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