Multi-objective flow measurement in software defined networks (SDN) for datacenter / Hamid Tahaei
Network traffic is growing exponentially due to the ever-increasing number of users, datacentres, Internet of Things (IoT) devices, and cloud-like applications/services. Network traffic monitoring and measurement has become a vital task and a crucial requirement for Datacentre Networks (DCNs) due to...
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| Format: | Thesis |
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2018
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| Online Access: | http://studentsrepo.um.edu.my/11968/1/Hamid.pdf http://studentsrepo.um.edu.my/11968/2/Hamid.pdf http://studentsrepo.um.edu.my/11968/ |
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| Summary: | Network traffic is growing exponentially due to the ever-increasing number of users, datacentres, Internet of Things (IoT) devices, and cloud-like applications/services. Network traffic monitoring and measurement has become a vital task and a crucial requirement for Datacentre Networks (DCNs) due to providing fine-grained and timely-based traffic flow information for network applications and management. Traditional network monitoring and measurement techniques either impose extra overhead into the network, or are inaccurate. In reducing the limitations in the traditional flow management systems, the most recent measurement methods elevate the accuracy and alleviate cost issues by applying an emerging technology known as Software-Defined Networking (SDN). SDN has emerged as an evolutionary paradigm in Datacentre Networks (DCN). It enables flexibility by separating the data from the control plane and centralising network decision making, and offers innovation in the network through network programmability. Despite the multitude of efforts proposed for traffic measurement in SDN, current solutions still incur high cost and limitations. These costs are seen as a multi-objective problem as it involves different overheads in the data and control plane such as controller overhead, communication overhead, and message interaction overhead. The problem is even more complex in different network deployments, “in-band and out-of-band”. Furthermore, the distinguishing property of SDN is the centralised controller architecture, which results in significant managerial benefits. Due to several scalability and availability issues of a centralised model, such as a single point of failure and network bottleneck, the controller has been made into a decentralised model that is physically distributed. However, little effort has been devoted to measurement techniques in SDN distributed controller architecture. Moreover, the imposed costs of flow measurement in distributed controller architecture are still an issue that remains unsolved. To address the aforementioned problems, a multi-objective and cost-effective network traffic flow measurement framework was proposed for DCNs. The proposed framework implements SDN capabilities to provide a fine-grained and accurate flow measurement that effectively minimises multi-objective costs for centralised and decentralised SDN controllers in different network deployments. The proposed framework is rigorously evaluated through several experiments, including emulation and simulation. The verification of both experiments is made with current state-of-the-art algorithms. To validate the simulation results, an available dataset from a public datacentre was used. The simulation results were then verified using statistical modelling and t-tests. The results obtained from the various experiments show the effectiveness of the proposed framework and algorithm.
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