The datacenters are need to transmit more dataflows towords huge servers are interconnected. The task of transmiting the data is give some difficult because it lead to no of issues are there is to manage work load efficiently and adaption of changing network states and arrival of new requests during transmission. For overcome this problem a dynamically load balancing technique may be implemented in software define networks to degedize the total overall response time and increasing network throughput. This approach work more efficiently when there is only one data center in the same network environment. When there is two or more datacenters in the same network region the conflict may occur which datacenter may be transmit the data flows through the servers, to avoid this type of situation we propose a priority based with round robin algorithm for selecting datacenter from the same network environment. for this first list out the datacenters from network environment and make index of the datacenters based on their priorities usually speed. And by using round robin techique for selecting the datacenter may be performed. For this we propose two algorithms for indexing the datacenters based on priorities and round robin approach for selecting datacenter. basically the dynamical load balancing technique gives high throughput on less response time. By combining the prioritised round robin algorithm with this for selecting datacenters is gives better efficient result than traditional model.

Cloud computing,Software defined network, Load balance, Data Center, Round-Robin

[1]. T.yang s Senior Member,Can tang,Jie li and Minyi Guo.A.D ynamical and Load-Balancing Flow Scheduling Approach for Big Data Centers in Cloud.IEEE Transaction on Cloud Computng. 2015
[2]. Q.Zhang, M.F.Zhani, Y.Yang et al. PRISM: Fine-Grained Resource-Aware Scheduling for MapReduce. IEEE Transactions on Cloud Computing, Vol.PP, No.99, 2015.
[3]. Z.Z.Cao, M.Kodialam and T.V.Lakshman. Joint Static and Dynamic Traffic Scheduling in Data Center Networks. in Proceedings of IEEE INFOCOM 2014, pp.2445-2553.
[4]. F.Zhang, J.Cao, K.Hwang et al. Adaptive Workflow Scheduling on Cloud Computing Platforms with Iterative Ordinal Optimization. IEEE Transactions on Cloud Computing, Vol.PP, No.99, 2014.
[5]. R.M.Ramos, M.Martinello and E.C.Rothenberg. SlickFlow: Resilient source routing in Data Center Networks unlocked by OpenFlow. Proc. of IEEE 38th Conference on Local Computer Networks (LCN), 2013, pp.606-613.
[6]. K.Greene, TR10: Software-Defined Networking, MIT Technology Review, Retrieved Oct. 7, 2011
[7].T.Feng,B.JunandH.Y.Hu.OpenRouter:OpenFlowextensionand implementation based on a commercial router. Proceedings of 19th IEEE International Conference on Network Protocols (ICNP 2011), 2011, pp.141-142.
[8].M.Schlansker,Y.Turner,J.Tourrilhes,andA.Karp,EnsembleRouting for Datacenter Networks, In ACM ANCS, La Jolla, CA, 2010.
[9]. N.Handigol, S.Seetharaman, M.Flajslik, N.McKeown, and R.Johari, Plug-n-Serve: Load-balancing web traffic using OpenFlow, Demo at ACM SIGCOMM, Aug. 2009.