A Load Balancing Algorithm for Equalising Latency Across Fog or Edge Computing Nodes

Abstract

When dealing with distributed applications in Edge or Fog computing environments, the service latency that the user experiences at a given node can be considered an indicator of how much the node itself is loaded with respect to the others. 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's perspective, and they cannot be used for a QoS-oriented load balancing. In this paper, we propose a load balancing algorithm that is focused on the service latency with the objective of levelling it across all the nodes in a fully decentralised 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 in real settings, we show both in simulation and in a real-world deployment, based on a cluster of Raspberry Pi boards, that our approach is able to level the service latency among a set of heterogeneous nodes organised in different topology.

VMMISD: An Efficient Load Balancing Model for Virtual Machine Migrations via Fused Metaheuristics With Iterative Security Measures and Deep Learning Optimizations

“…IDS models detect malicious activities by monitoring network traffic and system behaviours. While IDS models are effective in identifying known attacks, they may not perform well against new or sophisticated attacks, as they rely on predefined rules and signatures [27,28,29].…”

“…Proposed methods in improving performance and capacity utilization in cloud storage for content delivery and sharing services. [27] A load balancing algorithm to equalize latency across fog or edge computing nodes. It optimizes workload distribution to minimize latency discrepancies.…”

Lifespan and energy-oriented load balancing algorithms across sets of nodes in Green Edge Computing

“…The last algorithm that we present follows from Algorithm 2 and it has the same purpose of finding the migration ratios m ij (t) for a given node i, a similar approach has been applied in case of leveling of latency [22]. Even in this approach, we reason with rounds of duration τ seconds and at the end of the round each node updates its migration ratios.…”