| Streaming multimedia applications such as live webcasts and interactive distance learning require real-time constraints for data capture and transmission in keeping with end-user QoS requirements. Meanwhile, they can also tolerate some packets being discarded or serviced late, as long as the consecutive number of such losses is limited. Likewise, other soft real-time applications, such as data generation applications in sensor networks and in embedded systems, also have similar delay and loss constraints.; To deal with the above classes of applications, this thesis presents window-constrained resource management models and polices to guarantee a Faction of their required service in every finite time window. For the single server case, the Virtual Deadline Scheduling (VDS) algorithm and its variant are introduced for both the original and the relaxed window-constrained model. Compared to the previous work on Dynamic Window-Constrained Scheduling (DWCS), VDS can provide better window-constrained service guarantees to jobs in certain circumstances, especially to those with potentially different request periods. VDS maximizes resource utilization while limiting the extent of delay and loss. The performance is evaluated by extensive simulations, and also by experiments in the Linux kernel, where window-constrained CPU scheduling algorithms such as DWCS and VDS are implemented.; Multi-hop Virtual Deadline Scheduling (MVDS) is introduced as an extension to VDS to provide end-to-end window-constraint guarantees for soft real-time streams. MVDS exploits he cooperation between hops by using a local virtual deadline based priority scheme and a utilization-based probabilistic drop scheme. Results from the NS simulation show that MVDS is capable of providing better window-constrained service guarantees than other related algorithms, while still maintaining high link utilization.; At the end of this thesis, some issues and possible solutions are briefly examined on the future topic of predictable window-constrained scheduling of inter-dependent jobs. |
