FleaRouting

FleaRouting is a decentralized routing approach for dynamic networks inspired by the hopping or foraging behavior of fleas. It aims to efficiently route data in wireless ad hoc networks and IoT by combining random exploration with reinforcement of successful routes.

Nodes maintain local route estimates to destinations using a probabilistic forwarding strategy. Each outgoing link is assigned a weight that reflects recent success metrics such as delivery rate and latency. Forwarding decisions sample neighbors with probability proportional to weights, allowing fast adaptation to topology changes.

To discover new routes, FleaRouting periodically issues lightweight probe messages to neighboring nodes. If a probe yields improved performance, weights are increased; if failures occur, weights decrease. This reinforcement promotes high-quality paths while maintaining diversity to avoid congestion.

Advantages include a low requirement for global information, robustness to mobility, and scalability. Limitations include that convergence speed can be slower in sparse networks, overhead from probes, and potential for short-term instability if weights oscillate.

Used in wireless sensor networks, disaster response networks, and vehicular ad hoc networks.