputingSensors10.3390/s2413419524:13(4195)Online publication date: 27-Jun-2024
https://doi.org/10.3390/s24134195
Giagkos DTzenetopoulos AMasouros DXydis SCatthoor FSoudris D(2024)AI-Driven QoS-Aware Scheduling for Serverless Video Analytics at the EdgeInformation10.3390/info1508048015:8(480)Online publication date: 13-Aug-2024
https://doi.org/10.3390/info15080480
Sharma PFuerst A(2024)Accountable Carbon Footprints and Energy Profiling For Serverless FunctionsProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698531(522-541)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3698038.3698531
Show More Cited By

Index Terms

LaSS: Running Latency Sensitive Serverless Computations at the Edge
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
      1. Scheduling algorithms

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cover image ACM Conferences

HPDC '21: Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing

June 2021

275 pages

ISBN:9781450382175

DOI:10.1145/3431379

General Chairs:
Erwin Laure
Max Planck Computing and Data Facility, Germany
,
Stefano Markidis
KTH Royal Institute of Technology, Sweden
,
Program Chairs:
Ana Lucia Verbanescu
University of Amsterdam UVA, Netherlands
,
Gerald Fredrick (Jay) Lofstead
Sandia National Laboratories, USA

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New York, NY, United States

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Published: 21 June 2021

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HPDC '21: The 30th International Symposium on High-Performance Parallel and Distributed Computing

June 21 - 25, 2021

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Cited By

Shahid UAhmed GSiddiqui SShuja JBalogun A(2024)Latency-Sensitive Function Placement among Heterogeneous Nodes in Serverless ComputingSensors10.3390/s2413419524:13(4195)Online publication date: 27-Jun-2024
https://doi.org/10.3390/s24134195
Giagkos DTzenetopoulos AMasouros DXydis SCatthoor FSoudris D(2024)AI-Driven QoS-Aware Scheduling for Serverless Video Analytics at the EdgeInformation10.3390/info1508048015:8(480)Online publication date: 13-Aug-2024
https://doi.org/10.3390/info15080480
Sharma PFuerst A(2024)Accountable Carbon Footprints and Energy Profiling For Serverless FunctionsProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698531(522-541)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3698038.3698531
Baresi LHu DQuattrocchi GTerracciano L(2024)NEPTUNE: A Comprehensive Framework for Managing Serverless Functions at the EdgeACM Transactions on Autonomous and Adaptive Systems10.1145/363475019:1(1-32)Online publication date: 14-Feb-2024
https://dl.acm.org/doi/10.1145/3634750
Liu TGuo JHuang B(2024)Efficient Cross-platform Multiplexing of Hardware Performance Counters via Adaptive GroupingACM Transactions on Architecture and Code Optimization10.1145/362952521:1(1-26)Online publication date: 19-Jan-2024
https://dl.acm.org/doi/10.1145/3629525
Aslanpour MToosi ACheema MChhetri M(2024)Faashouse: Sustainable Serverless Edge Computing Through Energy-Aware Resource SchedulingIEEE Transactions on Services Computing10.1109/TSC.2024.335429617:4(1533-1547)Online publication date: Jul-2024
https://doi.org/10.1109/TSC.2024.3354296
Verma ASatpathy ADas SAddya S(2024)LEASE: Leveraging Energy-Awareness in Serverless Edge for Latency-Sensitive IoT Services2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops59983.2024.10502788(302-307)Online publication date: 11-Mar-2024
https://doi.org/10.1109/PerComWorkshops59983.2024.10502788
Wang BIrwin DShenoy PTowsley D(2024)INVAR: Inversion Aware Resource Provisioning and Workload Scheduling for Edge ComputingIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621417(1511-1520)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621417
Li GTan HZhang XZhang CZhou RHan ZChen G(2024)Online Container Caching with Late-Warm for IoT Data Processing2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00127(1547-1560)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00127
Lou JTang ZLu XYuan SLi JJia WWu C(2024)Efficient Serverless Function Scheduling in Edge ComputingICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10622991(1029-1034)Online publication date: 9-Jun-2024
https://doi.org/10.1109/ICC51166.2024.10622991
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