PrivHab: A privacy preserving georouting protocol based on a multiagent system for podcast distribution on disconnected areas

We present PrivHab, a privacy preserving georouting protocol that improves multiagent decision-making. PrivHab learns the mobility habits of the nodes of the network. Then, it uses this information to dynamically select to route an agent carrying a piece of data to reach its destination. PrivHab makes use of cryptographic techniques from secure multi-party computation to make the decisions while preserving nodes' privacy. PrivHab uses a waypoint-based routing that achieves a high performance and low overhead in rugged terrain areas that are plenty of physical obstacles. The store-carry-and-forward approach used is combined with mobile agents that provide intelligence, and it is designed to operate in areas that lack network infrastructure. We have evaluated PrivHab under the scope of a realistic podcast distribution application in remote rural areas, where these programs have to be recorded into a physical format and distributed to the local radio stations. The usage of PrivHab aims to reduce this spending of resources. The PrivHab protocol is compared with a set of well-known delay-tolerant routing algorithms and shown to outperform them.