Splitter Placement in AllOptical WDM Networks


 Imogen Dennis
 1 years ago
 Views:
Transcription
1 plitter Placement in AllOptical WDM Networks HwaChun Lin Department of Computer cience National Tsing Hua University Hsinchu 3003, TAIWAN hengwei Wang Institute of Communications Engineering National Tsing Hua University Hsinchu 3003, TAIWAN Abstract In alloptical WDM networks, splitters at branch nodes are used to realize multicast trees. It is expensive to place splitters at all of the nodes in an alloptical WDM network. To reduce the cost, splitters can be placed at a subset of nodes. The problem of selecting a subset of nodes to place the splitters such that certain performance measure is optimized is called the splitter placement problem. plitter placement problems in alloptical WDM networks in which a single light tree is constructed to realize each multicast connection have been studied in previous researches. This paper studies the splitter placement problem in alloptical WDM networks in which a light forest consisting of a collection of light trees is used to realize a multicast connection. The goal is to place a given number of splitters in the network such that the average per link wavelength resource usage of multicast connections is minimized. An upper bound and a lower bound on the per link average wavelength resource usage for a given number of multicast connections are derived. Two splitter placement methods are proposed for this problem. The two proposed splitter methods are shown to yield significant lower average wavelength resource usage than the random placement method. One of the methods is shown to produce near minimum average wavelength resource usage. I. INTRODUCTION A number of multimedia applications such as video on demand, video conference, distance education and etc. require a vast amount of bandwidth. The demand for networks with high bandwidth is increasing. An optical fiber can provide a large amount of bandwidth (nearly 50 Tb/s [3]) by using wavelength division multiplexing (WDM) [] technology to satisfy the increasing bandwidth demand. Wavelength division multiplexing (WDM) technology is able to divide the vast bandwidth of a fiber into a number of highspeed channels each of which is located at different wavelength. Each channel is capable of operating at the peak rate of an electronic interface. Optical WDM networks are promising transport networks for providing vast amount of bandwidths. If some or all of the switches in an optical WDM network are electronic switches, the bandwidth of the optical network is limited by the speed of the opticalelectricaloptical (OEO) conversion. Alloptical WDM networks in which the signals remain in the optical domain throughout the networks are desirable for providing large amount of bandwidths. In all optical WDM networks, each of the connections going through a link is assigned a wavelength. If a connection is assigned the same wavelength on all of the links along its path, the signal is able to travel from the source node to the destination node using the same wavelength. In case that the connection has to be assigned two or more wavelengths on different links, one or more nodes along its path must have the capability of converting the signal from one wavelength to another wavelength. If all nodes along the path of a connection are incapable of converting a wavelength to another wavelength, the connection must be assigned the same wavelength on all links along its path. Otherwise, the connection is blocked. This is known as the wavelength continuity constraint. A connection that is assigned the same wavelength on all links along its path is called a light path [2]. The WDM networks considered in this paper are alloptical WDM networks without wavelength conversion. In alloptical WDM networks without wavelength conversion, multicast communications can be supported by establishing a light path from the source node to each of the destination nodes. However, two or more light paths of the same multicast connection may go through the same link resulting in a waste of bandwidth. It is desirable to establish a treeshaped path that uses the same wavelength on all links on the treeshaped path from the source node to all destination nodes in order to conserve bandwidth. A treeshaped path using only a single wavelength is called a light tree []. In order to realize a light tree in an alloptical WDM network, the node(s) at the branching point(s) of the light tree must be capable of splitting an input light signal into two or more output signals of the same wavelength. A node with such capability is called a multicast capable node or a splitter [3]. A node without such capability is called a multicast incapable node. When a signal goes through a splitter, the power of the output signals is degraded by a factor of the number of output signals. To maintain the power level of the signal, a costly active amplification device is required to be installed in the splitter [3]. Therefore, a multicast capable node is much more expensive than a multicast incapable node. An alloptical WDM network in which all nodes are multicast capable is very expensive. To reduce the cost, splitters can be placed at a subset of selected nodes. Given that only a subset of nodes in the network are equipped with splitters, a multicast routing protocol needs to construct a light tree for each multicast connection according to the locations of the splitters in order to improve the probability of successfully establishing the multicast connection. Another approach is to construct multiple light trees, which is collectively called a light forest, to realize a single multicast connection [5], [6], [7]. Each of the light trees in the light forest is assigned a different wavelength. Multicast routing algorithms using this approach are known as sparse light splitting multicast routing algorithms. Note that the performance of the multicast routing algorithm is highly affected by the locations of the splitter in the network. How to place a given number of splitters at suitable locations IEEE Globecom /05/$ IEEE
2 such that the performance of the multicast routing algorithm can be improved is an important issue. This problem is referred to as the splitter placement problem which is the focus of this paper. plitter placement problems in alloptical WDM networks in which a single light tree is constructed to realize each multicast connection have been studied in [], []. Note that each of the branch nodes on a light tree must be a splitter. If such a light tree cannot be found to fulfill a multicast request, the multicast request is blocked. The objective in [] is to place a given number of splitters in the network such that the blocking probability of a multicast request is minimized. The problem was proved to be NPcomplete. Integer linear programming was used to solve the problem. everal heuristic algorithms were also studied. A different objective function was considered in []. The objective in [] is to place the splitters in the network such that the probability that a destination node of a multicast connection cannot be reached by the light tree for the multicast connection is minimized. A heuristic algorithm was proposed for the problem. This paper considers the splitter placement problem in alloptical WDM networks in which a light forest consisting of a collection of light trees rooted at the source node is used to realize a multicast connection. In such a network, in the worse case a multicast connection can be realized by multiple light paths without requiring any splitter. Thus, a multicast request will never be blocked due to poor placement of the splitters. Instead, it will be blocked because of insufficient wavelength resource in the network. The advantage of placing splitters in such a network is that the required wavelength resource for multicast connections can be reduced. The objective of this paper is to place a given number of splitters in the network such that the wavelength resource utilized by the multicast connections is minimized. To our knowledge, this problem has not been studied in previous researches. In this paper, a lower bound and an upper bound on the per link average wavelength resource usage for a given number of multicast connections are derived. Two splitter placement methods, namely, kmaximum degree and kmaximum WR methods are proposed. The performances of the proposed splitter placement methods are compared with a random placement method and the optimal placement. Our simulation results show that the two proposed splitter placement methods yield significantly lower average wavelength resource usage than the random placement method. In particular, the kmaximum WR method is able to produces near optimal average wavelength resource usage. The rest of this paper is organized as follows. The splitter placement problem is given in the next section. The lower and upper bounds on the per link average wavelength resource usage are derived in ection III. The two proposed splitter placement methods are described in ection IV. The performances of the proposed splitter placement methods are studied in ection V. Finally, some concluding remarks are given in ection VI. II. THE PLITTER PLACEMENT PROBLEM The objective of this paper is to place a given number of splitters in an alloptical WDM network such that the wavelength resource utilized by the multicast connections is minimized. When the number of connections in the network is large, some of the links may become out of wavelengths resulting in blocking further connection requests. Blocked connection requests are not accounted for in the usage of wavelength resource. A poor placement of splitters may lead to poor wavelength resource utilization that in turn blocks a high percentage of the connection requests resulting in reduced usage of the wavelength resource. In order to isolate the effect of the splitter placement on the usage of wavelength resource from the restriction of the wavelength resource on each link, we assume that each link in the network has unlimited number of wavelengths. Let G = (V,E) represent an alloptical WDM network where V is the set of nodes and E is the set of links. If there is a link from node u to node v, there is also a link in the reversed direction. Let the number of splitters to be placed in G be denoted as k. A placement of splitters P = {p(v); v V } is defined as follows: { if a splitter is placed at node v, p(v) = () 0 if no splitter is placed at node v. The total number of splitters in the network is k. Thus, p(v) =k. (2) v V Let R = {r i, i =, 2,,m} be a sequence of m multicast requests. Let w i be the wavelength resource usage of the multicast request r i. If a multicast request requires one wavelength on one link, the wavelength resource usage of the request on the link is one unit of the wavelength resource. The total wavelength resource usage of a multicast request is the sum of the wavelength resource usage of the request on all links. Given a splitter placement P, the wavelength resource usage for a multicast request r i is calculated as follows. An IPlayer multicast tree is first constructed for the multicast request r i. Base on the locations of the splitters, P, a set of light trees T = {t,t 2,,t b } is constructed to realized the IPlayer multicast tree. The number of required light trees to realized an IPlayer multicast tree depends on the splitter placement P. Each of the light trees in the set T is assigned a different wavelength. Let light tree t j traverse through l(t j ) links. It is clear that the wavelength resource usage of light tree t j is l(t j ). The wavelength resource usage of multicast request r i is the sum of the wavelength resource usages of the light trees that realize its IPlayer multicast tree, i.e. b w i = l(t j ). (3) j= For example, Fig. (a) shows an IPlayer multicast tree for a multicast request rooted at source node. If node is the only splitter on the multicast tree, the multicast tree needs to be realized by a light forest consisting of three light trees as shown in Fig. (b). Each of the three light trees is assigned a wavelength. The wavelength resource usages of the three light trees are 6, 5, and 3 respectively from left to right. The wavelength resource usage of the multicast tree is the sum of IEEE Globecom /05/$ IEEE
3 (a) Fig.. Example of a light forest. The source is node. The rest of the nodes are destination nodes. Node is a multicast capable node, i.e. a splitter. The rest of the nodes are multicast incapable nodes. The multicast tree in (a) needs to be realized by a light forest consisting of three light trees in (b). the wavelength resource usages of the three light trees which is. Let W denote the total wavelength resource usage of all multicast requests in the sequence R = {r i, i =, 2,,m}. It is given as follows: m W = w i. () i= Let U be the per link average wavelength resource usage, which is calculated as m U = W E = w i i= E 2 6 (b), (5) where E is the number of links in the networks. The splitter placement problem is formulated as follows: Given an alloptical WDM network G =(V,E), a sequence of m multicast requests R = {r i, i =, 2,,m}, and k splitters, the objective is to find the splitter placement P that minimizes the per link average wavelength resource usage U. III. LOWER AND UPPER BOUND In this section, we derive the lower and upper bounds of the per link average wavelength resource usage U. The lower bound provides a reference value for the minimum required number of wavelengths per link in an alloptical WDM network for a given number of multicast connections. The upper bound provides a reference value for the maximum required number of wavelengths per link to supports a given number of multicast connections simultaneously. The lower bound is achieved when each of the multicast connections is actually a unicast from a source node to one of its neighbor nodes, whose wavelength resource usage is exactly one. Thus the lower bound of the per link average wavelength resource usage is simply m E, i.e. U m E. The upper bound of the per link average wavelength resource usage is given in the following theorem. Theorem : Given an alloptical WDM network G =(V,E), a sequence of m multicast requests R = r i, i =, 2,, m, and k splitters. The upper bound of the per link average wavelength resource usage is m V 2 E, i.e. Proof: Let ˆr be the multicast request among the m multicast requests that yields the maximum wavelength resource usage. Let the wavelength resource usage of multicast request ˆr be wˆr. Then the upper bound of the per link average wavelength resource usage is mwˆr E, i.e. U mwˆr. (7) E The maximum possible value of wˆr is derived as follows. Let ˆt be the IPlayer multicast tree corresponding to the multicast request ˆr. uppose that there are n nodes on the multicast tree ˆt. Thus, there are n links on the multicast tree ˆt. Recall that the wavelength resource usage wˆr is the sum of the wavelength resource usages of the light trees that realized the multicast tree ˆt. In other words, it is the sum of the wavelength resource usages of the multicast request ˆr on all the links on the multicast tree ˆt. uppose that there are k i links on which the wavelength usages of the multicast request ˆr are i units of wavelength resource, where i =, 2,,n. The wavelength resource usage of multicast request ˆr is calculated as follows: wˆr = k +2 k 2 + +(n ) k n. () We need to find the maximum possible value of wˆr for all possible combinations of k,k 2,,k n under the constraint that k + k k n = n, () since the total number of links on multicast tree ˆt is n. Now, consider the value of k, i.e. the number of links whose wavelength resource usages of multicast request ˆr are exactly one. If k =, multicast tree ˆt must be a tree consisting of two neighbor nodes and one link. By assumption, ˆr is the multicast request among the m multicast requests that yields the maximum wavelength resource usage. Then the network must be a network consisting of only two nodes connected by two links, one on each direction. The per link average wavelength resource usage is m 2 which is the same as its upper bound. Thus, the case where k =is proved. Next, consider the case where k 2. For notational convenience, let k = z. Consider the worst case where no splitter is on any one of the branch nodes of the IPlayer multicast tree ˆt. In this situation, the IPlayer multicast tree ˆt must only be realized solely by light paths instead of light trees. If there are k = z links on multicast tree ˆt whose wavelength resource usages of multicast request ˆr are exactly one, there must be no link whose wavelength resource usages of multicast request ˆr is more than z, i.e. k j =0, j = z +,z+2,,n. Thus, from equation (), we have k 2 + k k z = n z. (0) ubstituting into equation (), the wavelength resource usage of multicast request ˆr becomes wˆr = z +2k zk z. () U m V 2 E. (6) For a given value of z (or k ), the values of k 2,k 3,,k z that maximize wˆr are k 2 = k 3 = = k z =0 and IEEE Globecom /05/$ IEEE
4 k z =(n z). ubstituting the values of k 2,k 3,,k z into equation (), we obtain wˆr = z + z(n z) = nz z 2. (2) The value of z (or k ) that maximizes wˆr is n 2. ubstituting z = n 2 into equation (), we have wˆr = n2. (3) Finally, the maximum value of wˆr is obtained when the number of nodes on multicast tree ˆt equals to the number V 2 of nodes in the network V, i.e. n = V and wˆr =. ubstituting into inequality (7), the upper bound is obtained. This completes the proof of Theorem. IV. PLITTER PLACEMENT METHOD We propose two splitter placement methods, namely, kmaximum degree and kmaximum WR (wavelength reduction) methods, for alloptical WDM networks. The two methods are described in the following. A. The kmaximum degree method The idea of this method is that a node with more neighbor nodes is more likely to become a branch node of a multicast tree. Hence, placing a splitter on the node is expected to be effective in reducing the wavelength resource usage of the multicast connections. Therefore, this method sorts the nodes in the network in descending order according to the number of links connected to them and selects the first k nodes to place the splitters. The computation time of this method includes the time for checking the degree of each of the nodes and the time for sorting the nodes according the degrees of the nodes. The computational complexity of this method is O( V log V ). B. The kmaximum WR (wavelength reduction) method The idea of this method is as follow. If the placement of a splitter on a node yields more reduction on the wavelength resource usage, it is more beneficial to place a splitter at the node. The details are described in the following. Let s i be the shortest path spanning tree rooted at node i. Let h(s i ) denote the wavelength resource usage of s i when no splitter is placed in the network. Note that when no splitter is placed in the network, each multicast connection is realized by multiple light paths. The wavelength resource usage h(s i ) can be calculated by traversing the shortest path spanning tree s i in depthfirst manner. The computational complexity for traversing a shortest path spanning tree is O(β d ), where β is the maximum branching factor and d is the maximum depth of the shortest path spanning tree. Let h be the total wavelength usage of the set of all shortest path spanning trees rooted at each of the nodes when no splitter is placed in the network. Then h is calculated as follows: h = h(s i ). () i V The computational complexity for calculating h is V O(β d ). Let f(i, s j ) be the wavelength resource usage of s j when a splitter is placed at node i. Letf(i) denote the wavelength resource usage of the set of all shortest path spanning trees rooted at each of the nodes when a splitter is place at node i. Then f(i) is obtained as follows: f(i) = f(i, s j ). (5) j V The computational complexity for calculating each f(i), is also V O(β d ). The computational complexity for calculating all f(i), i V,is V 2 O(β d ). Let R(i) be the amount of reduction in wavelength resource usage when a splitter is placed at node i compared with no splitter in the network. Then R(i) is given as follows: R(i) =h f(i). (6) The kmaximum WR method sorts the values of R(i), i =, 2,, V, in descending order and selects the first k nodes to place the splitters. The overall computational complexity of the kmaximum WR method is dominated by the computational complexity for calculating all f(i), i V, which is V 2 O(β d ). V. IMULATION imulations are performed to study the performances of the proposed splitter placement methods. The performances of the proposed splitter placement methods are compared with that of a random placement method and that of the optimal placement. The random placement method randomly selects k nodes in the network and places the splitters at the k nodes. The optimal placement is obtained by exhaustive search. In addition, the effects of different algorithms for constructing light forests on the performance are also investigated. A. imulation Model Pure random graphs generated using the GTITM [0] tool are used to represent the networks. Two network sizes are considered in our simulations: 30nodes and 00nodes networks. For each simulation run, 00 random networks are generated. For each network, m multicast requests are generated. The source node of each multicast request is randomly selected from the nodes in the network. The set of destination nodes for a multicast request is selected in the following manner. First, a destination probability is chosen randomly between 0 and. Then the destination probability is used to determine whether each of the rest of the nodes in the network is included in the destination set. Therefore, the average number of destination nodes of the multicast connections is (N )/2. For each multicast request, the shortestpath multicast routing algorithm is used to construct a multicast tree. The reroutetosource algorithm proposed in [5] is used to construct a light forest to realize the multicast tree unless otherwise specified. For each network, the per link average wavelength resource usage U is first calculated. Then the average value over the 00 networks is calculated. Each data point in our graph is the average value of U over the 00 networks. IEEE Globecom /05/$ IEEE
5 Average wavelength resource usage per link (U) Random method k maximum degree method k maximum WR method Optimal placement Number of splitters Fig. 2. Average wavelength resource usage per link, N =30and m =60. Average wavelength resource usage per link (U) Random RerouteToource Degree RerouteToource WR RerouteToource Random MemberOnly Degree MemberOnly WR MemberOnly Number of splitters Fig. 3. Average wavelength resource usage per link, N = 00 and m = 200. B. imulation Results First, we compare the performances of different splitter placement methods for 30nodes networks. The number of multicast requests, m, generated for each network is 60. The number of splitters, k, to be placed in the network ranges from to 30. The results for the nodes networks are plotted in Fig. 2. From the figure, we can make the following observations: Both of the proposed splitter placement methods yield significant lower per link average wavelength resource usage than the random method. The kmaximum WR method produces lower per link average wavelength resource usage than the kmaximum degree method. The kmaximum WR method produces near optimal per link average wavelength resource usage. The maximum difference of the per link average wavelength resource usages produce by the kmaximum WR method and the optimal placement is.33%. Next, the performances of different splitter placement methods are compared for 00nodes networks. Optimal placement is not compared due to long computation time. The effects of different algorithms for constructing light forests on the per link average wavelength resource usage is also studied. Two algorithms for constructing light forests, namely, reroutetosource and memberonly, proposed in [5] are considered. Three splitter placement methods, namely, random, kmaximum degree, and kmaximum WR methods, are combined with the two algorithms for constructing light forests resulting in a total of six combinations. The number of multicast requests, m, generated for each network is 200. The number of splitters, k, to be placed in the network ranges from to 00. The results are plotted in Fig. 3. From the figure, in addition to the first and second observations made from Fig. 2, we can observe that a good algorithm for constructing light forests is able to further reduce the per link average wavelength resource usage. VI. CONCLUION Placing splitters at a subset of nodes instead of all nodes in an alloptical WDM network leads to significant cost reduction. A good splitter placement method is beneficial in efficient utilization of the wavelength resource and improving the performance of the network. The kmaximum WRmethod proposed in this paper is able to yield near optimal per link average wavelength resource usage. This method will be useful in the networkplanning phase for selecting suitable locations of the splitters. The kmaximum WRmethod combined with a good algorithm for constructing light forests for the multicast connection can further reduce the average wavelength resource usage. ACKNOWLEDGMENT This research was supported by the National cience Council, Taiwan, under grant NC223E , and under the Program for Promoting Academic Excellence of Universities, NC2752E PAE. REFERENCE [] C. A. Brackett,, Dense Wavelength Division Multiplexing Networks: Principles and Applications, IEEE Journal of elected Area on Communications, vol., no. 6, pp.6, August 0. [2] I. Chlamtac, A. Ganz, and G. Karmi, Lightpath Communications: An Approach to High Bandwidth Optical WAN s, IEEE Transactions on Communications, vol. 0, no. 7, pp.72, July 2. [3] C. iva Ram Murthy and M. Gurusamy. WDM Optical Networks: Concepts, Design, and Algorithms, PrenticeHall, [] L. H. ahasrabuddhe and B. Mukherjee, Light Trees: Optical Multicasting for Improved Performance in Wavelength Routed Networks, IEEE Communications Magazine vol. 37, no. 2, pp.6773, February. [5] X. Zhang, J. Y. Wei, and C. Qiao, Constrained Multicast Routing in WDM Networks with parse Light plitting, Journal of Lightwave Technology, vol., no. 2, pp. 727, December [6] W. Tseng and. Kuo, Alloptical Multicasting on WavelengthRouted WDM Networks with Partial Replication, Proceedings of IEEE ICOIN, 200, pp.3. [7] K. D. Wu, J. C. Wu and C.. Yang, Multicast Routing with Power Consideration in parse plitting WDM Networks, ICC 200, vol.2, pp [] M. Ali and J. Deogun, Allocation of Multicast Nodes in Wavelength Routed Networks, ICC 2000, vol.2, pp [] M. Ali, Optimization of plitting Node Placement in WavelengthRouted Optical Networks, IEEE Journal on elected Area in Communications, vol. 20, no., pp , October [0] E. W. Zegura, GTITM: Georgia Tech Internetwork Topology Models (software), itm.tar.gz, 6. Zegura/gtitm/gt IEEE Globecom /05/$ IEEE
Analysis and Algorithms for Partial Protection in Mesh Networks
Analysis and Algorithms for Partial Protection in Mesh Networks Greg uperman MIT LIDS Cambridge, MA 02139 gregk@mit.edu Eytan Modiano MIT LIDS Cambridge, MA 02139 modiano@mit.edu Aradhana NarulaTam MIT
More informationNetwork Topology Control and Routing under Interface Constraints by Link Evaluation
Network Topology Control and Routing under Interface Constraints by Link Evaluation Mehdi Kalantari Phone: 301 405 8841, Email: mehkalan@eng.umd.edu Abhishek Kashyap Phone: 301 405 8843, Email: kashyap@eng.umd.edu
More informationDynamic Wavelength Assignment for WDM AllOptical Tree Networks
Dynamic Wavelength Assignment for WDM AllOptical Tree Networks Poompat Saengudomlert, Eytan H. Modiano, and Robert G. Gallager Laboratory for Information and Decision Systems Massachusetts Institute of
More informationA Heuristic Algorithm for Designing Logical Topologies in Packet Networks with Wavelength Routing
A Heuristic Algorithm for Designing Logical Topologies in Packet Networks with Wavelength Routing Mare Lole and Branko Mikac Department of Telecommunications Faculty of Electrical Engineering and Computing,
More informationAn Improved Multicast Routing Algorithm in Sparse Splitting WDM Networks
Author manuscript, published in "ComManTel'01: International Conference on Computing, Management and Telecommunications Conference, Viet Nam (01)" An Improved Multicast Routing Algorithm in Sparse Splitting
More informationADAPTIVE LINK WEIGHT ASSIGNMENT AND RANDOM EARLY BLOCKING ALGORITHM FOR DYNAMIC ROUTING IN WDM NETWORKS
ADAPTIVE LINK WEIGHT ASSIGNMENT AND RANDOM EARLY BLOCKING ALGORITHM FOR DYNAMIC ROUTING IN WDM NETWORKS ChingLung Chang, YanYing, Lee, and Steven S. W. Lee* Department of Electronic Engineering, National
More informationOPTICAL NETWORKS. Virtual Topology Design. A. Gençata İTÜ, Dept. Computer Engineering 2005
OPTICAL NETWORKS Virtual Topology Design A. Gençata İTÜ, Dept. Computer Engineering 2005 Virtual Topology A lightpath provides singlehop communication between any two nodes, which could be far apart in
More informationEstablishment of Survivable Connections in WDM Networks using Partial Path Protection
Establishment of Survivable Connections in WDM Networks using Partial Path Protection G. Xue 1, Senior Member, IEEE, W. Zhang 1,J.Tang 1, and K. Thulasiraman 2, Fellow, IEEE Abstract As a generalization
More informationHeuristic Algorithms for Multiconstrained QualityofService Routing
244 IEEE/ACM TRANSACTIONS ON NETWORKING, VOL 10, NO 2, APRIL 2002 Heuristic Algorithms for Multiconstrained QualityofService Routing Xin Yuan, Member, IEEE Abstract Multiconstrained qualityofservice
More informationRollout Algorithms for Logical Topology Design and Traffic Grooming in Multihop WDM Networks
Rollout Algorithms for Logical Topology Design and Traffic Grooming in Multihop WDM Networks Kwangil Lee Department of Electrical and Computer Engineering University of Texas, El Paso, TX 79928, USA. Email:
More informationARELAY network consists of a pair of source and destination
158 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 55, NO 1, JANUARY 2009 Parity Forwarding for MultipleRelay Networks Peyman Razaghi, Student Member, IEEE, Wei Yu, Senior Member, IEEE Abstract This paper
More informationLID Assignment In InfiniBand Networks
LID Assignment In InfiniBand Networks Wickus Nienaber, Xin Yuan, Member, IEEE and Zhenhai Duan, Member, IEEE Abstract To realize a path in an InfiniBand network, an address, known as Local IDentifier (LID)
More informationA Network Optimization Model for MultiLayer IP/MPLS over OTN/DWDM Networks
A Network Optimization Model for MultiLayer IP/MPLS over OTN/DWDM Networks Iyad Katib and Deep Medhi Computer Science & Electrical Engineering Department University of MissouriKansas City, USA {IyadKatib,
More informationAn Ant Colony Optimization Implementation for Dynamic Routing and Wavelength Assignment in Optical Networks
An Ant Colony Optimization Implementation for Dynamic Routing and Wavelength Assignment in Optical Networks Timothy Hahn, Shen Wan March 5, 2008 Montana State University Computer Science Department Bozeman,
More information3 NoWait Job Shops with Variable Processing Times
3 NoWait Job Shops with Variable Processing Times In this chapter we assume that, on top of the classical nowait job shop setting, we are given a set of processing times for each operation. We may select
More informationIO2654 Optical Networking. WDM network design. Lena Wosinska KTH/ICT. The aim of the next two lectures. To introduce some new definitions
IO2654 Optical Networking WDM network design Lena Wosinska KTH/ICT 1 The aim of the next two lectures To introduce some new definitions To make you aware about the tradeoffs for WDM network design To
More informationDistributed Clustering Method for LargeScaled Wavelength Routed Networks
Distributed Clustering Method for LargeScaled Wavelength Routed Networks Yukinobu Fukushima, Hiroaki Harai, Shin ichi Arakawa, and Masayuki Murata Graduate School of Information Science and Technology,
More informationAdaptive Weight Functions for Shortest Path Routing Algorithms for MultiWavelength Optical WDM Networks
Adaptive Weight Functions for Shortest Path Routing Algorithms for MultiWavelength Optical WDM Networks Tibor FabryAsztalos, Nilesh Bhide and Krishna M. Sivalingam School of Electrical Engineering &
More informationA Novel Optimization Method of Optical Network Planning. Wu CHEN 1, a
A Novel Optimization Method of Optical Network Planning Wu CHEN 1, a 1 The engineering & technical college of chengdu university of technology, leshan, 614000,china; a wchen_leshan@126.com Keywords:wavelength
More informationResearch on Control Routing Technology in Communication Network
Appl. Math. Inf. Sci. 6 No. 1S pp. 129S133S (2012) Applied Mathematics & Information Sciences An International Journal @ 2012 NSP Natural Sciences Publishing Cor. Research on Control Routing Technology
More informationMWPG  AN ALGORITHM FOR WAVELENGTH REROUTING
MWPG  AN ALGORITHM FOR WAVELENGTH REROUTING Student Lecture Mohammed Pottayil 050703 1 1 OUTLINE Review of Wavelength Rerouting Concepts  What is Wavelength Rerouting  Lightpath Migration operations
More informationPerformance Analysis of the Signaling Channels of OBS Switches
296 Performance Analysis of the ignaling Channels of OB witches Hulusi YAHYAGİL A.Halim ZAİM M.Ali AYDIN Ö.Can TURNA İstanbul University, Computer Engineering Department, Avcılar İstanbul, TURKEY Abstract
More informationA Novel Generic Graph Model for Traffic Grooming in Heterogeneous WDM Mesh Networks
IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 11, NO. 2, APRIL 2003 285 A Novel Generic Graph Model for Traffic Grooming in Heterogeneous WDM Mesh Networks Hongyue Zhu, Student Member, IEEE, Hui Zang, Member,
More informationUnavoidable Constraints and Collision Avoidance Techniques in Performance Evaluation of Asynchronous Transmission WDMA Protocols
1th WEA International Conference on COMMUICATIO, Heraklion, reece, July 35, 8 Unavoidable Constraints and Collision Avoidance Techniques in Performance Evaluation of Asynchronous Transmission WDMA Protocols
More informationA New Multicast Wavelength Assignment Algorithm in WavelengthConverted Optical Networks
Int J Communications, Network and System Sciences, 2009, 2, 912916 doi:104236/ijcns200929106 Published Online December 2009 (http://wwwscirporg/journal/ijcns/) A New Multicast Waelength Assignment Algorithm
More informationn = 2 n = 1 µ λ n = 0
A Comparison of Allocation Policies in Wavelength Routing Networks Yuhong Zhu, George N. Rouskas, Harry G. Perros Department of Computer Science, North Carolina State University Abstract We consider wavelength
More informationI R TECHNICAL RESEARCH REPORT. A Local Optimization Algorithm for Logical Topology Design and Traffic Grooming in IP over WDM Networks
TECHNICAL RESEARCH REPORT A Local Optimization Algorithm for Logical Topology Design and Traffic Grooming in IP over WDM Networks by KwangIl Lee, Mark Shayman TR 20033 I R INSTITUTE FOR SYSTEMS RESEARCH
More informationA New Architecture for Multihop Optical Networks
A New Architecture for Multihop Optical Networks A. Jaekel 1, S. Bandyopadhyay 1 and A. Sengupta 2 1 School of Computer Science, University of Windsor Windsor, Ontario N9B 3P4 2 Dept. of Computer Science,
More informationMulticast Routing with Delay and Delay Variation Constraints for Multimedia Applications
Multicast Routing with Delay and Delay Variation Constraints for Multimedia Applications Shankar M. Banik 1, Sridhar Radhakrishnan 1, and Chandra N. Sekharan 2 1 School of Computer Science, University
More informationLogical Topology Design for Linear and Ring Optical Networks
62 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL 20, NO 1, JANUARY 2002 Logical Topology Design for Linear and Ring Optical Networks Amrinder S Arora, Suresh Subramaniam, Member, IEEE, and HyeongAh
More informationLighttree routing under optical power budget constraints
Lighttree routing under optical power budget constraints Yufeng Xin MCNCRDI, RTP, 3021 Cornwallis Road, Research Triangle Park, North Carolina 277093910 yxin@anrmcncorg George N Rouskas Department of
More informationLink Selection Algorithms for LinkBased ILPs and Applications to RWA in Mesh Networks
Link Selection Algorithms for LinkBased ILPs and Applications to RWA in Mesh Networks Zeyu Liu, George N. Rouskas Department of Computer Science, North Carolina State University, Raleigh, NC 276958206,
More informationMulticasting in the Hypercube, Chord and Binomial Graphs
Multicasting in the Hypercube, Chord and Binomial Graphs Christopher C. Cipriano and Teofilo F. Gonzalez Department of Computer Science University of California, Santa Barbara, CA, 93106 Email: {ccc,teo}@cs.ucsb.edu
More informationPerformance Analysis on Various Wavelength Assignment Algorithms with Traffic Grooming
Proc. of Int. Conf. on Emerging Trends in Engineering and Technology Performance Analysis on Various Wavelength Assignment Algorithms with Traffic Grooming Vikas Kaushik 1, R.S Chauhan 2 1 JMIT Radaur/ECE
More informationAdvanced Algorithms Class Notes for Monday, October 23, 2012 Min Ye, Mingfu Shao, and Bernard Moret
Advanced Algorithms Class Notes for Monday, October 23, 2012 Min Ye, Mingfu Shao, and Bernard Moret Greedy Algorithms (continued) The best known application where the greedy algorithm is optimal is surely
More informationGATEWAY MULTIPOINT RELAYS AN MPRBASED BROADCAST ALGORITHM FOR AD HOC NETWORKS. Ou Liang, Y. Ahmet Şekercioğlu, Nallasamy Mani
GATEWAY MULTIPOINT RELAYS AN MPRBASED BROADCAST ALGORITHM FOR AD HOC NETWORKS Ou Liang, Y. Ahmet Şekercioğlu, Nallasamy Mani Centre for Telecommunication and Information Engineering Monash University,
More informationDesign of Logical Topologies in WavelengthRouted IP Networks
DESIGN OF LOGICAL TOPOLOGIES... 1 Design of Logical Topologies in WavelengthRouted IP Networks M.Ajmone Marsan ½ A.Grosso ¾, E.Leonardi ½, M.Mellia ½, A.Nucci ½ ½ Dipartimento di Elettronica  Politecnico
More informationDesign of LargeScale Optical Networks Λ
Design of LargeScale Optical Networks Λ Yufeng Xin, George N. Rouskas, Harry G. Perros Department of Computer Science, North Carolina State University, Raleigh NC 27695 Email: fyxin,rouskas,hpg@eos.ncsu.edu
More informationAutomatic Service and Protection Path Computation  A Multiplexing Approach
Automatic Service and Protection Path Computation  A Multiplexing Approach Loay Alzubaidi 1, Ammar El Hassan 2, Jaafar Al Ghazo 3 1 Department of Computer Engineering & Science, Prince Muhammad bin Fahd
More informationAN EFFICIENT ALGORITHM FOR SHORTEST PATH MULTICAST ROUTING UNDER DELAY AND DELAY VARIATION CONSTRAINTS
AN EFFICIENT ALGORITHM FOR SHORTEST PATH MULTICAST ROUTING UNDER DELAY AND DELAY VARIATION CONSTRAINTS Mohamed F. Mokbel Department of Computer Science Purdue University West Lafayette, Indiana 47907 email:
More informationReversing Ticket Based Probing Routing Protocol for MANET
Reversing Ticket Based Probing Routing Protocol for MANET TURGUT YUCEL and MIN SONG Department of Electrical and Computer Engineering Old Dominion University Norfolk, VA 23529 U.S.A. http://www.odu.edu/networking
More informationAPPROXIMATING A PARALLEL TASK SCHEDULE USING LONGEST PATH
APPROXIMATING A PARALLEL TASK SCHEDULE USING LONGEST PATH Daniel Wespetal Computer Science Department University of MinnesotaMorris wesp0006@mrs.umn.edu Joel Nelson Computer Science Department University
More informationReducing the Size of Routing Tables for Largescale Network Simulation
Reducing the Size of Routing Tables for Largescale Network Simulation Akihito Hiromori, Hirozumi Yamaguchi, Keiichi Yasumoto, Teruo Higashino and Kenichi Taniguchi Graduate School of Engineering Science,
More informationThe Encoding Complexity of Network Coding
The Encoding Complexity of Network Coding Michael Langberg Alexander Sprintson Jehoshua Bruck California Institute of Technology Email: mikel,spalex,bruck @caltech.edu Abstract In the multicast network
More informationA Review of Traffic Management in WDM Optical Networks: Progress and Challenges
www.ijecs.in International Journal Of Engineering And Computer Science ISSN:23197242 Volume 6 Issue 8 August 2017, Page No. 2230922313 Index Copernicus value (2015): 58.10 DOI: 10.18535/ijecs/v6i8.13
More informationTopic: Local Search: MaxCut, Facility Location Date: 2/13/2007
CS880: Approximations Algorithms Scribe: Chi Man Liu Lecturer: Shuchi Chawla Topic: Local Search: MaxCut, Facility Location Date: 2/3/2007 In previous lectures we saw how dynamic programming could be
More informationFlexibility Evaluation of Hybrid WDM/TDM PONs
Flexibility Evaluation of Hybrid WD/TD PONs Abhishek Dixit, Bart Lannoo, Goutam Das, Didier Colle, ario Pickavet, Piet Demeester Department of Information Technology, Ghent University IBBT, B9 Gent, Belgium
More informationA Hierarchical Model for Multigranular Optical Networks
A Hierarchical Model for Multigranular Optical Networks Mohan Iyer, George N. Rouskas, Rudra Dutta {mliyer, rouskas, rdutta}@ncsu.edu Department of Computer Science, North Carolina State University, Raleigh,
More informationA NOVEL DECENTRALIZED ETHERNETBASED PASSIVE OPTICAL NETWORK ARCHITECTURE
A NOVEL DECENTRALIZED ETHERNETBASED PASSIVE OPTICAL NETWORK ARCHITECTURE A. Hadjiantonis, S. Sherif, A. Khalil, T. Rahman, G. Ellinas, M. F. Arend, and M. A. Ali, Department of Electrical Engineering,
More informationWavelengthRouted Optical Networks: Linear Formulation, Resource Budgeting Tradeoffs, and a Reconfiguration Study
598 IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 8, NO. 5, OCTOBER 2000 WavelengthRouted Optical Networks: Linear Formulation, Resource Budgeting Tradeoffs, and a Reconfiguration Study Dhritiman Banerjee
More informationTraffic Grooming in WDM Networks
TOPICS IN LIGHTWAVE SERIES Traffic Grooming in Networks Eytan Modiano, MIT Philip J. Lin, Tellabs ABSTRACT The recent emergence of wavelengthdivision multiplexing technology has led to a tremendous increase
More informationDynamic service Allocation with Protection Path
www.ijcsi.org 115 Dynamic service Allocation with Protection Path Loay Alzubaidi Department of Computer Engineering & Science, Prince Muhammad bin Fahd University ALKhobar, Saudi Arabia Abstract Path
More informationA Novel Approach to Reduce Packet Loss in OBS Networks
A Novel Approach to Reduce Packet Loss in OBS Networks Amit Gupta 1, Harbhajan Singh 2, Jagdish Kumar 3 1 Deptt. of Electronics and Communication Engg, PTU, Jalandhar, India. 2 Deptt. of Electronics and
More informationLIGHT TREE A SEMINAR REPORT. Submitted By SUJIT KUMAR. In partial fulfillment of the award of the degree BACHELOR OF TECHNOLOGY
LIGHT TREE A SEMINAR REPORT Submitted By SUJIT KUMAR In partial fulfillment of the award of the degree of BACHELOR OF TECHNOLOGY IN COMPUTER SCIENCE AND ENGINEERING SCHOOL OF ENGINEERING COCHIN UNIVERSITY
More informationAlgorithms Exam TIN093/DIT600
Algorithms Exam TIN093/DIT600 Course: Algorithms Course code: TIN 093 (CTH), DIT 600 (GU) Date, time: 22nd October 2016, 14:00 18:00 Building: M Responsible teacher: Peter Damaschke, Tel. 5405 Examiner:
More informationBit Index Explicit Replication (BIER) Multicasting in Transport Networks [Invited]
Bit Index Explicit Replication (BIER) Multicasting in Transport Networks [Invited] A. Giorgetti, A. Sgambelluri, F. Paolucci, N. Sambo, P. Castoldi Scuola Superiore Sant Anna Pisa, Italy Email: a.giorgetti@santannapisa.it
More informationSOLVING LARGE CARPOOLING PROBLEMS USING GRAPH THEORETIC TOOLS
July, 2014 1 SOLVING LARGE CARPOOLING PROBLEMS USING GRAPH THEORETIC TOOLS Irith BenArroyo Hartman Datasim project  (joint work with Abed Abu dbai, Elad Cohen, Daniel Keren) University of Haifa, Israel
More informationPerformance of Optical Burst Switching Techniques in MultiHop Networks
Performance of Optical Switching Techniques in MultiHop Networks ByungChul Kim *, YouZe Cho *, JongHyup Lee **, YoungSoo Choi **, and oug Montgomery * * National Institute of Standards and Technology,
More informationResearch Article Comparative Analysis of Routing and Wavelength Assignment Algorithms used in WDM Optical Networks
Research Journal of Applied Sciences, Engineering and Technology 7(13): 26462654, 2014 DOI:10.19026/rjaset.7.581 ISSN: 20407459; eissn: 20407467 2014 Maxwell Scientific Publication Corp. Submitted:
More informationBacktracking and BranchandBound
Backtracking and BranchandBound Usually for problems with high complexity Exhaustive Search is too time consuming Cut down on some search using special methods Idea: Construct partial solutions and extend
More informationModule 6 P, NP, NPComplete Problems and Approximation Algorithms
Module 6 P, NP, NPComplete Problems and Approximation Algorithms Dr. Natarajan Meghanathan Associate Professor of Computer Science Jackson State University Jackson, MS 39217 Email: natarajan.meghanathan@jsums.edu
More informationA BranchandCut Algorithm for the Partition Coloring Problem
A BranchandCut Algorithm for the Partition Coloring Problem Yuri Frota COPPE/UFRJ, Programa de Engenharia de Sistemas e Otimização Rio de Janeiro, RJ 21945970, Brazil abitbol@cos.ufrj.br Nelson Maculan
More informationAvoidance of Multicast Incapable Branching Nodes for Multicast Routing in WDM Networks
Noname manuscript No. (will be inserted by the editor) Avoidance of Multicast Incapable Branching Nodes for Multicast Routing in WDM Networks Fen Zhou Miklós Molnár Bernard Cousin Received: date / Accepted:
More informationChapter 9 Graph Algorithms
Introduction graph theory useful in practice represent many reallife problems can be if not careful with data structures Chapter 9 Graph s 2 Definitions Definitions an undirected graph is a finite set
More informationAbsolute QoS Differentiation in Optical BurstSwitched Networks
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 22, NO. 9, NOVEMBER 2004 1781 Absolute QoS Differentiation in Optical BurstSwitched Networks Qiong Zhang, Student Member, IEEE, Vinod M. Vokkarane,
More informationLiterature Survey of nonblocking network topologies
Literature Survey of nonblocking network topologies S.UMARANI 1, S.PAVAI MADHESWARI 2, N.NAGARAJAN 3 Department of Computer Applications 1 Department of Computer Science and Engineering 2,3 Sakthi Mariamman
More informationApplication Layer Multicast For Efficient PeertoPeer Applications
Application Layer Multicast For Efficient PeertoPeer Applications Adam Wierzbicki 1 email: adamw@icm.edu.pl Robert Szczepaniak 1 Marcin Buszka 1 1 PolishJapanese Institute of Information Technology
More informationA Comparison of Path Protections with Availability Concern in WDM Core Network
A Comparison of Path Protections with Availability Concern in WDM Core Network M. A. Farabi Photonic Technology Lab, Universiti Teknologi, S. M. Idrus Member, IEEE Photonic Technology Lab, Universiti Teknologi,
More informationNonblocking WDM Switching Networks With Full and Limited Wavelength Conversion
2032 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL 50, NO 12, DECEMBER 2002 Nonblocking WDM Switching Networks With Full and Limited Wavelength Conversion Xiangdong Qin, Student Member, IEEE, and Yuanyuan Yang,
More informationEfficient QoS Partition and Routing in Multiservice IP Networks
Efficient QoS Partition and Routing in Multiservice IP Networks I. Atov H. T. Tran R. J. Harris RMIT University Melbourne Box 2476V Vic. 3001, Australia Abstract This paper considers the combined problem
More informationData Caching in Networks with Reading, Writing and Storage Costs
Data Caching in Networks with Reading, Writing and Storage Costs Bin Tang a, Himanshu Gupta b a Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS 67260 b
More informationOptical networking technology
1 Optical networking technology Technological advances in semiconductor products have essentially been the primary driver for the growth of networking that led to improvements and simplification in the
More informationDynamic Routing in Translucent WDM Optical Networks: The Intradomain Case
University of Nebraska  Lincoln DigitalCommons@University of Nebraska  Lincoln CSE Journal Articles Computer Science and Engineering, Department of 32005 Dynamic Routing in Translucent WDM Optical Networks:
More informationLeveraging Set Relations in Exact Set Similarity Join
Leveraging Set Relations in Exact Set Similarity Join Xubo Wang, Lu Qin, Xuemin Lin, Ying Zhang, and Lijun Chang University of New South Wales, Australia University of Technology Sydney, Australia {xwang,lxue,ljchang}@cse.unsw.edu.au,
More informationChapter 9 Graph Algorithms
Chapter 9 Graph Algorithms 2 Introduction graph theory useful in practice represent many reallife problems can be if not careful with data structures 3 Definitions an undirected graph G = (V, E) is a
More informationEffect of Link Bandwidth, Number of Channels and Traffic Load on Designing Optical Burst Switching Networks
Effect of Link Bandwidth, Number of Channels and Traffic Load on Designing Optical Burst Switching Networks Wael Hosny 1 (drwaelhosny@aast.edu), Mohamed M. Ali 1 (m.mahmoud@aast.edu), Moustafa H. Aly 1*
More informationShared Risk Link Group (SRLG)Diverse Path Provisioning Under Hybrid Service Level Agreements in WavelengthRouted Optical Mesh Networks
University of Nebraska  Lincoln DigitalCommons@University of Nebraska  Lincoln CSE Journal Articles Computer Science and Engineering, Department of 82005 Shared Risk Link Group (SRLG)Diverse Path Provisioning
More informationEndToEnd Signaling and Routing for Optical IP Networks
EndToEnd Signaling and Routing for Optical IP Networks Mark Joseph Francisco, Lambros Pezoulas, Changcheng Huang, Ioannis Lambadaris Carleton University Department of Systems and Computer Engineering
More informationNPHardness. We start by defining types of problem, and then move on to defining the polynomialtime reductions.
CS 787: Advanced Algorithms NPHardness Instructor: Dieter van Melkebeek We review the concept of polynomialtime reductions, define various classes of problems including NPcomplete, and show that 3SAT
More informationCOMP 355 Advanced Algorithms Approximation Algorithms: VC and TSP Chapter 11 (KT) Section (CLRS)
COMP 355 Advanced Algorithms Approximation Algorithms: VC and TSP Chapter 11 (KT) Section 35.135.2(CLRS) 1 Coping with NPCompleteness Bruteforce search: This is usually only a viable option for small
More informationOn the MinMax 2Cluster Editing Problem
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 29, 11091120 (2013) On the MinMax 2Cluster Editing Problem LIHSUAN CHEN 1, MAWSHANG CHANG 2, CHUNCHIEH WANG 1 AND BANG YE WU 1,* 1 Department of Computer
More informationFor example, in the widestshortest path heuristic [8], a path of maximum bandwidth needs to be constructed from a structure S that contains all short
A Note on Practical Construction of Maximum Bandwidth Paths Navneet Malpani and Jianer Chen Λ Department of Computer Science Texas A&M University College Station, TX 778433112 Abstract Constructing maximum
More informationCURRENT routing schemes typically focus on discovering
IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 15, NO. 2, APRIL 2007 413 Multipath Routing Algorithms for Congestion Minimization Ron Banner, Senior Member, IEEE, and Ariel Orda, Fellow, IEEE Abstract Unlike
More informationConstrained Minimum Spanning Tree Algorithms
December 8, 008 Introduction Graphs and MSTs revisited Minimum Spanning Tree Algorithms Algorithm of Kruskal Algorithm of Prim Constrained Minimum Spanning Trees Bounded Diameter Minimum Spanning Trees
More informationMulticast OLSP Establishment Scheme in OVPN over IP/GMPLS over DWDM
Multicast OLSP Establishment Scheme in OVPN over IP/GMPLS over DWDM JeongMi Kim 1, OhHan Kang 2, JaeIl Jung 3, and SungUn Kim 1,4 1 Pukyong National University, 5991 Daeyeon 3Dong NamGu, Busan,
More informationAn Evolutionary Algorithm for the Multiobjective Shortest Path Problem
An Evolutionary Algorithm for the Multiobjective Shortest Path Problem Fangguo He Huan Qi Qiong Fan Institute of Systems Engineering, Huazhong University of Science & Technology, Wuhan 430074, P. R. China
More informationAn Efficient Algorithm for Computing Nonoverlapping Inversion and Transposition Distance
An Efficient Algorithm for Computing Nonoverlapping Inversion and Transposition Distance Toan Thang Ta, ChengYao Lin and Chin Lung Lu Department of Computer Science National Tsing Hua University, Hsinchu
More informationConstruction of the Bounded Applicationlayer Multicast Tree in the Overlay Network Model by the Integer Linear Programming *
Construction of the Bounded Applicationlayer Multicast Tree in the Overlay Network Model by the Integer Linear Programming * Petr Jurčík Department of Control Engineering Faculty of Electrical Engineering
More informationOptimization Algorithms for Data Center Location Problem in Elastic Optical Networks
Optimization Algorithms for Data Center Location Problem in Elastic Optical Networks Mirosław Klinkowski 1, Krzysztof Walkowiak 2, and Róża Goścień 2 1 National Institute of Telecommunications, Warsaw,
More informationMulticast routing Draft
Multicast routing Draft Lucia Tudose Nokia Research Center Email: tudose@research.nokia.com Abstract Multicast routing is establishing a tree which is routed from the source node and contains all the
More informationRouting and Wavelength Assignment in Optical Networks 1
Routing and Wavelength Assignment in Optical Networks 1 by Asuman E. Ozdaglar and Dimitri P. Bertsekas 2 Abstract The problem of routing and wavelength assignment (RWA) is critically important for increasing
More informationEliminating Bottlenecks in Overlay Multicast
Eliminating Bottlenecks in Overlay Multicast Min Sik Kim, Yi Li, and Simon S. Lam Department of Computer Sciences The University of Texas at Austin {minskim,ylee,lam}@cs.utexas.edu Abstract. Recently many
More informationApproximation Algorithm for Ndistance Minimal Vertex Cover Problem
Approximation Algorithm for Ndistance Minimal Vertex Cover Problem Tarun Yadav Scientist, Scientific Analysis Group Defence R & D Organisation, INDIA Email: tarunyadav@sag.drdo.in Koustav Sadhukhan, Rao
More information1 The Traveling Salesperson Problem (TSP)
CS 598CSC: Approximation Algorithms Lecture date: January 23, 2009 Instructor: Chandra Chekuri Scribe: Sungjin Im In the previous lecture, we had a quick overview of several basic aspects of approximation
More informationMultipath Routing for Video Unicast over BandwidthLimited Networks
Multipath Routing for Video Unicast over BandwidthLimited Networks Jiancong Chen S.H. Gary Chan Department of Computer Science The Hong Kong University of Science and Technology Hong Kong Abstract Video
More informationChapter 9 Graph Algorithms
Chapter 9 Graph Algorithms 2 Introduction graph theory useful in practice represent many reallife problems can be slow if not careful with data structures 3 Definitions an undirected graph G = (V, E)
More informationA Scalable and BandwidthEfficient Multicast Algorithm based on Segment Routing in Software Defined Networking
A Scalable and BandwidthEfficient Multicast Algorithm based on Segment Routing in Software Defined Networking JangPing Sheu and YinChen Chen Department of Computer Science, National Tsing Hua University
More informationVertex Cover Approximations
CS124 Lecture 20 Heuristics can be useful in practice, but sometimes we would like to have guarantees. Approximation algorithms give guarantees. It is worth keeping in mind that sometimes approximation
More informationSteiner Trees and Forests
Massachusetts Institute of Technology Lecturer: Adriana Lopez 18.434: Seminar in Theoretical Computer Science March 7, 2006 Steiner Trees and Forests 1 Steiner Tree Problem Given an undirected graph G
More information35 Approximation Algorithms
35 Approximation Algorithms Many problems of practical significance are NPcomplete, yet they are too important to abandon merely because we don t know how to find an optimal solution in polynomial time.
More information