Quality of Service (QoS) Performance Analysis in a Traffic Engineering Model for Next-Generation Wireless Sensor Networks

Author:

Mazhar Tehseen1ORCID,Malik Muhammad Amir2ORCID,Mohsan Syed Agha Hassnain3ORCID,Li Yanlong34ORCID,Haq Inayatul5ORCID,Ghorashi Sara6ORCID,Karim Faten Khalid6,Mostafa Samih M.7ORCID

Affiliation:

1. Department of Computer Science, Virtual University of Pakistan, Lahore 51000, Pakistan

2. Department of Computer Science and Software Engineering, International Islamic University, Islamabad 44000, Pakistan

3. Optical Communications Laboratory, Ocean College, Zhejiang University, Zheda Road 1, Zhoushan 316021, China

4. Key Laboratory of Cognitive Radio Information Processing of the Ministry of Education, Guilin University of Electronic Technology, Guilin 541004, China

5. School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China

6. Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia

7. Computer Science Department, Faculty of Computers and Information, South Valley University, Qena 83523, Egypt

Abstract

Quality of Service (QoS) refers to techniques that function on a network to dependably execute high-priority applications and traffic reliably run high-priority applications and traffic even when the network’s capacity is limited. It is expected that data transmission over next-generation WSNs (Wireless Sensor Networks) 5G (5th generation) and beyond will increase significantly, especially for multimedia content such as video. Installing multiple IoT (Internet of Things refers to the network of devices that are all connected to each other) nodes on top of 5G networks makes the design more challenging. Maintaining a minimal level of service quality becomes more challenging as data volume and network density rise. QoS is critical in modern networks because it ensures critical performance metrics and improves end-user experience. Every client attempts to fulfill QoS access needs by selecting the optimal access device(s). Controllers will then identify optimum routes to meet clients’ core QoS needs in their core network. QoS-aware delivery is one of the most important aspects of wireless communications. Various models are proposed in the literature; however, an adaptive buffer size according to service type, priority, and incoming communication requests is required to ensure QoS-aware wireless communication. This article offers a hybrid end-to-end QoS delivery method involving customers and controllers and proposes a QoS-aware service delivery model for various types of communication with an adaptive buffer size according to the priority of the incoming service requests. For this purpose, this paper evaluates various QoS delivery models devised for service delivery in real time over IP networks. Multiple vulnerabilities are outlined that weaken QoS delivery in different models. Performance optimization is needed to ensure QoS delivery in next-generation WSN networks. This paper addresses the shortcomings of the existing service delivery models for real-time communication. An efficient queuing mechanism is adopted that assigns priorities based on input data type and queue length. This queuing mechanism ensures QoS efficiency in limited bandwidth networks and real-time traffic. The model reduces the over-provisioning of resources, delay, and packet loss ratio. The paper contributes a symmetrically-designed traffic engineering model for QoS-ensured service delivery for next-generation WSNs. A dynamic queuing mechanism that assigns priorities based on input data type and queue length is proposed to ensure QoS for wireless next-generation networks. The proposed queuing mechanism discusses topological symmetry to ensure QoS efficiency in limited bandwidth networks with real-time communication. The experimental results describe that the proposed model reduces the over-provisioning of resources, delay, and packet loss ratio.

Funder

Princess Nourah bint Abdulrahman University

Publisher

MDPI AG

Subject

Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)

Reference35 articles.

1. Potential key technologies for 6G mobile communications;Yuan;Sci. China Inf. Sci.,2020

2. Mourad, A., Yang, R., Lehne, P.H., and De La Oliva, A. (2020). A baseline roadmap for advanced wireless research beyond 5G. Electronics, 9.

3. Wong, V.W., Schober, R., Ng, D.W.K., and Wang, L.-C. (2017). Key Technologies for 5G Wireless Systems, Cambridge University Press.

4. Cisco (2020). Global Mobile Data Traffic Forecast Update, 2018–2023 White Paper, Cisco.

5. Taha, M., and Ali, A. (2013). Smart algorithm in wireless networks for video streaming based on adaptive quantization. Concurr. Comput. Pract. Exp., e7633.

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