Task Reweighting under Global Scheduling on Multiprocessors

Partitioning and global scheduling are two approaches for scheduling real-time tasks in multiprocessor environments. Partitioning is the more favored approach, although it is sub-optimal. This is mainly due to the fact that popular uniprocessor real-time scheduling algorithms, such as EDF and RM, can be applied to the partitioning approach with low scheduling overhead. In recent years, much research has been done on global real-time multiprocessor scheduling algorithms based on the concept of “proportionate fairness”. Proportionate fair (Pfair) scheduling [5],[6] is the only known optimal algorithm for scheduling real-time tasks on multiprocessor. However, frequent preemptions caused by the small quantum length for providing optimal scheduling in the Pfair scheduling make it impractical. Deadline Fair Scheduling (DFS) [1] based on Pfair scheduling tried to reduce preemption-related overhead by means of extending quantum length and sharing a quantum among tasks. But extending quantum length causes a mis-estimation problem for eligibility of tasks and a non-work-conserving problem. In this paper, we propose the Enhanced Deadline Fair Scheduling (E-DFS) algorithm to reduce preemption-related overhead. We show that E-DFS allows us to decrease quantum length by reducing overhead and save wasted CPU time that is caused by preemption-related overhead and miss-estimation of eligibility.

Fair scheduling or Fair Queueing (FQ) algorithms have received much attention in recent years because of their ability to provide a wide range of Quality-ofService (QoS) guarantees to end users. In this paper, we present a new analysis method that can statistically model such fair scheduling algorithms under Poisson arrivals and a general packet length distribution. We coin the new term M/G/FQ to describe this analysis method, which fits a broad range of scheduling policies including WFQ, SCFQ, SFQ and SPFQ.

Analysis of temporal and throughput fair scheduling in multirate WLANs

Fair scheduling algorithms have been proposed to tackle the problem of bursty and location-dependent errors in wireless packet networks. Most of those algorithms ensure the fairness property and guarantee the QoS of all sessions in a large-scale cellular network such as GSM or GPRS. In this paper, we propose the Weighted-Sacrificing Fair Queueing (WSFQ) scheduling algorithm for small-area and device-limited wireless networks. WSFQ slows down the growth of queue length in limited-buffer devices, still maintains the properties of fairness, and guarantees the throughputs of the system. Moreover, WSFQ can easily adapt itself to various kinds of traffic load. We also implement a packet-based scheduling algorithm, the Packetized Weighted Sacrificing Fair Queueing (PWSFQ), to approach the WSFQ. WSFQ and PWSFQ are evaluated by comparing with other algorithms by mathematical analysis and simulations.

This paper proposed an efficient real time scheduling algorithm using global scheduling paradigm running in multicore environment known as Global Preemptive Utility Accrual Scheduling (GPUAS) algorithm. The existing TUF/UA multiprocessor scheduling algorithms known as Greedy-Global Utility Accrual (G-GUA) and Non Greedy-Global Utility Accrual (NG-GUA) algorithms is seen to overlook the efficiency on its task scheduling algorithm. These algorithms have adapted the task migration attribute considering the load balancing problem in multi core platform. The existing PUAS uniprocessor scheduling algorithm is mapped into the multicore scheduling environment that consists of the global scheduling schemes considering the migration attribute of the executed tasks. The main principal of global scheduling is that it allows the executed tasks to migrate from one processor to the other processors whenever a scheduling event occurs in the system. The proposed GPUAS algorithm inherits the characteristics of PUAS in uniprocessor where it can preempt the highest PUD task at any event that occurs in the system. In this research, the proposed GPUAS algorithm enhanced the existing NG-GUA and G-GUA algorithms. The developed simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. The proposed GPUAS algorithm achieved the highest accrued utility for the entire load range. The proposed GPUAS algorithm is more efficient than the existing algorithms, producing the highest accrued utility ratio and less abortion ratio making it more suitable and efficient for real time application domain.

Long Term Evolution(LTE) 시스템은 멀티미디어 서비스와 같은 다양한 서비스를 이동 사용자에게 제공할 수 있다. 실제로 HSPA+(High Speed Packet Access plus)는 다운링크의 비트 율(bit rate)을 크게 향상 시켰으나, 다양한 멀티미디어 서비스에서 요구하는 서비스 품질을 어떻게 만족시킬 것인가에 대한 연구는 매우 미비한 상태이다. 본 논문에서는 proportional fair(PF) 알고리즘을 기반으로 하여 LTE를 위한 효율적인 패킷 스케쥴링 알고리즘을 제안하였다. 제안된 알고리즘에서는 패킷 스케쥴링을 할 때 패킷의 우선순위를 결정하는 가장 중요한 요소인 트래픽 클래스의 가중치와 순간 사용자 데이터 전송율을 최적화 하였다. 또한 다중 셀(multi-cell) 환경에서 LTE를 통해서 사용자에게 전송되는 멀티미디어 트래픽을 시뮬레이션 함으로써 제안된 알고리즘의 성능이 향상되었음을 보였다. The Long Term Evolution (LTE) system is already able to provide a background of variety services for mobile users with multimedia services such as audio, video, and data. In fact, the High Speed Packet Access plus (HSPA+) solution can greatly enhance bit rates on down-link. However, the supporting for multimedia applications with different QoS (Quality of Service) requirements is not devised yet. Hence, in this paper we propose an effective packet scheduling algorithm based on Proportional Fairness (PF) scheduling algorithms for the LTE. In this proposed packet scheduling scheme, we optimized instantaneous user data rates and the traffic class weight which prioritize user's packets. Finally, we evaluated and showed the performance of the proposed scheduling algorithm through simulations of multimedia traffics being transmitted to users over LTE links in a multi-cell environment.

The effective reuse of the radio resources in D2D communication underlaying cellular system is pivotal for enhancing the total system capacity. Developing practical and effective scheduling schemes is critical to the success of D2D-based cellular systems. An optimal proportionally fair (PF) scheduling scheme that maximizes the logarithmic sum of the user data rates is proposed in this paper. Considering the fact that the computational complexity of the optimal PF scheduling is significantly high, low-complexity heuristic algorithm has also been proposed. It has been shown that the heuristic algorithm achieves high logarithmic sum of the average user data rates while maintaining low-computational complexity. Simulation results are used to verify the performance of the proposed algorithm, and to compare it with the optimal PF scheduling algorithms.

Scheduling algorithms are fundamental components in the process of resource management in mobile communication networks with heterogeneous QoS requirements such as delay, delay jitter, packet loss rate or throughput. The random characteristics of the propagation environment and the use of complex physical layers in order to combat this random behavior further complicates the design of simple, efficient, scalable and fair scheduling algorithms. This paper presents the main criteria used in the design of scheduling algorithms for 3G/4G mobile communications networks and provides a survey of scheduling mechanisms proposed for use in TDMA and CDMA based systems.Keywordsscheduling4GGPSutility functions

We consider the downlink of a multiuser multiple-input multiple-output (MIMO) system, where the base station and the mobile receivers are equipped with multiple antennas. We propose simplified algorithms for channel-aware multiuser scheduling in conjunction with receive antenna selection for two downlink multiuser orthogonal space-division multiplexing techniques: block diagonalization and successive optimization. The algorithms greedily maximize the weighted sum rate. The algorithms add the best user at a time from the set of users that are not selected yet to the set of selected users until the desired number of users has been selected. To apply the proportional fairness criterion, simplified user scheduling metrics are proposed for block diagonalization and successive optimization. Two receive antenna selection algorithms are also proposed, which further enhance the power gain of the equivalent single-user channel after orthogonal precoding by selecting a subset of the receive antennas that contributes the most toward the total power gain of the channel. A user grouping technique is used to further lower the complexity of the selection algorithms. We compare various multiuser MIMO scheduling strategies that are applied to block diagonalization and successive optimization transmission techniques through simulation. Simulation results demonstrate the effectiveness of the proposed algorithms in ensuring throughput fairness among users. Results also show that when the number of users is large, the proposed scheduling algorithms perform close to the exhaustive search algorithms and previously proposed greedy scheduling algorithms, but with much lower complexity.

Fairness amongst multiple users sharing a common resource has been an important criterion in the evaluation of scheduling algorithms in networks. Anonymous networking, where sources of transmitted packets are undecipherable to an eavesdropper, requires that packets from multiple sources are randomly reordered prior to transmission which works against the notion of fair scheduling. Consequently, it is important to understand the relationship between fairness and achievable anonymity in networking. In this paper, this relationship is characterized for the class of fair scheduling axioms defined by considering the equal treatment ex ante and demand mono-tonicity, under which the proportional method is known to be the unique scheduling algorithm that achieves the desired fairness. Using an information theoretic quantitative framework, the anonymity of this scheduling algorithm is characterized and proven to be asymptotically optimal with increase in buffer size. The anonymity achieved by the proportional method is also shown to be significantly better than conventional fair scheduling algorithms such as first come first serve and round robin, thus making a case for its application in data networks.

We present Start-time Fair Queuing (SFQ) algorithm that is computationally efficient, achieves fairness regardless of variation in a server capacity, and has the smallest fairness measure among all known fair scheduling algorithms. We analyze its throughput, single server delay, and end-to-end delay guarantee for variable rate Fluctuation Constrained (FC) and Exponentially Bounded Fluctuation (EBF) servers. We show that SFQ is better suited than Weighted Fair Queuing for integrated services networks and it is strictly better than Self Clocked Fair Queuing. To support heterogeneous services and multiple protocol families in integrated services networks, we present a hierarchical SFQ scheduler and derive its performance bounds. Our analysis demonstrates that SFQ is suitable for integrated services networks since it: (1) achieves low average as well as maximum delay for low-throughput applications (e.g., interactive audio, telnet, etc.); (2) provides fairness which is desirable for VBR video; (3) provides fairness, regardless of variation in a server capacity, for throughput-intensive, flow-controlled data applications; (4) enables hierarchical link sharing which is desirable for managing heterogeneity; and (5) is computationally efficient.

IEEE 802.16 standards specify four types of services, while how to design an efficient scheduling algorithm remains an open issue. Manufacturers can implement their own scheduling algorithms depending on their specific requirements. There are a lot of scheduling algorithms proposed in the literature. Several scheduling algorithms propose hierarchical structures with strict priority or one-level scheduling mechanism. They are based conceptually on the round-robin approaches. However, they don't consider an important factor: fairness. In this paper we propose a fairness strategy algorithm for IEEE 802.16 broadband wireless access networks. The proposed algorithm applies a fairness strategy to utilize the system bandwidth, to achieve the QoS requirements of high priority service flows, and to reduce starvations of low priority service flows. The simulation studies show that the proposed scheduling algorithm provides a flexible way to utilize the system bandwidth.

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Cell-based input-queued crossbars are widely used in networking equipments. A number of crossbar scheduling algorithms have been proposed to provide high performance scheduling. It is critical for a crossbar scheduling algorithm to be fair and efficient in real world conditions, which include the presence of over-subscribed ingress ports and the possible flow control from the egress ports. Several commonly deployed algorithms are not fair when there are ingress congestions due to over-subscription. Furthermore, these algorithms lose fairness and can even cause starvation when there is flow control or backpressure from the egress ports. We illustrate the problems in detail using the well-known iSLIP algorithm. In this paper, we present a new algorithm, iSKIP, which performs as efficiently as iSLIP in a benign environment but remains fair and starvation-free in the cases of ingress congestion and egress backpressure. The iSKIP algorithm can be implemented in fast and simple hardware. Simulation results are presented to illustrate the advantages of the iSKIP algorithm.

Scheduling allots the frequency and time resources of the LTE network to the users based on certain algorithms. The aim of an efficient fair scheduling is to provide the radio resources such that all the users are serviced almost equally over time without reducing the average user throughput. In this paper a fair scheduling algorithm named Blind Equal Throughput is modified and tested in different user conditions and a new scheduling scheme named Proportional Equal Throughput (PET) is developed which offers better fairness among users without reducing average user throughput, in comparison with other scheduling algorithms.