Scalable load balancing and flow management in dynamic heterogeneous wireless networks​


The number of connected devices has reached 18 billion in 2017 and this will nearly double by 2022, while also new wireless communication technologies become available. Since these modern devices support the use of multiple communication technologies, efforts have been made to enable simultaneous usage and handovers between the different technologies for these devices. However, existing solutions are missing the intelligence to decide on fine-grained (e.g. flow or packet level) optimizations that can drastically enhance the network’s performance (e.g., throughput) and user experience. To this extent, we present a multi-technology flow-management load balancing approach for heterogeneous wireless networks that dynamically re-routes traffic through heterogeneous networks, in order to maximize the global throughput. This dynamic approach can be deployed on top of existing solutions and takes into account the specific characteristics of the different technologies, as well as station mobility. We both present a mathematical problem formulation and a heuristic that ensures practical scalability. We demonstrate the heuristic’s ability to increase the network-wide throughput by more than 100% across a variety of scenarios and scalability up to 10,000 devices.

Journal of Network and Systems Management