vpn stipulation based vibrant

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VPN STIPULATION BASED VIBRANT

DEVELOPMENT

S.M.KRISHNA GANESH1

Lecturer, Department of Computer Science and Engineering,

St.Joseph College of Engineering and Technology, [email protected]

A.SILES BALASINGH2

Lecturer, Department of Computer Science and Engineering,St.Joseph College of Engineering and Technology, India

[email protected]

Abstract:A virtual private network (VPN) is a private network that makes use of a public network (such as the Internet),while maintaining security and privacy through encryption and security procedures [1]. VPN's give companiesan alternative to leasing an expensive, dedicated private connection from one office to another. Many businesses

are using VPN on their servers to allow their employees to connect to their server from home. VPN serviceproviders provide new services with Quality of Service (QoS) guarantees are also resilient to failures. The mainobjective is to find the optimal path a with scheduled routing to improve the QoS, by maintaining routingalgorithm based on shortest path and scalable scheduling of packets being routed which provides a minimizedbandwidth and guaranteed delay. An algorithm for optimal shortest path with scheduling is described withsimulation results and compared with other algorithms

Keywords: QoS, Scalable Scheduling, optimal path, Encryption, Routing.

1. IntroductionA virtual private network (VPN) is a private data network that makes use of the public Internet [2] to maintainprivacy through the use of IP tunneling technology and network security protocols. VPNs can be regarded as a

replacement of the expensive private leased lines. The main purpose of a VPN is to provide a company securecommunication among multiple sites through the shared Internet. More detailed descriptions of VPNs can be

found in [3]. To support a VPN, a service provider has to allocate predetermined paths to connect amongcustomer sites reservation while minimizing the total bandwidth used becomes an important problem to theservice provider.

Figure 1 shows Virtual Private Network.

The simulated Environment includes the ingress and Egress Bandwidth which seem to be synchronous. Theingress bandwidth of an endpoint is the capacity required for aggregating the incoming traffic to the endpoint

Krishna Ganesh S.M et al. / International Journal of Engineering Science and Technology (IJEST)

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from other endpoints [4]. The egress bandwidth is the capacity required for aggregating the outgoing trafficfrom the endpoint into the network. The case is that for asymmetric bandwidth with synchronization. The majorissue with this is to reduce the traffic among the VPN end points. The figure 2 shows the over all work flow.The proposed work describes a new VPN Stipulation algorithm called K-Optimized Route VPN Stipulation

Algorithm (KORPA) and Efficient Schedule Time Scheduling [5] to address this issue.

Figure 2 Diagram of Algorithmic approach

2. Proposed Algorithm

2. K-Optimized Route VPN Stipulation Algorithm2.1 Phase 1 for K-path calculation

The proposed algorithm KOPR tries to find the cost of the VPN endpoints using the asymmetric bandwidthbased on the pseudo code

Pseudo code for Proposed K-optimal path algorithm

1. Vnode =

2. For each V N

3. Loop4 Tv = KOPR (G, V)5. Compute RS (PT, V)6. Ed loop7. if (Cost (V) > = optimal)

8. Reject Link PT9. else10 for each link compute KOPRA(G,V)11 End if12 End if13 Repeat for BFS (g,v) for comparison14 End

The Network managed by service providers ismodeled

The VPN setup request describing the VPN

service requested by customers is modeled

Efficient Schedule Time Scheduling of Packets

Transmitted

The K optimized Route VPN StipulationAlgorithm


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The network backbone is modeled by an undirected graph G= (N, L), whereNandL are the set of routers andthe set of links, respectively. Let n and m denote the cardinality of N, respectively. Let B be the residualbandwidth of links on L and the amount of residual bandwidth on link l (lL) is denoted by B(l). A subset =

{ar1, ar2arp} N) is the set of VPN access routers. Each endpoint eiof a VPN gains access to VPN serviceby connecting to a specific VPN access routerariinAR. In other words, for each endpoint of a VPN, there is acorresponding VPN.

2.2 Phase 2 EST Development

Each VPN in the active router environment contains two types of agents on the active routers: queue agents, andcontrol agents [6]. VPN endpoints control a delay of sessions according to the maximum and minimum delaybounds specified by the clients. Control agents control the end-to-end delay of a VPN by monitoring the delay

of a session on a routing path. However the EST scheduling one such active scheduling algorithm, hereproposed does not require any control at the VPN endpoints. In figure 3 we adjust the delay of the packetsrouted and is calculated based on the Schedule time and transmitted to meet the QoS parameters [7]

Figure 3 shows the EST scheduling frame work.

Pseudo code for efficient agenda Time

1.Let Pn be Packet transmitted2. Transmission Time Tt > Packet Deadline Time (d)3. Packet Deadline Time - Packet Time gives the Schedule Time4. The Schedule time left out is added to Previous transmission Time5. If delay(Packets) >= Threshold then packet drop6.Then Count++7. When the packet is dropped then retransmit the packet.

The delay of packet remitted is compute with the rejection ratio as below

Number of dropped packetRejection ratio = * 100

Total no of packets Transmitted

The rejection ratio % seems to be reduced in our scheduling algorithm compared to Static Priority. Thusthe delay of the packet transmitted is reduced effectively with improves QoS in Virtual Private Network.

3. Environment to be replicatedConsider the simulated environment in which the number of packets to be routed Pn, is given via VPN

end points based on which the EST is implemented. The packets routed seem to be 20 packets then calculate the


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Schedule time in routing. The routed are adjusted dynamically to reduce the delay. The Schedule time is addedto the transmission time which could result in improved bandwidth utilization and efficiency. The delay andSchedule time determines the efficiency of routing.

Figure 4 shows the simulated Environment model

Thus the above figure 4 is simulated environment as the VPN network and with sufficient Bandwidth and delay

for efficient packet routing among the VPN Endpoints.

4. Experimental Results4.1 Designed and developed KORPA Vs BFS and Steiner Routing

We compared the Stipulation cost (that is, the total bandwidth reserved on links of the VPN tree) and

the running times of the algorithms for the symmetric as well as the asymmetric bandwidth models. In the study,we examined the effect of varying the following two parameters on Stipulation cost: 1. VPN endpoints 2.Number of VPN nodes. Most of the plots in the following subsections were generated by running eachexperiment five times (with different random networks) and using the average of the cost/execution times forthe five repetitions as the final result.

4.2 Replication 1: (Network Size)

Graph 1 depicts the Stipulation cost of the BFS and Steiner tree algorithms as the number ofnetwork nodes is increased from 100 to 1000. VPN endpoints are assigned equal ingress/egress bandwidth. TheKORPA algorithm is optimal and efficient for the symmetric case than compared to Steiner and BFS algorithm.Thus KORPA algorithm provides low cost of their shortest path than BFS and Steiner.


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Graph 1 shows KORPA Vs BFS, Steiner

The table 1 shows the cost of KORPA algorithm with BFS and Steiner which shows the proposed algorithm hasthe lowest cost compare to others.

KOSR BFS STEINER

27 60 100

49 80 131

75 100 168

105 140 202

130 163 226

140 207 258

177 228 284

187 245 300

219 301 333Table 1 shows the Cost of KORPA Vs BFS, Steiner

Graph 2 depicts the comparative study of EST Vs Static scheduling algorithm

Com parision of Shortest Path Algorithm s

0

50

100

150

200

250

300

350

100 300 500 700 900

No o f Nodes

Cost

KOSR

BFS

STEINER

Com parative gr aph EST vs Static Pr ioir ty

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9

No o f Nodes

Delay

Static Prio

Scheduling

EST

Scheduling


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The table 2 shows the comparative study of proposed scheduling algorithm (EST) with Static Priority

Static PriorityScheduling

EST Scheduling

0 0

21 12

34 20

40 26

50 37

60 42

67 53

80 72

93 83

Table 2 shows the efficiency of EST Vs static priority

Conclusion and Future Work

We have presented a new scheduling scheme called Efficient Schedule Time scheduling. In this paperVirtual private networks consisting of VPN endpoints with their K-optimal path have been implemented in NS2.The Active VPN Endpoints reconfigure the delays of packet routed dynamically in their shortest path thus

minimizing the packet loss and delay compared to the existing static algorithm. In future there are still a numberof issues relating to VPN routing. For example: (1) The problem of fitting failure of lowest cost path andrestoration mechanisms (2) Stipulation for the Asymmetric VPN nodes in VPN Environment.

Acknowledgments

First of all we thank the almighty for giving us the knowledge and courage to complete the research work

successfully. We express our gratitude to our respected Rev.Fr.Dr.Arulraj Founder, DMI Group of institutions,East Africa and India, Dr.T.X.A.Ananth, Director(International Operations), DMI group of institutions, East

Africa and India,Mr.Ignatius Herman, Director(Academic),DMI group of institutions, East Africa and India andDr.V.KrishnanPh.D,Principal,DMI.St.Joseph College of Engg & Technology, Tanzania for allowing us to dothe research work internally. Also we acknowledge the support provided by Rev.Sr.Fatima Mary, Vice Principal(Administration), DMI.St.Joseph College of Engg & Technology, Tanzania and Mr.N.Ressel Raj, Vice Principal

(Academic), DMI.St.Joseph College of Engg & Technology, Tanzania. We thank our friends and collegues fortheir support and encouragement.

References

[1] Rocketfuel project(200), Computer Science and Engineering, Univ. of Washington. and HIST algorithm.6 April vol 12 pp.123-140[2] H. Liang et al,(2002) MinimalCost Design of Virtual Private Networks, inIEEE Proceedings of the CCECE 02 , may 2002, vol.3,

pp. 1610 1615.[3] T. Erlebach et al,(2004), Optimal Bandwidth Reservation in Hose-Model VPNs with Multi-Path Routing, INFOCOM,

vol.4,pp.2275-2282[4] N. G. Duffield et al(1999), A Flexible Model for Resource Management in Virtual Private Networks,In Proc. ACM SIGCOMM, pp.

95-108.

[5] A. Gupta et al (2001), Stipulation a Virtual Private Network: A Network Design Problem for Multicommodity Flow, In Proc. ACMSTOC, pp. 389-398.

[6] A. Kumar et al, (2002), Algorithms for Stipulation Virtual Private Networks in the Hose Model, IEEE/ACM Trans. on Networking,vol.10, issue 4, pp. 565-578.

[7] A. Juttner et al(2003), On Bandwidth Efficiency of the Hose Resource Management Model in Virtual Private Networks, In Proc.INFOCOM,vol 1, pp.386-395

[8] I. Matta et al,(1999), QDMR: An Efficient QoS Dependent Multicast Routing Algorithm, In Journal of Communications andNetworks, Real-time Technology and Applications Symposium, pp. 213-222.

[9] P. P. Mishra, et al (2000), Capacity Management and Routing Policies for Voice over IP Traffic, IEEE Network, vol. 14, no. 2, pp.20-27, pp. 20-27.

[10] B. M. Waxman (1988), Routing of Multipoint Connection, IEEE Journal on Selected Areas in Communications, vol. 6, issue 9, pp.1617-1622.

[11] Zhanfeng Jia et al (2006), Heuristic Methods for Delay Constrained Efficient Cost Routing Using K-Shortest-Paths, IEEETRANSACTIONS On Automatic control, vol. 51, no. 4, pp.707-712

[12] Li-Der Chout Mao Yuan Hong (2006), Design and Implementation of Two Level VPN Service Stipulation Systems over MPLSNetworks,IEEE International Symposium on Computer Networks, pp 42-48.


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THE AUTHORS

Mr. S.M.Krishna Ganesh has completed Masters of Technology Degreein Computer Scienceand Engineering at Kalasalingam University in the year 2009, Tamil Nadu, India.He is currentlyworking as Lecturer in St. Joseph College of Engineering and Technology,Dar Es Salaam,

Tanzania, East Africa. He has 8 publications to his credit. He has guided more than 20 projectsto final year B.E/B.Tech students with good industry and teaching experience. His areas of

interests are Image Processing, Computer Networks, Neural networks and Bioinformatics.

Mr. A.Siles Balasingh working as Lecturer in St. Joseph College of Engineering andTechnology, Dar Es Salaam, Tanzania, East Africa. He has guided 12 projects for B.E finalyear students. His areas of interests are Computer Architecture, Computer Networks andsecurity, and Ethical hacking.


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