In this paper, we address the problem of best-effort scheduling of (m,k)-ยฎrm real-time streams in multihop networks. The existing solutions for the problem ignore scalability considerations because the solutions maintain a separate queue for each stream and maintain per-stream state information. In this context, we propose a scheduling algorithm, Enhanced Distance Based Priority (EDBP), which is scalable (ยฎxed scheduling cost) while offering performance close to that of the existing solutions. The proposed EDBP algorithm achieves this by allowing multiplexing of streams into a ยฎxed number of queues and by using the notion of a look-ahead window. In the EDBP algorithm, at any point of time, the best packet for transmission is selected based on the state of the stream combined with the laxity of the packet. We have conducted extensive simulation studies to evaluate the effectiveness of the proposed EDBP algorithm by comparing it with existing algorithms for the problem. The simulation studies reveal that the dynamic failure performance of the EDBP algorithm is very close to that of the existing algorithms with a signiยฎcant reduction in scheduling cost.