ISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 4, Issue 6, December 2014

Transcription

1 Access Latency Model of Popularty Based QOS-Aware Replca Management Algorthms for Effcent Content Dstrbuton n Dstrbuted Computng Networks 1 Dr. Anna Saro Vendran, 2 S. Thavaman 1 M.C.A., M.Phl., Ph.D., 2 M.Sc., M.Phl. Abstract In ths paper analyze the settng of methodologcal (analytc models for dstrbuted computng network performance analyss. Ths paper presents the basc of dstrbuted computng network analyzes and dscussons of dstrbuted computng network desgn procedure. Fnally, ths paper presents some of the ssues surroundng the desgn and behavor of dstrbuted computng networks. In the heterogeneous peer s scenaro, we propose the access latency model of popularty based QOS aware replca management algorthms for effcent content dstrbuton n dstrbuted computng network. Ths schedule gves the large data transmsson of a reduced transmsson delay, bandwdth utlzaton and ncreased throughput. The soluton of proposed model based on the popularty of objects, peers weght values and cost model whch could be consdered nto account several factors such as processor speed, access latency, and flow of bandwdth, storage capacty of peers. Routng s performed herarchcally by broadcastng the query to the clusters. From wde smulatons usng NS2 smulator, ths proposed access latency model proves analyss of reduced delay. Index Terms Dstrbuted Computng, Content Dstrbuton, Performance analyss, Smulaton, Access Latency, Dstrbuted Computng Networks. I. INTRODUCTION Peer-to-peer(P2P whch s a dstrbuted computer archtecture are desgned for sharng the computer resources such as storage, content, CPU cycles drectly rrespectve usng a centralzed server. P2P networks are classfed based on ther falure adaptaton abltes, connectvty along wth mantenance of sutable connectvty. Remarkable research attenton has been pertaned to content dstrbuton whch s a sgnfcant peer-to-peer applcaton on the nternet. Overlay networks are supple and easy to deploy whch allows users to acheve dstrbuted operatons wthout changng or modfyng the avalable underlyng physcal network. Peer-to-peer (P2P archtectures for fle sharng among large dstrbuted computng network, possbly dynamc, collecton of peers are generatng an ncreased fracton of the traffc on today's Internet and are reshapng the way new network applcatons are desgned. The dea s to have the peers partcpate n an applcaton level overlay networks enablng the sgnalng, routng, and searchng among the partcpatng peers. Once a peer locates the objects/ fle(s of nterest, drect connectons are establshed to medate theransfer. The key prncple s to allow, and n fact encourage, partcpatng peers to play vtal roles as servers or clents or routers. [1][2] The fact s, there are a number of ways for dong network system performance analyss. They are as follows 1. Conduct a mathematcal analyss whch produces ex plct performance expressons. 2. Conduct a mathematcal analyss whch produces an algorthmc or numercal evaluaton procedure. 3. Wrte and run a smulaton. 4. Buld the system and measure ts performance [11] There s no explct dervaton enough to develop the frst type of soluton. That s, there s no explct dervaton to solve the mathematcal model for our system. Because that the mathematcal models never do an exact job n representng the actual network beng analyzed. Thus t always ends up wth an approxmaton soluton, even f our analyss s exact. Sometmes, all we can do s to provde an approxmate soluton wth the help of mathematcal model; ths often takes cleverness on the part of the analyst. So we analyze the actual measurements of the real network wth smulaton. Here we are analyzng and evaluatng the performance of QOS matrces by usng NS2 smulator. Ths document emphaszes the expermental performance evaluaton of our proposed replca management algorthm through smulatons. To smulate our proposed QOS aware dynamc replca management algorthms we used NS2 smulator. NS2 smulator s a general-purpose smulaton tool that provdes dscrete event smulaton of user defned networks. Based on the assumpton that the overhead of the P2P network s at the access lnks of the users and not at the routers, we use a bnomal topology n our smulatons. II. THE EARLY NETWORK ANALYSIS MODELS The frst models of computer networks were developed n the early 1960's [5],[6], However, t was not untl the late 1960's when the Unted States Department of Defense Advanced Research Projects Agency (DARPA funded the development of the ARPANET that serous effort began n ths area. Indeed, t was the combnaton of a relatvely small amount of government money and a large amount of vson n fundng peeo peer network research that propelled the entre feld of networkng and packet swtchng forward and 113

2 produced the extensve analytcal work and physcal networks n whch the authors fnd themselves swmmng today. One of the frst general results was an exact expresson fohe mean delay experenced by a message as t passed through a network. The evaluaton of ths delay requred the ntroducton of an assumpton (the author's Independence Assumpton wthout whch the analyss remans ntractable, and wth whch the analyss becomes qute straghtforward. Let us begn the author s journey through the analytcal thread wth the model [5]. Here the authors assumed n the peeo peer network that there are N peers correspondng to the network swtches and n whch y assume there are M lnks correspondng to data channels connectng the swtches. They assumed that messages arrve from a poson process at orgn peer j and headed for destnaton peer k at a rate γ j k; that s, the varables γ j k correspond to the entres n the peeo peer network traffc matrx. In addton, the authors assume that the messages are exponentally dstrbuted wth mean length 1/µ bts per message. Snce each channel n the network s, n fact, a full-duplex channel, the authors choose to represent a channel as two smplex channels. Thus there are three ways ncomng and outgong of the peer fohe moment. Now, when a message arrves to such a peer, a routng decson must be made whch determnes over whch outgong channel the message wll travel next. Once ths decson s made, the message s placed on the tal of a queue of other messages watng to be transmtted out ovehs channel (say channel. In the peeo peer network the authors have dentfed a queung system consstng of such a queue and ts correspondng channel. They denote by ƛ the traffc carred on ths channel (n messages per second and let C be the capacty of ths channel (bts per second. In addton, let T be the mean response tme of ths lttle queung system. Let us also defne some global quanttes. Frst, the authors defne the total (external traffc carred by the peeo peer network as ( 1 and the total (nternal network traffc carred by the channels as (2 Furthermore f the author let be the average number of hops that a message must take n ts journey through the network (averaged over all orgn-destnaton pars, then t s easy to show that the followng s true [5]: (3 performance varables for a peeo peer network. It can easly be seen (by two applcatons of Lttle's result [7] that [5] (4 Ths s an exact equaton and s an mportant general result for peeo peer networks of all sorts. The only dffculty wth ths last equaton s that the authors have not gven an explct expresson for T t. In general, ths turns out to be an unsolvable problem. It s probably true that the author wll never be able to gve a tractable expresson for T! Ths may come as a surprse to those famlar wth queung networks; ndeed, t appears that they have been set up a perfect Jackson open queung network whose soluton s smple and well-known [8]. It turns out that f the authors change the model to one whch s, n fact, more representatve of object/data traffc, and then the authors gave an exact soluton for a restrcted topology. The modfcaton s to assume that the message lengths are all the same (rathehan the exponental assumpton above and that the topology s a tandem network; n ths case, Rubn [10] was able to gve an exact soluton for the response tme when all traffc enters at one end of the tandem and exts at the other end. Unfortunately, the analyss does not extend to the case of non-tandem networks. Let us now return to the author s orgnal model usng exponentally dstrbuted message lengths. As mentoned above, extreme analytcal dffculty comes from the dependence among message servce and nter-arrval tmes. The Independence Assumpton assumes that the length of a message s chosen ndependently from the exponental dstrbuton each tme t enters a swtchng node n the computer network! Ths s clearly a sweepng assumpton whch s patently false; however, t turns out (from measurements and smulaton that ths assumpton has a neglgble effect on the mean message delay. AND, f the authors do make the assumpton, then ther analyss becomes trval snce they wll have then reduced the system to a Jackson open queueng network model. If the authors make the Independence Assumpton, then the expresson for T fohe th queueng system reduces to an M/M/l queueng system [8] whose soluton s smply. (5 Note that µc s the capacty of the th channel expressed n messages per second. When they substtute ths nto (4, they end up wth an explct and smple expresson fohe mean message delay T as follows: Fnally, and most mportantly, we defne T to be the mean delay of all messages (agan, averaged over all orgn-destnaton pars. T s the mean response tme of the peeo peer network and s one of the most mportant (6 Ths equaton s very effectve for desgn calculatons were below. However, t gnores certan realtes whch become mportant when one wshes to gve a more precse predcton 114

3 of network delay. For example, the authors have assumed K = 0 and P = 0 (where K = nodal processng tme and P = propagaton delay. When they came to apply ths analyss to any realstc network, they must nclude these varables as well as other consderatons. If the authors let 1/µ denote the average length of a data packet and f we let 1/µ represent the average length of all packets, then they have seen that a more accurate expresson for T s Of course, f the authors set, ths would reduced to equaton (5. If the authors now account fohe nodel processng tme K and the channel propagaton tme P they may then wrte down the followng approxmaton fohe average message delay: from the servers. It s assumed that each node always stores one copy of ts own content tem whch t serves to clents and that t has addtonal storage space to store the replcated content tems from other nodes whch t can also serve. The object s assocated wth an authortatve orgn server (OS n the network where the content provder makes the updates to the object. The object copy located at the orgn server s called the orgn copy and an object copy at any remanng server s called a replca. B. Assumptons 1. Each peer ncludng the requestng peer can store replca copy. 2. Peer storage space s lmted and addtonal replca f needed can only be placed by replca replacement. 3. Prmary copy can resde only n one peer 4. Dstrbuted lst of replca nformaton s stored across the overlay network n a peer n each cluster. 5. Cluster of peers s a set of nodes grouped physcally. (e.g. nodes under a ISP, nodes n a unversty campus The term n the brackets s just our new expresson for T and the addtonal term K comes from the fact that messages pass through one more peehan they do channels n ther travels through the peeo peer network.[6] From ths delay analyss we may predct quanttatve as well as phenomenologcal behavor of the average message delay n peeo peer networks. In partcular, f we assume a relatvely homogeneous set of C and A,, then as we ncrease the load on the network, no ndvdual term n the sum for delay as gven n equatons (4,9 wll domnate the summaton untl the flow n one channel (say channel 0 approaches the capacty of that channel; ths channel corresponds to the network bottleneck. At that pont, the term T o, and hence T, wll grow rapdly. The expresson for delay wll then be domnated by ths term and T wll exhbt a threshold behavor; proo ths threshold, T remans relatvely constant and as we approach the threshold, T wll suddenly grow. Thus we expect an average delay n networks that has a much sharper behavohan the average M/M/l delay. III. DESIGN ISSUES A. System Model Replcaton n Overlays network can be defned as graph G = (V, E, where V s the set of nodes and E V V the set of lnks between the nodes n the overlay network. Each node s assocated wth a bandwdth Nb (node (. The system model s consdered wth a collecton of N server nodes that form a peeo peer (P2P overlay network. Along the part of the overlay, each node n the network functons as a server respondng to queres whch come from clents outsde of the overlay network. As an example could be that each node s a web server wth the overlay lnkng the servers and clents beng web browsers on remote machnes requestng content C. Replca Placement Matrx Representaton of Replca Management Algorthms Replca placement matrx s representng the requested object O j whch s n ether Local peer or n Strong or medum or n weak cluster peer or n the orgn server. A peer P knows the request rates (number of requests r, =1,2, m of all peers and j=1,,n of ts local users for all objects. The vector of request rates of the users at peer P s denoted by r =( r 1, r 2, r 3,, r m the m X n of request rates of all objects at all peers. Fohe replca placement matrx and t s denoted by m X n matrx whose entres are represented as follows 1, f o jn Localcatch 0, f o jnstrongclusterpeer 1, f o jnmedumclusterpeer 2, f o jnweakclusterpeer 2, f o jnorgnserver For =1, 2,,m and j=1,2,,n. The system goal s to mnmze the access cost each server overall objects. IV. ACCESS LATENCY MODEL OF POPULARITY BASED QOS AWARE REPLICA MANAGEMENT ALGORITHMS In dstrbuted replcaton group a server peer needs to respond to the requests of varous clents and also from other servers. At an nstance a server consumes a request from the clent, t quckly responds to the clent f the requested object s avalable n ts local storage. Else f, the requested object s fetched from other server peers wthn the group whch wll result n hgher access cost. Else, the orgn server access cost wll be hghest. A server needs to reduce ts load through respondng to the local clent requests by replcas. 1. Let us defne an N x M replcaton matrx wth elements of = -1, 0, 1, 2, and >2. For = 1,2,, N number of 115

4 peers and j = 1,2,, M number of objects taken for replca creaton and accessng n P2P network. An element of ths matrx wll be equal to -1 f object O j s replcated at local catch. The replca management problem and access latency may be formulated as follows 2. Fnd the assgnment of -1, 0, 1, 2, >2 values at the matrx ( 1that mnmzes access latency. 3. Subject to the storage capacty constrants (e. C The system s goal s to mnmze access tme at each peer overall objects are as follows T mn m 1 l 1 M 1and ( PW andpw W 2&&( PW S 0and ( PW max mn max mn OS 2&&( PW mn 9 The terms of the objectve functon represents the access tme correspondng to the objects that are cached from local peer, from strong, medum, weak cluster peers, and from OS respectvely. V. EXPERIMENTAL PERFORMANCE EVALUATION OF ACCESS LATENCY MODEL The performance s evaluated n terms of QOS metrc such as end to end delay durng content dstrbuton fohe proposed methods of SRMA [4] and PQSRMA [3]. The smulaton wll be conducted n two dfferent scenaros to obtan an effcent result n terms of QOS performance metrcs. Scenaro 1 compares the proposed methods of PQSRMA [3] and SRMA [4] wth the exstng method QIRMA[14] n terms of QOS metrcs such as throughput, packet drop, end to end delay, bandwdth utlzaton, query effcency wth load. Fg.1 Load Vs Delay Scenaro 2 compares the proposed methods of PQSRMA and RRTIR wth the exstng method QIRMA n terms of QOS metrcs such as throughput, packet drop, end to end delay, bandwdth utlzaton, query effcency wth data transfer rate. Fg.2 Rate Vs Delay In ths experment, the rate of the requested content s vared from 2.0mb to 8.0 Mb. The response delay of packets s measured n seconds. From the Fgure.2, t s evdent that, when the rate ncreases, the delay also ncreases. Also t s shown that the delay of our proposed methods SRMA [4] and PQSRMA [3] s sgnfcantly less than the delay of QIRMA [14] snce the proposed SRMA [4] and PQSRMA [3] utlzes the network less than that of QIRMA [14]. VI. CONCLUSION In ths paper, we have taken the analytc model of a peeo peer network for proposed methods. The purpose was to gve the reader, the understandng as to the approxmate state of the art n performance modelng and analyss of access latency. From the above two fgures we came to know that the delay ncreases when ncreases the load. Accordng to the lttle s law when the load ncreases that the delay ncreases automatcally. PQSRMA [3] has reduced delay when comparng wth QIRMA [14] and SRMA [4]. REFERENCES [1] Dr. Anna Saro Vendran, S.Thavaman, Oct Survey of Cachng and Replca Placement Algorthm for Content Dstrbuton n Peeo Peer Overlay Networks. The 2 nd Internatonal conference on Computatonal Scence, Engneerng and Informaton Technology (CCSEIT 2012 October 2012, Combatore. Inda. Conference proceedngs publshed by ACM that avalable n ACM dgtal lbrary. [2] Dr. Anna Saro Vendran, S.Thavaman, Nov Analyss Study on Cachng and Replca Placement Algorthm for Content Dstrbuton n Dstrbuted Computng Networks, Internatonal Journal of Peer-to-Peer Networks. Nov-2012, Vol.3, No: 6.PP [3] Dr. Anna Saro Vendran, S.Thavaman, Jan Popularty Based QOS-Aware Smart Replca Management Algorthm for Content Dstrbuton n Peeo Peer Overlay Networks. The 7 th Internatonal conference on Intellgent Systems and Control (ISCO th & 5 th Jan. 2013, Combatore, TN, Inda. Conference proceedngs publshed by IEEE Xplore that avalable n IEEE dgtal lbrary. [4] Dr. Anna Saro Vendran, S.Thavaman, March An effcent algorthm for clusterng nodes, classfyng and replcaton of content on demand bass for content dstrbuton n P2P overlay networks, Internatonal Journal of Computer 116

5 and Communcaton Technology, ISSN (PRINT: , Volume-4, Issue-1, 2013, PP APRIL [5] L. Klenrock, Communcaton Nets; Stochastc Message Flow and Delay. New York: McGraw-Hll, (Out of prnt. Reprnted by Dover Publcatons, [6] P. Baran, "On dstrbuted communcatons," RAND Seres Reports, Aug [7] J. D. C. Lttle, "A proof of the queueng formula L = AW." Oper. Res., vol. 9, pp , [8] L. Klenrock, Queueng Systems, Vol I: Theory. New York: Wley, [9] O.J. Boxma, "Analyss of models foandem queues," Ph.D. dssertaton, Unversty of Utrecht, Utrecht, The Netherlands, [10] I. Rubn, Communcaton networks: Message path delays," IEEE Trans. Inform. Theory, vol. IT- 20, pp , [11] LEONARD KLEINROCK, FELLOW, IEEE. On the Modelng and Analyss of Computer Network, Proceedngs of the IEEE, Vol.81, No. 8, August [12] Report: Napster users lose that sharng feelng, n CNN news, URL: /. [13] Peer-to-peer fle sharng: The effects of fle sharng on a servce provder s network, n Industry Whte Paper, Sand vne Incorporated, [14] S. Ayyasamy and S.N. Svanandam,(2009 A QOS-Aware Intellgent Replca Management Archtecture for Content Dstrbuton n dstrbuted peer-to-peer Overlay Networks, Internatonal Journal on Computer Scence and Engneerng, Vol.1, No.2, PP [15] Sharrukh Zaman, and Danel Grosu, "A Dstrbuted Algorthm fohe Replca Placement Problem", IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 22, NO. 9, SEPTEMBER 2011, pp Conferences. She s currently a supervsor for M.Phl research works of varous Unverstes. She s currently pursung Ph.D Degree n SNR Sons College, under Bharathar Unversty, Combatore. AUTHOR BIOGRAPHY Dr. Anna Saro Vendran s the Drector MCA n SNR Sons College, Combatore, Inda. She has a teachng experence of 21 years n the feld of Computer scence. Her area of Specalzaton s Dgtal Image Processng and Artfcal Neural Networks.She has presented more than 40 Papers n varous Conferences and her research works have been publshed n Internatonal Journals. She s currently a Supervsor for research works of varous Unverstes and also Revewer for reputed Journals. S. Thavaman s an Assstant Professor n Department of Computer Applcatons, SNR Sons College, Combatore, Inda. She has a teachng experence of 14 years n the feld of Computer scence. Her area of Specalzaton s Dstrbuted Computng and Networks. She has presented more than 15 Papers n varous Internatonal and Natonal 117