Performance analysis of opportunistic scheduling in wireless multimedia and data networks using stochastic network calculus

• Published in: Multimedia tools and applications Vol. 74; no. 1; pp. 25 - 41
• Main Authors: Wang, Gaocai, Wang, Nao, Yu, Xin, Li, Taoshen, Zhang, Zhenzhen
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.01.2015; Springer Nature B.V
• Subjects: Algorithms; Analysis; Calculus; Code Division Multiple Access; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Mathematical models; Multimedia; Multimedia communications; Multimedia Information Systems; Networks; Quality of service; Queuing theory; Scheduling; Scheduling algorithms; Special Purpose and Application-Based Systems; Stochastic models; Stochasticity; Studies; Telecommunications systems; Traffic engineering; Traffic flow; Wireless communication; Wireless networks; Opportunistic scheduling; Wireless multimedia and data networks; Performance analysis; Stochastic network calculus; MPF scheduling algorithm
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-013-1448-2

In this paper, performance of opportunistic scheduling (OS) in wireless multimedia and data networks is studied based on popular stochastic network calculus (SNC). For this purpose, we firstly bound traffic arrival process by using exponentially bounded burstiness (EBB) traffic model of SNC and establish stochastic arrival curve. Then we propose a new wireless opportunistic scheduling-Modified Proportional Fairness (MPF) scheduling algorithm which can provide better fairness for input traffic to guarantee quality of service (QoS) performance and obtain stochastic service curve. Compared with traditional Round-Robin (RR), Greedy (GY) and Proportional Fairness (PF) scheduling algorithms, MPF scheduling algorithm can get better equilibrium between delay and backlog. More specifically, our MPF scheduling algorithm can provide better fairness and QoS by introducing a weighted factor to identify user’s priority. On the other hand, the framework based on SNC also provides higher utilization of network resource and statistical meanings for delay and backlog, so MPF can schedule input traffic effectively as long as the input traffic satisfies some bounded conditions. The numerical results show that our stochastic model and MPF scheduling algorithm can provide better QoS performance.