RDNA Balance: Load Balancing by Isolation of Elephant Flows using Strict Source Routing (original) (raw)

An OpenFlow-Based Load Balancing Strategy in SDN

Computers, Materials & Continua

In today's datacenter network, the quantity growth and complexity increment of traffic is unprecedented, which brings not only the booming of network development, but also the problem of network performance degradation, such as more chance of network congestion and serious load imbalance. Due to the dynamically changing traffic patterns, the state-of the-art approaches that do this all require forklift changes to data center networking gear. The root of problem is lack of distinct strategies for elephant and mice flows. Under this condition, it is essential to enforce accurate elephant flow detection and come up with a novel load balancing solution to alleviate the network congestion and achieve high bandwidth utilization. This paper proposed an OpenFlow-based load balancing strategy for datacenter networks that accurately detect elephant flows and enforce distinct routing schemes with different flow types so as to achieve high usage of network capacity. The prototype implemented in Mininet testbed with POX controller and verify the feasibility of our load-balancing strategy when dealing with flow confliction and network degradation. The results show the proposed strategy can adequately generate flow rules and significantly enhance the performance of the bandwidth usage compared against other solutions from the literature in terms of load balancing.

Load Balance in Data Center SDN Networks

International Journal of Electrical and Computer Engineering (IJECE), 2018

In the last two decades, networks had been changed according to the rapid changing in its requirements. The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations. The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs. Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and forwarding planes. So, due to the rapid increase in the number of applications, websites, storage space, and some of the network resources are being underutilized due to static routing mechanisms. To overcome these limitations, a Software Defined Network based Openflow Data Center network architecture is used to obtain better performance parameters and implementing traffic load balancing function. The load balancing distributes the traffic requests over the connected servers, to diminish network congestions, and reduce underutilization problem of servers. As a result, SDN is developed to afford more effective configuration, enhanced performance, and more flexibility to deal with huge network designs.

Path based load balancing for data center networks using SDN

International Journal of Electrical and Computer Engineering (IJECE), 2019

Due to the increase in the number of users on the internet and the number of applications that is available in the cloud makes Data Center Networking (DCN) has the backbone for computing. These data centre requires high operational cost and also experience the link failures and congestions often. Hence the solution is to use Software Defined Networking (SDN) based load balancer which improves the efficiency of the network by distributing the traffic across multiple paths to optimize the efficiency of the network. Traditional load balancers are very expensive and inflexible. These SDN load balancers do not require costly hardware and can be programmed, which it makes it easier to implement user-defined algorithms and load balancing strategies. In this paper, we have proposed an efficient load balancing technique by considering different parameters to maintain the load efficiently using Open FlowSwitches connected to ONOS controller.

OFLoad: An OpenFlow-Based Dynamic Load Balancing Strategy for Datacenter Networks

IEEE Transactions on Network and Service Management

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Revisiting flow-based load balancing: Stateless path selection in data center networks

Computer Networks, 2013

Hash-based load-balancing techniques are widely used to distribute the load over multiple forwarding paths and preserve the packet sequence of transport-level flows. Forcing a long-lived, i.e., elephant, flow to follow a specific path in the network is a desired mechanism in data center networks to avoid crossing hot spots. This limits the formation of bottlenecks and so improves the network use. Unfortunately, current per-flow load-balancing methods do not allow sources to deterministically force a specific path for a flow.

Software Defined Network for Data Center Using Open Flow Protocol

The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations. The current networking devices with its control and forwarding planes coupling resulted in network architectures that are not suitable for dynamic computing and storage needs. Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling the control and the forwarding planes. In this paper a programmable data center network architecture using SDN based OpenFlow protocol is demonstrated to measure some of the network performance parameters such as delay and throughput and compared them to that of traditional network. In addition, the possibility of adding a Load Balancing application is also introduced for DCN using multi-POX controllers in the SDN network. Two scenarios of DCNs using tree topology are used to implement the traditional and SDN based networks. In the first, the delay performance of DCN is reduced in the SDN based network by about 15% in comparison to that of traditional network due to OpenFlow protocol and the centralized POX controller. The use of SDN slightly increases the throughput when compared to traditional network with about 1.7 Mbit/sec.. In the second scenario; a load balancing application is implemented in tree DCN/SDN network topology using two POX controllers to handle traffic distribution among many servers. This leads to better resource utilization as a result of using SDN.

IJERT-Dynamic Load Balancing Algorithm in SDN-based Data Center Networks

International Journal of Engineering Research and Technology (IJERT), 2021

https://www.ijert.org/dynamic-load-balancing-algorithm-in-sdn-based-data-center-networks https://www.ijert.org/research/dynamic-load-balancing-algorithm-in-sdn-based-data-center-networks-IJERTV10IS030200.pdf Current networking architectures have many drawbacks that must be overcome to meet modern IT requirements. To overcome these limitations; Software Defined Networking (SDN) is taking place as the new networking approach. One of the major issues is that they use static switches that cause poor utilization of the network resources. Another issue is the slow response and delays are the main problems in current networking trend. This research proposes an implementation of a dynamic load balancing algorithm for SDN based three tier Data Center network to overcome these issues. A test has been implemented using Floodlight controller as SDN controller and Mininet software to emulate the network. Python programming language is used to define a network topology and to write the load balancing algorithm program. Finally, iPerf is used to test network performance. The network was tested before and after running the load balancing algorithm. The testing focused on Quality of Service (QoS) parameters such as throughput, bandwidth, and response time. The algorithm increased throughput with at least 50% at distribution level and with 33% at core level which also result in faster response time as well.

Traffic-aware adaptive server load balancing for software defined networks

International Journal of Electrical and Computer Engineering (IJECE), 2021

Servers in data center networks handle heterogeneous bulk loads. Load balancing, therefore, plays an important role in optimizing network bandwidth and minimizing response time. A complete knowledge of the current network status is needed to provide a stable load in the network. The process of network status catalog in a traditional network needs additional processing which increases complexity, whereas, in software defined networking, the control plane monitors the overall working of the network continuously. Hence it is decided to propose an efficient load balancing algorithm that adapts SDN. This paper proposes an efficient algorithm TA-ASLB-traffic-aware adaptive server load balancing to balance the flows to the servers in a data center network. It works based on two parameters, residual bandwidth, and server capacity. It detects the elephant flows and forwards them towards the optimal server where it can be processed quickly. It has been tested with the Mininet simulator and gave considerably better results compared to the existing server load balancing algorithms in the floodlight controller. After experimentation and analysis, it is understood that the method provides comparatively better results than the existing load balancing algorithms.

MiceTrap: Scalable Traffic Engineering of Datacenter Mice Flows using OpenFlow

IFIP/IEEE International Symposium on Integrated Network Management (IM), 2013

Datacenter network topologies are inherently built with enough redundancy to offer multiple paths between pairs of end hosts for increased flexibility and resilience. On top, traffic engineering (TE) methods are needed to utilize the abundance of bisection bandwidth efficiently. Previously proposed TE approaches differentiate between long-lived flows (elephant flows) and short-lived flows (mice flows), using dedicated traffic management techniques to handle elephant flows, while treating mice flows with baseline routing methods. We show through an example that such an approach can cause congestion to shortlived (but not necessarily less critical) flows. To overcome this, we propose MiceTrap, an OpenFlow-based TE approach targeting datacenter mice flows. MiceTrap employs scalability against the number of mice flows through flow aggregation, together with a software-configurable weighted routing algorithm that offers improved load balancing for mice flows.

Hedera: Dynamic Flow Scheduling for Data Center Networks

2010

Today's data centers offer tremendous aggregate bandwidth to clusters of tens of thousands of machines. However, because of limited port densities in even the highest-end switches, data center topologies typically consist of multi-rooted trees with many equal-cost paths between any given pair of hosts. Existing IP multipathing protocols usually rely on per-flow static hashing and can cause substantial bandwidth losses due to longterm collisions.