Abstract

When deploying a distributed application in the Fog or Edge computing environments, the average service latency among all the involved nodes can be an indicator of how much a node is loaded with respect to the other. Indeed, only considering the average CPU time, or the RAM utilisation, for example, does not give a clear depiction of the load situation because these parameters are application- and hardware-agnostic. They do not give any information about how the application is performing from the user perspective and they cannot be used for a QoS-oriented load balancing of the system. Moreover, due to the displacement of the nodes and the heterogeneity of the computing devices the necessity of a load balancing algorithm is clear. In this paper, we propose a load balancing approach that is focused on the service latency with the objective to level it across all the nodes in a fully decentralized manner, in this way no user will experience a worse QoS than the other. By providing a differential model of the system and an adaptive heuristic to find the solution to the problem, we show both in simulation and in a real-world deployment that our approach is able to level the service latency among a set of heterogeneous nodes organized in different topologies.

Citation

Proietti Mattia, G., Magnani, M., & Beraldi, R. (2022, October). A latency-levelling load balancing algorithm for Fog and Edge Computing. 25th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM’22).

@inproceedings{2022ProiettiALatency,
  author = {{Proietti Mattia}, Gabriele and Magnani, Marco and Beraldi, Roberto},
  title = {A latency-levelling load balancing algorithm for Fog and Edge Computing},
  year = {2022},
  month = oct,
  booktitle = {25th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM'22)},
  address = {Montreal, Canada},
  days = {24},
  keywords = {Edge Computing; Fog Computing; Load Balancing; Service Latency}
}