Energy Efficient Cache Invalidation in a Mobile Environment

Transcription

1 Enegy Efficient Cache Invalidation in a Mobile Envionment Naottam Chand, Ramesh Chanda Joshi, Manoj Misa Electonics & Compute Engineeing Depatment Indian Institute of Technology, Rookee INDIA {naotdec, joshifcc, manojfec@iit.enet.in Abstact: Caching in mobile computing envionment has emeged as a potential technique to impove data access pefomance and availability by educing the inteaction between the client and seve. A cache invalidation stategy ensues that cached item at a mobile client has same value as on the oigin seve. To maintain the cache consistency, the seve peiodically boadcasts an invalidation epot (IR so that each client can invalidate obsolete data items fom its cache. The IR stategy suffes fom long quey latency, lage tuning time and poo utilization of wieless bandwidth. Using updated invalidation epot (UIR, the long quey latency can be educed. This pape pesents a caching stategy that peseves the advantages of existing IR and UIR based stategies and impoves on thei disadvantages. Simulation esults pove that ou stategy yields bette pefomance than IR and UIR based stategies. Categoies and Subject Desciptos C.2.1 [Netwok Achitectue and Design]: Wieless Communication Geneal Tems Netwok Achitectue, Netwok Design, Mobile Computing Keywods: : Mobile computing, cache invalidation, wieless, data boadcast, invalidation epot, disconnection, failue. Received 30 Oct.2004; Reviewed and accepted 30 Jan Intoduction The advances in potable computing devices and wieless technology have damatically changed the way of infomation access. Wieless communication pemits uses to access global data fom any location by caying mobile devices. Howeve, the mobile computing paadigm pesents a damatic discepancy elative to cuently matued wied netwok computing. Mobile clients in wieless envionments suffe fom scace bandwidth, low-quality communication, fequent netwok disconnections (eithe voluntee o involuntee, and limited local esouces (computing powe, battey, stoage, display, etc. Caching of fequently accessed data items on the client side is an effective technique to educe netwok taffic and quey latency. Bandwidth and battey powe ae saved, as no tansmission is equied fo clients to access data fom thei caches. Futhemoe, the availability of data is impoved because even when a mobile client is disconnected fom the netwok, data stoed in its local cache is still accessible, making disconnection opeations a possibility. Data consistency must be ensued between client and seve to pevent clients fom answeing quey by out-of-date cached data items updated by seve. In ode to assist mobile clients in maintaining the consistency of thei caches, a numbe of cache invalidation techniques have been poposed [1-14]. In these appoaches, the seve peiodically boadcasts invalidation epots (IRs to infom the clients about which data items have been updated duing the most ecent past. When a mobile client eceives an IR, it can use the epot to identify out-dated data items in its cache and discad them befoe using the cache to answe queies. Howeve, the IR based scheme suffes fom long quey latency and they make poo utilization of available wieless bandwidth. Cao [1, 4, 5, 15] has poposed seveal updated invalidation epot (UIR based caching stategies to addess the poblem. Each UIR contains infomation about most ecently updated data items since the last IR. In case of cache hit, thee is no need to wait fo the next IR and hence the quey latency is educed. Howeve, if thee is a cache miss, the client still needs to wait fo the data to be deliveed. Thus, due to cache miss, the UIR stategy has same quey latency as IR stategy. To ovecome the limitations of existing cache invalidation stategies, this pape pesents a synchonous stateful caching stategy whee cache consistency is maintained by peiodically boadcasting update epots (URs and equest epots (RRs. The cente design of ou stategy includes educing the quey latency, impoving the cache hit atio, minimizing the client disconnection oveheads, bette utilization of wieless channel, and conseving the client enegy. The tack of cached items fo each client is maintained at the home mobile suppot station in the fom of cache state infomation (CSI. Use of CSI educes the size of IR by filteing out non-cached items and handles long disconnection [25]. In diffeent IR based stategies [2, 3, 6-11, 13, 14, 16], even though many clients cache the same updated data item, all of them have to quey the seve and get the data sepaately fom the seve. It misuses a lage amount of wieless bandwidth and client battey enegy. Ou stategy peiodically boadcasts update epot (UR [24], to minimize uplink equests and downlink boadcasts. To futhe educe quey latency, the stategy uses equest epots (RRs, whee all the ecently equested items ae boadcast afte the UIR. Selective tuning is used to conseve the client enegy. Anothe dawback common to IR based appoaches is that if the disconnection time of a client is lage than a fixed peiod of time, the client should discad its entie cache even if some of the cached items may still be valid. This pape demonstates a moe efficient handling of abitaily long client disconnection as compaed to IR and UIR appoaches. The est of the pape is oganized as follows. Section 2 gives a bief eview on some epesentative appoaches on cache invalidation. In section 3, we explain ou poposed caching stategy. Simulation esults ae pesented and discussed in Section 4. Concluding emaks ae given in section 5. 2 Related Wok A numbe of boadcast based cache invalidation stategies have been poposed fo mobile envionments. Existing stategies can be boadly classified into two types: stateful and stateless seves, distinguished by whethe clients cache infomation is maintained at the seve o not. Babaa and Imielinski [14] have poposed the basic stateless appoach called timestamp (TS, whee the seve boadcasts an IR evey L seconds, indicating which data items ae updated in the last w*l seconds, whee w is the boadcast window size. Advantages of IR based appoaches include high scalability and enegy efficiency because the size of each IR is independent of the numbe of clients, and IRs ae scheduled to be boadcast peiodically (synchonously. As such, clients can switch to doze mode opeation between successive IRs to save battey powe. The majo dawback, howeve, is: clients must flush thei entie caches afte long disconnection (> w*l, even if some of the cached items may still be valid. Anothe dawback is long quey latency, as clients must at least wait fo the next IR befoe answeing a quey to ensue consistency. Vaious appoaches have been poposed to addess the long disconnection poblem [3, 10]. Jing et al. [10] poposed a Bit-Sequence (BS scheme that uses a hieachical stuctue of binay bit sequences to epesent IRs. The scheme is good fo clients with long disconnections but has vey lage size of IR and assumes that update ate to the database is not high. Hu and Lee [3] have poposed a family of invalidation algoithms. The advantage of these algoithms is that the type of invalidation epot to be sent is detemined Jounal of Digital Infomation Management Volume 3 Numbe 2 June

2 dynamically based on system status. Tan [7] eexamined the BS method and studied diffeent oganizations of the invalidation epot. These oganizations facilitate clients to selectively tune to the potion of the epots. Hou et al. [12] poposed a scheme to educe the false invalidation ates based on BS epots. Wu et al. [6] poposed a scheme which modifies the IR algoithm to include cache validity checks afte econnection. The method has same basic poblem as in IR method (e.g. when the disconnection time is geate than W, nothing can be salvaged. Cao [4, 15] has done some pioneeing wok to educe the long quey delay associated with basic IR based stategy by intoducing the idea of updated invalidation epot (UIR. In this appoach, a small faction of the essential infomation (called UIR elated to cache invalidation is eplicated seveal times within an IR inteval, and hence the client can answe a quey without waiting until next IR. Howeve, if thee is a cache miss, the client still needs to wait fo the data to be deliveed. In [1, 15] autho intoduced a counte based method whee clients intelligently pefetch the data that ae most likely used in the futue. Kahol et al. [2, 9] pesent an asynchonous stateful (AS invalidation scheme whee each mobile client maintains its own Home Location Cache (HLC to deal with the disconnections. The stategy suffes fom lage numbe of uplink equests and downlink boadcasts fo the same updated item. Yuen et al. [8] poposed a scheme based on absolute validity inteval (AVI fo each data item. A mobile client can veify the validity of a cached item by compaing the last update time and its AVI. To solve the poblem of lage size invalidations epots and duplicate uplink equests, Lai et al. [18, 19], poposed two techniques: Validation- Invalidation Repots (VIR and Delayed Request Scheme (DRS. In VIR appoach when size of IR becomes lage, the validation epot can be used instead. Use of DRS educes the numbe of uplink equests. Chuang et al. [20] addess some of the cache invalidation issues like disconnection handling, enegy consumption in a synchonous stateless envionment. Wang et al. [21] poposed a hybid invalidation stategy called Scalable Asynchonous Cache Consistency Scheme (SACCS. Unlike stateful algoithms, SACCS maintains only one flag bit fo each data item in MSS and unlike the existing synchonous stateless appoaches, it does not equie peiodic boadcast of IRs. Because of asynchonous natue of SACCS appoach, it does not povide any guaantee on waiting time of clients and hence they can aely switch to powe save mode. Authos in [22] descibe the cache consistency maintenance fo inta- and inte-oaming clients. Thee stategies: homogenous IR, inhomogeneous IR without oaming check and inhomogeneous IR with oaming check ae applied to TS and SACCS stategies. 3 Poposed Caching Stategy In this section, we pesent ou synchonous stateful caching stategy. 3.1 Mobile Computing Envionment Figue 1 illustates the mobile computing envionment assumed in this study. The model consists of two distinct sets of entities: Mobile Hosts (MHs and Fixed Hosts (FHs. Some of the fixed hosts called Mobile Suppot Stations (MSSs, ae augmented with a wieless inteface in ode to communicate with the mobile hosts, which ae located within a adio coveage called a cell. We use the tems client and mobile host intechangeably. Wieless cells cove the entie suface of installation (e.g., a univesity campus, industy. MSSs ae also known as Base Stations (BSs and ae inteconnected by means of fixed LAN infastuctue. An MSS acts like a gateway between wied LAN and wieless netwok. Individual LANs ae inteconnected by means of outes; one of them is acting as an Intenet gateway. An MH communicates with the seve via an MSS ove a wieless communication link. A fixed netwok has a lage bandwidth (ode of Mbps o Gbps; while the bandwidth of the wieless channel is scace (19.2 Kbps 10 Mbps. An MH can move within a cell o between cells while etaining its netwok connection. When an MH moves fom one cell to anothe (called handoff, its wieless connection is switched to the new cell. An MH eithe connects to an MSS though a wieless link o disconnects fom the MSS by opeating in a powe save mode [2]. is of same size S data (in bits and has two timestamps: t i is the most ecent timestamp when d i got updated at the seve and t, called i latest equest time, epesents the most ecent time when d i was last equested by any client. Clients only issue simple equests to ead the most ecent copy of data items. In ode to seve a equest sent fom a client, the MSS needs to communicate with the database seve to etieve the database items. Caching techniques may also be applied at MSS. Since the communication between the MSS and the database seve is tanspaent to the clients, fom the client point of view, the MSS is the same as the database seve. Figue 1 Mobile computing envionment. Fequently accessed data items ae cached on the client side. Each client has same cache capacity of C items. When caching is used, data consistency issues must be addessed. We assume the latest value consistency model [9]. To ensue cache consistency, the seve boadcasts UR evey L seconds and it also boadcasts (m- 1 RRs between two URs. The stuctue of UR i at time T i is as follows: IR i UR_INDE i UR_DATA i IR I = {( d, T (D D ( n > 0 (T - W*L < T T I I UR_INDE i = {d x ((T i -1 < t x T i (n x >0 (T i 1,m-1 < t T x i UR_DATA i = {D x d x UR_INDE i IR contains the update histoy of past w boadcast intevals wheeas UR_DATA contains actual data value fo the items which have been updated duing pevious UR inteval and the items that have been equested duing the latest RR inteval. At inteval time T i,k, RR i,k is constucted as follows: UIR I,K RR_INDE I,K RR_DATA I,K UIR i,k = {d x (d x D (T i,0 < t x T i,k (n x > 0 (0 < k < m RR_INDE i,k = {d x (T i,k-1 < T i,k RR_DATA i,k = {D x d x RR_INDE i,k To enable selective tuning, the MSS boadcasts the index infomation befoe the boadcast of actual data. An index (UR_INDE/RR_INDE is list of the items boadcast as pat of UR_DATA/RR_DATA. It is notable that use of index in ou stategy does not incease size of the epot. Fo instance, fo an item d x, the numbe of bits in both the appoaches (with and without index emains S id +S data (whee S id = d x, is size of the item id and S data = D x, is numbe of bits in actual data of the item. Within index, the items ae aanged in nondeceasing ode of thei cache counts to futhe educe the quey latency [23]. To answe a quey, the client listens to the IR/UIR pat of epot (UR/ RR and uses it to decide cache validity. If thee is a valid cached copy of the equested item, the client etuns the item immediately; 3.2 Cache Invalidation Stategy Seve database D is a collection of N data items with ids: d 1, d 2,..., d N. D i denotes the actual data of an item with id d i. Each data item d i Jounal of Digital Infomation Management Volume 3 Numbe 2 June

3 othewise, it sends a quey equest to the seve. Fo each client MH x, the home MSS maintains cache state infomation CSI x (i.e. list of cached items and equest timestamp (i.e. last time the client communicated with the MSS. The MSS also maintains cache count n i fo each item d i. Fo a client equest, the MSS updates the elevant countes, coesponding CSI and timestamp, and fowads the equest to the seve. To save enegy a client may powe off and only tuns on duing the epot boadcast. Ou stategy educes the size of IR by filteing out non-cached items, thus enhancing the oveall pefomance [25]. Reduced size of IR/UIR epots impoves the downlink channel utilization. Futhe, it enhances the uplink channel utilization by adopting delayed uplink (DU technique [25]. To illustate the woking of poposed stategy conside an example as shown in Figue 2 fo the mobile scenaio of Figue 1. whole pocess is eflected in two algoithms: Algoithm 1 uns on the MSS and Algoithm 2 uns on the client side. Algoithm 1. The algoithm at the MSS The MSS eceives econnect(t l fom client MH j ; DIV j = 0; Set DR j to empty; T j = cuent_time; fo each item d x CSI j do if (t x > T l /* item has become invalid */ DIV j [k] = 1 whee CSI j [k] = d x ; /*d x is the kth cached item */ if all bits in DIV j ae same then DR j = DIV j [1]; /* DR j has one bit 0/1 */ else append DIV j to DR j ; send DRj to MHj; Algoithm 2. The algoithm at the client Figue 2 Woking of ou stategy In UIR scheme, the equested data ae boadcast afte the next IR, thus, due to cache miss the expected quey latency is L/2 seconds. To educe the quey latency due to cache miss, ou stategy boadcasts the ecently equested data items afte the next epot (IR/UIR as pat of UR/RR whicheve aives ealie, such that the expected quey latency is L/(2*m seconds instead of L/2 seconds. Fo example, when a client eceives a cache miss equest between T i,1 and T i,2, it cannot answe the quey until T i+1 in the UIR appoach, but it can answe the quey at T i,2 in ou appoach (see Figue 3. The MH j econnect afte the disconnection; if (disconnection time w*l eceive next UR to invalidate the cache; else /* long disconnection */ { send econnect(t l to the MSS; wait until eceiving DR j ; if DR j has single bit, use it to invalidate the cache; else { fo each kth bit b k (stating fom MSB in DR j if b k = 1 then d k = invalid else d k = valid; As compaed to UIR stategy [1, 4, 5, 15], which handles disconnection by sending the ids fo updated items, ou stategy uses only one bit fo an item, thus educing the econnection oveheads temendously. Fo ou stategy the maximum econnection ovehead is C bits which is vey low as compaed to UIR. Because of smalle size of ovehead, ou stategy is also vey much effective in tems of bandwidth utilization, client tuning time and enegy consumption. Conside a caching scenaio of Figue 2. Let client MH 5 disconnects at time 14 and econnects at time 47 as shown in Figue 4. Figue 3 Reducing the quey latency Handling client disconnection Since a UR boadcasts infomation about the items that have been updated duing past w*l time, ou stategy handles the client disconnection less than w*l without any additional ovehead. When a client econnects afte a disconnection time longe than w*l, it sends an uplink equest with the last eceived UR timestamp T l (befoe disconnection to the MSS. On eceipt, the MSS constucts a binay vecto DIV called disconnection infomation vecto. DIV is of size C bits and contains the validity infomation about the cached items by the client. In compaison to ou pevious disconnection handling stategy [25], hee we intoduce the idea of disconnection epot (DR, that futhe enhances the expected value of disconnection ovehead. The ationale behind the use of DR is that, thee may be two exteme cases of all the cached items being valid (DIV=0 o invalid (DIV=1 afte the long disconnection. When all the bits in DIV ae same (i.e. 0 o 1 then it is bette to send one bit to the client instead of C bits. The MSS computes DR (of size 1 o C bits fom DIV and sends it to the client. Afte downloading DR, the client invalidates the cache. The Figue 4 Disconnection example Disconnection peiod = 33 (i.e. > w*l. MH 5 has no infomation about updates between (12, 47], and it misses URs at 24 and 36. On wake up it sends T l = 12 to the MSS A. The MSS A constucts DR as shown below: d 1 d 2 d 8 d Jounal of Digital Infomation Management Volume 3 Numbe 2 June

4 When MH 5 eceives DR 5 = 0010, it is intepeted as: items d 1, d 2 & d 9 ae still valid, wheeas item d 8 has become invalid. The econnection ovehead fo ou stategy is 4 bits. Fo UIR, the ovehead = min {invalid items, valid items*item id size (S id. Geneally S id = 32 bits, theefoe the ovehead value = 32 bits Handling client failue Fom a client pespective a failue is teated as a long disconnection. When a client ecoves fom a failue longe than w*l seconds, it sends an uplink equest with the last eceived UR timestamp T l to the MSS. Due to client failue, the CSI may not epesent the actual state of client cache. Moeove, all cache countes may gow vey lage afte some amount of time and fail to epesent the numbe of caching clients. Fo a client MH x, the last equest timestamp T maintained x at the home MSS is used to handle such situation. If the value (cuent_time-tx is lage than some fail_theshold, the MSS ties to communicate with MH x. If the client does not espond in a cetain time peiod, the MSS assumes that it has failed. Hence, the MSS deceases the elevant countes and emoves the associated CSI x. On eceiving T l fom the client MH x, the MSS updates the T, ceates x a new CSI x list and esponds to the client with DR x =1 indicating that whole cache is invalid. 4 Pefomance Evaluation 4.1 Methodology To evaluate the pefomance of the poposed scheme, we have developed a simulation model. Table 1 shows system paametes and thei values. The model consists of a single seve seving multiple clients. The database can only be updated by the seve, while the queies ae geneated by the clients following an exponential distibution. The database items ae distibuted into two categoies: the hot data subset and the cold data subset. The hot data subset includes data items fom 1 to 50 and the cold data subset includes the emaining data items of the database. Clients have a lage pobability (80% to access the data in the hot subset and a low pobability (20% to access the data in the cold subset. The seve boadcasts IRs (URs in ou algoithm evey L seconds and UIRs (RRs in ou algoithm evey L/m seconds. The seve geneates a single steam of updates sepaated by an exponentially distibuted update aival time. All updates ae andomly distibuted inside the hot data subset and the cold data subset, while 40% of the updates ae applied to the hot data subset. The mean inteaival time of queies geneated by all clients is T q. The inte-aival time of updates at the seve is distibuted exponentially with a mean of T u. A client follows exponential distibuted disconnection with mean time T d and has pobability p d to ente the disconnection mode only when the outstanding quey has been seved.. The client pocesses geneate queies one by one. If the efeenced data items ae not cached on the client side, the data ids ae sent to the seve fo fetching. Once the equested data items appea on the channel, the client bings them into its cache. Client cache management follows I- LRU (invalid LRU eplacement policy, whee invalid cache items ae fist eplaced. If thee is no invalid cache item, the valid items ae eplaced in LRU fashion. Hot data items (D H 1-50 Cold data items (D c Remainde of D Pecentage of access on hot data subset 80 Pecentage of updates on hot data subset 40 Mean quey geneate time (T q sec Mean update aival time (T u sec Mean disconnection time (T d sec Client disconnection pobability (p d 0.10 Bandwidth of uplink channel (B up 19.2 Kbps Bandwidth of downlink channel (B down 100 Kbps Table 1 Simulation paametes 4.2 Results The effects of diffeent wokload paametes such as mean update aival time, mean quey geneate time, etc. on the elative pefomance of the IR (TS, UIR and ou stategy have been pesented The cache hit atio Figue 5 shows that the cache hit atio of ou stategy is always highe than IR and UIR stategies. In the IR algoithm, a client only downloads the data items that it has equested fom the seve, wheeas in UIR and ou stategy, a client also downloads the updated data items that ae boadcast by the seve, thus, inceasing the cache hit atio. Due to cache miss, the UIR stategy boadcasts the equested data items only afte the next IR, wheeas ou stategy also boadcasts the equested data items afte evey UIR (as pat of RR. Because of such distibuted quey eplies, cache hit atio of ou stategy is highe than UIR stategy. Figue 5a shows that cache hit atio dops with the decease in mean update aival time. As shown in Figue 5b, the cache hit atio educes due to client disconnections. All the thee stategies eact diffeently to the disconnections. In the IR algoithm, if a client disconnects longe than w*l, it invalidates all cached data items and deletes them fom the cache although some of them may be valid. This esults in many cache misses fo the client befoe it fills up the cache again. (a Paamete Value Seve database size (N 1000 items Item size (S data 4096 bits Client cache size (C items Numbe of clients (M 50 Item id size (S id 32 bits Update timestamp size (T data 32 bits Boadcast inteval (L 20 sec Numbe of UIR/RR boadcasts (m-1 4 Boadcast window (w 10 L (b Figue 5 Cache hit atio as a function of mean update aival time (T q = 100 sec, N = 1000 items, C = 50 items. (a no client disconnection (b client disconnection pobability (p d is 0.10 (T d = 400 sec. Jounal of Digital Infomation Management Volume 3 Numbe 2 June

5 4.2.2 The effect of mean update aival time We measue the quey latency and thoughput (the numbe of queies seved pe IR/UR inteval as a function of the mean update aival time. Figue 6a shows the effect of mean update aival time ove the quey latency. Ou stategy outpefoms the IR and UIR stategies, because a client only needs to wait fo the next RR to seve the queies and hence the quey latency is about 20/(2*5 = 2 seconds (L/(2*m. stategy has the highest uplink cost and the UIR stategy is in the middle. This can be explained by the fact that the thee stategies have diffeent cache miss atios. In the IR stategy, when a cached data item becomes invalid, the client has to send the uplink equest. Thus, a lage numbe of uplink equests ae also esulted due to the invalidation of cache contents. In ou stategy, thee is no uplink due to updates at the seve. As the mean quey geneate time inceases the numbe of uplink equests deceases because thee will be less numbe of cache misses. In Figue 8b, when the mean quey geneate time dops below 50 seconds, because of the use of DU technique ou stategy behaves significantly bette than IR and UIR stategies. (a (a (b Figue 6 The quey latency and thoughput as a function of the mean update aival time (T q = 100 sec, T d = 400 sec, N = 1000 items, C = 50 items. (b Figue 7 The quey latency and thoughput as a function of the mean quey geneate time (T u = 10 sec, N = 1000 items, C = 50 items, no client disconnection. In ou simulation model, a quey is geneated only when thee is no pending equest fom the client. As the quey latency dops, the next quey may aive ealie and be seved ealie. Thus, the seve can seve moe queies within one boadcast inteval. Since thee stategies have diffeent quey latencies, they have diffeent thoughput. As shown in Figue 6b, ou stategy has the highest thoughput, wheeas IR stategy has the lowest, and UIR stategy in the middle The effect of mean quey geneate time As shown in Figue 7a, the quey latency of the IR stategy gows longe than the IR inteval when the mean quey geneate time dops below 50 seconds. Due to the distibuted boadcast of equested data, ou stategy has always less quey latency as compaed to UIR stategy. Since ou stategy has highe cache hit atio than the IR and UIR stategies, it can seve moe queies locally. Due to delayed uplink (DU, ou stategy futhe educes the numbe of uplink equests as compaed to UIR and IR stategies. As a esult, it has always highe thoughput than the IR and UIR stategies when the mean quey geneate time is vey low. Fo example, as shown in Figue 7b, when the quey geneate time educes fom 20 seconds to 5, the thoughput of the IR algoithm emains at about 30, wheeas the thoughput of UIR stategy inceases fom about 70 to about 103. At the same time the thoughput of ou stategy inceases fom 82 to 122. When the mean quey geneate time is vey high i.e., aound 300 seconds, the boadcast channel has enough bandwidth to seve the client equest, and hence thee stategies have almost simila thoughput The numbe of uplink equests To evaluate the effectiveness of ou stategy to uplink bandwidth utilization, we study the effect of mean update aival time and mean quey geneate time ove numbe of uplink equests. As shown in Figue 8, ou stategy has the lowest uplink cost, wheeas the IR (a (b Figue 8 The numbe of uplink equests pe inteval (N = 1000 items, C = 50 items, no client disconnection. (a T q = 50 sec (b T u = 100 sec The disconnection ovehead Figue 9 shows the effect of diffeent disconnection times on the disconnection ovehead. The ovehead consideed is the additional numbe of bits tansmitted on downlink channel due to cached items those have become invalid duing the disconnection. Since ou stategy has no oveheads due to disconnection less than 200 Jounal of Digital Infomation Management Volume 3 Numbe 2 June

6 seconds (w*l, the compaison between UIR and ou stategies has been shown fo disconnection time longe than 200 seconds. The figue shows that the UIR stategy has always highe ovehead than ou stategy. As ou stategy uses disconnection epot (DR, the maximum ovehead is C bits. When disconnection time is slightly highe than w*l o has vey lage value, the ovehead is less than C bits as all the cached items may be valid/invalid. In UIR stategy, the numbe of invalid items inceases with the incease of disconnection time, thus inceasing the econnection ovehead. Fo IR stategy, if the disconnection time is longe than 200 seconds, a client assumes that all the cached data items have become invalid and deletes them fom the cache. To seve the futue equests the client will download the items fom the seve and thus, the ovehead is a vey lage value as compaed to ou scheme and hence not shown in the figue. Figue 9 Client disconnection ovehead as a function of the mean disconnection time (T u = 10 sec, T q = 50 sec, N = 1000 items, C = 50 items The effect of client disconnection time Figue 10 shows the effects of the client disconnection time. In ou stategy, the client keeps the valid cache items even though it has been disconnected fo a long time (lage than w*l seconds. Thus, the quey latency of ou stategy does not change too much as the client disconnection time changes. Since a client geneates less queies when the mean disconnection time inceases, the thoughput of UIR and ou stategies dops as the mean disconnection time inceases. In the IR stategy, if a client disconnects longe than w*l seconds, it has to discad the whole cache. Since the client disconnection time is exponentially distibuted, the cache hit atio of IR stategy dops as the disconnection time gows until w*l = 200 seconds. Since the quey latency inceases as the cache hit atio dops, the quey latency of the IR stategy gows to almost 20 seconds as the disconnection time inceases to 200 seconds. (b (a Figue 10 The quey latency and thoughput as a function of the mean disconnection time (T u = 100 sec, T q = 25 sec, N = 1000 items, C = 50 items. 5 Conclusions and Futue Wok With the inceased use of potable computing devices, the mobile computing has eached a stage that enables foeseeing easy access to infomation anywhee, anytime. Howeve, it demands solutions to mask unstable connectivity and limited enegy. Caching at mobile client can enhance the data access pefomance in such envionments. To ovecome the demeits of existing IR and UIR stategies, this pape pesents a synchonous stateful cache invalidation stategy that educes the quey latency, disconnection oveheads, use of wieless channel and conseve the client battey enegy. Simulation expeiments show that ou stategy pefoms bette than IR and UIR schemes. 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7 19. Lai, K. Y., Tai, Z., & Betok, P. (2003. An Analytical Study of Boadcast Based Cache Invalidation in Mobile Computing Netwoks. CoopIS/DOA/ODBASE, Chuang, P.J., & Hsu, C.Y. (2004. An Efficient Cache Invalidation Stategy in Mobile Envionments. IEEE Intenational Confeence on Advanced Infomation Netwoking and Application (AINA. 21. Wang, Z., Das, S. K., Che, H., & Kuma, M. (2003. Scalable Asynchonous Cache Consistency Scheme (SACCS fo Mobile Envionments. ICDCS Wokshops, Wang, Z., Kuma, M., Das, S. K., & Shen, H. (2003. Investigation of Cache Maintenance Stategies fo Multi-cell Envionments. Mobile Data Management (MDM, Chand, N., Joshi, R. C., & Misa, M. (2004. Boadcast Based Cache Invalidation and Pefetching in Mobile Envionment. Intl. Conf. on High Pefomance Computing (HiPC, Spinge LNCS 3296, Chand, N., Joshi, R. C., & Misa, M. (2005. Enegy Efficient Cache Invalidation in Wieless Mobile Envionment. Poceedings of IEEE Intenational Confeence on Pesonal Wieless Communications (ICPWC, Chand, N., Joshi, R. C., & Misa, M. Enegy Efficient Cache Invalidation in a Disconnected Wieless Mobile Envionment. Intenational Jounal of Ad Hoc and Ubiquitous Computing (IJAHUC, to appea. Jounal of Digital Infomation Management Volume 3 Numbe 2 June