A Neighbor-Based Probabilistic Broadcast Protocol for Data Dissemination in Mobile IoT Networks

The recent trend of implementing Internet of Things (IoT) applications is to transmit sensing data to a powerful data center, and try to discover the valuable knowledge behind ``Big Data'' by various intelligent but resource-consuming algorithms. However, from the discussion with some industrial companies, it is understood that disseminating real-time sensing data to their nearby network-edge-applications directly would produce a more economical design and lower service latency for some important smart city applications. Therefore, this paper proposes an efficient broadcast protocol to disseminate data in mobile IoT networks. The proposed protocol exploits the neighbor knowledge of mobile nodes to determine a rebroadcast delay that prioritizes different packet broadcasts according to their profits. An adaptive connectivity factor is also introduced to make the proposed protocol adaptive to the node density of different network parts. By combining the neighbor knowledge of nodes and adaptive connectivity factor, a reasonable probability is calculated to determine whether a packet should be rebroadcasted to other nodes, or be discarded to prevent redundant packet broadcast. Extensive simulation results have validated that this protocol can improve the success ratio of packet delivery by 13% ~ 28% with a similar end-to-end transmission delay and network overhead of the most state-of-art approaches.