To solve the problem of group task allocation with time constraints in open and dynamic network environments, this paper proposes a decentralized combinatorial auction-based approach for group task allocation. In the proposed approach, both resource providers and consumers are modeled as intelligent agents. The proposed approach is decentralized, so all the agents are limited to communicating with their neighboring agents. The proposed approach also allows agents to enter and leave the network environments freely, and is robust for the dynamism and openness of the network environments. Tasks in the proposed approach have deadlines, and may need the collaboration of a group of self-interested providers. The experimental results demonstrate that the proposed approach outperforms two well-known task allocation approaches in terms of success rate of task allocation, the individual utility of the agents, the speed of task allocation and scalability.