Alfredo A Rodriguez, Sander Aarts, Ali Amadeh, Jacob Dentes, Alex Coy, Kenneth Schlather, David Shmoys, K Max Zhang

LoRaWAN is a popular Long-Range Low-Power wireless communications protocol that is enabling many IoT applications worldwide, with more networks growing both in size and number around the world. To effectively plan and operate these networks, it is necessary to have tools that reliably quantify, measure, and predict the connection quality provided by LoRaWAN receivers. This paper proposes a novel data-driven approach to connection quality modeling that is tailored for LoRaWAN.

Sander Aarts, Jacob Dentes, Manxi Wu, David B Shmoys

We consider the problem of fairly allocating the cost of providing a service among a set of users, where the service cost is formulated by an NP-hard covering integer program (CIP). The central issue is to determine a cost allocation to each user that, in total, recovers as much as possible of the actual cost while satisfying a stabilizing condition known as the core property. Motivated by an application of cost allocation for network design for LPWANs, an emerging IoT technology, we investigate a general class of CIPs and give the first non-trivial price-of-fair-sharing bounds by using the natural LP relaxation strengthened with knapsack-cover inequalities