Scalability Issues of Firefly-Based Self-Synchronization in Collective Adaptive Systems

Abstract

In this paper we investigate scalability issues of self-synchronization emergent properties, described with the pulse coupled oscillator model. As in the pulse coupled oscillator model the information propagation process is a gossip-like process, huge amounts of network traffic can be generated, causing thus scalability issues of the whole collective adaptive systems. These issues are even more emphasized in collective adaptive heterogeneous systems called Machine-to-Machine (M2M) systems. Namely, these systems consist not only from one large complex network, but also from a larger number of different interconnected complex networks. The easiest way to reduce network traffic in large networks is to use different overlay network topologies. An overlay network topology can be seen as a layer of a virtual network topology on top of a physical network, enabling significantly less messages to be exchanged during a synchronization process. However, the implementation process of overlay network topologies is not very efficient in real-world environments, as will be discussed in the paper. Therefore, we propose a mechanism for selective coupling implemented on the sender side that can be used to reduce both network traffic and time to synchronization without negatively affecting the entire synchronization process. Moreover, in some cases the rate of successful synchronization outcomes can be also increased when using the proposed mechanism.