Head-of-Line Access Delay-Based Scheduling Algorithm for Flow-Level Dynamics

The LTE specification provides Quality of Service (QoS) of multimedia services with fast connectivity, high mobility, and security. However, 3GPP specifications have not defined scheduling algorithms to support real-time and non-realtime application services, this has led to the development of a variety of scheduling algorithms in the recent years. Performance is a key factor for assessing the scheduling algorithms. However, the performance analysis and evaluation for existing scheduling algorithms are limited to QoS parameters (e.g. in terms of throughput, packet loss and delay) and/or fairness metrics. It is not clear how these scheduling algorithms perform in terms of Quality of Experience (QoE) metrics (e.g. MOS score) which are more closely linked with end user experience or user perceived quality. In this paper, we investigate and evaluate the performance of three popular LTE downlink schedulers (proportional fairness (PF), exponential proportional fairness (EXP-PF), and modified largest weight delay first (M-LWDF)) in terms of QoE metric (i.e. MOS score) in addition to normal QoS metrics (e.g. packet loss and delay) for VoIP applications. Simulation results (based on LTE-Sim) show that the best suitable downlink scheduling algorithm is MLWDF, which has short end-to end delay (less than 50ms) and allowing maximum number of user access (more than 50 users) at acceptable MOS score (MOS over 3.5). The widely used scheduling algorithm (PF) will increase its end-to-end delay over 200ms, when number of user access is over 30. This will limit its application for VoIP when user access number increases. This work would help to assist the design and development of QoE-driven scheduling algorithms for mobile multimedia applications in the future.

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

As the penetration level of plug-in hybrid electric vehicles (PHEVs) increases, the stress on the distribution system will become more pronounced. In this paper, we concentrate on PHEV charging in public infrastructures, such as shared parking lots in commercial office campuses and shopping malls. In such clustered scenarios, PHEV charging demand can vary significantly and stochastically with time, and the overall system performance is a result of a trade-off between the peak load on the distribution system and the consumer specified charging deadlines that are met successfully. However, unlike distributed residential charging, those scenarios can benefit from centralized algorithms to schedule the charging of vehicles. This paper considers the design of such scheduling algorithms. We show that through proper design of the scheduling algorithms, the parking lot owner can balance distribution system load with quality of charging service.

Wireless Mesh Networks offer a high-performance and low-cost solution to last-mile broadband Internet access. Routing and Scheduling play a critical role in determining the performance of a wireless mesh network. Efficiency of Routing and Scheduling algorithms is highly dependent on the availability of accurate traffic information. In this paper, we predict network traffic based on past data using ARIMA model, and provide that input to the routing and scheduling algorithm. Joint routing and scheduling results in significant performance improvement over the routing only algorithms. So, we provide predicted network traffic information to a Joint routing and scheduling algorithm known as Traffic Oblivious Routing and Scheduling. Traffic Oblivious Routing and Scheduling algorithm optimizes the worst case performance under traffic uncertainty but when accurate traffic information is available to the algorithm, its performance is enhanced. In the Traffic Oblivious Routing and Scheduling algorithm, computing the routing and the scheduling values is a one time overhead. In this paper, we present a system where we predict network traffic information using past data, then use the predicted information to formulate the input for the Traffic Oblivious routing and scheduling algorithm and finally we evaluate the performance of the algorithm using simulations.

Capturing urgency and parallelism using quasi-deadlines for real-time multiprocessor scheduling

Improved schedulability analysis of the contention-free policy for real-time systems

Bluetooth enables wireless communication via ad hoc networks. The basic topology (piconet) is a collection of slaves controlled by a master. A scatternet is a multihop network of piconets. We anticipate that most scatternets will be composed of only a few piconets. However, even in small scatternets, efficient data flow requires the design of inter-piconet scheduling algorithms. Thus, this article presents and evaluates a load adaptive scheduling algorithm tailored for small-scale scatternets. The main advantage of this algorithm is the use of the Bluetooth low-power hold mode, which allows greater flexibility than other low-power modes. A simulation model has been developed in order to evaluate the performance of the algorithm. We show that the results obtained by the model are very close to the analytic results. Then we evaluate the performance of various intra-piconet scheduling algorithms. Finally, we present simulation results regarding inter-piconet scheduling, and compare the proposed algorithm to algorithms using the sniff mode.

The objective of this research is to design and implement real-time scheduling algorithms for flexible manufacturing systems. Four CNC machines with a load/unload station and a conveyor belt are combined as a flexible manufacturing system. Three fuzzy-based scheduling algorithms have been developed for operation sequencing, task sequencing and routing. LabVIEW environment has been used for the system modelling and testing. Several case studies have been carried out to test and verify the flexibility of the system and the effectiveness of the proposed schedulers. The obtained results indicate that the proposed scheduling algorithms for sequencing and routing are promising for such FMS. The performances of the proposed fuzzy scheduling algorithms are compared with those obtained from published literature.

Scheduling algorithms in wavelength division multiplexing (WDM) single-hop networks aim at producing an effective schedule in order to improve the networks' performance. Apart from channel assignment, the message sequencing is an important issue that have to be addressed when designing media access control (MAC) protocols for WDM networks. Up until now, popular approaches have not extensively addressed the order in which the messages are scheduled even though the messages' service order can considerably contribute to the advance of network performance. This paper introduces a new approach to the design of message scheduling algorithms for WDM star networks, which is based on the use of clustering techniques. The proposed clustering oriented-earliest available time scheduling (CO-EATS) creates groups of nodes whose messages are destined to common nodes. The goal of the proposed CO-EATS scheme is to decrease the probability of scheduling messages to the same destination at successive order. The simulation results have shown that the proposed scheme improves channel utilization and as a result it leads to higher network throughput while it keeps mean packet delay at low levels in comparison with conventional scheduling algorithms.

Results of the design and performance analysis of two new algorithms for efficient and fair scheduling of variable-length frames in a wavelength division multiplexing (WDM)-passive optical network (PON) under the Stanford University aCCESS-Hybrid PON (SUCCESS-HPON) architecture are reported. The WDM-PON under the SUCCESS-HPON architecture has unique features that have direct impacts on the design of scheduling algorithms. First, an optical line terminal (OLT) uses tunable transmitters and receivers that are shared by all the optical network units (ONUs) served by the OLT to reduce the number of expensive dense WDM (DWDM) transceivers. Second, also for cost reduction, ONUs have no local DWDM light sources but use optical modulators to modulate optical continuous wave (CW) bursts provided by the OLT for upstream transmissions. Therefore, the tunable transmitters at the OLT are used for both upstream and downstream transmissions. To provide efficient bidirectional communications between the OLT and the ONUs and guarantee fairness between upstream and downstream traffic, two scheduling algorithms have been designed: 1) batching earliest departure first (BEDF); and 2) sequential scheduling with schedule-time framing (S/sup 3/F). The BEDF is based on the batch scheduling mode where frames arriving at the OLT during a batch period are stored in virtual output queues (VOQs) and scheduled at the end of the batch period. It improves transmission efficiency by selecting the frame with the earliest departure time from a batch of multiple frames, which optimizes the usage of tunable transmitters in scheduling. Considering the high complexity of the optimization process in BEDF, the S/sup 3/F based on the sequential scheduling mode has also been designed as in the original sequential scheduling algorithm proposed earlier. In S/sup 3/F, the authors use VOQs to provide memory space protection among traffic flows and a granting scheme together with schedule-time framing for both upstream and downstream traffic to reduce framing and guard band overhead. Through extensive simulations under various configurations of the tunable transmitters and receivers, it has been demonstrated that both the BEDF and S/sup 3/F substantially improve the throughput and delay performances over the original sequential scheduling algorithm, while guaranteeing better fairness between upstream and downstream traffic.

Many of today's high-level parallel languages support dynamic, fine-grained parallelism. These languages allow the user to expose all the parallelism in the program, which is typically of a much higher degree than the number of processors. Hence an efficient scheduling algorithm is required to assign computations to processors at runtime. Besides having low overheads and good load balancing, it is important for the scheduling algorithm to minimize the space usage of the parallel program. This article presents an on-line scheduling algorithm that is provably space efficient and time efficient for nested-parallel languages. For a computation with depth D and serial space requirement S 1 , the algorithm generates a schedule that requires at most S 1 + O (K•D•p ) space (including scheduler space) on p processors. Here, K is a user-adjustable runtime parameter specifying the net amount of memory that a thread may allocate before it is preempted by the scheduler. Adjusting the value of K provides a trade-off between the running time and the memory requirement of a parallel computation. To allow the scheduler to scale with the number of processors we also parallelize the scheduler and analyze the space and time bounds of the computation to include scheduling costs. In addition to showing that the scheduling algorithm is space and time efficient in theory, we demonstrate that it is effective in practice. We have implemented a runtime system that uses our algorithm to schedule lightweight parallel threads. The results of executing parallel programs on this system show that our scheduling algorithm significantly reduces memory usage compared to previous techniques, without compromising performance.

In order to effectively utilize the broadcast bandwidth, it is necessary to have efficient on-line scheduling algorithms that can balance individual and overall performance and can scale in terms of database sizes and client populations. Moreover, the scheduling algorithm should be applicable to a heterogeneous environment where data items have different sizes. We address these issues in this paper. As stretch is widely adopted as a performance metric for variable-size data requests, we propose a broadcast scheduling algorithm to optimize the system performance in terms of stretch. We show by analysis that the proposed algorithm can indeed achieve the optimal performance in terms of stretch. Moreover, the proposed scheduling algorithm has very low decision overhead, which makes it a practical solution for on-demand broadcast scheduling. Simulation results demonstrate that our algorithm significantly outperforms existing scheduling algorithms under various scenarios.

Load balancing mechanisms and scheduling algorithms play a critical role in achieving efficient server utilization and providing robust delay performance in a wide range of networked systems. We will review some celebrated schemes and optimality results which typically assume that detailed state information, e.g. exact knowledge of queue lengths, is available in assigning jobs to queues or allocating a shared resource among competing users. In practice, however, obtaining such state information is non-trivial, and usually involves a significant communication overhead or delay, which is particularly a concern in large-scale networked systems with massive numbers of queues. These scalability issues have prompted increasing attention for the implementation complexity of load balancing and scheduling algorithms as a crucial design criterion, besides the traditional performance metrics. In this talk we examine the delay performance in such networks for various load balancing and scheduling algorithms, in conjunction with the associated implementation overhead. In the first part of the talk we focus on a scenario with a single dispatcher where jobs arrive that need to be assigned to one of several parallel queues. In the second part of the talk we turn to a system with a single resource, e.g. a shared wireless transmission medium, which is to be allocated among several nodes. We will specifically explore the delay scaling properties in a mean-field framework where the total load and service capacity grow large in proportion. The mean-field regime not only offers analytical tractability, but is also highly relevant given the immense numbers of servers in data centers and cloud networks, and dense populations of wireless devices and sensors in Internet-of-Things (IoT) applications. Time permitting, we will also discuss the impact of the underlying network structure and a few open research challenges.

This paper addresses online scheduling of malleable parallel jobs to minimize the maximum completion time, i.e., makespan. It is assumed that the execution time of a job Jj with processing time pj is pj/k + (k-1)c if the job is assigned to k machines, where c > 0 is a constant setup time. We consider online algorithms for the scheduling problem on two identical machines. Namely, the job Jj can be processed on one machine with execution time pj or alternatively two machines in parallel with execution time pj/2+c. For the asymptotical competitive ratio, we provide an improved online algorithm with makespan no more than (3/2)C* +c/2, where C* is the optimal makespan. For the strict competitive ratio, we propose an online algorithm with competitive ratio of 1.54, which is close to the lower bound of 1.5.

High efficient task scheduling algorithms can greatly influence the performance of reconfigurable systems. This paper analyzed the disadvantages of some current on-line reconfigurable system task scheduling algorithms, and proposed a new scheduling algorithm based on placement cost. This scheduling algorithm considered three types of cost, including hardware task execution time in FPGA, occupied FPGA area and fragmentation situation of FPGA, and also considered the unified scheduling of hardware and software tasks. When a hardware task was in scheduling, if the placement cost exceeded the setting threshold value, the task would be rejected to run in FPGA, but its software implementation could run in CPU. By reasonably rejecting some high cost tasks, this algorithm could achieve a higher overall successful scheduling rate. The simulation results show that this scheduling algorithm can achieve a higher deadline-guarantee ratio than others.