Fair queuing is a well-studied problem in modern computer networks. However, there remains a gap between scheduling algorithms that have provably good performance, and those that are feasible and practical to implement in highspeed routers. In this paper, we propose a novel packet scheduler called Stratified Round Robin, which has low complexity, and is amenable to a simple hardware implementation. Stratified Robin Robin exhibits good fairness and delay properties that are demonstrated through both analytical results and simulations. In particular, it provides a single packet delay bound that is independent of the number of flows. This property is unique to Stratified Round Robin among all other schedulers of comparable complexity.

This paper describes an algorithm for scheduling packets in real-time multimedia data streams. Common to these classes of data streams are service constraints in terms of bandwidth and delay. However, it is typical for realtime multimedia streams to tolerate bounded delay variations and, in some cases, finite losses of packets. We have therefore developed a scheduling algorithm that assumes streams have window-constraints on groups of consecutive packet deadlines. A window-constraint defines the number of packet deadlines that can be missed in a window of deadlines for consecutive packets in a stream.

and useful abstraction for multiplexing time-shared resources. We present Group Ratio Round-Robin (GR ), the first proportional share scheduler that combines accurate proportional fairness scheduling behavior with O(1) scheduling overhead on both uniprocessor and multiprocessor systems. GR uses a novel client grouping strategy to organize clients into groups of similar processor allocations which can be more easily scheduled. Using this grouping strategy, GR combines the benefits of low overhead round-robin execution with a novel ratio-based scheduling algorithm. GR can provide fairness within a constant factor of the ideal generalized processor sharing model for client weights with a fixed upper bound and preserves its fairness properties on multiprocessor systems.

In this paper, we propose an O(1) complexity round robin scheduler, called Fair Round Robin (FRR), that provides good fairness and delay properties. Unlike existing O(1) complexity round robin schedulers that can only achieve long term fairness, FRR not only provides proportional fairness, but also maintains a constant normalized worst-case fair index as defined in Bennett and Zhang's work.

Many studies show that the wireless network interface (WNI) accounts for a significant part of the power consumed by mobile terminals. Thus, putting the WNI into sleep when it is idle is an effective technique to save power. To support streaming applications, existing techniques cannot put the WNI into sleep due to strict delay requirements. In this paper, we present a novel power-aware and QoS-aware service model over wireless networks. In the proposed model, mobile terminals use proxies to buffer data so that the WNIs can sleep for a long time period. To achieve power-aware communication while satisfying the delay requirement of each flow, a scheduling scheme, called prioritybased bulk scheduling (PBS), is designed to decide which flow should be served at which time. Through analysis, we prove that the PBS service model can provide delay assurance and achieve power efficiency. We use Audio-on-Demand and Web access as case studies to evaluate the performance of the PBS service model. Experimental results show that PBS achieves excellent QoS provision for each flow and significantly reduces the power consumption.

Generalized Processor Sharing (GPS) is a fluid scheduling policy providing perfect fairness. The minimum deviation (lead/lag) with respect to the GPS service achievable by a packet scheduler is one packet size. To the best of our knowledge, the only packet scheduler guaranteeing such minimum deviation is Worst-case Fair Weighted Fair Queueing (WF   Q), that requires on-line GPS simulation. Existing algorithms to perform GPS simulation have ¡£¢¥¤§¦ complexity per packet transmission ( ¤

We consider the problem of task reweighting in fair-scheduled multiprocessor systems wherein each task’s processor share is specified using a weight. When a task is reweighted, a new weight is computed for it that is then used in future scheduling. Task reweighting can be used as a means for consuming (or making available) spare processing capacity. The responsiveness of a reweighting scheme can be assessed by comparing its allocations to those of an ideal scheduler that can reweight tasks instantaneously. A reweighting scheme is fine-grained if any additional per-task “error ” (in comparison to an ideal allocation) caused by a reweighting event is constant. Similarly, a reweighting scheme is coarse-grained if the additional “error ” per reweighting event is non-constant. While fine-grained reweighting produces only a small amount of error when changing task weights, it has a worst-case time complexity of Θ(NlogN), where N is the number of tasks. If the number of tasks exceeds the number of processors, then such time complexity is larger than that of coarse-grained reweighting, which is Θ(MlogN), where M is the number of processors. In this paper, we construct two new reweighting algorithms that are hybrids of fine- and coarse-grained reweighting that have time complexity less than Θ(NlogN) and produce less error than current coarse-grained techniques. We also present an experimental evaluation of these scheme to compare their relative advantages.

Applications such as video and audio streaming, online gaming, video conferencing, Voice over IP (VoIP) and File Transfer Protocol (FTP) demand a wide range of QoS requirements such as bandwidth and delay. Existing wireless technologies that can satisfy the requirements of heterogeneous traffic are very costly to deploy in rural areas and “last mile ” access. Worldwide Interoperability for Microwave Access (WiMAX) provides an affordable alternative for wireless broadband access supporting a multiplicity of applications. The IEEE 802.16 standard provides specification for the Medium Access Control (MAC) and Physical (PHY) layers for WiMAX. A critical part of the MAC layer specification is scheduling, which resolves contention for bandwidth and determines the transmission order of users. It is imperative for a scheduling algorithm to have a multi-dimensional objective of satisfying QoS requirements of the users, maximizing system utilization and ensuring fairness among the users. In this thesis, we categorize and study various scheduling algorithms for the uplink traffic in WiMAX in view of these objectives. The algorithms

scheduler which has good fairness and delay properties, and low quasi- (1) complexity. It is unique among all other schedulers of comparable complexity in that it provides a single packet delay bound that is independent of the number of flows. Importantly, it is also amenable to a simple hardware implementation, and thus fills a current gap between scheduling algorithms that have provably good performance and those that are feasible and practical to implement in high-speed routers. We present both analytical results and simulations to demonstrate its performance properties. Index Terms—High-speed router design, packet scheduling, quality of service. I.

Reducing the power consumption of the wireless network interface (WNI) is an effective way to prolong the battery lifetime of the mobile terminal. It takes some time for the WNI to transit from the power-saving mode to the active mode. This transition delay and the error-prone wireless link bring many challenges for designing power-aware and QoS-aware service models. In this paper, we present a novel power-conserving service model for streaming applications over wireless networks. At the base station side, a new scheduling algorithm, called rate-based bulk scheduling (RBS), is designed to decide which flow should be served at which time. The mobile terminal relies on a proxy to buffer data so that the WNI can sleep for a long time period to save power. To deal with channel errors, a novel adaptive technique is presented to adjust the sleep time of the WNI according to the channel condition. Through analysis, we prove that RBS can provide delay guarantee and it is more power efficient than other rate-based fair queuing algorithms.