Flocking Virtual Machines in Quest for Responsive IoT Cloud Services

TL;DR

Flock is a scalable protocol enabling live VM migration across edge and cloud platforms, improving IoT service responsiveness through autonomous, flocking-inspired decisions validated by game theory and simulations.

Contribution

This work introduces Flock, a novel protocol for autonomous VM migration using flocking principles, with theoretical bounds and simulation validation.

Findings

Flock achieves convergence to Nash Equilibrium in VM placement.

The protocol improves responsiveness and load balancing in IoT cloud services.

Flock's objectives can be tailored for energy efficiency and load balancing.

Abstract

We propose Flock; a simple and scalable protocol that enables live migration of Virtual Machines (VMs) across heterogeneous edge and conventional cloud platforms to improve the responsiveness of cloud services. Flock is designed with properties that are suitable for the use cases of the Internet of Things (IoT). We describe the properties of regularized latency measurements that Flock can use for asynchronous and autonomous migration decisions. Such decisions allow communicating VMs to follow a flocking-like behavior that consists of three simple rules: separation, alignment, and cohesion. Using game theory, we derive analytical bounds on Flock's Price of Anarchy (PoA), and prove that flocking VMs converge to a Nash Equilibrium while settling in the best possible cloud platforms. We verify the effectiveness of Flock through simulations and discuss how its generic objective can simply be tweaked to achieve other objectives, such as cloud load balancing and energy consumption minimization.