We propose an adaptive framework for computing multiple paths in temporal and spatial domains to transmit a large volume of data packets from a source s to a destination d in ad hoc wireless networks. The objective is to achieve quality of service (QoS) by minimizing end-to-end delay for packet delivery. We consider two aspects in this framework. The first aspect is to perform preemptive route rediscoveries before the occurrence of route errors while transmitting a large volume of data from s to d. This helps us to find out dynamically a series of possible paths in temporal domain to complete the data transfer. The second aspect is to select multiple paths in spatial domain for data transfer at any instant of time, and to distribute the data packets in sequential blocks over those paths in order to reduce congestion and end-to-end delay. A notion of link stability and path stability is also defined, and a unified mechanism is proposed to address the above two aspects that relies on evaluating a path based on link and path stability. Our solution method uses Lagrangean relaxation and subgradient heuristics to solve an optimization formulation of the problem in order to compute the paths and the corresponding data distribution, both in temporal and spatial domains. Simulation experiments demonstrate that the proposed framework helps in significantly reducing the end-to-end delay and the required number of route-rediscoveries.