scholarly journals Throughput Maximization for Delay-Sensitive Random Access Communication

2019 ◽  
Vol 18 (1) ◽  
pp. 709-723 ◽  
Author(s):  
Derya Malak ◽  
Howard Huang ◽  
Jeffrey G. Andrews
2021 ◽  
Author(s):  
Abiraami T V ◽  
Maithili K ◽  
Nivetha J E

In delay-sensitive IoT applications, the acquisition and processing of data from the sensor devices to the cloud-based computing environment result in higher computational cost and inefficient system. The cloud servers dedicated to performing larger tasks are found quite difficult as IoT applications collect data frequently. Hence there is a constant retrieval and updating leads to the synchronization of data in the cloud. The potential of cloud servers and virtual machines tend to lose the ability of computing larger tasks. Hence the scope of parallel computing in cloud-based IoT applications are proposed with certain parallel shared models of computation. The Parallel Random Access Machine is introduced in cloud-based IoT applications. The parallel algorithms are designed to eliminate the conflicts encountered in the proposed model. Hence Conflicts of Concurrent Read Concurrent Write PRAM and Conflicts of Concurrent Read Exclusive Write PRAM algorithms are introduced which promotes the efficiency of cloud-based IoT applications.


Author(s):  
Nizar Zorba ◽  
Christos V. Verikoukis

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.


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