The Environmental Legacy of the Soviet Regime
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Traffic grooming issue is important to reduce the network design cost and improve network operational performance. In full grooming network services provided to users are costly due to their throughput; same nearly performance will be achieved by grooming some nodes called as "sparse grooming network". In this paper we design heuristic approach for selection of G-node based on Maxconnectivity nodes in Optical Mesh network. Our work mainly focus on dynamic traffic connection request .Simulation results show that blocking performance of Sparse Grooming Network similar with as full grooming Network.
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The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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International Journal of Research Studies in Computer Science and Engineering (IJRSCSE)
Volume. 1, Issue 5, September 2014, PP 6-12
ISSN 2349-4840 (Print) & ISSN 2349-4859 (Online)
www.arcjournals.org
Sparse Traffic Grooming and Performance Analysis of
Backbone Network
Ms. A. S. Shinde
Prof. M. R. Dhage
Department of Information Technology
Sinhgad Academy of Engineering
Pune, India
archana.shinde46@gmail.com
Department of Computer Engineering
Sinhgad College of Engineering
Pune, India
satavmm@rediffmail.com
Abstract: Traffic grooming issue is important to reduce the network design cost and improve network
operational performance. In full grooming network services provided to users are costly due to their
throughput; same nearly performance will be achieved by grooming some nodes called as “sparse
grooming network”. In this paper we design heuristic approach for selection of G-node based on Maxconnectivity nodes in Optical Mesh network. Our work mainly focus on dynamic traffic connection request
.Simulation results show that blocking performance of Sparse Grooming Network similar with as full
grooming Network.
Keywords: OXC - Optical Cross Connect, OC-Optical carrier, RWA-Routing & wavelength assignment,
WDM - wavelength division multiplexing, G-Fabric - Grooming Fabric, G-Node – Grooming Node, G-OXC
– Grooming Optical Cross Connect, W-Fabric - wavelength-switching fabric.
1. INTRODUCTION
The backbone network is mostly a mesh network with optical fibers. Optical fiber technology
gives very high speed transmission speed because of its potentially limitless capabilities, a huge
bandwidth (over 50 terabits per second (Tbps)). On the other hand, only a fraction of customers
are expected to have a need for such a high bandwidth. Due to large cost of the optical backbone
infrastructure it is necessary to combine low-speed traffic streams onto high-speed wavelengths in
order to minimize the network- wide cost in terms of line terminating equipment and/or network
switching, technique called as ”Traffic Grooming”.
In WDM mesh networks, it is assumed that every network node has traffic-grooming capability,
which may not be practical or cost-effective in a nationwide WDM backbone network. In a WDM
mesh network not all nodes need to have grooming capabilities. A network with only a fraction of
nodes having grooming functionalities, called as a Sparse Grooming network. A node which has
traffic -grooming capability is called as grooming node (G-Node). This sparse grooming network
must give the performance of nearly equals to the full groomed network, hence the service
provider and the customers will use this type of network. Due to this the problem of designing a
sparse-grooming WDM mesh network is a very important and practical problem.
Following Figure shows a sample G-OXC architecture. There are two switching fabrics in this
OXC, a wavelength-switching fabric (W-Fabric) and a grooming fabric (G-Fabric). Because a
grooming OXC may be more costly than an OXC without grooming capability (i.e., the OXCs
which only have the WFabric), and in some optical WDM mesh network, only a few network
nodes may have traffic-grooming capability. This type of network a “sparse-grooming network”,
and a node which has traffic-grooming capability to be a grooming node (G-Node)
Once we design sparse grooming network from given physical optical backbone network, it forms
a network with some nodes to be designated as grooming nodes. The grooming nodes along with
the non-grooming nodes form a logical or virtual topology of the backbone network. Based on the
arrival of call or traffic request the light-paths are established between source and destination
nodes. The light paths established are based on the k-shortest path routing, and depending on the
availability of wavelength channels. To establish a lightpath in a WDM network, it is necessary to
determine the route over which the lightpath should be established and the wavelength to be used
©ARC
Page 6
Ms. A. S. Shinde & Prof. M. R. Dhage
on all the links along the route. This problem is called the routing and wavelength assignment
(RWA) problem.
Fig1. An OXC with a two-level hierarchy and grooming capability
Most of the research in optical WDM mesh network focused on static traffic arrival in which
connection request known in advance and as per requirement lightpaths is established to fulfill the
corresponding requirement. Over the period of time many researcher have proposed various
heuristics algorithms and compare their performance in terms of blocking probability. Heuristic
methods are capable of producing near optimal solutions in acceptable time. Most of the previous
work done in grooming on backbone network assume a full grooming network, in which all
switching nodes in the network are assumed to have traffic grooming capabilities [1]. Research
done in sparse grooming, attempts to find the locations of grooming sites [2]- [10]. They often
require the number of grooming nodes as an input parameter. In our work, we select the number
of nodes for performing traffic grooming as well as their placement. This approach is more
reasonable due to cost considerations.
The rest of the paper is organized as follows. Section 2 includes the heuristic approach to Select
Following Diagram Shows an example of designing of sparse grooming network where the
network has consists of five nodes and each edge represents a pair of unidirectional fiber links.
For sake of convenience each fiber supports two wavelength channels named as λ1 and λ2. To
design a sparse grooming network only one node is allowed to become a G-node. Assume there
are four connection requests arrived namely four between node pair (0-3) and one between (13).fig. 3 shows a network designed when node 3 is to be a G-node, Dashed line indicates light
paths is established between node (0-3) and (1-3) as with this design only three connection
request satisfied successfully two between (0-3) and one between(1-3).But With the same design
if G-node is node 1 then all connection request satisfied successfully two between node pairs(03), two between(0-3) groomed with one request between (1-3) shown in fig 4. So the above
example shows that with effective design of sparse grooming network performance of the
network can be improved.
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) age 7
Sparse Traffic Grooming and Performance Analysis of Backbone Network
Grooming node solve dynamic traffic grooming problem with grooming resources on the nodes
having maximum connectivity. Section 3, discusses the performance of our proposed heuristic
approach with full grooming network. Section 4 includes the conclusion of the work.
Fig2. Network with five node Fig3. Network Design I (node 3 as G node) Fig4. Network Design II (node 1
as G node)
2. HEURISTIC APPROACH FOR SPARSE TRAFFIC GROOMING
In literature basically grooming node selection of optical network based on static traffic load [1].
In this paper we proposed the heuristic approach which selects grooming node on basis of max
connecting nodes for a given network design for dynamic traffic grooming. This Approach gives
near optimal performance as with full grooming network shown in fig.5.
2.1 Sparse Node Selection Algorithm
Selection of grooming node for given optical WDM network based on Following algorithm.
Step1:
Start
Step2:
select the max-connectivity node
Step3:
Sort the nodes according to descending order of max-connectivity
Step4:
Consider Non traffic grooming algorithm
Step5:
Calculate the blocking probability of each node, while assigning request
Step6:
Sort nodes in decreasing order of above step
Step6:
Finally take intersection of step 4 and 7
Step8:
Resultant set forms G-node of the network.
Step9:
Repeat step 2 to 8 till blocking probability is near optimal
Step10:
exit
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Page 8
Ms. A. S. Shinde & Prof. M. R. Dhage
Fig5. Flowchart of Sparse Traffic Grooming
2.2 Call Blocking Probability of the Network
Blocking Probability is determined as follows.
CBP
TNC NCS
*100
TNC
CBP=call blocking probability
TNC=total number of calls
NCS=Number of calls served
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) age 9
Sparse Traffic Grooming and Performance Analysis of Backbone Network
2.3 Total Cost of the Network
Total cost includes the cost of wavelengths used to establish lightpath request from source to
destination node plus the cost of all wavelength convertors and traffic grooming devices used by
the lightpath requests.
CT
CT
NGN * CG NW * CW
( NGN Rc * NW ) * CG
Where,
CW=cost to support single wavelength channel
CG= cost to employ grooming capability
CT=total cost of Network
NGN=Number of Grooming Nodes
NW=Number of Wavelengths
Rc = Cost ratio
CW
Rc
CG
3. RESULTS AND DISCUSSION
Simulations have been carried out to investigate the performance of the proposed heuristic
approach by considering the network topologies illustrated in Fig. 6. For a given network
topology and given values of nodes and number of wavelengths we design a heuristic approach
which chooses G node and routes the traffic requests to maximize the network throughput.
Fig6. A Sample network used for simulation (NSFNET)
We have compared our results of max-connectivity node grooming with all node grooming. We
found that for a given network if it is to be designed using heuristic approach gives better
throughput instead of placing grooming nodes randomly. It is observed from the graph that when
number of grooming nodes increases the blocking probability decreases. Whereas at certain point
it reaches near to the stability. So we proved that the sparse grooming node in the traffic grooming
will achieve the performance of near optimal to the full traffic grooming.
Fig7. Blocking probability Vs Number of grooming nodes
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Page 10
Ms. A. S. Shinde & Prof. M. R. Dhage
As we have used WDM in the Optical mesh network the use of number of wavelengths may
affect the performance of the network. That is if the number of wavelengths in use are more then
call blocking probability is less as shown in figure 8.
Fig8. Blocking % probability Vs Number of Wavelengths
We also have analyzed the system performance for dynamic traffic at the same time. For varying
number of packets i.e. the traffic demand goes on increasing the blocking probability also
increases. This analysis of the result is shown in figure 9. Where it is observed that the blocking
probability for varying traffic demand in sparse traffic grooming and full traffic grooming is
nearly same.
Fig9. Blocking % probability Vs traffic rate
The two aspects of using wavelengths for assigning to different requests is used one is wavelength
continuity and wavelength conversion. Now a day’s most of the research is focusing on
wavelength conversion capability. In this project we used the wavelength conversion capability
but we are comparing the results with wavelength continuity i.e. wavelength non conversion. This
is as shown in the figure10.
Fig10. Blocking % probability Vs Traffic rate for wavelength
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) age 11
Sparse Traffic Grooming and Performance Analysis of Backbone Network
4. CONCLUSION
In this paper, we have developed a heuristic procedure for dynamic traffic grooming in WDM
optical mesh networks for finding optimum number of Grooming–nodes based on maxconnectivity.
Our simulation results show that the proposed G-node selection approach gives near same
performance with full grooming. We have also compared network performance of full wavelength
conversion with No wavelength conversion approach and results shows that Full wavelength
gives better throughput by reducing number of call blocks.
REFERENCES
[1] K. Zhu, H. Zang, B. Mukherjee, “Design of WDM Mesh Networks with Sparse Grooming
Capability”, in Proc. IEEE Globecom 2002, vol.3.pp. 2696-2700, Nov. 2002.
[2] W. Yao, M. Li, and B. Ramamurthy, “Performance analysis of sparse traffic grooming in
WDM mesh networks”, in Proc. IEEE ICC, 2005, pp. 1766-1770.
[3] Partha Paul, Balbeer. S. Rawat, Swapan K. Ghorai, “Dynamic Traffic Grooming in WDM
Optical Networks with Full Wavelength Conversion and Grooming Devices on MaxConnectivity Nodes”, International Journal of Computer Applications(0975-8887), Volume
57-No.11, November 2012.
[4] K. Zhu and B. Mukherjee, “Traffic grooming in an optical WDM mesh network”, IEEE
Journal on Selected Areas in Communications, vol. 20, no. 1, pp. 122-133,Jan. 2002.
[5] M. EI Houmaidi, M. A. Bassiouni and G. Li, “Optimal traffic grooming in WDM mesh
networks under dynamic traffic”, in Optical Fiber Communication Conference, Technical
Digest (CD) (Optical Society of America, 2004).
[6] W. Yao, M. Li. and B. Ramamurthy, “Design of Sparse Grooming Networks for
Transporting Dynamic Multi-granularity Sub-wavelength Traffic”, 2004.
[7] O. Awwad, A. Al-Fuqaha, and M. Guizani, “Genetic Approach for Traffic Grooming,
outing, and Wavelength Assignment in WDM Optical Networks with Sparse Grooming
Resources”, IEEE ICC 2006.
[8] Osama Awwad, Ala Al-Fuqaha and Ammar Rayes, “Performance of WDM Mesh Networks
with Limited Traffic Grooming Resources”, IEEE WOCN 2007, Singapore, July 2-4, 2007.
[9] N. S. C. Correia ,J. Coimbra and M. C. R. Medeiros, “Sparse Traffic Grooming in WDM
Networks Using Coarse Granularity OXCs”, Photonic Network Communications August
2008.
[10] H. Zang, J. P. Jue, and B. Mukherjee, “A Review of Routing and Wavelength Assignment
Approaches for Wavelength- Routed Optical WDM Networks”, SPIE Optical Networks
Magazine, vol. 1, no. 1, pp.47-60, January 2000.
[11] Bishwanath Mukherjee, “Optical WDM Networks”, Springer Publication 2006.
[12] Keyao Zhu, Hongyue Zhu and Bishwanath Mukherjee, “Traffic Grooming in Optical WDM
Mesh Networks”, Springer Publication 2006.
[13] H. Zang, J. P. Jue, and B. Mukherjee, “A review of routing and wavelength assignment
approaches for wavelength routed optical WDM networks”, Optical Network Mag., vol. 1,
no. 1, pp. 4760, Jan. 2000.
[14] Jin Y. Yen, “Finding the K Shortest Loopless Paths in a Network”, Management Science,
Vol. 17, No. 11, Theory Series (Jul., 1971), pp. 712716.
AUTHOR’S BIOGRAPHY
Archana S. Shinde received B.E. degree in Computer Science and
Engineering from Swami Ramanand Teerth University in May 2003. Currently
she submitted her thesis of Master degree in the Department of Computer
Engineering (specialization in Computer Network), Pune University. Her
research field of interest includes traffic grooming in Optical Network and
Wireless Communication.
International Journal of Research Studies in Computer Science and Engineering (IJRSCSE) Page 12
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