Task allocation is an essential part of many applications of WSANs. The key problem of task allocation in these systems such as intelligent minefield is how to obtain the node-target assignment. Mathematical model with task effectiveness as the evaluation index was built on the analysis of multi-node cooperative decision problem. Combing with the target's parameters and node's own status, the influence factors of task effectiveness were analyzed and the task effectiveness function was proposed. Then the value of this function can be utilized as the evaluation index of assignment schemes since it reflected the integrated impact of system by target's threat and node's status more comprehensively. The essence of multi-node cooperative task allocation was how to make node-target assignment to achieve the maximum task effectiveness of the whole system. Because every node can attack only one target, multi-node cooperative attack decision problem turned into assignment problem. An application of Multi-Scale Quantum Harmonic Oscillator Algorithm was implemented to solve the assignment problem for multiple nodes with multiple targets. The results show that the algorithm is suitable for multifactor task allocation problem in WSANs.