• Title/Summary/Keyword: WRR

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KOINONIA High-Rate WPAN Channel Time Allocation and CAC Algorithm for Multimedia Transmission (KOINONIA 고속 WPAN의 멀티미디어 전송을 위한 채널 타임 할당 및 CAC 알고리즘)

  • Park Jong-Ho;Lee Tae-Jin;June Sun-Do;Youn Kyu-Jung;Won Yun-Jae;Cho Jin-Woong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.5A
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    • pp.417-425
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    • 2005
  • KOINONIA is high-rate Wireless Personal Area Network (WPAN) technology, and is developed for multimedia traffic transmission in personal area. A KOINONIA piconet is a collection of one or more associated slaves under a single master. Efficient scheduling of a master for the traffic of slaves is essential to use channel effectively and to guarantee QoS of multimedia traffic. We propose a new scheduling algorithm to allocate channel time at desired intervals regardless of superframe length, and a Connection Admission Control(CAC) algorithm to regulate the number of traffics in a piconet. Our proposed algorithms have been shown to save channel time and to meet QoS requirements compared to the conventional weighted round-robin algorithm.

On Addressing Network Synchronization in Object Tracking with Multi-modal Sensors

  • Jung, Sang-Kil;Lee, Jin-Seok;Hong, Sang-Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.4
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    • pp.344-365
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    • 2009
  • The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

An open Scheduling Framework for QoS resource management in the Internet of Things

  • Jing, Weipeng;Miao, Qiucheng;Chen, Guangsheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.9
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    • pp.4103-4121
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    • 2018
  • Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

A Modified-DWRR Cell Scheduling Algorithm improved the QoS of Delay (지연 특성을 개선한 Modified-DWRR 셀 스케쥴링 알고리즘)

  • Gwak, Ji-Yeong;Nam, Ji-Seung
    • The KIPS Transactions:PartC
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    • v.8C no.6
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    • pp.805-814
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    • 2001
  • In this paper, we propose a new scheduling algorithm that guarantees the delay property of real-time traffic, not considered in previous DWRR(Dynamic Weighted Round Robin) algorithm and also transmits non-real-time traffic efficiently. The proposed scheduling algorithm is a variation of DWRR algorithm to guarantee the delay property of real-time traffic by adding cell transmission method based on delay priority. It also uses the threshold to prevent the cell loss of non-real-time traffic due to cell transmission method based on delay priority. Proposed scheduling algorithm may increase some complexity over conventional DWRR scheme because of cell transmission method based on delay priority. However, the consideration of delay priority can minimize cell delay and require less size of temporary buffer. Also, the results of our performance study shows that the proposed scheduling algorithm has better performance than conventional DWRR scheme due to reliable ABR service and congestion avoidance capacity.

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