Bandwidth Guaranteed Multicast Scheduling for Buffered Crossbar

2011 ◽  
Vol 474-476 ◽  
pp. 1819-1824
Author(s):  
Peng Wang ◽  
Shu Qiao Chen ◽  
Hong Chao Hu

The limitations in complexities and extensibilities of current scheduling policies based on combined input and cross-point queuing switch (CICQ) are first analyzed. To overcome the deficiencies in supporting fair and QOS scheduling, we propose a fair and simple high-performance multicast scheduling algorithm for Combined Input Crosspoint Queued Switches, which is called multicast Fair Service and Group Smoothed Round Robin (mFGSR). The complexity of the algorithm is onlyO(1).mFGSR groups and schedules flows according to the weight of flows, thus it has good fairness and can adapt to the need of real-time performance. Theorotical analysis and simulation results show that mFGSR exhibits good delay, throughput and anti-burst performance.

2011 ◽  
Vol 268-270 ◽  
pp. 2101-2107
Author(s):  
Mei Yue Yang ◽  
Peng Wang ◽  
Xiang Tao Li ◽  
Sheng Ping Zhu

The limitations in complexity and scalability of current combined input and cross-point queuing switching scheduling policies are first analyzed. To overcome the deficiencies in supporting fair and QOS scheduling, we propose a fair and simple high-performance scheduling algorithm for Combined Input-Cross-point-Queued Switches, which is called Fair Service and Group Smoothed Round Robin (FGSR). The main idea of FGSR is that it first groups flows according to their weight, then decides which group to be scheduled by SRR and finally decides which flow from the selected group to be scheduled. FGSR is based on round robin mechanism, whose complexity is only O(1). FGSR groups and schedules flows according to the weight of flows, thus it has good fairness and can adapt to the need of real-time performance. Theoretical analysis and simulation results show that FGSR exhibits good delay, throughput and anti-burst performance.


Author(s):  
Jop Vermeer ◽  
Leonardo Scandolo ◽  
Elmar Eisemann

Ambient occlusion (AO) is a popular rendering technique that enhances depth perception and realism by darkening locations that are less exposed to ambient light (e.g., corners and creases). In real-time applications, screen-space variants, relying on the depth buffer, are used due to their high performance and good visual quality. However, these only take visible surfaces into account, resulting in inconsistencies, especially during motion. Stochastic-Depth Ambient Occlusion is a novel AO algorithm that accounts for occluded geometry by relying on a stochastic depth map, capturing multiple scene layers per pixel at random. Hereby, we efficiently gather missing information in order to improve upon the accuracy and spatial stability of conventional screen-space approximations, while maintaining real-time performance. Our approach integrates well into existing rendering pipelines and improves the robustness of many different AO techniques, including multi-view solutions.


Author(s):  
Lavanya Dhanesh ◽  
P. Murugesan

Scheduling of tasks based on real time requirement is a major issue in the heterogeneous multicore systemsfor micro-grid power management . Heterogeneous multicore processor schedules the serial tasks in the high performance core and parallel tasks are executed on the low performance cores. The aim of this paper is to implement a scheduling algorithm based on fuzzy logic for heterogeneous multicore processor for effective micro-grid application. Real – time tasks generally have different execution time and dead line. The main idea is to use two fuzzy logic based scheduling algorithm, first is to assign priority based on execution time and deadline of the task. Second , the task which has assigned higher priority get allotted for execution in high performance core and remaining tasks which are assigned low priority get allotted in low performance cores. The main objective of this scheduling algorithm is to increase the throughput and to improve CPU utilization there by reducing the overall power consumption of the micro-grid power management systems. Test cases with different task execution time and deadline were generated to evaluate the algorithms using  MATLAB software.


2014 ◽  
Vol 596 ◽  
pp. 511-518
Author(s):  
Lin Qi ◽  
Hai Peng Wang ◽  
Yu Liu ◽  
Cong Wang

To achieve fast and accurate association for AIS and radar tracks, provide associated track-pairs for subsequent sensor bias registration and situational fusion, this paper presents an anti-bias association algorithm for AIS and radar tracks according to centroid reference topological characteristics (CRT). The algorithm describes the topological characteristics of track-points set on the basis of targets position relative to the centroid of the set to achieve AIS and radar tracks fine association in the presence of radar bias. The proposed algorithm outperforms the traditional tracks association algorithms based on image matching principle (IM) or targets reference topology feature (TRT) in terms of real-time performance, simultaneously has high correctly associated rate. Simulation results show that the falsely associated rate of this algorithm maintains 0, the correctly associated rate maintains above 85%. It can provide reliable associated track-pairs for system errors registration; while the average time-consuming of the algorithm is 1/4 and 1/417 of TRT and IM algorithm, the practicality has been significantly improved.


Author(s):  
Sonia Zouaoui ◽  
Lotfi Boussaid ◽  
Abdellatif Mtibaa

<p>This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.</p>


Author(s):  
Wael Farag ◽  

In this paper, a real-time road-Object Detection and Tracking (LR_ODT) method for autonomous driving is proposed. The method is based on the fusion of lidar and radar measurement data, where they are installed on the ego car, and a customized Unscented Kalman Filter (UKF) is employed for their data fusion. The merits of both devices are combined using the proposed fusion approach to precisely provide both pose and velocity information for objects moving in roads around the ego car. Unlike other detection and tracking approaches, the balanced treatment of both pose estimation accuracy and its real-time performance is the main contribution in this work. The proposed technique is implemented using the high-performance language C++ and utilizes highly optimized math and optimization libraries for best real-time performance. Simulation studies have been carried out to evaluate the performance of the LR_ODT for tracking bicycles, cars, and pedestrians. Moreover, the performance of the UKF fusion is compared to that of the Extended Kalman Filter fusion (EKF) showing its superiority. The UKF has outperformed the EKF on all test cases and all the state variable levels (-24% average RMSE). The employed fusion technique show how outstanding is the improvement in tracking performance compared to the use of a single device (-29% RMES with lidar and -38% RMSE with radar).


2019 ◽  
Vol 39 (5) ◽  
pp. 753-768 ◽  
Author(s):  
Ruochen Tai ◽  
Jingchuan Wang ◽  
Weidong Chen

Purpose In the running of multiple automated guided vehicles (AGVs) in warehouses, delay problems in motions happen unavoidably as there might exist some disabled components of robots, the instability of networks and the interference of people walking. Under this case, robots would not follow the designed paths and the coupled relationship between temporal and space domain for paths is broken. And there is no doubt that other robots are disturbed by the ones where delays happen. Finally, this brings about chaos or even breakdown of the whole system. Therefore, taking the delay disturbance into consideration in the path planning of multiple robots is an issue worthy of attention and research. Design/methodology/approach This paper proposes a prioritized path planning algorithm based on time windows to solve the delay problems of multiple AGVs. The architecture is a unity consisting of three components which are focused on scheduling AGVs under normal operations, delays of AGVs, and recovery of AGVs. In the components of scheduling AGVs under normal operations and recovery, this paper adopts a dynamic routing method based on time windows to ensure the coordination of multiple AGVs and efficient completion of tasks. In the component for scheduling AGVs under delays, a dynamical prioritized local path planning algorithm based on time windows is designed to solve delay problems. The introduced planning principle of time windows would enable the algorithm to plan new solutions of trajectories for multiple AGVs, which could lower the makespan. At the same time, the real-time performance is acceptable based on the planning principle which stipulates the parameters of local time windows to ensure that the computation of the designed algorithm would not be too large. Findings The simulation results demonstrate that the proposed algorithm is more efficient than the state-of-the-art method based on homotopy classes, which aims at solving the delay problems. What is more, it is validated that the proposed algorithm can achieve the acceptable real-time performance for the scheduling in warehousing applications. Originality/value By introducing the planning principle and generating delay space and local adjustable paths, the proposed algorithm in this paper can not only solve the delay problems in real time, but also lower the makespan compared with the previous method. The designed algorithm guarantees the scheduling of multiple AGVs with delay disturbance and enhances the robustness of the scheduling algorithm in multi-AGV system.


2020 ◽  
Vol 2020 ◽  
pp. 1-6 ◽  
Author(s):  
Yali Xue ◽  
Hu Chen ◽  
Jie Chen ◽  
Jiahui Wang

This paper based on the Gaussian particle filter (GPF) deals with the attitude estimation of UAV. GPF algorithm has better estimation accuracy than the general nonlinear non-Gaussian state estimation and is usually used to improve the system’s real-time performance whose noise is specific such as Gaussian noise during the mini UAV positioning and navigation. The attitude estimation algorithm is implemented on FPGA to verify the effectiveness of the Gaussian particle filter. Simulation results have illustrated that the GPF algorithm is effective and has better real-time performance than that of the particle filter.


2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Rashmi Sharma ◽  
Nitin

In Real Time System, the achievement of deadline is the main target of every scheduling algorithm. Earliest Deadline First (EDF), Rate Monotonic (RM), and least Laxity First are some renowned algorithms that work well in their own context. As we know, there is a very common problem Domino's effect in EDF that is generated due to overloading condition (EDF is not working well in overloading situation). Similarly, performance of RM is degraded in underloading condition. We can say that both algorithms are complements of each other. Deadline missing in both events happens because of their utilization bounding strategy. Therefore, in this paper we are proposing a new scheduling algorithm that carries through the drawback of both existing algorithms. Joint EDF-RM scheduling algorithm is implemented in global scheduler that permits task migration mechanism in between processors in the system. In order to check the improved behavior of proposed algorithm we perform simulation. Results are achieved and evaluated in terms of Success Ratio (SR), Average CPU Utilization (ECU), Failure Ratio (FR), and Maximum Tardiness parameters. In the end, the results are compared with the existing (EDF, RM, and D_R_EDF) algorithms. It has been shown that the proposed algorithm performs better during overloading condition as well in underloading condition.


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