Load valancing Using Software Defined Networking in cloud environment

Koushika, A M; Selvi, S. Thamarai

doi:10.1109/icrtit.2014.6996164

Cited by 14 publications

(9 citation statements)

References 14 publications

(13 reference statements)

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“…However, network load was not distributed to the under loaded paths, so the fitness value is not optimized. SDN controller (Koushika and Selvi, 2014) (Lim et al, 2016) was proposed for both resource allocation and scheduling. Hadoop Cluster is deployed on Amazon EC2 to handle user's tasks with compromise of SLAs.…”

Section: Related Workmentioning

confidence: 99%

SDN-cloud: a power aware resource management system for efficient energy optimization

Swagatika

Rath

2020

IJIUS

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PurposeIn modern cloud services, resource provisioning and allocation are significant for assigning the available resources in efficient way. Resource management in cloud becomes challenging due to high energy consumption at data center (DC), virtual machine (VM) migration, high operational cost and overhead on DC.Design/methodology/approachIn this paper, the authors proposed software-defined networking (SDN)-enabled cloud for resource management to reduce energy consumption in DC. SDN-cloud comprises four phases: (1) user authentication, (2) service-level agreement (SLA) constraints, (3) cloud interceder and (4) SDN-controller.FindingsResource management is significant for reducing power consumption in CDs that is based on scheduling, VM placement, with Quality of Service (QoS) requirements.Research limitations/implicationsThe main goal is to utilize the resources energy effectively for reducing power consumption in cloud environment. This method effectively increases the user service rate and reduces the unnecessary migration process.Originality/valueAs a result, the authors show a significant reduction in energy consumption by 20 KWh as well as over 60% power consumption in the presence of 500 VMs. In future, the authors have planned to concentrate the issues on resource failure and also SLA violation rate with respect to number of resources will be decreased.

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Section: Related Workmentioning

confidence: 99%

SDN-cloud: a power aware resource management system for efficient energy optimization

Swagatika

Rath

2020

IJIUS

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“…And enjoy the possibility of management of flow. Hardware methods will require a lateral security tool [20].…”

Section: Ids Load Balancing In a Cloud Contextmentioning

confidence: 99%

“…Unlike methods based on currency, there is no need to periodically adjust specifications. Also, similar to hardware methods, there is no redundant security tools overhead [2], [19], [20]. Two methods can be used to characterize the efficiency of a distributed IDS in a cloud context.…”

Section: Ids Load Balancing In a Cloud Contextmentioning

confidence: 99%

A Collaborative Load Balancer for Network Intrusion Detection in Cloud Environments

Arian¹,

Kusedghi²,

Raahemi³

et al. 2017

JCP

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Information security and permeability in the system is a major concern for cloud computing. Cloud service providers should ensure that user information remains private from other people (external or internal). Deployment of an intrusion detection system (IDS) is a technique to protect the cloud from existing security and intrusion threats. Due to the high traffic volume and the need for flexibility and the diversity of applications in a cloud environment, a distributed IDS is used to apply traffic management, and provide scalability concurrently. The challenge is to propose a method of load balancing that distributes input traffic among IDS sensors, and optimally balance the workload on the sensors, to improve the overall performance of the IDS, with minimum degradation in quality. In this paper, a load balancing method is presented which operates based on the sensors' hardware specification and their compatibility with incoming requests, and the sensors' available resources. Dynamic request allocation to sensors is done in real time, using application layer load distribution, with no need to migrate requests or sensors, which could lead to extra overhead. The accuracy of IDS sensors in detection of attacks can be affected by the distribution of input traffic, but this shortcoming is resolved by our method. We compare the proposed method with existing algorithms in terms of load balancing and IDS functionality. The results confirm superior performance of IDS functionality in the proposed architecture.

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“…This load balance algorithm cannot objectively show the accurate real-time load condition of each path as well. [10] implements the heuristic method of load balance by classifies the best path and best servers combining with global network view of SDN. This heuristic method applies Ant Colony Optimization to decide transmission path and servers .This method collects the information to calculate the link usage and monitors the delay in links.…”

Section: Related Workmentioning

confidence: 99%