Dynamic load-balanced path optimization in SDN-based data center networks

Lan, Yuan-Liang; Wang, Kuochen; Hsu, Yi-Huai

doi:10.1109/csndsp.2016.7573945

Cited by 42 publications

(18 citation statements)

References 8 publications

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“…In contrast, dynamic scheduling algorithms dynamically distribute flows through optimum links by considering the current state of a network. The 'least congested' algorithm is an example of a dynamic scheduling algorithm, which forwards a new request to the least loaded or congested link [11], [20], [21], [22].…”

Section: Path Selection Methodsmentioning

confidence: 99%

Performance Analysis of a Graph-Theoretic Load Balancing Method for Data Centers

AlShammari¹,

Mohammed²

2020

IJACSA

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Modern data centers can process a massive amount of data in a short time with minimal errors. Data center networks (DCNs) use equal-cost, multi-path topologies to deliver split flows across alternative paths between the core layer and hosted servers, which could lead to significant overload if path scheduling is inefficient. Thus, distributing incoming requests among these paths is crucial for providing higher throughput and protection against link or switch failures. Several approaches have been proposed for path selection, mainly relying on round-robin and least-congested methods. In this paper, we propose a loadbalancing method based on betweenness centrality to improve the overall performance of a data center in terms of throughput, delay, and energy consumption. For evaluation, we compare our method with baseline methods of different DCN topologies: fattree, DCell, and BCube. On average, the evaluation results show that our method outperforms the others. It increases throughput by 202% and 33% while reducing delay by 20% and 22%, and energy consumption by 40% and 41% compared to the roundrobin and least-congested methods, respectively.

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Section: Path Selection Methodsmentioning

confidence: 99%

Performance Analysis of a Graph-Theoretic Load Balancing Method for Data Centers

AlShammari¹,

Mohammed²

2020

IJACSA

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“…To avoid excessive single-link burden and packet loss caused by static routing due to diversified network conditions, such as burst traffic, link breakups, and device crashes, dynamic routing schemes have been proposed. Lan et al [27] proposed a dynamic routing scheme with load-balanced path configuration. Song et al [28] calculated each path utilization at the controller with link utilizations being received periodically from the data plane, and then changed the forwarding path, if necessary.…”

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence Enabled Routing in Software Defined Networking

Hwang²,

Hwang³

et al. 2020

Applied Sciences

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Software defined networking (SDN) is an emerging networking architecture that separates the control plane from the data plane and moves network management to a central point, called the controller. The controller is responsible for preparing the flow tables of each switch in the data plane. Although dynamic routing can perform rerouting in case of congestion by periodically monitoring the status of each data flow, problems concerning a suitable monitoring period duration and lack of learning ability from past experiences to avoid similar but ineffective route decisions remain unsolved. This paper presents an artificial intelligence enabled routing (AIER) mechanism with congestion avoidance in SDN, which can not only alleviate the impact of monitoring periods with dynamic routing, but also provide learning ability and superior route decisions by introducing artificial intelligence (AI) technology. We evaluate the performance of the proposed AIER mechanism on the Mininet simulator by installing three additional modules, namely, topology discovery, monitoring period, and an artificial neural network, in the control plane. The effectiveness and superiority of our proposed AIER mechanism are demonstrated by performance metrics, including average throughput, packet loss ratio, and packet delay versus data rate for different monitoring periods in the system.

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“…Lan et al 33 addressed the congestion problem using a dynamic load‐balanced path optimization (DLPO) method. This method distributes the flow across the least‐congested path by considering the highly loaded links.…”

Section: Background and Related Workmentioning

confidence: 99%

“…To summarize the related studies discussed above, we observed that Zakia and Ben Yedder 19 selected the least‐loaded path based on the shortest path algorithm, whereas Fizi and Askar 32 also considered the least congested path and packet loss rate metric to select the proper path. Moreover, Lan et al 33 and Shafiee and Ghaderi 34 selected the path based on the least‐congested metric, whereas Wang et al 35 used the same approach, but with only partial flow going into multiple flowcells, which were then distributed to the least‐loaded path. Moreover, we observed that Alenazi and Sterbenz 31 used the betweenness centrality metric as an indicator to increase the number of links and the network robustness against attacks, whereas Challa et al 30 used the same metric among the degree‐centrality metrics to select the proper paths from the available shortest paths.…”

Section: Background and Related Workmentioning

confidence: 99%

BL‐Hybrid: A graph‐theoretic approach to improving software‐defined networking‐based data center network performance

AlShammari

Alenazi

2020

Trans Emerging Tel Tech

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Existing data centers can handle a massive amount of data transmitted in a short time with minimum errors. Data center networks (DCNs) use cost‐effective, multipath topologies to distribute flows through alternative paths between core layers and hosting servers. Software‐defined networking (SDN) separates the control plane from the data plane to ease network management. To perform active load balancing among different paths, we address the challenges of load balancing in multipath DCNs. However, most DCNs' load balancing systems rely on a static approach that distributes flows among different paths sequentially, regardless of the path status. Consequently, some paths become congested, degrading the overall performance of the DCN in terms of throughput and delay. Increasing the number of requests worsens the congestion problem, causing some connections to become overwhelmed, thereby decreasing DCN efficiency. In this paper, we propose and evaluate the performance of a novel dynamic load‐balancing system named BL‐Hybrid, which uses the graph‐theoretical centrality of betweenness as a base metric for data forwarding. We perform a comprehensive comparative analysis of our proposed method relative to the round‐robin and least‐congested algorithms in different traffic scenarios, using the most popular SDN‐based DCNs, namely, fat tree, BCube, and DCell. Our evaluation results show that BL‐Hybrid outperforms the round‐robin and least‐congested schemes. It maximizes the average throughput by 4% and 11% and the average data transferred by 7% and 13%, respectively. Also, it reduces the average round‐trip time latency by 14% and 41%, respectively.

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Dynamic load-balanced path optimization in SDN-based data center networks

Cited by 42 publications

References 8 publications

Performance Analysis of a Graph-Theoretic Load Balancing Method for Data Centers

Performance Analysis of a Graph-Theoretic Load Balancing Method for Data Centers

Artificial Intelligence Enabled Routing in Software Defined Networking

BL‐Hybrid: A graph‐theoretic approach to improving software‐defined networking‐based data center network performance

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