Improving the QoE of DASH over SDN: A MCDM Method with an Intelligent Approach

Ozcan, Simge Gizem; Sayıt, Müge

doi:10.1109/icin.2019.8685903

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…The experiment is formulated using the multi-criteria decision-making [MCDM] mathematical model to find a suitable solution for the loadbalancing problems involving multiple and conflicting objectives. This model works on the basic principle of the weighted sum method [WSM], i.e., the rank of the best load-balancing technique is evaluated based on the WSM of the MCDM technique [20][21][22][23][24][25].…”

Section: Experiments and Resultsmentioning

confidence: 99%

An Intelligent Server load balancing based on Multi-criteria decision-making in SDN

Vani

2023

Int. j. electr. comput. eng. syst. (Online)

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In an environment of rising internet usage, it is difficult to manage network traffic while maintaining a high quality of service. In highly trafficked networks, load balancers are crucial for ensuring the quality of service. Although different approaches to load-balancing have been proposed in traditional networks, some of them require manual reconfiguration of the device to accommodate new services due to a lack of programmability. These problems can be solved through the use of software-defined networks. This research paper presents a dynamic load-balancing algorithm for software-defined networks based on server response time and content mapping. The proposed technique dispatches requests to servers based on real-time server loads. This technique comprises three different modules, such as a request classification module, a server monitoring module, and an optimized dynamic load-balancing module using content-based routing. There are a variety of robust mathematical tools to address complex problems that have multiple objectives. Multi-Criteria Decision-Making is one of them. The performance of the proposed scheme has been validated by applying the Weighted Sum Method of the multi-criteria decision-making technique. The proposed method Server load balancing based on Multi-criteria Decision Making[SDLB-MCDM] is compared with different load-balancing schemes such as round robin, random, load-balancing scheme based on server response time [LBBSRT], and An SDN-aided mechanism for web load- balancing based on server statistics [SD-WLB]. The experimental results of SDLB-MCDM show a significant improvement of 58% when weights are equal and 50% when unequal weights are assigned to various QoS parameters in comparison with the ROUND ROBIN, RANDOM, LBBSRT and SD-WLB techniques.

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Section: Experiments and Resultsmentioning

confidence: 99%

An Intelligent Server load balancing based on Multi-criteria decision-making in SDN

Vani

2023

Int. j. electr. comput. eng. syst. (Online)

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“…The authors focus on providing QoE fairness among HAS clients, where different SVC layers can be downloaded from different servers in [55]. In [56], the SDN controller suggests the appropriate SVC layer for DASH clients to request by using a machine learning approach that takes network conditions as input. Constructing a multicast tree for each SVC layer for multicasting DASH traffic over SDN is proposed in [58].…”

Section: B Has Architectures Based On Sdn and Sandmentioning

confidence: 99%

SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming

Kalan

Sayıt

2021

IEEE Access

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Adaptive streaming over HTTP is the dominant video streaming technology for more than a decade. HTTP Adaptive Streaming (HAS) systems provide a framework which enables clients to adapt quality with respect to network fluctuations during streaming, hence to optimize the perceived quality on the client side. Recently, network assistance is integrated with HAS in order to improve underlying network conditions and to provide network-related information to the clients. The performance of HAS systems can be further enhanced if the characteristics of the streamed video are considered. In this paper, we propose a HAS system architecture where Software Defined Networking (SDN) technology is utilized for assisting clients to select the most appropriate video codec and bitrate under the constraint of current network conditions as well as routing the video packet over the appropriate paths. In the proposed architecture, layered video is used, where each additional layer improves the quality. The controller estimates the packet loss probability by taking video codec characteristics, the bitrates of the layers and network capacity into account. Based on these estimations, the controller selects the appropriate codec type and video quality for the clients and manage the network. Simulation results show that the performance of the video streaming architecture can be improved significantly when codec, quality and path selection are jointly considered, and combined with SDN flexibility and advantageous.

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Multipath transmission aware ABR algorithm for SVC HAS

Ozcan

Sayıt

2023

Computer Communications

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Improving the QoE of DASH over SDN: A MCDM Method with an Intelligent Approach

Cited by 4 publications

References 14 publications

An Intelligent Server load balancing based on Multi-criteria decision-making in SDN

An Intelligent Server load balancing based on Multi-criteria decision-making in SDN

SDN Assisted Codec, Path and Quality Selection for HTTP Adaptive Streaming

Multipath transmission aware ABR algorithm for SVC HAS

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