scholarly journals Slice Management for Quality of Service Differentiation in Wireless Network Slicing

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2745 ◽  
Author(s):  
Namwon An ◽  
Yonggang Kim ◽  
Juman Park ◽  
Dae-Hoon Kwon ◽  
Hyuk Lim
Keyword(s):  
Quality Of Service ◽  
Random Network ◽  
Service Differentiation ◽  
Traffic Flows ◽  
Average Throughput ◽  
Average Delay ◽  
Network Slicing ◽  
Management Scheme ◽  
Simulation Results

Network slicing is a technology that virtualizes a single infrastructure into multiple logical networks (called slices) where resources or virtualized functions can be flexibly configured by demands of applications to satisfy their quality of service (QoS) requirements. Generally, to provide the guaranteed QoS in applications, resources of slices are isolated. In wired networks, this resource isolation is enabled by allocating dedicated data bandwidths to slices. However, in wireless networks, resource isolation may be challenging because the interference between links affects the actual bandwidths of slices and degrades their QoS. In this paper, we propose a slice management scheme that mitigates the interference imposed on each slice according to their priorities by determining routes of flows with a different routing policy. Traffic flows in the slice with the highest priority are routed into shortest paths. In each lower-priority slice, the routing of traffic flows is conducted while minimizing a weighted summation of interference to other slices. Since higher-priority slices have higher interference weights, they receive lower interference from other slices. As a result, the QoS of slices is differentiated according to their priorities while the interference imposed on slices is reduced. We compared the proposed slice management scheme with a naïve slice management (NSM) method that differentiates QoS among slices by priority queuing. We conducted some simulations and the simulation results show that our proposed management scheme not only differentiates the QoS of slices according to their priorities but also enhances the average throughput and delay performance of slices remarkably compared to that of the NSM method. The simulations were conducted in grid network topologies with 16 and 100 nodes and a random network topology with 200 nodes. Simulation results indicate that the proposed slice management increased the average throughput of slices up to 6%, 13%, and 7% and reduced the average delay of slices up to 14%, 15%, and 11% in comparison with the NSM method.

Distributed TXOP Allocation Scheme in IEEE 802.11e Wireless LANs

2013 ◽  
Vol 284-287 ◽  
pp. 2904-2907
Author(s):  
Sunmyeng Kim
Keyword(s):  
Quality Of Service ◽  
Wireless Lans ◽  
Service Differentiation ◽  
Ieee 802.11E ◽  
Multimedia Traffic ◽  
Allocation Scheme ◽  
Delay Bound ◽  
Transmission Opportunity ◽  
Simulation Results

Multimedia traffic is expected to be one of the most important traffic types in wireless LANs. However, multimedia traffic is very sensitive to delay so that the traffic has to be transmitted to receivers within its delay bound. The IEEE 802.11e EDCA (Enhanced Distributed Channel Access) defines a TXOP (Transmission Opportunity) parameter to provide service differentiation and QoS (Quality of Service) of the traffic. A station can continuously transmit multiple packets for the duration of a TXOP. When stations support multimedia applications with different QoS requirements, fairness problem occurs. In order to alleviate the fairness problem, we propose a distributed TXOP allocation scheme based on the delay bound. In the proposed scheme, a station checks the delay bound of each data packet in the queue, and allocates its TXOP value to guarantee the delay bounds of all the packets in the queue. Simulation results show that the proposed scheme outperforms other TXOP allocation schemes.

scholarly journals On the Design of Efficient Hierarchic Architecture for Software Defined Vehicular Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1400
Author(s):  
Muhammad Adnan ◽  
Jawaid Iqbal ◽  
Abdul Waheed ◽  
Noor Ul Amin ◽  
Mahdi Zareei ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Traffic Management ◽  
Vehicular Networks ◽  
Scheduling Algorithm ◽  
Main Research ◽  
First Come First Serve ◽  
Computing Framework ◽  
Simulation Results

Modern vehicles are equipped with various sensors, onboard units, and devices such as Application Unit (AU) that support routing and communication. In VANETs, traffic management and Quality of Service (QoS) are the main research dimensions to be considered while designing VANETs architectures. To cope with the issues of QoS faced by the VANETs, we design an efficient SDN-based architecture where we focus on the QoS of VANETs. In this paper, QoS is achieved by a priority-based scheduling algorithm in which we prioritize traffic flow messages in the safety queue and non-safety queue. In the safety queue, the messages are prioritized based on deadline and size using the New Deadline and Size of data method (NDS) with constrained location and deadline. In contrast, the non-safety queue is prioritized based on First Come First Serve (FCFS) method. For the simulation of our proposed scheduling algorithm, we use a well-known cloud computing framework CloudSim toolkit. The simulation results of safety messages show better performance than non-safety messages in terms of execution time.

Quality-of-service differentiation and fairness in optical burst-switched networks

2002 ◽  
Author(s):  
Fabrice Poppe ◽  
Koenraad Laevens ◽  
Herman Michiel ◽  
Serge Molenaar
Keyword(s):  
Quality Of Service ◽  
Service Differentiation ◽  
Switched Networks ◽  
Optical Burst

scholarly journals Introducing a Mobility Access Category for IEEE 802.11e

2020 ◽  
Vol 9 (5) ◽  
pp. 1610-1614
Keyword(s):  
Quality Of Service ◽  
Wireless Network ◽  
Ieee 802.11E ◽  
Network Simulator ◽  
Mobile Nodes ◽  
Mobile Stations ◽  
Simulation Scenario ◽  
Simulation Results ◽  
The Impact

With traffic increase in a wireless network beyond its capacity and as the number of connected devices continue to grow, the quality of service (QoS) degrades. In this paper we study the impact of mobility on throughput in the case of an infrastructure wireless network using IEEE 802.11 Wi-Fi standard. Since we found in the literature that the mobility of stations can have an impact on the quality of service, we try to remedy to this by implementing a new access category reserved for mobile stations. First we compare the throughput between static and mobile nodes, both connected to a QoS station. Then we propose our new model that consists of adding a new access category used by mobile nodes regardless of their traffic category. The study was made by simulating different scenarios using Network Simulator-3 (NS-3). We found that the throughput may vary depending on the simulation scenario. The simulation results show that with the proposed solution the mobile nodes can have a better throughput.

Application of Fuzzy Logic for Slice QoS in 5G Networks

2021 ◽  
Vol 12 (2) ◽  
pp. 18-35
Author(s):  
Phudit Ampririt ◽  
Ermioni Qafzezi ◽  
Kevin Bylykbashi ◽  
Makoto Ikeda ◽  
Keita Matsuo ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Additional Parameter ◽  
Software Defined Network ◽  
5G Networks ◽  
Network Slicing ◽  
Fifth Generation ◽  
5G Network ◽  
Simulation Results ◽  
Qos Performance

The fifth generation (5G) network is expected to be flexible to satisfy quality of service (QoS) requirements, and the software-defined network (SDN) with network slicing will be a good approach for admission control. In this paper, the authors present and compare two fuzzy-based schemes to evaluate the QoS (FSQoS). They call these schemes FSQoS1 and FSQoS2. The FSQoS1 considers three parameters: slice throughput (ST), slice delay (SD), and slice loss (SL). In FSQoS2, they consider as an additional parameter the slice reliability (SR). So, FSQoS2 has four input parameters. They carried out simulations for evaluating the performance of the proposed schemes. From simulation results, they conclude that the considered parameters have different effects on the QoS performance. The FSQoS2 is more complex than FSQoS1, but it has a better performance for evaluating QoS. When ST and SR are increasing, the QoS parameter is increased. But, when SD and SL are increasing, the QoS is decreased. When ST is 0.1, SD is 0.1, SL is 0.1, and the QoS is increased by 32.02% when SR is increased from 0.3 to 0.8.

scholarly journals A Lightweight Slice-Based Quality of Service Manager for IoT

IoT ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 49-75
Author(s):  
Antonio Oliveira-Jr ◽  
Kleber Cardoso ◽  
Filipe Sousa ◽  
Waldir Moreira
Keyword(s):  
Quality Of Service ◽  
Industry 4.0 ◽  
Farming Systems ◽  
Smart Manufacturing ◽  
Network Slicing ◽  
Wide Range ◽  
The Internet Of Things ◽  
Service Manager ◽  
Digital Farming

Industry 4.0 and digital farming rely on modern communication and computation technologies such as the Internet of Things (IoT) to provide smart manufacturing and farming systems. Having in mind a scenario with a high number of heterogeneous connected devices, with varying technologies and characteristics, the deployment of Industry 4.0 and digital farming solutions faces innovative challenges in different domains (e.g., communications, security, quality of service). Concepts such as network slicing and Software-Defined Networking (SDN) provide the means for faster, simpler, scalable and flexible solutions in order to serve a wide range of applications with different Quality-of-Service (QoS) requirements. Hence, this paper proposes a lightweight slice-based QoS manager for non-3GPP IoT focusing on different use cases and their varying requirements and characteristics. Our focus in this work is on non-3GPP IoT unlicensed wireless technologies and not specifically the end-to-end network slice perspective as described in 5G standards. We implemented and evaluated different QoS models in distinct scenarios in a real experimental environment in order to illustrate the potential of the proposed solution.

scholarly journals A New Resource Management Scheme for Ad Hoc and Sensor Networks

2005 ◽  
Vol 1 (1) ◽  
pp. 9 ◽  
Author(s):  
Ronan De Renesse ◽  
Vasilis Friderikos ◽  
Hamid Aghvami
Keyword(s):  
Quality Of Service ◽  
Resource Management ◽  
Sensor Networks ◽  
Ad Hoc ◽  
Recent Literature ◽  
Best Effort ◽  
Network Layer ◽  
Management Scheme ◽  
Real Challenge

Ad hoc and sensor networks have received tremendous attention in the recent literature due to its unpredictable nature and its many applications. Imposing any kind of reliability in such networks represents a real challenge. In this paper, we propose a new resource management scheme which virtually reserves and releases resources at the network layer when necessary. Results show that our scheme distributes resources efficiently between Best Effort and Quality of Service traffics even when congestion arises.

scholarly journals R-learning-based team game model for Internet of things quality-of-service control scheme

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668755 ◽  
Author(s):  
Sungwook Kim
Keyword(s):  
Quality Of Service ◽  
Internet Of Things ◽  
Power Control ◽  
Service Management ◽  
Simulation Analysis ◽  
Learning Algorithm ◽  
Control Approach ◽  
Management Scheme ◽  
Internet Of Things Technology

In modern times, it has been observed that Internet of things technology makes it possible for connecting various smart objects together through the Internet. For the effective Internet of things management, it is necessary to design and develop service models that ensure appropriate level of quality-of-service. Therefore, the design of quality-of-service management schemes has been a hot research issue. In this work, we formulate a new quality-of-service management scheme based on the IoT system power control algorithm. Using the emerging and largely unexplored concept of the R-learning algorithm and docitive paradigm, system agents can teach other agents how to adjust their power levels while reducing computation complexity and speeding up the learning process. Therefore, our proposed power control approach can provide the ability to practically respond to current Internet of things system conditions and suitable for real wireless communication operations. Finally, we validate the introduced concept and confirm the effectiveness of the proposed scheme in comparison with the existing schemes through extensive simulation analysis.

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