Load Balancing Algorithm of Switched Dynamic Iteration

Transcription

1 Send Orders for Reprnts to 236 The Open Cybernetcs & Systemcs Journal, 2015, 9, Load Balancng Algorthm of Swtched Dynamc Iteraton Open Access Chen Yansheng 1,3,* Wu Zhongkun 1 and Ren Jangtao 2 1 Guangdong Industry Techncal College, Guangzhou, Chna ; 2 School of Software, Sun Yat-Sen Unversty, Guangzhou, Chna ; 3 Kun Shan Unversty, Tanan, Tawan Abstract: In order to reduce busness latency and packet loss rate, to mprove the throughput of ntegraton of heterogeneous wreless network, to acheve load dversfcaton and to mprove end qualty of servce, whle there are many problems on the dropout rate of the tradtonal load balancng algorthm n processng throughput, delay and busness, therefore, gateway load balancng algorthm s proposed n ths paper. All termnals n the access network can reflect the effectveness of the average network load level of the network; ths algorthm wll gan weght of the load n the network of small busness termnal to swtch to the network load whch s lght. Frst, t defnes the heterogeneous networks and network termnal payoff functon utlty functons whch are used to characterze the experence and network QOS termnal load stuaton, and then presents the specfc processes of the gateway load balancng algorthm. Fnally, swtchng decsonal load balancng algorthm, proposed by Yan X, etc. s compared wth smulaton experments and t shows that: the proposed gateway load balancng algorthm has strong robustness to acheve network load balancng and to acheve a balanced use of network resource. Keywords: Effcency, loadng dfferences, real-tme busness, swtchng decson. 1. INTRODUCTION Load balancng s an mportant way, whch makes full use of heterogeneous wreless network resources. Through the load balancng among the heterogeneous networks, the hgh probablty of network load can be reduced, the overall utlzaton of network resources s mproved and the blockng probablty s reduced to provde users a better QOS, so the load balancng between the networks s also an mportant aspect of consderng the access algorthm selected [1-3]. The user can only access a knd of network at the same tme wth the tradtonal hard load balancng servce, whch can not satsfy dfferentaton of the user servce, resultng n partally utlzed heterogeneous network resources and hgher traffc blockng rato. Lterature [4] proposes the soft load balancng algorthm, whch dynamcally changes the best rato of IP flow; when the network load s heavy, each network sub-flow rate of accessng users s consstently mprove, whle when the network load s lght, there s a dfferences between the needs of users busness rate and wreless resources [5-7]. The man purpose of heterogeneous networks s to acheve a varety of fast, relable and secure exchange and transmsson of nformaton, that s, through the network to provde a wde range of hgh qualty servces, thus, busness development, prosperty and evoluton s the foundaton and a key procedure of network development, prosperty and evoluton [8-10]. Ths pont s especally evdent snce 2000, whch s durng a commercal 3G network and the development process X/15 of the Internet. As a whole, moble communcatons operators can provde a varety of servces through a varety of networks, and fully guarantee the user n the network to enoy a varety of servces, to mprove the qualty of the user experence. It s an nevtable tendency of development of wreless networks [11-14]. The ntegraton of heterogeneous networks has become the developmental drecton of next-generaton wreless networks, wreless resources shared s the premer ntenton for the ntegraton of heterogeneous wreless networks and reasonable heterogeneous network resource schedulng s a key technologes to acheve effcent rado resource sharng [15-17]. Load balancng s determned by multple servers n a symmetrcal manner to form a collecton of servers, each server has the equvalent status, and t can provde servce outsde ndependently wthout the ad of other servers. Through some sort of load balancng technology that s to be sent to external requests whch are evenly dstrbuted to the symmetrcal structure of a server, and the server receves the request ndependently and responds to customers requests [18]. Load balancng evenly gves out clent requests to a server array, amng at provdng quck access to mportant data, to solve a large number of concurrent access to servce ssues. Network load balancng can effectvely reduce the mbalance of resource utlzaton among heterogeneous networks, ratonal management of network resources s one mportant way. In the fuson of heterogeneous wreless network, termnals can carry out dynamc network choces, accessng and swtchng, to acheve load balancng of the RAN n heterogeneous rado access network (Rado access network, RAN), thereby mproves network throughput and overall performance. Currently, the network load balancng research has focused on homogeneous network load balancng between dfferent cells and certan types of load balanc Bentham Open

2 Load Balancng Algorthm of Swtched Dynamc Iteraton The Open Cybernetcs & Systemcs Journal, 2015, Volume ng among heterogeneous networks. Depended on the mplementaton of exstng research, methods can be dvded nto two categores: one s the accessng load balancng, the other s swtched load balancng. Compared wth the accesstype load balancng, swtchng load balancng has ts quck response, fast convergence advantages. However, the key premse of load balancng swtch s correct assessment of each cell load. For homogeneous network, the load of each cell s avalable and can be stated by unfed ndcators. However, n heterogeneous wreless network envronment, the busness type, resource allocaton, and the assurance capabltes of servce qualty of the heterogeneous network, etc. are dfferent. How to measure and compare the heterogeneous network load becomes a problem. LOUHA K put forward the concept of soft load balancng - the downlnk IP groupng nto sub-streams, each substream accessng to dfferent wreless network. Ths method can mprove resource utlzaton n heterogeneous wreless networks. But when SON H and LOUHA K nvestgated the best dverson rates of n the case of specfc network topology and deal channel, the fndngs dd not have unversal applcablty. Load balancng algorthm proposed by SHI Wenxao, etc [19-22]. Presentng a method that can dynamcally change optmal splttng rato of IP flow; when the network load s heavy, t can constantly adust the rate of user accessng to each network sub-flow. However, t dd not consder that when the load s lght, there s a dfference between rate requrements of user busness and wreless servce. Meanwhle, Sun Zhuo also ponted out that as the rado resource unts were approprately allocated to the approprate users to better meet user QOS, t wll also mprove the utlzaton of rado resources [23-25]. For the above what we has dscussed, a gateway load balancng algorthm s put forward, whch s based on the QOS (Qualty of servce, QOS), and the algorthm frst defnes a generalzaton for payoff functon of network termnal and the utlty functon of heterogeneous networks respectvely, to characterze the qualty of servce and network load termnal stuaton. Then, n a dynamc, teratve manner, the heavest load of the network QOS gans and lower resource effcency of termnal can be mproved and scheduled to gan network lghtest load n QOS revenue, to reduce load varaton of between the networks and mprove effcency n the use of network resources. Ths paper manly made a work n the followng areas expansvely and nnovatvely: (a) When dealng wth throughput, latency and packet loss rate on busness, the tradtonal load balancng algorthm n heterogeneous wreless network has many problems, so gateway load balancng algorthm s proposed. The QOS ncome of generalzed users and network utlty of the algorthm, whch s based on the features of wreless busness, are able to characterze the qualty of servce experence n the termnal network and network load condtons. And for a varety of heterogeneous network t s unversal. Among them, the network utlty s unversalty to heterogeneous network makes load condtons of each heterogeneous network comparable. TTERATIVE algorthm, by schedulng the QOS gans n the network wth the heavest load and the termnal wth the lower resource effcency to the network that s able to mprove the QOS beneft wth the lghtest load, whch can acheve swtchng load balancng among heterogeneous networks. (b) In order to further valdate the correctness and effcency of the proposed gateway load balancng algorthm about the packet loss rate, packet delay and throughput performance, the author made a comparson wth swtchng decsonal algorthm proposed by Yan X for load balancng, and smulaton experments evaluated ts performance of gateway load balancng algorthm based on QOS by usng OMNET Settng there are two types of and RAN n the system, each type of RAN has 2. Both algorthms at packet loss rate of a constant rate traffc remaned unchanged, but the proposed algorthm n ths paper sgnfcantly reduces packet loss rate of the real-tme varable rate busness and packet delay; as the load ncreases, the proposed algorthm can sgnfcantly mprove the whole network throughput. Experments show that: QOS-based gateway load balancng algorthm has strong robustness, and t can sgnfcantly mprove the ntegraton of heterogeneous network throughput, reduce busness latency and packet loss rate. It can reach the effects of mprovng effcency of network resource utlzaton. 2. PROPOSED SCHEME The core dea of algorthm s: the QOS ncome of termnal end can reflects the current level of network qualty of servce receved, the greater the benefts s, the better the resultng qualty of servce s, and vce versa; the average QOS beneft of all termnals n a accessng network (herenafter defned as a network utlty) can reflects the load level of the network, the larger the average gan of the termnal s, the load on the network s lghter, and vce versa. In order to acheve dversfcaton and to ncrease the servce qualty of load termnal, the algorthm wll swtch small busnesses wth gan heavy load n the network to a lghter termnal network load. In order to carry out the termnal to select the RAN and ts access effectvely and dynamcally, the multmode termnal wll experence unfed management from the network sde, whch wll be completed by the network sde management entty (Network sde manager, NSM). The termnal wll nteract wth NSM through the termnal-sde management entty (Termnal-sde manager, TSM), dynamcally achevng refactorng of swtchng/accessng. The nteracton between NSM and TSM s completed through management control channel (Management and control channel, MCC). NSM s deployed n the core network, and s shared by a pluralty of RAN. RAN wll convey each context nformaton to NSM, then NSM transfer each context nformaton of RAN to the termnal for the decsons through the MCC downlnk transmsson. TSM of each termnal sends context nformaton of the termnal through uplnk transmsson of the MCC to NSM. Based on context nformaton of RAN and termnal, NSM uses the approprate network selecton algorthm to develop strateges and polces ssued under the varous termnals. Termnal then chooses accordng to ther needs and network reconfguraton decsons and confgures

3 238 The Open Cybernetcs & Systemcs Journal, 2015, Volume 9 Yansheng et al. Table 1. Wreless network traffc types and ther QOS requrements. Rate of Change The Mnmum Rate Maxmum Rate Tme Delay Requrements A Typcal Busness Real-tme busness constant r mn = r max r mn = r max d max VoIP varable r mn r max d max MPEG The real-tme busness varable r mn r max HTTP to access the approprate RAN. The paper wll assume the termnal n the network / nter-cell handover fast enough, and thus, the load balancng process, due to swtchng delay caused by the upper rsk of busness dsrupton can be gnored QoS Revenue and RAN Utlty Dfferent types of wreless network servces have dfferent QOS requrements. Based on the characterstcs of the varous servces, wreless servces can be classfed nto three types of basc servces, as shown n Table 1. Accordng to real-tme requrements, the wreless busness can be classfed nto real-tme busness (Real tme, RT) and non-real-tme servce (Non-real tme, NRT). Accordng to whether the rate can change or not, real-tme servce has been dvded nto two types of constant rate and varable rate. Mnmum servce tme at a constant rate mn and the maxmum rate requrements max are equal, that s the rate are unchanged. The varable rate real-tme servce s possessed of the mnmum and maxmum rate requrements. When the watng tme of a real-tme servce exceeds the maxmum packet delay tolerance d max, the packet wll be dscarded. Non-real-tme servce needs not to delay, and the mnmum bandwdth can become zero. In order to characterze the obtaned termnal from the current network qualty of servce, based on the QOS requrements of dfferent busness, s gmond functon to construct the termnal payoff functon s used. So suppose J s the set of knds of RAN, I represents the set of termnals n the network, defnng an accessng termnal I of RAN J QOS beneft functon s as follows: (1 U = ( exp( m d d e d max d ) m 1 1+ exp( m d d e d mn d ) r ).BT ).BRT For real-tme servces, at the premse to meet the mnmum bandwdth, usng an average delay d to measure user gans, the smaller the tme delay s, the hgher the gan s; for non-real-tme servces to the user, usng average speed r of the user gans to measure, the larger the rate s, the hgher the ncome s; (1) d e d d e d max r d If delay for real-tme servces the normalzed, wheren denotes the expectancy of average delay of real-tme servces: e max r As the normalzaton about Non-real-tme servces rate, t helps to ensure a mnmum rate of non-real-tme servces; and s constant parameters, whch determnes the steepness of the curve of the functon, the larger the value s, the steeper the curve changes, the hgher the senstvty to the end qualty of servce s. Formula (1) as defned n revenue functon reflects QOS-awareness of termnal, the functon maps a pluralty of QOS parameters wth reasonable percepton or experence for the user to QOS level, gves a measurement of the QOS of dfferent users by usng unform quantzaton levels standards. To characterze the load level of the accessng network, the wreless access network defnes the utlty of all the termnals connected to the network average of QOS beneft. Suppose at a tme, a termnal can only access a RAN, then the gan RAN J I can be expressed as: n R =, 0 I J (2) J I 1, = 0 wheren, = 1 termnal nt o RAN 0 other Obvously, the heaver network load wll result n lower average QOS beneft of termnal, otherwse the termnal average QOS gans wll be hgher. Therefore, the average QOS beneft of the termnal, namely the network load of the network utlty can reflects the stuaton. Network utlty s hgher, ndcatng that the network load s lghter, otherwse t ndcates the network load s heaver Load Balancng Algorthm Desgn When the ntegraton of heterogeneous networks presents a state of uneven load dstrbuton, load balancng algorthm

4 Load Balancng Algorthm of Swtched Dynamc Iteraton The Open Cybernetcs & Systemcs Journal, 2015, Volume based on QOS -awareness wll be trggered. Network load dstrbuton algorthm wll undergoes teratve adustments. Each teraton process can be descrbed as: (1) Select a heavy-duty accessng network from an entre network called upon burdens; (2) Select offloadng termnal from the accessng network, as a swtch to a dfferent accessng network of the termnal, called subect to swtch the termnal; (3) Select an accessng network wth a lghter load from subect to swtch the termnal, swtched to as the purpose of swtchng the termnal accessng network, called upon subect to ncreasng negatve network; (4) If the selected network can be added to mprove the negatve termnal, the qualty of servce to be swtched, then the swtch termnal s swtched to be negatve to the network whch s to be added nto the next teraton; otherwse, the termnal remans n the burden upon the network, then offloadng network s selected to be another termnal as a termnal to be swtched and t s performed (3) and (4) agan. If the burdens upon all termnals n the network choose to stay n the accessng network to be reduce the burden, t s consdered as a more balanced dstrbuton of network load that can no longer mprove the algorthm ends. The core of load balancng algorthm based on QOS - awareness s: Web-based utlty accessng network selecton to be burdens, to be based on the weghted QOS gans selecton of subectng to swtch termnals, termnal and networkbased utlty and accessblty testng negatve access network to be ncreased selecton Web-Based Utlty Accessng Network Selecton to be Burdens In order to make load balancng rapdly converge, algorthms n each teraton fnd the heavest load of the whole network accessng network, and select one of the approprate termnal swtch to other accessng networks. Accordng to the defnton and analyss of the effectveness of the network utlty n the secton of 3.1, t can effectvely reflect the access network load condtons. Therefore, the algorthm selects the lowest utlty network accessng network as a network to be burdens. If pendng burdens network denoted J I, then: r n = arg mn m J r = arg mn m I The Weghted Selecton of Subectng to Swtch Termnal about QoS Beneft to be Based on In order to make load balancng rapdly converge, algorthms n each teraton fnd the heavest load of the whole network accessng network, and select one of the approprate termnal swtch to other accessng networks. When the accessng network subect to reducng the burdens selects to (3) swtch's termnal, t not only needs to consder the qualty of servce experence of termnal at the correspondng to the accessng network, namely t should choose a lower the QOS experence n order to the user expects to swtch to other network medum to get mproved; and t needs to consder the users rado resource utlzaton effcency to be burdens n the accessng network, whch should tend to choose the channel condtons of poor termnal to swtch to other networks, n order to termnate ther treatment on resources neffcent usage n subectng to reducng the burdens n the accessng network channel. Consderng two aspects as defned n the termnal n the weghted QOS beneft functon of the RAN s as follows: J * = a J J * = (a + J ) Wheren the weghtng factor a reflects resource utlzaton effcency of the termnal n the rado accessng network, whch s defned as: a = J ( ) J max a = u g J ( ) s the actual rate that each unt bandwdth obtaned for the accessng termnal to the accessng network ; t ndcates channel condton between the termnal and max accessng network ; R, presents the maxmum rate can obtan per unt of bandwdth from accessng termnal to the accessng network theoretcally. Thus, the greater a s, ndcatng that the channel condtons s better between termnals and accessng network the termnal has a good utlzaton effcency n the accessng network channel. Consderng the qualty of servce experence and rado resource utlzaton of termnal accessng network, algorthm selects the lowest weghted termnal of subectng to reducng the burdens based on QOS gans as a termnal to be swtched. So suppose s the set of e, all of the access termnals, then e, the termnal to be swtched, selected n the offloadng accessng network, s supposed to be met: e = arg mn.t ( * n) { e * n} The Selecton of the Accessng Network Subect to be Negatve Growth When the termnal to be swtched selects e, the ntendng accessng network, for the purpose of swtchng accessng networks, on the one hand, t needs to dentfy whether the termnal s wthn the coverage area of the accessng network e, and the remanng capacty of e can (4) (5) (6)

5 240 The Open Cybernetcs & Systemcs Journal, 2015, Volume 9 Yansheng et al. e h, h meet the mnmum rate requrements of. That the ntendng accessng network e shall meet: e n (r n,e ) 0 e max + mn max r (7) Among whch, r max represents the maxmum network capacty of accessng networks e. On the other hand, for the beneft of rapd convergence load balancng, you should choose a lghter network load to be swtched as the ntendng accessng network. Thus, the algorthm for all the condton (7) of the accessng network ( except the accessng termnal subect to beng swtched and reducng the burdens) of a collecton (referred to as ), select the accessng network wth hghest utlty network, as the purpose of the accessng network termnal to be swtched, the network to be negatve growth can be expressed as: = arg max m (8) mn QoS-awareness Load Balancng Algorthm Based on the above analyss, the desgnaton of gateway load balancng algorthm process s as follows: Intalzaton: Let J represents algorthm converged network wthn the scope of all the heterogeneous collecton of RAN, I represents the set of all termnals n the network; / / Algorthm carres through load balancng to a certan geographcal area of heterogeneous converged network. Step 1: Select (3) to satsfy the access network e as a network to be the network subect to reducng the burdens; as a collecton of all termnals e swtch the termnal to be set = e. connected, optonally / / selects the heavest accessng network, ready to be moved to another part of the load n the accessng network. Step 2: In e, select the termnal e = arg mn m * { } as to be swtchng termnals. / / selects the termnal wth a lower servce qualty of experence and resource utlzaton, ready to be swtched to another accessng network. Step 3: Among other accessng network optons except e, select to meet (7) formula and (8) as accessng network to be negatve growth. / / selects an accessng network termnal wth a lghter load to be swtched as the ntendng accessng network. Step 4: Swtch the termnal to be swtched e to the accessng network to be negatve growth e, f The termnal e swtch to, then return to step 1; otherwse termnal e gong back to, whle the optonal ter- mnal to be swtch can s updated to e = form step 5. { e } and per- / / If the accessng network can be ncreased to mprove the negatve termnal of the qualty of servce to be swtched, the adustment s successful and re-select the accessng network of subectng to reducng the burdens to carry out a new round of adustment; otherwse the termnal to be swtched from the optonal subect can be removed from the termnal concentrator. Step 5: If e 0, then go back to step 2; / / From the accessng network of pendng burdens to be swtched of the termnal concentrator, choose optonal weghted QOS beneft low end tmes, try to swtch to another accessng network. Otherwse, the algorthm termnates. / / Accessng network to reduce the burden of all the termnals are choose to stay n the accessng network, unable to further mprove the extent of the network load balancng, t can be consdered that the state has acheved load balancng. It can be seen that network utlty and termnal benefts can acheve quanttatve balance from the algorthm through a unfed QOS revenue functon desgnaton. By choosng and swtchng network and termnal QOS beneft between the network utlty and termnals tends to equlbrum. The cost s based on algorthm desgnaton, need to run on the network and termnal management entty executon algorthm, and the correspondng QOS nformaton and nteractve network selecton strategy. Network sde and termnal sde executng algorthm, network management entty, can be naturally and easly completed by heterogeneous network convergence n the framework of NSM and TSM, nteracton of nformaton and strateges can be completed by the contextual messages of the MCC. In the current level of technology, NSM and TSM tself has a powerful computng capabltes, and load balancng does not requre strct real-tme and nteractve nformaton and data of selecton strateges for QOS s a small amount, therefore the proposed algorthm can obtan mproved network and termnal performance sgnfcantly at lttle cost. 3. EXPERIMENTAL RESULTS By usng OMNET , t can evaluate ts performance of load balancng algorthm based on QOS-awareness. Supposng that, there are two types of and RAN n the system, each type of RAN has 2. Smulaton only consder the upstream traffc, RAN adopts the TDD mode of sngle carrer, each TDD frame n the uplnk and downlnk frames has each half; RAN uses DCF mode. There are 30 supposed user (termnal), each user uses only one busness, each has 10 busness users. Settng the densty of user n RAN, the user from the SNR to the

6 Load Balancng Algorthm of Swtched Dynamc Iteraton The Open Cybernetcs & Systemcs Journal, 2015, Volume Table 2. Expermental parameters. Parameter Names The Parameter Value Parameter Names The Parameter Value The frame length/ms 1 Packet length/bt 1000 The dsabled when the tme/ms w xy /ms Frame when the number of dsabled 5000 w xy /ms 100 The dsabled when the tme/ms x 0.53 The SIFS length/ms y 0.02 The DIFS length/ms Table 3. Smulaton results. SN Busness Flow Rate on Average (Kbt/s) Real tme constant varable bt rate of packet loss rate (%) The average packet delay of tme busness (ms) The throughput of whole network (Mbt/s) HDLBA QALBA HDLBA QALBA HDLBA QALBA RAN randomly changed. Users can access a RAN at the same moment. Servce packets arrve to Posson dstrbuton. The mnmum rate of Varable rate servces reached 1/2 of average rate. Users ntally access network, whose selectons are based on SINR (Sgnal-to-nterference plus nose rato, SINR) crteron, that s, channel condtons between the user and the varous RAN, dynamcally select the hghest RAN of SINR to access, whle accordng to network selecton prncple of / converged network users to access, busness users access to networks real-tmely at a constant rate. The assocated parameter settngs used by network smulaton are shown n Table 2. In order to verfy the performance of the proposed gateway load balancng algorthm, by usng handover decson load balancng algorthm (Handoff decson load-balancng algorthm, HDLBA) proposed by Yan X, etc as a compared algorthm, the packet loss rate, packet delay and throughput performance were compared. Table 3. Shows the smulaton results of the comparson. Table 3 parts for Real tme constant varable bt rate of packet loss and The average packet delay of tme busness show that the changng stuaton of real tme constant bt rate and real tme constant varable bt rate, average packet loss rate and packet delay varaton when the average rate of each connecton from 100Kbt /s ncreased to 450Kbt /s. As can be seen, the proposed gateway load balancng algorthm sgnfcantly reduces the real-tme varable rate, packet loss rate and packet delay; whle the average delay and packet loss rate of real-tme busness a constant rate n the two algorthms s bascally to keep unchanged. It s because the prortes safeguard mechansm of networks for realtme busness wth a constant rate can guarantee QOS servce of real-tme at a constant rate, whle the two algorthms, whch can ensure a constant rate of real busness users, always stay n the network, and get a guaranteed qualty of servce. Table 3 part of the throughput of whole network, shows as the load ncreases, the proposed gateway load balancng algorthm can sgnfcantly mprove the throughput of the whole network. Smulaton results show that: QALBA algorthm can balance the network load, and compared to the tradtonal MLB algorthm and DLBD algorthm, the average blockng rate of packet servce and the throughput performance have been mproved sgnfcantly, and the robustness of algorthm s really strong, whch can acheve network load balancng to acheve a balanced use of network resources. 4. CONCLUSION For the ntegraton of heterogeneous wreless network communcaton scenaro, the network load balancng algorthm was proposed based on the QOS, whch s fallen nto swtchable load balancng algorthm. Algorthm s based on QOS gans and network utlty of a generalzed feature for wreless busness users, and t s able to characterze the qualty of servce termnal network experence and network load condtons, and t s unversally applcable for a varety

7 242 The Open Cybernetcs & Systemcs Journal, 2015, Volume 9 Yansheng et al. of heterogeneous network. Among them, the unversalty of network utlty to heterogeneous network makes heterogeneous network load comparablty comparable, able to acheve swtchng between heterogeneous network load balancng. Smulaton results show that the proposed gateway load balancng algorthm can mprove ntegraton of heterogeneous network throughput, reduce busness latency and packet loss rate, wth strong robustness to acheve network load balancng and to acheve a balanced use of network resources. CONFLICT OF INTEREST The authors confrm that ths artcle content has no conflct of nterest. ACKNOWLEDGEMENTS Ths work was fnancally supported by Guangdong Industry Techncal College Foundaton (KJ ). REFERENCES [1] K. Suhar, and F.L. Gaol, The measurement of optmzaton performance of managed servce dvson wth ITIL framework usng statstcal process control, Journal of Networks, vol. 8, no. 3, pp , [2] Y. Guang, Y. Zhu, C. 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