An adaptive load monitoring solution for logically centralized SDN controller

Shah, Syed Asif Raza; Bae, Sejong; Jaikar, Amol; Noh, S. Y.

doi:10.1109/apnoms.2016.7737207

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…To achieve this, it is required to be able to send an automatic data request for immediate inquiries, including data integrity to inference in cloud storage to verify the integrity of a third party for security purposes [11][12][13], when an additional request should be sent out to all networks. We will implement and experiment to measure the network response time with accuracy in this case, as well as how accurately the proposed method can provide the best optimized data sampling at large scale using big data in the cloud server, which may be located in a centralized location, in the context of software defined network (SDN) infrastructure with fault tolerant mechanisms [14,15].…”

Section: Discussionmentioning

confidence: 99%

An Enhanced Inference Algorithm for Data Sampling Efficiency and Accuracy Using Periodic Beacons and Optimization

Kang

Fahd²,

Venkatraman³

2019

BDCC

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Transferring data from a sensor or monitoring device in electronic health, vehicular informatics, or Internet of Things (IoT) networks has had the enduring challenge of improving data accuracy with relative efficiency. Previous works have proposed the use of an inference system at the sensor device to minimize the data transfer frequency as well as the size of data to save network usage and battery resources. This has been implemented using various algorithms in sampling and inference, with a tradeoff between accuracy and efficiency. This paper proposes to enhance the accuracy without compromising efficiency by introducing new algorithms in sampling through a hybrid inference method. The experimental results show that accuracy can be significantly improved, whilst the efficiency is not diminished. These algorithms will contribute to saving operation and maintenance costs in data sampling, where resources of computational and battery are constrained and limited, such as in wireless personal area networks emerged with IoT networks.

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Section: Discussionmentioning

confidence: 99%

An Enhanced Inference Algorithm for Data Sampling Efficiency and Accuracy Using Periodic Beacons and Optimization

Kang

Fahd²,

Venkatraman³

2019

BDCC

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“…The collection part is the most basic and important part pf the monitoring framework because its efficiency can affect the monitoring accuracy to a great extent. Generally, the monitoring frameworks can be classified into two kinds: distributed frameworks [7] and centralized frameworks [8]. Distributed frameworks are often applied to very-large-scale networks and their deployment is rather complex.…”

Section: Related Workmentioning

confidence: 99%

FlexMonitor: A Flexible Monitoring Framework in SDN

Wang

2018

Symmetry

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Efficient network monitoring is an important basis work for network management. Generally, many management applications require accurate and timely statistics about network states at different aggregation levels at low cost, such as malicious traffic detection, traffic engineering, etc. Moreover, the network environment to be monitored is constantly changing and expanding, including not only the data center for cloud computing but also the Internet of Things (IoT) for smart urban sensing, which requires the intensive study of more fine-grained network monitoring. As is well known, the development of efficient network monitoring approaches greatly relies on a flexible monitoring framework. Software defined network (SDN) can provide dramatic advantages for network management by separating the control plane and data plane. Therefore, it is a good choice to design a flexible monitoring framework based on the advantages of SDN. However, most research works only take advantage of the centralized control feature in SDN, which leads to limited improvement in the flexibility of the monitoring framework. This paper proposes a flexible monitoring framework named FlexMonitor, which can realize greater flexibility based on not only the centralized control feature, but also the high programmability in the controller and the limited programmability in the openflow switches in SDN. There are two key parts in FlexMonitor, namely the monitoring strategy deployment part and the monitoring data collection part, which can enrich the deployment methods of monitoring strategies and increase the kinds of monitoring data sources, respectively. Based on the NetMagic platform, this monitoring framework was implemented and evaluated through realizing a distributed denial of service (DDoS) detection approach. The experimental results show that the proposed DDoS detection approach has a better detection performance compared with other related approaches as well as indirectly show that FlexMonitor can flexibly support a variety of efficient monitoring approaches.

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“…Because the analysis will be done according to the collected statistics. Monitoring approaches can be grouped into two types: distributed frameworks (Phan et al, 2017) and centralized frameworks (Shah et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Yazılım Tanımlı Ağlarda Ölçeklenebilir ve Verimli Bir Port Tabanlı Adaptif Kaynak İzleme Yaklaşımı

ÖZER

OKUMUŞ

2022

Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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The need for communication tools is increasing from the past to the present, therefore the tools and methods in network technologies are evolving. Depending on this development, network scale and complexity increase and the limitations of traditional network technology are surfaced. Software-defined Network (SDN) provides a variety of opportunities for the management and optimization of these challenges. Network resource monitoring is very important for providing information to network applications. This study introduces an adaptive port-level bandwidth monitoring method designed for SDN networks. The proposed approach uses a polling-based monitoring paradigm. There is a trade-off between measurement accuracy and monitoring overhead. With this adaptive method, it is aimed to decrease the overhead while maintaining an acceptable level of accuracy of the measurements and also to use network resources more efficiently. The proposed adaptive monitoring approach has 46% less overhead than the periodic polling method and 6.7% less overhead than the PayLess approach. At the same time, this approach is 5.4% more accurate than the periodic polling approach.

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An adaptive load monitoring solution for logically centralized SDN controller

Cited by 7 publications

References 8 publications

An Enhanced Inference Algorithm for Data Sampling Efficiency and Accuracy Using Periodic Beacons and Optimization

An Enhanced Inference Algorithm for Data Sampling Efficiency and Accuracy Using Periodic Beacons and Optimization

FlexMonitor: A Flexible Monitoring Framework in SDN

Yazılım Tanımlı Ağlarda Ölçeklenebilir ve Verimli Bir Port Tabanlı Adaptif Kaynak İzleme Yaklaşımı

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