Online job dispatching and scheduling in edge-clouds

By Haisheng Tan, Zhenhua Han, Xiangyang Li, Francis Chi-Moon Lau. 2017

250 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Shiqiang Wang
2. Sameh Sorour
3. Umair Mohammad
4. Kin Kwong Leung
5. Frederic Desprez
6. Christian Makaya
7. Farah Ait Salaht
8. Theodoros Salonidis

In Information Systems

1. Frederic Desprez
2. Farah Ait Salaht
3. Kevin Sean Chan
4. Adrien Lebre

Citations in the corpus

• Adaptive Federated Learning in Resource Constrained Edge Computing Systems (2018, background): “Existing work on MEC focuses on generic applications, where solutions have been proposed for application offloading [11], [12], workload scheduling [13], [14], and service migration triggered by user mobility [15], [16].”
• All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, background): “[303], where they formulate the problem of online job scheduling and dispatching in edge clouds.”
• An Overview of Service Placement Problem in Fog and Edge Computing (2020, methodology): “C/On/S/nM Approximation [139] Minimizes the total response time over all the deployed tasks .”
• When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning (2018, background): “R ELATED W ORK Existing work on MEC focuses on generic applications, where solutions have been proposed for application offload-ing [7], [8], workload scheduling [9], [10], and service migration triggered by user mobility [11], [12].”