Multicriterion Evolutionary Algorithm for Workload. Balancing of the Web Bank Servers

Transcription

1 06 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October 006 Multicriterion Evolutionary Algorith for Workload Balancing of the Web Bank Servers erzy Balicki Naval University of Gdynia ul. Sidowicza Gdynia Poland Suary Load balancing of the nternet bank can be ipleented by reduction of the workload of the bottleneck Web server. Load balancing iproves both a perforance of the coputer syste and the reliability of a server network. An evolutionary algorith iproved by introducing a tabu search procedure is discussed for solving ulti-criteria optiization proble of finding a set of Pareto-suboptial task assignents. A tabu utation is used for iniization the workload of the bottleneck coputer. Key words: Evolutionary algorith ulti-criterion optiization nternet bank systes. algorith has been considered for finding solutions to ultiobjective optiization probles related to task assignent that iniize a workload of a bottleneck coputer and the cost of achines []. The total nuerical perforance of workstations is another criterion for assessent of task assignent. Additionally a reliability of the syste is a criterion that is significant to assess the quality of a task assignent in bank systes. Consequently the proble with above criteria and soe eory constraints is discussed.. Model of Web bank network ntroduction Bank transactions can be parallel perfored subject to geographic spread of users. An average cost of a transaction through the nternet is lower several ties than the cost of a transaction carried out in the bank with the network of branches []. Furtherore the nternet transaction cost is significantly lower than the transaction cost for the cash achine network or for the financial advise syste through a phone network [3]. t is a decisive otivation of the tendency displayed itself in the Web banking expenditure has been doubled each year since 997 [4]. Besides coputer technology is suitable for ipleentation of bank transactions [5]. Coputer data can be processed stored and transferred with using the relevant coputer network technology. On the other hand evolutionary algoriths can inherit soe abilities of tabu search techniques to iprove a quality of obtained Pareto-suboptial solutions []. A tabu search is the powerful eta-heuristic approach that has been applied for crucial applications in engineering econoics and science [0]. An advanced of a ulticriteria evolutionary algorith with a tabu search has been suggested in []. A relevant allocation of progra odules in the Web bank network ay significantly reduce the entirety tie of a progra run by taking a benefit of the particular properties of soe workstations or an advantage of the balanced coputer load. An adaptive evolutionary Banks use the nternet to support their tasks that are related to fundaental services. t ay ipact on the acceleration of the service and it perits users to save tie. t iproves radically the cofort for the bank clients because they ay require an access to the database via the nternet to view the balance of the account or display a transaction history. On the other hand soe coplicated secure procedures have to be introduced and still developed to protect this access to inforation. A teporary deposit can be anaged reotely what saves tie of a client and gives an opportunity to an efficient anaging of financial eans. Furtherore a oney transfer between interior accounts is peritted for a user. n this way the differences of interest rates can be respected and an advantage fro a short-ter save can be taken. Data of a bank transaction history can be exported to a progra that supports the financial control of the hoe budget. Monitoring of transactions including those paid by a credit card gives inforation about the current rate of payent. Thus we can reasonably plan the other expenditures. A WWW hoe page of the bank often includes soe procedures for an estiation of an interest of the deposit. t supports aking decision about credits as well as deposits. Moreover the process of required data preparing is subject to shorten. An inforation service gives the arketing advantage for a bank and it is relevant for users that active anage their financial resources. t is an essential proposal of conventional banks at the beginning of the nternet using. Manuscript received October Manuscript revised October

2 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October These fundaental tasks can be relatively effortless ipleented by using the Apache server that is a powerful and flexible web server []. t ipleents the latest protocols and it is extreely configurable and extensible with other odules. What is ore it runs on crucial operating systes. This server is dynaically being developed and also it encourages user feedback through new ideas bug reports and patches. The Apache server ipleents any frequently requested features including databases for authentication. t allows setting up password-protected pages with assive nubers of authorized users without bogging down the server. Custoized responses to errors let setting up files or even soe scripts which are returned by the server in response to errors. t is possible to setting up a script to intercept nuerous server errors and perfor onthe-fly diagnostics. A transaction of payent fro a bank account requires a ore advanced approach related to the filling up a appropriate for in the secured web docuent. An order of payent is prepared and then it is send to the destination account. Data fro this order are translated by an additional progra odule to the forat of data that are applied in the national inter-bank counication syste. A persistent order of payent can be started or cancelled fro the user terinal too. A direct debit is another order of payent ade by a client but a purpose of this transaction is an account of user. Fors with invariable data are stored by the depository syste and soe ost recent parts of prepared for ay be altered only. Prediction and optiization of payents are an extended bank tasks. A schedule of payent can be found subject to the history of transactions. Prediction of the payents can be ade by using artificial intelligence techniques like neural networks or expert systes. The ters of transactions can be set up just before their deadlines as well as cheaper credits can be suggested. Above tasks are supported by bank servers and client browsers. Advanced tasks ake use of the interactivity flexibility and ultiedia property of the nternet what gives an innovative approach to bank services. To attract clients banks enrich their web pages by suppleentary and conteporary inforation about exchange rates tax regulations and stock exchange. Moreover the high-quality web service is supposed to be included as the preferred page to the browser of users what gives the opportunity to proote novel products or possibilities of cross selling. The WWW bank service ay recoends selling of the copleentary financial products that are not proposed by the bank. Life insurance pension funds stockholder services and deposit certificates of the other copanies are adissible on the web pages of the bank. n addition airline tickets tickets to cineas theatres and sport atches can be sell as well as DVDs CDs books or even holidays. That is a bank ought to create the nternet shop with the relevant catalog of financial and nonfinancial products. The WWW bank service is supposed to be profiled to adapt its content and an appearance to the personal preferences. The ost leading banks want to take advantage of the virtues of the worldwide distributed syste. Because a potential client can apply a cell phone to receive and send the written voice or ultiedia essages banks use these channels of counication to infor the clients about the state of their accounts. The obile network and a icro browser can be used in effective way especially if a obile phone cooperates with a coputer. Online advising can be ipleented by chat and conference software for written questions by a client and then reading answers during the real-tie dialog with a bank expert. A voice and vision counication can be carried out with using odern software. Payent can be perfored by sending an encoded nuber of a credit card with using the secure protocol. The safety of the transaction increases if the secure electronic transaction is used with the wallet software the certificate and the accounting center.. Reliability of bank software syste Clients of a bank generate requires to a bank coputer syste and these events are handled by web servers that anage the progra odules. A progra odule in the bank syste can be activated several ties during the interval of tie when the heaviest load occurs. A set of progra odules {M...M...M M } counicated to each others is considered aong the coherent coputer network with coputers located at the processing nodes fro the set W = { w... w i... w }. n results a set of progra odules is apped into the set of parallel perforing tasks {T...T v...t V } [8]. Let the task T v be executed on coputers taken fro the set of available coputer sorts Π = {... j... }. The overhead perforing tie of the task T v by the coputer j is represented by t vj. Let a coputer j be failed independently due to an exponential distribution with rate λ j. The longer tie of task execution the higher probability of coputer failure. We do not take into account of repair and recovery ties for failed coputer in assessing the logical correctness of an allocation. nstead we shall allocate tasks to coputers on which failures are least likely to occur during the execution of tasks. Coputers can be allocated to nodes

3 08 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October 006 and also tasks can be assigned to the in purpose to axiize the reliability function R defined as below: V R( = exp( λ jtvj xij ) () v= i= j= where if is assigned to the w x = j i ij 0 in the other case. if task T is assigned to w x = v i vi 0 in the other case x = [ x... x ] T xv x x x ij x j x. A coputer can be chosen several ties fro the set Π to be assigned to the node and one coputer is allocated to each node. On the other hand each task is allocated to any node. 3. Workload of the bottleneck coputer The cost of the parallel progra perforing is the ost coon used easure of an allowance evaluation. f the nuber of coputers is greater than 3 or the eory in a coputer is liited then a proble of the progra copletion cost iniization by task assignent is NP-hard []. The workload of the bottleneck coputer is another fundaental criterion for the evaluation of an allocation quality. A coputer with the heaviest task load is the bottleneck achine and its workload is a critical value that is supposed to be iniized [6]. The workload Z i + ( of a coputer allotted to the ith node for the allocation x is provided as follows: Z + i V = tvj xij + τ vu xui j= v= V V v= u= i= u v i i where τ vu the total counication tie between the task T v and T u. The workload Z + i ( of the bottleneck achine in the syste is the critical value that should be iniized: { + Zax( = in Zi }. (3) i= An optial task allocation for the cost of the parallel progra perforing does not guarantee the load stability on coputers in soe assignents because the workstation with the heaviest load ight possess a heavier workload than another bottleneck achine for the other task allocation in the distributed syste. The workload of the bottleneck coputer can be eployed as an () assessent easure of an allotent quality in systes where the iniization of a response tie is required too. Each coputer ought to be equipped with required capacities of resources for a progra run. Let the following eories z...z r...z R be available in an entire syste and let d jr be denote the capacity of eory z r in the workstation j. We assue the odule v reserves c vr units of eory z r and holds it during a progra run. Both values c vr and d jr are nonnegative and liited. The eory liit in a achine cannot be exceeded in the ith node what is written as bellows: V c x vr vi d x jr ij i = r = R. (4) v= j= The other easure of the task assignent is a cost of coputers: F ( x ) = i= j= κ x j ij where κ j corresponds to the cost of the coputer j. The fourth easure of the task assignent is a total aount of coputer perforance that can be deliberated according to the following forula: ~ F = ϑjx ij (6) i= j= where ϑ j is the nuerical perforance of the coputer j for assued bank task benchark. 4. Optiization of task assignent The total coputer cost is in conflict with the nuerical perforance of a distributed syste because the cost of a coputer usually depends on the quality of its coponents. Additionally the workload of the bottleneck coputer is in conflict with the cost of the syste. f the inexpensive and non-high quality coponents are used the load is oved to the high quality ones and workload of the bottleneck coputer increases. Let (X F P) be the ulti-criterion optiization question for finding the representation of Pareto-optial solutions [9]. t can be established as follows: ) X - an adissible solution set (5)

4 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October V v= j= X = { x B ( V+ ) cvr djrxij i = r = R; = v = V; xij = i = } B = {0 } i= j= ) F - a vector superiority criterion 4 F : X R (7) where R the set of real nubers ~ F( = [ R( Z ax ( F ( F ] T for x X ~ R( Z ax ( F ( and F are calculated by () (3) (5) and (6) respectively 3) P - the Pareto relation [7]. n above ultiobjective optiization proble related to bank task assignent a workload of a bottleneck coputer and the cost of achines are iniized. On the other hand a reliability of the syste and nuerical perforance are axiized. 5. Multi-criterion evolutionary algorith Evolutionary algoriths can be used for solving soe cobinatorial optiization probles for instance the Consensus Tree Proble [8]. An overview of evolutionary algoriths for ultiobjective optiization probles is subitted in [7]. The nae adaptive evolutionary algorith for evolutionary ones is related to the changing of soe paraeters as a crossover probability a utation rate a population size and the others during the searching [4 5]. For considered algorith the crossover probability is decreased due to the nuber of new generations [9]. Figure shows a schee of the adaptive ulticriterion evolutionary algorith called AMEA. This algorith perits on achieving better results for task assignent than the other ultiobjective evolutionary algoriths []. The preliinary population is created in a specific anner (Fig. line 3). Generated individuals satisfy constraints x = v V; i= vi = ij j= x = i = by introducing integer representation of chroosoes as follows: X = ( X... X v... XV X... Xi... X ) (8) where X = for v i = and X = for i j x ij =. Furtherore we assue that X v and X i. An integer representation of chroosoes lessen the quantity of allotents x fro (V+) to V. f x is adissible then the fitness function value (Fig. line 4) is estiated as below:. BEGN. t:=0 set the size of population L p :=/M M the length of x 3. generate initial population P(t) t the nuber of population 4. calculate ranks r( and fitness f x P( t) 5. finish:=false 6. WHLE NOT finish DO 7. BEGN /* new population */ 8. t:= t+ P (t) := 9. calculate selection probabilities p s ( x P ( t ) 0. FOR L/ DO. BEGN /* reproduction cycle */. WT-selection of a potential parent pair (ab) fro the P(t-) 3. S-crossover of a parent pair (ab) with the adaptive crossover t / T rate p c p : ax c = e 4. S-utation of an offspring pair (a'b') with the rate p 5. P(t):=P(t) (a'b'} 6. END 7. calculate ranks r( and fitness f x P( t) 8. F (P(t) converges OR t T a THEN finish:=true 9. END 0. END Fig.. Adaptive ulticriteria evolutionary algorith f = rax r( + Pax + (9) where r( denotes the rank of an adissible solution r( rax. n the two-weight tournaent selection (Fig. line ) the roulette rule is carried out twice. f two potential parents (a b) are adissible then a doinated individual is eliinated. f two adissible solutions nondoinate each other then they are accepted. f potential parents (a b) are non-adissible then an alternative with the saller penalty is selected. The fitness sharing technique can be substituted by the adaptive changing of ain paraeters. The quality of attained solutions increases in optiization probles with one criterion if the crossover probability and the utation rate are changed in an adaptive way proposed by Sheble and Britting [6]. The crossover point is randoly chosen for the chroosoe X in the S-crossover operator (Fig. line 3). The crossover probability is equal to at the initial population and each pair of potential parents is obligatory taken for the crossover procedure. A crossover operation supports the finding of a high-quality area in the search space. Especiallyit is

5 0 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October 006 iportant in the early search stage. f the nuber of generation t increases the crossover probability decreases t/t according to the forula p ax c = e. Soe search areas are identified after several crossover operations on parent pairs. That is why value p c is saller and it is equal to if t =00 for axiu nuber of population T ax =00. The final sallest value p c is A crossover probability decreases fro to exp(-) exponentially. n S-utation (Fig. line 4) the rando swap of the integer value by another one fro a feasible discrete set is applied. f the gene X v is randoly taken for utation the value is taken fro the set {... }. f the gene X i is randoly chosen the value is selected fro the set {... }. A utation rate is constant in the AMEA and it is equal to /M where M represents the nuber of decision variables. 6. Level of convergence to Pareto front The AMEA is able to find task assignent representation for several nuerical instances of ultiobjective optiization proble [7] that was confired by extended siulations. Quality of obtained solutions can be assessed by a level of convergence to the Pareto front []. Let the Pareto points {P P... P U } be given for a instance of the task assignent proble (7). f the AMEA finds the efficient point (A u A u P u3 A ) for the cost P u3 this point is associated to the uth Pareto result (P u P u P u3 P ) with the sae cost of coputers. The distance between points (A u A u P u3 A ) and (P u P u P u3 P ) is calculated according to an expression ( P ) ( ) ( ) u Au + Pu Au + Pu 4 Au 4. f the point (A u A u P u3 A ) is not discovered by the algorith we assue the distance is ( P A in) + ( P A ax ) + ( P A in) in u u u u where A u is the inial reliability of the syste A u ax is the axiu load of the bottleneck coputer and A in is the iniu perforance of the syste for the instance of proble (7). The level of convergence to the Pareto front is calculated as follows: U S = u= ( P A ) + ( P A ) + ( P A ) u u u u. (0) An average level S is calculated for several runs of the evolutionary algorith. 7. Tabu search as utation operation nitial nuerical exaples indicated that soe obtained task assignents had higher value of the workload of the bottleneck coputer than an optial one for instances with the nuber of tasks larger than 5. We suggest reducing this disadvantage by an introduction a tabu algorith [] as an advanced utation operator. According to this concept a new procedure should be added to the line 4 (Fig. ) as follows: 4 b) Tabu-utation of an offspring pair (a'b') with the constant tabu-utation probability p tabu A tabu-utation is ipleented as the tabu algorith TSZax [] that has been designed to find the task assignent with the iniu value of the function Z ax. Better outcoes fro the tabu utation are transfored into iproveent of solution quality obtained by the adaptive ulticriteria evolutionary algorith with tabu utation AMEA+. This algorith gives better results than the AMEA (Fig. ). After 00 generations an average level of Pareto set obtaining is.8% for the AMEA+ 3.4% for the AMEA. 30 test preliinary populations were prepared and each algorith starts 30 ties fro these populations. For integer constrained coding of chroosoes there are decision variables. The binary search space consists of.0737x0 9 chroosoes and includes adissible solutions. For the other instance with 5 tasks 4 nodes and 5 coputer sorts there are 80 binary decision variables. An average level of convergence to the Pareto set is 6.7% for the AMEA+ and 8.4% for the AMEA. A axial level is 8.5% for the AMEA+ and 9.6% for the AMEA. For this instance the average nuber of optial solutions is 9.5% for AMEA+ and.% for AMEA. An average level of convergence to the Pareto set an axial level and the average nuber of optial solutions becoe worse when the nuber of task nuber of nodes and nuber of coputer types increase. An average level is 34.6% for the AMEA+ versus 357% for the AMEA if the instance includes 50 tasks 4 nodes 5 coputer types and also 0 binary decision variables. Using tabu search as a utation operator causes that this hybrid algorith is a eetic algorith [3]. Meetic algoriths is a population-based approach for heuristic search in optiization probles. They are orders of agnitude faster than traditional genetic algorith for soe proble doains. They cobine local search heuristics with crossover operators. Since they are ost suitable for parallel coputers and distributed coputing

6 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October 006 systes they are called parallel genetic algoriths genetic local search or hybrid genetic algorith. 5 4 S [%] AMEA+ 9 9 AMEA t 00 Fig.. Outcoe convergence for the AMEA+ and AMEA Figure 3 shows the Pareto front for the test proble with 30 decision variables. We take into account two criteria F and Z ax. Pareto points are denoted as P P... P 5. Points deterined by AMEA+ are arked by circles. All points have been found by AMEA+ for this instance. F [MU] P P P 3 P 4 P 5 N* Fig. 3. Pareto front and results of AMEA+ 8. Concluding rearks Z ax [ TU ] The copetitiveness between banks and between banks and the other financial institutions directly caused the developent of the nternet banking. t forces finding ethods for iproving possibilities of distributed coputer systes. The load balancing ay iprove both perforance of the syste and the safety of the bottleneck hosts in the bank syste using the nternet. t can be obtained by task assignent as well as a selection of suitable coputer sorts. To find optial solutions the adaptive evolutionary algorith with a tabu utation AMEA+ is proposed. t is an advanced technique for finding Paretooptial task allocations in four-objective optiisation proble with the axiisation of the syste reliability and distributed syste perforance. Moreover the workload of the bottleneck coputer and the cost of coputers are iniized. Tabu search algorith can be used to iprove a quality of an offspring that is randoly chosen fro the current population aintained by an evolutionary algorith. The workload of the bottleneck coputer is selected to be iproved by the tabu algorith for the fourcriterion task assignent proble. Our future works will concern on a developent the cobination between tabu search and evolutionary algoriths for finding Pareto-optial solutions. Tabu search algoriths can be used for the local iproving of non-doinated solution in population. References [] Balicki. une Systes in Multi-criterion Evolutionary Algorith for Task Assignents in Distributed Coputer Syste. Lectures Notes in Coputer Science Vol pp [] Burkhardt T. Lohann K. (Eds.). Banking und electronic coerce in nternet. Springer Verlag Berlin 998. [3] Chissick M. Kelan A. Electronic coerce: law and practice. Sweet - Maxwell London 000. [4] Chorafas D. The Coercial banking handbook. McMillan Business London 999. [5] Cronin M.. (Ed) Banking and finance on the nternet ohn Wiley &Sons New York 997. [6] Chu W. W. Lan L. M. T. Task Allocation and Precedence Relations for Distributed Real-Tie Systes. EEE Transactions on Coputers Vol. C-36 No pp [7] Coello Coello C. A. Van Veldhuizen D. A. Laont G.B. Evolutionary Algoriths for Solving Multi-Objective Probles. Kluwer Acadeic Publishers New York 00. [8] Cotta C. On the Application of Evolutionary Algoriths to the Consensus Tree Proble. n G. R. Raidl. Gottlieb (Eds.): Evolutionary Coputation in Cobinatorial Optiization Proceedings on the 5th European Conference 005 Lausanne Switzerland pp [9] Deb K. Multi-Objective Optiization using Evolutionary Algoriths ohn Wiley & Sons Chichester. [0] Glover F. Laguna M Tabu Search. Kluver Acadeic Publishers Boston 00.

7 CSNS nternational ournal of Coputer Science and Network Security VOL.6 No.0 October 006 [] Hansen M. P. Tabu Search for Multicriteria Optiisation: MOTS. Proceedings of the Multi Criteria Decision Making 997 Cape Town South Africa. pp [] aszkiewicz A. Hapke M. Koinek P. Perforance of Multiple Objective Evolutionary Algoriths on a Distributed Syste Design Proble Coputational Experient. Lectures Notes in Coputer Science. Special ssue: Evolutionary Multi-Criterion Optiization by E. Zitzler K. Deb L. Thiele (Eds) Vol Springer-Verlag. pp [3] Merz P. Freisleben B. Meetic Algoriths and the Fitness Landscape of the Graph Bi-Partitioning Proble. Lecture Notes in Coputer Science Vol pp [4] Michalewicz Z. Genetic Algoriths + Data Structures = Evolution Progras. Springer Verlag Berlin Heidelberg New York 996. [5] Schaefer R. Kołodziej. Genetic Search Reinforced by the Population Hierarchy. n De ong K. A. Poli R. Rowe. E. (eds): Foundation of Genetic Algoriths Morgan Kaufan Publisher. 003 p [6] Sheble G. B. Britting K. Refined Genetic Algorith Econoic Dispatch Exaple. EEE Transactions on Power Systes Vol. 0 No pp [7] Van Veldhuizen D. V. Laont G. B. Multiobjective Evolutionary Algoriths: Analyzing The State-Of-The-Art. Evolutionary Coputation. Vol. 8 No. 000 pp [8] Weglarz. Nabrzyski. Schopf. Grid Resource Manageent: State of the Art and Future Trends. Kluwer Acadeic Publishers Boston 003. [9] Zitzler E. Deb K. and Thiele L. Coparison of Multiobjective Evolutionary Algoriths: Epirical Results. Evolutionary Coputation Vol. 8 No pp Gdynia. erzy Balicki received the M.S. and Ph.D. degrees in Coputer Science fro Warsaw University of Technology in 98 and 987 respectively. During he stayed in Coputer Center High School of Gdynia to study anageent systes obile systes and decision support systes. He is now with Distributed Coputer Laboratory of Naval University of