An efficient QoS-based scheduling algorithm for MIMO wireless systems

2006 ◽  
Author(s):  
W. Ajib ◽  
D. Haccoun ◽  
J.-F. Frigon
Keyword(s):  
Scheduling Algorithm ◽  
Wireless Systems

scholarly journals Analytical Evaluation of the Performance of Proportional Fair Scheduling in OFDMA-Based Wireless Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Mohamed H. Ahmed ◽  
Octavia A. Dobre ◽  
Rabie K. Almatarneh
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Scheduling Algorithm ◽  
Wireless Systems ◽  
Packet Delay ◽  
Frequency Division ◽  
Analytical Evaluation ◽  
Proportional Fair ◽  
High Data ◽  
Proportional Fair Scheduling

This paper provides an analytical evaluation of the performance of proportional fair (PF) scheduling in Orthogonal Frequency-Division Multiple Access (OFDMA) wireless systems. OFDMA represents a promising multiple access scheme for transmission over wireless channels, as it combines the orthogonal frequency division multiplexing (OFDM) modulation and subcarrier allocation. On the other hand, the PF scheduling is an efficient resource allocation scheme with good fairness characteristics. Consequently, OFDMA with PF scheduling represents an attractive solution to deliver high data rate services to multiple users simultaneously with a high degree of fairness. We investigate a two-dimensional (time slot and frequency subcarrier) PF scheduling algorithm for OFDMA systems and evaluate its performance analytically and by simulations. We derive approximate closed-form expressions for the average throughput, throughput fairness index, and packet delay. Computer simulations are used for verification. The analytical results agree well with the results from simulations, which show the good accuracy of the analytical expressions.

Quality of Service in Heterogeneous Traffic Wireless Systems

2010 ◽  
pp. 71-86
Author(s):  
Nizar Zorba ◽  
Christos V. Verikoukis
Keyword(s):  
Quality Of Service ◽  
Queue Length ◽  
Scheduling Algorithm ◽  
Wireless Systems ◽  
Heterogeneous Traffic ◽  
Throughput Maximization ◽  
Trade Off ◽  
Delay Sensitive ◽  
Opportunistic Transmission

The use of real-time delay-sensitive applications in wireless systems has significantly increased during the last years. Consequently, the demand to guarantee certain Quality of Service (QoS) is a challenging issue for the system’s designers. On the other hand, the use of multiple antennas has already been included in several commercial standards, where the multibeam opportunistic transmission beamforming strategies have been proposed to improve the performance of the wireless systems. A cross-layer based dynamically tuned queue length scheduler is presented in this chapter, for the Downlink of multiuser and multiantenna WLAN systems with heterogeneous traffic requirements. An opportunistic scheduling algorithm is applied, while users from higher priority traffic classes are prioritized. A trade-off between the throughput maximization of the system and the guarantee of the QoS requirements is obtained. Therefore the length of the queue is dynamically adjusted to select the appropriate conditions based on the operator requirements.

Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

2018 ◽  
pp. 96-101
Author(s):  
Shailendra Raghuvanshi ◽  
Priyanka Dubey
Keyword(s):  
Load Balancing ◽  
Task Scheduling ◽  
Waiting Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Cloud Environment ◽  
Task Scheduling Algorithm ◽  
Machine Utilization ◽  
Independent Tasks ◽  
Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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