ITC19/ ITU & ITC Workshop for Developing Countries LIANG X.J and XIN Z.H.(Editors) V.B IVERSEN and KUO G.S.(Editors) Beijing University of Posts and Telecommunications Press 1997-2003 An Optimized Scheme to Organize Softswitch-based Next Generation Network1 Yin Zeming State Key Laboratory of Switching Technology and Telecommunication Networks, Beijing University of Posts and Telecommunications, Box 187, Beijing 100876, China yinzeming2002@163.com Liu Yuzhang liuyz@mail.dascom.com.cn Yang Fangchun fcyang@bupt.edu.cn Abstract: This paper outlines the network organizing in softswitch-based NGN First, a non-linear programming scheme that aims to minimize the cost of organizing networks under the constraint of required reliability and delay is analyzed, and we present a heuristic algorithm to solve it The reliability of the network is guaranteed with both the reliability of the links and that of the softswitch nodes considered, and ‘state-sharing’ is adopted to assure the node’s reliability A design scheme of softswitch node supporting ‘state-sharing’ is presented Finally, the evaluation for the heuristic algorithm is presented Keywords: NGN, softswitch, non-linear programming, heuristic algorithm INTRODUCTION Now it is a trend that the various networks running independently will converge to Next Generation Network (NGN), and softswitch-based scenario is one of the effectual schemes Accordingly, organizing scheme and call routing become important issues to be researched However, few researches have focused on organizing technology and call routing of softswitch-based NGN so far NGN is all-IP network, and is operates in a manageable and operable mode rather than the best-effort mode in current Internet At the same time, while Public Switched Telephone Network (PSTN) has accumulated rich solutions in organizing networks, it is based on circuit-switch architecture whose service traffic doesn’t behave like that in the data networks Up to now there is no determined scheme for softswitch-based NGN’s organizing in the related standards This remainder of the paper is organized as follows In Section 2, we describe NGN’s objectives in organizing network, and analyze them from the economic view and the performance view We present a model based on the foundation that the average delay in data networks is got through Kleinrock Approximation [1] and Jackson theorem A heuristic algorithm and its related heuristic strategies are presented to The work is supported by National Nature Science Fund (90104024), National Science Fund for Distinguished Young Scholars (60125101) 1998 solve the model Section describes a state-sharing scheme with which to increase the reliability of softswitch node Finally, the heuristic algorithm is evaluated in Section NON-LINEAR PROGRAMMING WITH LEAST-COST OBJECTIVE There are a few schemes that can be adopted to organize NGN, such as hierarchical, non-hierarchical or mixed In the hierarchical way, softswitch works like switches in PSTN In the non-hierarchical way, softswitch works in the same way as routers in IP networks In [2], a mixed scheme is presented In the scheme, the non-hierarchical architecture of softswitch is revised a little with Routing Agent added There are other schemes to organize NGN, and here we only discuss the non-hierarchical scheme Our objective in organizing the network includes: Keeping the average delay of each packet or each message under a certain level Raising the reliability of a single softswitch node Minimizing the cost under the condition that the two requirements above are met It is assumed that the location of the softswitch node and the traffic are known, and our aim is to organize the network meeting the requirement in traffic and performance with least cost It is a difficult and synthesized problem Considering the complexity, we launch on minimizing the cost by programming the capacity of the links between softswitches The problem of organizing network is boiled down to programming the capacity of each link (which is described as ( i, j )), ∑ p ij C ij (i , j ) s.t γ ∑C (i , j ) Fij ij − Fij (1) ≤T where C ij is the capacity of the link (i, j ) , p ij is the cost of each unit capacity, and the constraint condition is that the average delay is no larger than T Fij is the flow of the link (i, j ) holding the same metric with C ij ∑C γ (i , j ) forcast, and Fij ij − Fij is the average delay got through the M/M/1 model based on Kleinrock γ is the total arriving rate into the network In [2], it is proved that Kleinrock forcast is an ef- fective framework to approximate the average delay of packet in data networks and the forcast fits well with the Jackson theorem Here we assume that a routing scheme is assigned originally and so the flow Fij is known As far as the expression (1) is concerned, it is clear that the minimum can be reached when the restriction is an equation Here we introduce a Lagrange multiplicator function L = ∑( p C ij (i , j ) ij + β and construct the Lagrange β Fij ) According to the knowledge of Lagrange product, we assume γ C ij − Fij that the derivative is equal to zero 1999 βFij ∂L = pij − =0 ∂C ij γ (C ij − Fij ) and we can get βFij γpij C ij = Fij + (2) put it into the constraint (1), and we can get T= Fij ∑C γ (i , j ) ij − Fij =∑ (i , j ) pij Fij βγ and so ⎛1 p ij Fij β =⎜ ∑ ⎜ T (i , j ) γ ⎝ ⎞ ⎟ ⎟ ⎠ (3) put it into the equation (2), and we can get C ij = Fij + T Fij γpij ∑ ( m,n ) p nm Fnm γ that is, ⎛ ⎜ C ij = Fij ⎜1 + ⎜⎜ γT ⎝ ∑ ( m,n ) p mn Fmn ⎞ ⎟ ⎟ pij Fij ⎟⎟ ⎠ (4) Finally, put it into the cost function, and we can get the optimized cost C Optimal = ∑ pij Fij + (i , j ) ( ∑ pij Fij ) γT (i , j ) (5) And now it is time to consider how to optimize the network according to the concrete flow Fij The problem can be solved by optimizing expression (5) to get Fij , however, (5) has so many local minimums that it is difficult to get the global minimum A more boring problem is that Fij and its corresponding C ij incline to zero in the local minimum, which may make the traffic focus on a small quantity of links, and thus decreases the reliability of the network According to the reasoning above, it is difficult to optimize Fij and C ij at the same time And even if the problem can be solved, the traffic will focus on some links with large capacity, which will lead to the condition that the requirement on the reliability of network can’t be met At the same time, the cost of the capacity is not linear to the capacity strictly speaking Thus, the only feasible method to solve the problem meeting the constraint is to adopt some heuristic algorithms Here we introduce a prototype of the iterative 2000 and heuristic algorithms Generally speaking, the algorithms begin with an existing topology, and iterates in changing the topology by modifying the capacity of one or more links At the beginning of iteration, a topology exists and after the iteration a new topology that can meet the requirement of delay and reliability but pay a lower cost is found We take the following assumptions: A predicted traffic demand exists; The demand and an routing model have determined a feasible topology In the topology, each link capacity is expressed as C ij , and the cost function is expressed as ∑D ij ( Fij ) , and the Dij can be (i , j ) described as the following equation: Dij ( Fij ) = Fij C ij − Fij + d ij Fij (6) Then Fij can be determined through minimizing the average packet delay D= ⎛ Fij ⎞ ⎜ ⎟ + d F ∑ ij ij ⎟ γ (i , j ) ⎜⎝ C ij − Fij ⎠ (7) A constraint on delay must be met Generally speaking, the delay got through (7) is required to be no larger than a certain threshold value; A constraint on reliability must be met For example, a k -connection network is required, that is, even if there are k − nodes that are disabled, the other nodes are all reachable; For a concrete evaluated network, there is a standard for cost; We are looking for a topology that meet the requirement of and mentioned above and pay a lowest cost in for it Here we present a heuristic algorithm working by iteration At the beginning of each iteration, there is a currently best topology and a topology to be tried The former meets the requirement on delay and reliability, and pays the least cost as far; the latter is the one to be evaluated in this iteration Here we assume that the original topology has been chosen by some special method The steps for iteration is the following: Step 1: Assigning the flow; calculate the flow Fij on the link (i, j ) with some special routing algorithm; Step 2: Inspecting the delay; estimate the average delay D under the condition of current topology with equation (7), and if D ≤ T ( T is a threshold) then proceed with step 3, else proceed with step 5; Step 3: Inspecting the reliability; test whether the trial topology meets the requirement on reliability, and if the requirement is met then proceed with step 4, else proceed with step 5; Step 4: Inspecting the amelioration of cost; replace the currently best topology with the trial topology if the cost of the trial topology is less than that of the currently best one; Step 5: Generating a new trial topology; generate a new trial topology generated by changing the capacity of one or more links with some heuristic methods, and then proceed with step for another iteration; 2001 Note that only when the trial topology in Step should meet the requirement in Step and Step 3, and the cost should be ameliorated, the trial topology can be accepted as the currently best topology The algorithm ends when no new trial topology will generate or when the cost can be ameliorated obviously In fact, the algorithm can’t guarantee that the final result is best; a method that can improve the result is that a new originating topology can be tried to initiate the algorithm Here we present a heuristic rule to generate new heuristic topology in step An approach is to decrease the capacity of a link whose Fij C ij is very low, or even withdraw the link Another possible approach is to increase the capacity of the links whose Fij C ij is so large that the requirement on delay can’t be met Thus, some links may be added or be deleted Here we present a method called saturation-cut, which aims to determine the partition zone between two sets, N and N The links of the partition zone is utilized high efficiently, and adding a link between N and N to lighten the high utility rate The working flow of the method is the following: Step 1: List all the non-directional links, and arrange them according to the value of max( Fij C ij , F ji C ji ) in a descending order; Step 2: Look for a link k to satisfy the following two conditions: a) if all the links above k are deleted, the network is also connected; b) if all the links above k and k are deleted, the network is non-connected and divided into two parts, N and N ; Step 3: Delete the least utilized links, and add a new link connecting a node in N and a node in N Fig.1 shows an example of the Saturation Cut strategy The number beside each arc of the graph is the utility rate of the link According to Fig.1, high utility rate links are removed temporarily until the network N2 N1 is divided into two parts, N and N When a 10 low utility rate link is deleted, a new link connect- 0.8 0.4 0.6 ing a node in N and a node in N is added deleted, we can take 0.5 0.75 There are also some other strategies to generate topologies for the step of the heuristic algorithm For example, when selecting the link to be 0.75 0.3 0.7 11 0.4 0.3 0.2 ∑ pij Cij for account 0.3 0.5 0.5 0.6 (i , j ) The link to be deleted THE RELIABILITY OF SOFTSWITCH The link to be added Saturation Cut NODE The reliability of the links has been ensured Fig An example of the Saturation Cut 2002 through the algorithm above Here we are taking measures to raise the reliability of softswitch nodes A fault-tolerant system is required to achieve the goal [3][4] In our scheme, state-sharing technology is adopted to provide reliable services in softswitch nodes In [5][6], state-sharing technology is introduced and applied in a SIP-based system Here in designing our scheme of deploying softswitch nodes, we use the state-sharing model for reference The scheme is shown as the following figure In the scheme shown as Fig.2, a text file is used as a medium for transporting SIP state update messages The scheme of a XXX system that implements the state-sharing mechanism consists of three components on each host STC (SUM-to-txt converter) Host Host FTS (File transfer script) XXX Server XXX Server TSC (Txt-to-SUM converter) MH SUM SM MH SUM SM The XXX server may be a SIP proxy STC STC server, a H.323 server or any other function Text file Text file TSC TSC deployed in softswitch node The STC and FTS FTS FTS are running in the server that generates/updates a state (source, i.e., host1), while TSC is running in the server (destinaFile transfer File transfer LAN tion, i.e., host2) that receives the text file containing the state update message (SUM) The SUM is generated in the message handler (MH) Fig The state-sharing scheme and added to the input queue of the state manager (SM) The STC takes a SUM from the MH as input and generates a text file as output The failure-detection and the fail-over management mechanisms of state-sharing technology are described in [6] According to the result of the experiment in [7], when a one-proxy scenario’s reliability is 98.95%, the reliability of the two-proxy scenario adopting the state-sharing technology is 99.98% EVALUATION OF THE HEURISTIC ALGORITHM With the node’s reliability provided with state-sharing, we assume that the reliability of the softswitch nodes is adequately ensured And in the concrete example to be shown, we only consider the reliability of the links And we assume that the links’ reliability can be ensured if each node has no less than two nodes as its neighbors The T in expression (1) is assumed to be seconds The initial cost shown in Fig.1 is 3542 The price matrix P and the flow matrix F is shown as the following: ⎡0 ⎢4 ⎢ ⎢3 ⎢ ⎢8 ⎢6 ⎢ P = ⎢7 ⎢10 10 ⎢ ⎢9 8 ⎢10 ⎢ ⎢13 12 13 ⎢ ⎣12 11 11 3 4 7 5 9 10 8 10 10 13 12⎤ 8 12 11⎥⎥ 10 8 13 11⎥ ⎥ 9⎥ 8⎥ ⎥ 10 ⎥ 4⎥ ⎥ 5⎥ 4⎥ ⎥ 4⎥ ⎥ 4 0⎦ ⎡ 25 28 0 0 0 0 ⎤ ⎢19 0 16 18 0 0 0 ⎥ ⎥ ⎢ ⎢22 0 17 21 0 0 ⎥ ⎥ ⎢ ⎢ 20 0 25 20 0 0 ⎥ ⎢ 16 20 17 14 24 0 ⎥ ⎥ ⎢ F = ⎢ 0 18 14 0 0 0 ⎥ ⎢ 0 22 0 19 24 ⎥ ⎥ ⎢ ⎢ 0 0 24 20 16 0 ⎥ ⎢ 0 0 0 14 0 12⎥ ⎥ ⎢ ⎢ 0 0 0 25 0 18⎥ ⎥ ⎢ ⎣ 0 0 0 0 15 15 ⎦ 2003 The routing method that we adopt in the algorithm is the N algorithm And the service traffic matrix is omitted here The results according to the strategies are the following: 10 0.6 0.5 0.65 0.75 0.7 0.6 0.6 Fig The result with heuristic strategy one 0.7 0.8 0.5 0.6 0.6 0.7 0.8 11 0.6 0.6 0.6 0.75 0.7 0.7 0.8 0.7 10 0.75 0.5 0.6 0.5 0.6 11 0.7 0.6 Fig The result with heuristic strategy two The cost in Fig.3 is 3156, and the cost in Fig.4 is 3095 The comparison between Fig.3 and Fig.4 shows that, if max( Fij C ij , F ji C ji ) is to be considered in the strategy, the utility rate in the links is very close, and if the cost is to be considered when deleting the low utility link, the flow will concentrate on the high capacity links which locates in the center of the network The heuristic algorithm is not the best optimized one, but it is scalable to various strategies with which the behavior of the network can be adjusted That is just what is needed in operating NGN REFERENCES: [1] M Gerla, L Kleinrock, “On the Topological Design of Distributed Computer Networks”, IEEE Transaction on Communications, Volume: 25, Issue: 1, Pages: 48 – 60, Jan 1977 [2] Z.G Wang, S Su, and J.L Chen, “A Research on the Call Routing of Softswitch”, Proceedings of ICCT2003, vol.2, Pages: 1594 – 1597, 2003 [3] A Helal, A Heddaya, and B Bhargava, Replication Techniques in Distributed Systems, Kluwer Academic Publishers, 1996 [4] G Coulouris, J Dollimore, and T Kindberg, Distributed Systems: Concepts and Design, 3rd Edition Addison Wesley, 2001 [5] M Bozinovski, L Gavrilovska, and R Prasad, “Report on State-sharing Concepts”, Internal Siemens -CPK project report, February 2002 [6] M Bozinovski, L Gavrilovska, and R Prasad, “Performance evaluation of a SIP-based state- sharing mechanism,” Proceedings of Vehicular Technology Conference, vol.4, Pages: 2041-2045, 2002 [7] M Bozinovski, L Gavrilovska, and R Prasad, “A State-sharing Mechanism for Providing Reliable SIP Sessions, Telecommunications in Modern Satellite, Cable and Broadcasting Service,” vol.1, Pages: 384388, 2003 2004 ... [2], a mixed scheme is presented In the scheme, the non-hierarchical architecture of softswitch is revised a little with Routing Agent added There are other schemes to organize NGN, and here we... location of the softswitch node and the traffic are known, and our aim is to organize the network meeting the requirement in traffic and performance with least cost It is a difficult and synthesized... into the cost function, and we can get the optimized cost C Optimal = ∑ pij Fij + (i , j ) ( ∑ pij Fij ) γT (i , j ) (5) And now it is time to consider how to optimize the network according to