• Corpus ID: 231740752

EdgeWorkflowReal: An Edge Computing based Workflow Execution Engine for Smart Systems

  title={EdgeWorkflowReal: An Edge Computing based Workflow Execution Engine for Smart Systems},
  author={Xuejun Li and R. Ding and Xiao Liu and Jia Xu and Yun Yang and John C. Grundy},
Current cloud-based smart systems suffer from weaknesses such as high response latency, limited network bandwidth and the restricted computing power of smart end devices which seriously affect the system’s QoS (Quality of Service). Recently, given its advantages of low latency, high bandwidth and location awareness, edge computing has become a promising solution for smart systems. However, the development of edge computing based smart systems is a very challenging job for software developers… 

Figures and Tables from this paper


FogWorkflowSim: An Automated Simulation Toolkit for Workflow Performance Evaluation in Fog Computing
  • Xinyu Liu, Lingmin Fan, +4 authors Yun Yang
  • Computer Science
    2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)
  • 2019
FogWorkflowSim is an efficient and extensible toolkit for automatically evaluating resource and task management strategies in Fog Computing with simulated user-defined workflow applications and can serve as an effective experimental platform for researchers in Fog based workflow systems as well as practitioners interested in adopting Fog Computing and workflow systems for their new software projects.
iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments
A simulator, called iFogSim, is proposed to model IoT and Fog environments and measure the impact of resource management techniques in latency, network congestion, energy consumption, and cost.
Serverless execution of scientific workflows: Experiments with HyperFlow, AWS Lambda and Google Cloud Functions
A prototype workflow executor functions using AWS Lambda and Google Cloud Functions, coupled with the HyperFlow workflow engine are developed, which can run workflow tasks in AWS and Google infrastructures, and feature such capabilities as data staging to/from S3 or Google Cloud Storage and execution of custom application binaries.
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.
Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources
This paper proposes an approach that allows users to build and run scientific workflows on top of a federation of multiple clouds and traditional resources, and achieves this by integrating the Kepler scientific workflow platform with the CometCloud framework.
Intelligent Offloading for Collaborative Smart City Services in Edge Computing
An intelligent offloading method (IOM) for smart city, realizing privacy preservation, improving offloading efficiency, and promoting edge utility, is proposed, and the information entropy mechanism is employed to be integrated with edge computing to obtain the balance between privacy preservation and collaborative service performance.
SAND: Towards High-Performance Serverless Computing
SAND is presented, a new serverless computing system that provides lower latency, better resource efficiency and more elasticity than existing serverless platforms, and introduces two key techniques: 1) application-level sandboxing, and 2) a hierarchical message bus.
Multi-Agent Imitation Learning for Pervasive Edge Computing: A Decentralized Computation Offloading Algorithm
This work proposes a decentrailized computation offloading algorithm with the purpose of minimizing average task completion time in the pervasive edge computing networks and shows that the solution has a significant advantage compared with other representative algorithms.
Mobilityaware workflow offloading and scheduling strategy for mobile edge computing
  • Proceedings of the International Conference on Algorithms and Architectures for Parallel Processing. Springer, pp. 184-199, 2019.
  • 2019