Self-enforcing Game Theory-based Resource Allocation for LoRaWAN Assisted Public Safety Communications

Abstract

Public safety networks avail to disseminate information during emergency situations through its dedicated servers. Public safety networks accommodate public safety communication (PSC) applications to track the location of its utilizers and enable to sustain transmissions even in the crucial scenarios. Despite that, if the traditional setups responsible for PSCs are unavailable, it becomes prodigiously arduous to handle any of the safety applications, which may cause havoc in the society. Dependence on a secondary network may assist to solve such an issue. But, the secondary networks should be facilely deployable and must not cause exorbitant overheads in terms of cost and operation. For this, LoRaWAN can be considered as an ideal solution as it provides low power and long-range communication. However, an excessive utilization of the secondary network may result in high depletion of its own resources and can lead to a complete shutdown of services, which is a quandary at hand. As a solution, this paper proposes a novel network model via a combination of LoRaWAN and traditional public safety networks, and uses a self-enforcing agreement based game theory for allocating resources efficiently amongst the available servers. The proposed approach adopts memory and energy constraints as agreements, which are satisfied through Nash equilibrium. The numerical results show that the proposed approach is capable of efficiently allocating the resources with sufficiently high gains for resource conservation, network sustainability, resource restorations and probability to continue at the present conditions even in the complete absence of traditional Access Points (APs) compared with a baseline scenario with no failure of nodes.