Research on a Method of Geographical Information Service Load Balancing

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1 Research on a Method of Geographcal Informaton Servce oad Balancng Heyuan a, Yongxng a, Xue Zhyong a, Feng Tao a a X an Research Insttute of Surveyng and Mappng, X an, Shaanx, Chna; @qq.com; yongxngl2017@163.com; zhyongxue2017@163.com; @qq.com Abstract: Wth the development of geographcal nformaton servce technologes, ho to acheve the ntellgent schedulng and hgh concurrent access of geographcal nformaton servce resources based on load balancng s a focal pont of current study. Ths paper presents an algorthm of dynamc load balancng. In the algorthm, types of geographcal nformaton servce are matched th the correspondng server group, then the RED algorthm s combned th the method of double threshold effectvely to udge the load state of serve node, fnally the servce s scheduled based on eghted probablstc n a certan perod. At the last, an experment system s bult based on cluster server, hch proves the effectveness of the method presented n ths paper. Keyords: geographcal nformaton servce, load balancng, ntellgent schedulng, concurrent access 1. Introducton Geographcal nformaton s playng an ncreasngly mportant role on government management decsonmakng, natonal defense safety and people's lvng standards mprove. Along th our country economy and the advancement of natonal defense nformatzaton constructon, agences at all levels and the publc s demand to authorty, relable geographc nformaton servce ncreases, need to mplement comprehensve utlzaton and onlne servces of mult-scale, mult-type of geographc nformaton resources(chen et al. 2009).The current netork geographc nformaton servce system s facng the unpredctable challenge of concurrency groth, capacty lmts and system response, and geographc nformaton servce scalablty and avalablty s beng more and more attenton(chen et al. 2013).Geographc nformaton servce dynamc load balancng s to solve ho to make vrtual multple servce node based on the Web server cluster nto a logcally unfed "super" geographc nformaton servce center, mplement the vrtualzaton management and ntellgent schedulng for each servce node thn the cluster resources, n order to support the servce of dynamc bndng, fnd and replace, thus mprove the concurrent access ablty of cluster system. Such as amazon servces can be on-demand ntellgent schedulng system capacty (such as servers, storage, and netork banddth), can be flexble deployment a varety of servces from provder re-sources, thout the need for extra confguraton for the uncertan demand n advance(wang et al. 2010). Among exstng netork Map servce systems, the Google Map has the ntellgent schedulng ablty of geographc nformaton servce resources th the support of dynamc load balance. In the feld of other Web servces, common load balance algorthm are rotaton schedulng algorthm (RR) and local percepton request dstrbuton algorthm (ARD). The man problems of the RR algorthm s not consderng the stuaton of load each servce node, resultng n a declne n performance of the system. If a certan type of servce request rate s hgh, the algorthm of ARD leads to a node of the utlzaton rate s very hgh, and the other nodes are dle for a long tme, astng server resources(genova and Chrstensen 2000; Ren et al. 2010). In ths paper, e proposed a dynamc load balancng algorthm for multple servce node. Accordng to servce node n the cluster, usng desgned load balancng algorthm to share a large number of concurrent access to busness to multple processng nodes respectvely, reducng the tme for a response, so as to acheve more servce node's geographcal nformaton servce vrtualzaton and global load balancng. 2. General dea of the algorthm The basc process of dynamc load balancng algorthm ncludes: recevng concurrent requests of users, load nformaton of server collecton feedback on the frst task scheduler, determnng the server load condton, selectng the best target server handlng user requests to access concurrently. Ths algorthm adopts the centralzed schedulng polcy, the geographc nformaton servce node real-tme montorng ther server load nformaton, and feedback to the front-end server at a certan perod, and then based on threshold method and RED algorthm for determnng the node load state and obtan the node dynamc resdual capacty. If the node s overload, there ll be an effectve arnng. By classfyng the geographc nformaton servce (conventonal geographc nformaton servce types are dvded nto map brosng, query, analyss, data subscrpton and donload, and metadata drectory servce, etc.), match a certan type of geographc nformaton servce to the specfc applcaton server group, on the bass of the resdual capacty of the node dynamcally determnng the schedulng eghts of multple nodes. The node remanng capacty s proportonal to the schedulng eghts, and the node load

2 2 of 5 current s nversely proportonal to the schedulng eghts, fnally determne the optmum target server handlng user requests to access concurrently. The applcaton of model dagram s shon n Fg 1. Concurrency control Scheduler Msson transmt Router feedback cycle s T. Ths algorthm adopts the dstrbuted load n-formaton collecton, namely the cluster servce node s montorng dynamc real-tme load nformaton, and then dynamc feedback to the front-end perodc task scheduler. W = {1, 2,..., m } s defned as the cluster server, (1 m) s defned as the number server nodes n a cluster, m s defned as node number. Server current load = ( cpu, I / O, mem, net ) cpu, I / O, mem, net are defned respectvely as the current CPU usage, dsk I/O usage, memory usage and netork banddth utlzaton rate of current servce node. Stchboard Server processng poer C = (Ccpu, CI / O, Cmem, Cnet ), Ccpu, CI / O, Cmem, Cnet Servcer Fg. 1. Dynamc oad Balancng Algorthm Model of Geographc Informaton Servce When user concurrent access to a geographcal nformaton servce, load balance algorthm comprehensvely consders the load ablty and the realtme servce value, contanng four server parameter, respectvely s: the CPU usage, memory usage, netork banddth utlzaton and dsk I/O utlzaton. Servce request va a router forardng to the task scheduler, the scheduler collects load nformaton at a certan cycle, and on the bass of the eghted value of load factor to determne the best target server. The target server ll respond then servce content s dssemnated through stches and routers drectly to the user. In one cycle, a geographcal nformaton servce for the user request s S, n the process load balance can be acheved by the follong steps, as s shon n Fg 2. Msson scheduler Request GIS servce T for the cycle Feedback dynamcally Refresh the nformaton of the servce group, collectng the nformaton of all pont and calculatng the value of comprehensve eghtng probablty true Match the accordng servce group n the servce colony Judge the type of GIS servce False, go on crculaton Reach the cycle T? Probablty value based on eghtng Found the target servcer(th the max ablty to solve the dynamc remander) Unoverload Reselectng among other servcer group Servcer W s overload? are defned respectvely as servce node rate of CPU, dsk I/O speed, memory capacty and netork throughput. Geographc nformaton servce type collecton S = {s1, s2, s3, s4 } s (1 4), s defned as the number geographc nformaton servce type, among them s1, s2, s3, s4, are defned respectvely as map brosng, query analyss, data subscrpton and donload, metadata and drectory servces. When the same server support dfferent types of geographc nformaton servces, t has the dfferent effect on ts load nformaton [5].Accordng to the dfferences n dfferent geographc nformaton servce type occupes system resources, set a eght vector for each knd of geographc nformaton servce type I /O a, a mem, a net a = (a cpu a = 1,a ), [0,3] has the hghest eght component sad that the geographc nformaton servce the more dependence on the correspondng resources. s Set server provdes servces of type, C, as the node processng poer, as the load of utlzaton, Cm as a benchmark server processng ablty, a as the correspondng eght vector to represent s geographc nformaton servce, the server of the real-tme load rato value If all the servcer of the servcer group s overload Warnng the user Fg. 2. Steps of Dynamc oad Balancng Algorthm 3. The specfc desgn of the algorthm 3.1 oad nformaton collecton and real-tme load calculaton oad nformaton collecton ncludes geographc nformaton servce type, the node ork ablty and the real-tme load. The load nformaton for the dynamc ω = a cpu ω be defned as follos: Ccpu cpu C I / O I / O C mem mem Cnet net + a I / O I / O + a mem mem + a net cmcpu cm cm cmnet For ntroduce the benchmark server Cm, because n a heterogeneous envronment, the orkng ablty of dfferent servers are need to be normalzed. Through the formula 1, hen ω s larger, that s to say the load of server s greater. 3.2 Determne the load condton based on the RED algorthm The udgement of load state refers to the load value accordng to the servce node, concludes that the node s

3 3 of 5 dle or overload. Ths artcle uses the RED algorthm to determne the load of servce node state, n order to avod the happenng of load dtherng phenomenon (load tter refers to the servce node s marked as overload state, lead to other server nodes hch ll take charge for the addtonal load). RED (Random Early Detecton) s put forard n packet-stched netorks at frst, to reduce congeston phenomenon n the greatest degree. The basc dea for determnng the load status based on the RED algorthm s: (1) If the load of servce node value s loer than the threshold lo, the node ll be marked as overload state probablty value of 0; (2) If the load of servce node values hgher than the threshold hgh, the node ll be marked as overload state probablty value of 1; (3) If the load of servce node values are beteen lo and hgh, the node ll be marked as the state of the overload probablty value of beteen 0 and 1, rather than absolutely marked as free or overload condton, the server at ths tme of real-tme load s beteen lo and hgh. 4. Experment and analyss 4.1 The overall archtecture of expermental system In ths paper, the desgned load balancng algorthm as appled to a large geographc nformaton servce sys-tem of test envronment. The expermental system s the servce system of small buldng n the local area netork (netork banddth of 1000 MB/s) based on the test envronment, hch has to sets of data storage server and one set of metadata server data storage server cluster, manly used for storage experment data; Database server cluster s conssts of to database server, manly used for management the expermental data; Applcaton server cluster s conssts of eght sets of geographc nformaton applcaton server (late test process dynamcally extenson), four knds of geographc nformaton servce mentoned above (map brosng, query analyss, data subscrpton and donload, drectores, and metadata servce) are dstrbuted for a server group of each category to servers, a total of four server group; One load balancer and to sets of Web server compose Web server cluster. Four PCS are used to smulate mass user concurrent access, specfc structure as shon n Fg 3. The group of data storage servcer Broser1 Broser2 Set the server node hch s marked as overload has the state probablty P, node load rato value of realtme s ω, then the formula may be defned as follos: k ( lo ) P= ( hgh lo ) Among them, k s constant, lo and hgh are the mnmum and maxmum load threshold respectvely. In addton to the mnmum and maxmum threshold settng load, also need to set the largest threshold for four sngle load parameters. When a sngle load value of the nodes exceeds the maxmum threshold, determne the node nto the overload condton. 3.3 Select the target server based on the eghted probablty Set the current node value of real-tme load percentage s, and ω s P probablty value for the current geographc nformaton servce type request forarded to nodes, the calculaton formula for P as follos: 1 ω P = n 1 (1 ω ) =0 The colony of appl yng serv cer The colony of data servcer Inqure and anylers Inqure and anylers2 Dat a Dat a Catalogue Catalogue donload1 donload2 serv cer1 serv cer2 Converge stchboard Internet freall Core stchboard Router WebServcer1 WebServcer2 oad equalzer WebServcer colony 1000Mb/s Test Computer Fg. 3. General Archtecture of Expermental System 4.2 The functon and process of load balancng system oad balancng system has realzed load balancng algorthm proposed and ntellgent schedulng of geographc nformaton servce, ts functon modules and process s shon n Fg 4, the load balancng system ncludes four modules: servce recevng, dspatchng decson module, load montorng and load. Among them, n s the total number of servers n server cluster. The target server selecton method based on the eghted probablty can acheve better load balancng degree.

4 4 of 5 Request GIS servce Servce schedule Servce accept oad equalzer Confrm target servcer oad oad udge montor GIS applyng servcer colony Fg. 4. Functon and Process of oad Balancng System Servce recevng module s deployed on the load balancer, to complete geographc nformaton servces receved, all user requests geographc nformaton servces are added to the task queue; Servce schedulng module s deployed on the master-slave load balancer, manly accordng to the above mentoned algorthm to determne the target server, to complete the schedulng of servce; oad montorng module s deployed n all geographc nformaton applcaton server cluster server, to complete the server load nformaton collecton; oad determnaton module s deployed n all geographc nformaton applcaton server cluster server, based on load nformaton collected by the load query module, to fnsh load the determnaton of calculaton and the load status of eghted value. 4.3 The expermental data and parameters To choose a regon thn the scope of a 1: all seres scale vector data and 25 meters netork of dgtal elevaton model, used for query analyss and data donload servce, the area thn the scope of a 1: grade 1-16 map tles data (generated by the area vector data), mage tles data and terran tles, used for map brosng servce, as Expermental data, amount of data about a total of 10T. Accordng to the mentoned above, ths desgned load balancng algorthm needs to determne many parameters and thresholds, ncludng geographcal nformaton servce type the correspondng eght vector, dynamc feed-back cycle T, benchmark server processng poer Cm, threshold lo and hgh, four ndvdual parameters and the nherent processng capacty C are the same, then type (1) can be represented as follos: cpu net ω = a cpu + a I / O I / O + a mem mem + a net Threshold value lo and the value hgh are 0.5 and 0.9 respectvely, four ndvdual parameters correspondng to the maxmum threshold s 0.95, T s 10 s, a value of k s The expermental process and results analyss arge-scale concurrent access of users to smulate the clent s nstalled on each test machne, and then start all testng machne, for roamng through operaton at the same tme for a partcular regon level 15 maps tles, usng the proposed algorthm, the RR algorthm and ARD algorthm respectvely. Set the ntal number of concurrent access s 20, every 10 seconds to repeat a concurrent access, a total of 5 mnutes, calculate the average system response tme and system throughput; On the bass of the above steps, ncrease the number of concurrent access to 40, 60, 80, 100, 120, 140, 160, 180, 200, calculate the average response tme of the computng system; Smlar to map brosng servce (statc), the average response tme on the bass of the above steps are tested un-der dfferent number of concurrent access query analyss (n the case of slope analyss, statc), data subscrpton and donload (donload the amount of data about 100 mnutes), catalog and metadata servce. Fg 5 (a), (b), (c) and (d) respectvely are the system average response tme for four knds of geographc nformaton servces usng three dfferent algorthms under dfferent number of concurrent access. correspondng to the maxmum threshold. Through the extensve pressure experment, determne the eghts of components cpu a as shon n Table 1: I /O mem net a1 a2 a3 a4 Fg. 5. Result of Experment a We can dra the follong concluson by the Analyss dagram 5: (1) Wth the ncrease of the number of concurrent users, the use of three knds of load balancng algorthm of four knds of geographc nformaton servce system response tme are ncreased, that declare th the ncrease of Table 1. Weght Component of In ths experment, the confguraton n the geographc nformaton applcaton server cluster s consstent, are all the to man frequency 1.9 GHz 6 core CPU, memory s 64G, therefore benchmark server processng ablty Cm

5 5 of 5 concurrency server load pressure gradually ncreases, the system throughput ncrease gradually; (2) For geographc nformaton brose and query analyss servces, under the same number of concurrent, ths load balancng algorthm correspondng to the system response tme s the shortest, and th the ncrease of concurrency ths advantage s more obvous, then ARD algorthm, orst RR algorthm. Man reason s: geographc n-formaton brosng servce n the form of access map tles, and tles and map s a map of a statc cache. Because ths desgn algorthm s one of the features of the geographc nformaton servce type to match up th the correspondng server group, hch has mproved the cache ht rato, at the same tme n the servce dspatch consderng the server's ablty to ork. Based on the RED algorthm can more accurately determne the server's load state, and n a certan perod to dspatch servce based on the eghted probablty. Taken together, ths algorthm can more accurately allocate the servce request to the lghter load nodes, reduce the response tme of the system. (3) For donload the data and metadata servces, hen concurrency s under 100, ths algorthm s advantage s not obvous compared th other to algorthms, ARD and RR algorthm basc qute, the man reason s that the to types of servce response tme n addton to the related th the load balancng algorthm and the applcaton server, to a large extent s related to the database server, hen the concurrent user data has ncreased dramatcally, load balance of the system response tme mpact gradually ncreased, ths algorthm s advantage reflect gradually compared th the other to algorthms. earth shared servce [J], Chna scence: Earth scence, 2013, 43: Zyou Wang, Mnghu Zhou, Hong Me. A dynamc clent sde load balancng mechansm [J]. Chna scence: Earth scence, 2013, 43: Genova Z, Chrstensen K J. Challenges n UR Stchng for Implementng Globally Dstrbuted Webstes. Proceedngs of The Workshops on Parallel Processng, 2000, 20(8): Guoqng Ren, Jnmn Yang, Dafang Zhang. Dynamc load balancng algorthm based on the content of the Web server[j]. Computer engneerng, 2010, 36(13): Concluson oad balancng algorthm s the core and key of ntellgent dspatchng for geographc nformaton servce. In or-der to develop th ndependent control, hgh relablty, hgh avalablty and extended geographc nformaton servce system, ths paper studes a knd of sutable for netork load balancng algorthm n geographc nformaton servce system, small geographc nformaton servce system s desgned and the experment results sho that based on ths algorthm can effectvely realze the geographc nformaton servce resources reasonable schedulng, reduce system response tme, can support mult-user hgh concurrent access to onlne geographc nformaton servce under the condton of operaton. 6. References Natonal geographc nformaton publc servce platform desgn gudelnes [G], Pekng: SBSM, Chen J, Jang J, Zhou X, et al. Geographc nformaton publc servce platform of technology on the overall desgn[j], Geographc n-formaton orld, 2009, No3: Chen J, onggang Xang, Janya Gong. Netork geographc nformaton ntegraton based on vrtual