The scheduling of tasks in distributed real-time systems has attracted many researchers in the recent past. The distributed real-time system considered here consists of uniprocessor or multiprocessor nodes connected through a multihop network. Scheduling in such a system involves scheduling of dynamically arriving tasks within a node (local scheduling) and migration of tasks across the network (global scheduling) if it is not possible to schedule them locally. Most of the existing schemes on distributed real-time task scheduling ignore the underlying message scheduling required for global scheduling of tasks. These schemes consider the load on the processors at a node as the basis to migrate tasks from a heavily loaded node (sender) to a lightly loaded node (receiver). We believe that the identification of a receiver node should be based not only on the load on its processors, but also on the availability of a lightly loaded path from the sender to that receiver. In this paper we present an integrated framework for distributed real-time dynamic task scheduling (i) by proposing algorithms for transfer location, and information policies which take into account the states of both the processors and the links, and (ii) by proposing interactions among these policies and schedulers so that the guarantee ratio (ratio of number of tasks guaranteed to the number of tasks arrived) is improved as compared to algorithms where only local scheduling is done. For local scheduling, we use a variation of myopic algorithm. The effectiveness of the proposed framework has been evaluated through simulation. © 1997 IEEE.