Overview. Network characteristics. Network architecture. Data dissemination. Network characteristics (cont d) Mobile computing and databases

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1 Overview Mobile computing nd dtbses Generl issues in mobile dt mngement Dt dissemintion Dt consistency Loction dependent queries Interfces Detils of brodcst disks thlis klfigopoulos Network rchitecture Network chrcteristics MU: FH: MSS: mobile units fixes hosts (w/o wireless interfce) mobile support sttion (w/ wireless interfce) ommuniction symmetry: Downstrem b/w (server client) is greter thn Upstrem b/w (client server) Resons? Physicl restrictions: MSS hs powerful trnsmitter while MH hs little or no trnsmission bility Informtion flow pttern: too mny clients for server to support ll requests simultneously Network chrcteristics (cont d) Dt dissemintion Frequent disconnections Resons? MHs disconnect to sve bttery power MHs disconnect from one cell nd connect to nother s they rom ttery power limittions Disply size nd interfce limittions In trditionl networks we hve pull-bsed communiction i.e. client initites dt trnsfer by plcing request to server Mobile networks re more suited for push-bsed communiction i.e. the server exploits the bundnt downstrem b/w nd brodcsts continuously nd repetedly dt to the clients 1

2 rodcst Disks Ds re periodic dissemintion rchitecture in the context of mobile systems nd its ttributes re tht: it is multilevel nd llows non-uniform brodcsting depending on n item s reltive importnce clients still hve the bility to enhnce performnce through cching nd prefetching rodcst disks (cont d) The brodcst chnnel becomes disk from which the clients retrieve dt s it goes by Server ssigns dt items to different disks of vrying size nd speed nd multiplexes them on the brodcst chnnel Fster disk mens fewer items but higher trnsmission frequency This leds to some sort of memory hierrchy Questions to nswer: How do we orgnize the bcst progrm to meet the ccess ptterns of the client popultion? How do the clients hndle their locl cche? rodcst disk scenrio The client popultion nd its ccess ptterns do not chnge i.e. sttic progrm Dt is red only i.e. no updtes lients don t do prefetching lients don t use the upstrem link t ll D exmple Three different bcst progrms for three dt items of equl length Flt Skewed Multi-disk (regulr) Sme s if items nd re stored on one disk nd item is stored on seprte disk spinning t twice the speed of the first disk D pros & cons Gins? Suits the symmetric communiction link Server is not interrupted by client requests Server cn propgte informtion tht would otherwise be ignored by the clients Problems? Server hs to constntly predict the client needs Server must decide whether to send dt periodiclly or periodiclly? (ltter does not llow clients to disconnect) Dt consistency Mobile hosts perform reds/writes t different servers leding to inconsistent views of the dtbse E.g. write on one server nd red of sme item on nother server before synchroniztion between the two servers 2

3 Dt consistency (sessions) onsistency cn be gurnteed through the session semntics Session is series of r/w opertions during the execution of n ppliction on client which follow specific rules: o red your writes: red must reflect the vlue of n erlier write o writes follow reds: writes re propgted fter the reds on which they depend o monotonic reds: successive reds reflect non decresing set of write o monotonic writes: writes re propgted fter writes tht logiclly preceded them Dt consistency (repliction) Two-tier repliction lgorithm with pps performing tenttive trnsctions over replics of dt t the mobile host during disconnection t reconnection the entire trnsction is reprocessed t the bse sttion over the mster copy of the dt nd my potentilly fil My result in uncceptble number of filures nd my led to different results between tenttive nd bse trnsctions which my be ginst the nture of the trnsction Dt consistency (ertifiction Reports) lients cn do some of the work to verify if the trnsctions they re currently running need to be borted ertifiction Report is sent over the bcst chnnel contining the red nd write sets of trnsctions tht declred their intention to commit in the previous bcst period This technique shifts most of the work on the mobile host s side but t lest trnsctions get borted s erly s possible Loction dependent queries Mobisic is n informtion retrievl system for mobile hosts tht llows documents to refer nd rect to the user s loction Dynmic URL: is URL tht includes n environment vrible which is defined ccording to the user s context. It is the client browser s responsibility to substitute the vrible. fter substitution the reference is hndled like common URL Loction dependent queries (cont d) Interfces ctive document: norml HTML document tht enbles clients to rect to chnges in user s environment It contins list of vribles the client hs to subscribe when loding the document dditionlly the client must relod the document whenever one of these vribles chnges its vlue pen bsed grphicl dtbse interfce tht hs the bility to: onnect to D through cell phone connection nd disply of schem metdt Rect to user s pen gestures to generte query nd retrieve results E.g. llows user to pick ttributes of interest by tpping on them, then sk for ll possible join pths between them nd finlly execute one t which point the results re presented long with the corresponding SQL query 3

4 D exmple nlysis Multi-disk vs. Skewed ccess Probbility Flt Expected dely (in bcst units) Skewed Multi-disk For equl ccess probbilities, flt is the best The more skewed the ccess probbilities, the better the non-flt progrms become The multi-disk lwys outperforms the skewed (bus stop prdox: incresing inter-rrivl vrince, increses dely) Rndomness of next rrivl for dt item disllows prefetching techniques Rndomness of next rrivl for dt item forbids going to doze mode No notion of period therefore hrd to introduce updtes i.e. restructure progrm Progrm construction Progrm construction (cont d) 1. Order pges from hottest to coldest nd prtition them into disks ech contining pges with similr ccess probbilities HOT c d e f g b h i j k OLD disk1 disk2 b c disk3 d e f g h i j k 4. Interleve chunks for ech disk in the following mnner: for j=0 to mx_chunks-1 for i=1 to num_disks brodcst chunk i,(j mod num_chunks(i)) 2. hose reltive frequency of bcst for ech disk (must be integer) rel_freq(1)=4 rel_freq(2)=2 rel_freq(3)=1 3. Split ech disk i into j chunks ij where: num_chunks(i)=mx_chunks/rel_freq(i) nd mx_chunks=lm(reltive frequencies) b c d e f g h i j k c d e f g b c b h i j k Minor ycle Mjor ycle 1,0 2,0 2,1 3,0 3,1 3,2 3,3 cst progrm prmeters Why should clients cche dt? Number of disks: determines the number of different frequencies t which pges will be brodcst Number of pges of ech disk: determines the size of the bcst Reltive frequency of ech disk: determines the rrivl rte of its pges We should configure fst disks to hold few pges. dding pge to fst disk cn cuse significnt dely increse to pges on slow disks Tuning the performnce of the bcst is zero-sum gme djusting the bcst to prticulr distribution of ccess probbilities utomticlly hurts ny other distribution 4

5 Wht should clients cche? Trditionlly clients cche their hottest dt In push-bsed environments this cn led to low performnce if server s brodcst is poorly mtched to the client s ccess pttern lients should cche the pges for which the locl probbility of ccess is significntly greter thn the pge s frequency of brodcst o if(pge P is significnt only for client ) then(p is probbly on slow disk, so should cche it) o if(pge P is ccessed by mny clients) then(none of them should cche it since it is probbly on fst disk nd therefore bcst frequently) Wht replcement strtegy? Trditionlly clients replce the pge with the lowest probbility of future ccess (LRU) Here we need cost-bsed replcement strtegy tht replces the pge with the lowest rtio of: ccess probbility (P) PIX= frequency on bcst (X) E.g. pge tht is ccessed 1% of time t client nd is brodcst 1% of the time is better replcement cndidte over pge tht is ccessed 0.5% of the time t the client (hlf ccess probbility) nd is bcst 0.1% of the time Is PIX effective? The LIX replcement strtegy PIX is not prcticl to implement becuse: it requires perfect knowledge of the ccess probbilities it needs to compre the PIX rtios of ll the pges resident in the cche every time it needs to do replcement LIX is like LRU but tkes into ccount the brodcst frequency of the pge to be replced, so it fctors in the cost of reccessing it In LRU the cche pges form linked list: On cche hit the ccessed pge I moved to the hed of the list On cche miss the til of the list is removed nd the new pge is dded t the hed LIX LIX mintins one linked list for ech disk of the bcst (sme s the single list in LRU) new pge enters the list corresponding to the disk it comes from On cche hit the pge is moved to the top of its list (sme s LRU) On cche miss: lix vlue is evluted for the til of every list the til with the minimum lix vlue is evicted the new pge is dded to its corresponding list lix=0.37 LIX (cont d) Since new pge my be inserted in queue different thn the one tht lost its til, queues grow nd shrink dynmiclly depending on current ccess pttern Disk1Q b c d e Disk2Q f g h lix=0.83 New pge z Disk1Q b c d Disk2Q z f g h 5

6 Wht is the lix vlue? Lix vlue = pge ccess probbility (P) pge frequency on bcst (X) ut now the ccess probbility of pge i is esier to evlute (initilly P i is zero): Λ P i = + (1-Λ)* P i (urrenttime t i ) Where Λ is constnt set to weigh the most recent ccess time ginst the running ccess probbility Further optimiztion? If there is no directory on the dt items, clients hve to be ctive until they get wht they re looking for Trnsmitting n index long with dt cn reduce the tuning time (1,m) indexing mens tht the index is bcst m times in every mjor cycle Distributed indexing is n optimiztion tht sends only the prt of the index relevnt to the remining items on the bcst (not replicting entire index ech time) Future work on Ds? How cn we incorporte dt updtes in between cycles Wht techniques cn be used to help the client estimte the cost of reccessing pge more efficiently? How should client do prefetching? 6