In view of the problems that the traditional many-to-one data fusion methods cannot effectively support the application scenarios with multi-source and multi-sink wireless sensor networks（WSNs）

and these methods are difficult to adapt to the dynamics and scalability of network

a distributed many-to-many data fusion method based on probabilistic routing is proposed. Without the requirement of global knowledge

multiple sink nodes can efficiently collect the sensing data from multiple source nodes at the same time. The new method exploits the chaotic ant colony optimization to guide the direction of data transmission

also combines data fusion and multicast technology to reduce the communication load. When the network environment remains stable

the routing structure gradually converges to an approximate optimal data fusion structure

but if any change happens on network environment

the routing structure can quickly adjust. Experimental simulation results show that the new method is feasible and efficient when comparing with the existing methods.