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

Trestian, Ramona; Katrinis, Kostas; Muntean, Gabriel‐Miro

doi:10.1109/tnsm.2017.2758402

Cited by 36 publications

(13 citation statements)

References 27 publications

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“…Likewise, approaches that are used in data centers environments, such as [31], where an OpenFlow-based framework is used to realize dynamic load balancing scheme for data-center networks, cannot be easily adopted for integrated satellite and terrestrial networks. In [31], the authors prose to treat socalled elephant flows (long-lived and high traffic) differently compared to mice flows (short-lived and low traffic), in order to achieve a benefit compared to typical Equal Cost Multipath (ECMP) routing. However, even though this approach already routes traffic based on its characteristics, it is not sufficient for the specific scenario considered here, due to the high latency that needs to be taken into account on satellite links.…”

Section: Traffic Offloadingmentioning

confidence: 99%

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Niephaus

Modeker

Ghinea

2019

IEEE Trans. on Broadcast.

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Whilst broadband Internet connectivity has become highly important, providing broadband connectivity nonetheless remains a considerable challenge, particularly in rural and remote regions where the deployment of optical fibers faces economical obstacles. A promising option to address this issue is that of the most recent satellite systems, capable of providing high capacities virtually everywhere. However, compared to most terrestrial systems, satellite networks have very different link and, more importantly, latency characteristics, which often render them only barely usable for delay intolerant traffic. Thus, convergence of terrestrial and satellite networks is required, so that only certain traffic flows can be offloaded onto a supplemental satellite connection. In this work, we propose a network architecture relying on modern Software Defined Network (SDN) concepts, which enable dynamic traffic offloading in a converged satellite and terrestrial network, in order to relieve the load in a narrowband terrestrial network. We show that with limited overhead, a traffic can be offloaded, leading to an increase in the user's Quality-of-Experience (QoE).

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Section: Traffic Offloadingmentioning

confidence: 99%

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Niephaus

Modeker

Ghinea

2019

IEEE Trans. on Broadcast.

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“…But the method failed to effectively reduce the makespan. An OpenFlow-based Dynamic Load Balancing approach was developed in [16] for increasing the throughput. But the designed approach did not minimize the response time and makespan.…”

Section: Related Workmentioning

confidence: 99%

Support Vector Regression based Mapreduce Throttled Load Balancer for Data Centers

Devi *,

Chezian

2019

IJITEE

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The process of analyzing big data and other valuable information is a significant process in the cloud. Since big data processing utilizes a large number of resources for completing certain tasks. Therefore, the incoming tasks are allocated with better utilization of resources to minimize the workload across the server in the cloud. The conventional load balancing technique failed to balance the load effectively among data centers and dynamic QoS requirements of big data application. In order to improve the load balancing with maximum throughput and minimum makespan, Support Vector Regression based MapReduce Throttled Load Balancing (SVR-MTLB) technique is introduced. Initially, a large number of cloud user requests (data/file) are sent to the cloud server from different locations. After collecting the cloud user request, the SVR-MTLB technique balances the workload of the virtual machine with the help of support vector regression. The load balancer uses the index table for maintaining the virtual machines. Then, map function performs the regression analysis using optimal hyperplane and provides three resource status of the virtual machine namely overloaded, less loaded and balanced load. After finding the less loaded VM, the load balancer sends the ID of the virtual machine to the data center controller. The controller performs migration of the task from an overloaded VM to a less loaded VM at run time. This in turn assists to minimize the response time. Experimental evaluation is carried out on the factors such as throughput, makespan, migration time and response time with respect to a number of tasks. The experimental results reported that the proposed SVR-MTLB technique obtains high throughput with minimum response time, makespan as well as migration time than the state -of -the -art methods.

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“…The basic configuration for the experiment is Intel Core 3.4 GHZ CPU 8 GB RAM. iPerf tools are used to generate network traffic in mininet [21][22].…”

Section: Experimental Prototype Setupmentioning

confidence: 99%

A Scalable Load Balancing Scheme for Software-Defined Datacenter Networks based on Fuzzy Logic

Guoyan¹,

Wang²,

Zhang³

et al. 2019

Int J Performability Eng

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In order to solve the problem that traditional load balancing technology lacks sufficient scalability and flexibility, we propose a dynamic and scalable load balancing scheme based on fuzzy logic for datacenter networks using the SDN architecture characteristics of control and forwarding separation, named LBSFL. The main parameters affecting the server load performance are analyzed and used as the input variables of fuzzy logic system to evaluate the server load, and then SDN controller schedules current network requests to achieve server load balancing. Additionally, we take into account the issue of server activation and deactivation under various traffic loads in this scheme. The experimental results show that the response time of the system can be increased by about 15% compared with LBBSRT, and it can also maintain the system load between the lower (30%) and normal (50%) boundaries. The scheme can greatly improve the load balance of servers under the premise of guaranteeing the network performance.

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

Cited by 36 publications

References 27 publications

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Support Vector Regression based Mapreduce Throttled Load Balancer for Data Centers

A Scalable Load Balancing Scheme for Software-Defined Datacenter Networks based on Fuzzy Logic

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