Heterogeneous distributed real-time systems are continuously evolving to realize many emerging mission critical applications, e.g., battle field vision systems. In such systems, there often exists a tradeoff between quality of results and security of task execution while satisfying real-time constraints. In this paper we consider a set of dependent real-time tasks, modeled as Directed Acyclic Graph (DAG), with security and QoS requirements for assignment and scheduling on a set of heterogeneous sites with the objective of maximizing Total Quality Value (TQV) of the system. This problem is NP-hard since the basic problem of scheduling a DAG on multiple processors is NP-hard. We make the following contributions; (i) define new metric, TQV, which captures QoS aspects of the DAG and helps in choosing a task in the task graph, DAG, to increase its QoS level so as to raise system TQV to the best value, (ii) based on the defined metric, we propose a polynomial time heuristic algorithm to maximize TQV, and (iii) we evaluate the algorithm through simulation studies by comparing it to baseline algorithms for variations of synthetic workloads. The proposed algorithm outperforms the baseline algorithms in all the simulated conditions for fully-connected and shared bus network topologies.