Hong Yao, Han Zhang, Changkai Zhang and Deze Zeng. Jie Wu* and Huanyang Zheng

Transcription

1 330 Int. J. Coputational Science and Engineering, Vol. 4, No. 4, 207 Data or index: a trade-off in obile delay tolerant network Hong Yao, Han Zhang, Changkai Zhang and Deze Zeng Hubei Key Laboratory of Intelligent Geo-Inforation Proceing, School of Coputer Science, China Univerity of Geocience, Wuhan, Hubei, , China Eail: yaohong@cug.edu.cn Eail: ylarohn@gail.co Eail: cug09evan@gail.co Eail: dazzae@gail.co Jie Wu* and Huanyang Zheng Departent of Coputer and Inforation Science, Teple Univerity, Philadelphia, PA 922, USA Eail: iewu@teple.edu Eail: huanyang.zheng@teple.edu *Correponding author Abtract: Acquiring content through obile network i a baic and general topic. Mobile node have two different way of obtaining data. The firt ethod i to download data quickly through 3G/4G network, which i expenive. The econd way i to get data fro other node by ean of delay tolerant network (DTN), which are uch cheaper, but are tie-conuing. Throwboxe deployed in DTN act a fixed ferry node. The index record the hitorical encounter inforation, in order to give the obile node predictive abilitie regarding future encounter event. We try to copare the effectivene when we replace oe pace for the data to index. We bring forward an index-baed buffer pace anageent echani for throwboxe, by which obile node can have the chance to fetch data at a lower total cot. Preliinary iulation deontrate that the buffer pace allocation trategy i affected by oe yte paraeter, and that replacing oe pace for data with an index can lower the yte total cot ignificantly in ot cae. Siulation reult alo how that the index-baed buffer pace anageent echani outperfor other echani which only tore data ite or hold an index of tatic ize. Keyword: obile network; delay tolerant network; DTN; throwbox; index. Reference to thi paper hould be ade a follow: Yao, H., Zhang, H., Zhang, C., Zeng, D., Wu, J. and Zheng, H. (207) Data or index: a trade-off in obile delay tolerant network, Int. J. Coputational Science and Engineering, Vol. 4, No. 4, pp Biographical note: Hong Yao received hi PhD in Coputer Architecture fro the Huazhong Univerity of Science and Technology, Wuhan, Hubei, China in 200. He i currently an Aociate Profeor with the School of Coputer Science, China Univerity of Geocience, Wuhan , China. He i alo with Hubei Key Laboratory of Intelligent Geo-Inforation Proceing, China Univerity of Geocience, Wuhan , China. Hi current reearch interet include coputer network and ditributed yte. Han Zhang received hi Mater degree in School of Coputer Science, China Univerity of Geocience, Wuhan , China in 205. Hi current reearch interet include coputer network and ditributed yte. Changkai Zhang i puring hi MS in School of Coputer Science at China Univerity of Geocience, Wuhan , China. Hi current reearch interet include coputer network, and ditributed yte. Copyright 207 Indercience Enterprie Ltd.

2 Data or index: a trade-off in obile delay tolerant network 33 Deze Zeng received hi PhD and MS in Coputer Science fro the Univerity of Aizu, Aizu-Wakaatu, Japan, in 203 and 2009, repectively. He received hi BS degree fro the School of Coputer Science and Technology, Huazhong Univerity of Science and Technology, China in He i currently an Aociate Profeor with the School of Coputer Science, China Univerity of Geocience, China. He i alo with Hubei Key Laboratory of Intelligent Geo-Inforation Proceing, China Univerity of Geocience, Wuhan , China. Hi current reearch interet include: cloud coputing, oftware-defined enor network, data centre networking, networking protocol deign and analyi. Jie Wu i the Chair and Laura H. Carnell Profeor in the Departent of Coputer and Inforation Science at Teple Univerity. Prior to oining Teple Univerity, he wa a Progra Director at the National Science Foundation and Ditinguihed Profeor at the Florida Atlantic Univerity. Hi current reearch interet include obile coputing and wirele network, routing protocol, cloud and green coputing, network trut and ecurity, and ocial network application. He regularly publihe in cholarly ournal, conference proceeding and book. Huanyang Zheng received hi BEng in Telecounication Engineering fro Beiing Univerity of Pot and Telecounication, Beiing, China, in 202. He i currently a PhD candidate in the Departent of Coputer and Inforation Science, Teple Univerity, Philadelphia, Pennylvania, USA. Hi current reearch focue on obile network, ocial network, and cloud yte. Introduction The rapid growth of all kind of obile device lead to a obile data exploion. According to Cico Viual Networking Index (Cico VNI) ( obile data traffic will increae ten-fold between 204 and 209. Mobile data traffic will grow at a CAGR of 57% between 204 and 209, reaching 24.3 exabyte per onth by 209. Mobile data offloading ee to be the ot proiing olution at thi oent. On the other hand, a lot of obile data flow are not delay-enitive, e.g., eaging, file tranfer, and data dieination. And, Lee et al. (203) indicate that delayed traniion can achieve ubtantial gain. In Meheti and Spyropoulo (204), the author further analye the proble and give oe expreion to chooe the optial deadline. In thi paper, we explore a new way to offload the obile data by uing DTN a a collaborative entirety. In Fall (2003), delay tolerant network (DTN) perfor the o-called tore-carry-forward paradig to deliver eage in an end-to-end fahion, ince the obile node ha a high node obility, a low cache capability, and a liited energy, haring data between node ay not be efficient enough. An alternative approach i to equip the DTN with dedicated fixed node, called throwboxe in Zhao et al. (2006), which are tationary wirele node with ignificantly iproved torage and energy capabilitie that iply act a fixed relay. Traditional offloading trategy and the deadline-driven echani ake obile node alway try to wait fetching data fro throwboxe until the deadline. For oe data requet which can hardly be fetched before deadline, obile node alo have to wait till the deadline. A lot of waiting tie i unneceary and wated. To addre thi iue, we bring index into throwboxe. Index i a table file recording the hitorical contact inforation between obile node and throwboxe. Throwboxe can ue thi knowledge to predict future contact event and give obile node prediction about whether they can fetch the data fro throwboxe. Many obility odel in Jereie et al. (2006), Spyropoulo et al. (2006) and Ibrahi et al. (2007) prove that the contact event between throwboxe and obile node i predictable. With the prediction, obile node can ake a wie choice to avoid the eaningle waiting. However, the added index file hare the liited buffer with the data. Soe data pace ut be acrificed for toring the index file. So, here coe the proble: i it worthy to add the index file into throwboxe although it ay reduce the hit rate of uer fetching data fro throwboxe? Our initial otivation i to find out the effect of replacing oe of the data pace with the index file. We define that the total cot of the data fetching i fored by the tie conuption and traniion cot. And how to balance data pace and index file pace, to achieve the iniied total cot, under different network condition, i the obective of thi work. The key contribution of thi paper are uaried a follow: We add an index file to the throwboxe, aking throwboxe able to not only tore data ite, but alo give obile node uggetion about how to fetch the requeted data in a in-cot way. We propoe a novel future event prediction algorith. Differing fro the traditional approach, we et the data contact event a the prediction target intead of the obile node contact event. We preent a index-baed buffer allocation echani to balance the data file pace and index file pace to achieve the iniie total cot. We conduct extenive iulation to evaluate the index-baed echani. The reult clearly how that the index-baed buffer allocation echani

3 332 H. Yao et al. ignificantly outperfor the traditional data-only echani. The reainder of thi paper i organied a follow. We introduce the yte odel in Section 2, and then we introduce the data encounter prediction approach in Section 3. The buffer pace allocation echani i preented in Section 4. Siulation reult which are preented in Section 5 prove our theory. Finally, we review the related work in Section 6 and conclude the paper in Section 7. 2 Syte odel In thi ection, we introduce the yte odel, including network odel, utility odel and delivery odel. 2. Network odel We conider a obile network with a node et N = N t N n, where N t and N n donate the et of throwboxe and obile node, repectively. All the obile node independently and randoly ove on a two-dienional plane. Throwboxe are ditributed on oe pot of the plane. We aue that all the throwboxe are fully connected. All the data tored in both obile node and throwboxe for a dataet M. Each data i with equal ize and can be copletely delivered within one encounter. Mobile node randoly requet data i M. The data i tored in throwboxe and obile node. Each throwbox ha a liited buffer. We conider all ditributed buffer for into an unifor one, becaue of they are fully connected. The ize of the big buffer i denoted a B and we define that b data and b index repreent the ize of buffer pace tored data and index file, repectively. Mobile node have two choice to fetch the requeted data: fetch the data through cellular network with traniion cot cc at any location 2 fetch the data fro throwboxe via Wi-Fi with traniion cot c d, when obile node are in a location near the throwbox, a hown in Figure. 2.2 Utility odel Baed on the baic network odel, we preent the utility odel a follow. Each ucceful data fetching contain a benefit, denoted by W(t). The benefit decreae linearly a tie t elape. The initial benefit of a data i denoted by W, while the initial benefit of different data are different. The ditribution for the initial benefit of different data follow the truncated noral ditribution, the ean value of which i denoted by W. The decreaed benefit value within each unit tie interval i defined a the benefit decay coefficient, denoted by ζ. Forally, the benefit atifie the following forula: Wt () = W tζ () The utility i defined a the benefit inu the traniion cot, denoted by U(t). Let c denote the total cot incurred by eage forwarding until tie t, then the utility atifie: Ut () = Wt () c (2) and (2) can be changed into: Ut () = W ( tζ + c) (3) We define the t d, which ake the utility equal zero, i the deadline of a data fetching. Aue that the total cot of a data fetching including the tie conuption and traniion cot i denoted a: a = tζ + c. Our obective i to axiie the utility. 2.3 Delivery odel A obile node generate different data requet, each requet with the deadline t d. Once a data requet i generated, according to the coparion of deadline and etiated encounter tie, obile node now need to decide whether to fetch the data in the cellular network. Depending on whether the throwbox tore the requeted data or not, there are two different ode for the obile node to get the data fro throwbox: Figure 2 Data contact tieline Figure The network odel 2.3. Direct ode If any throwbox hold the requeted data, the obile node will reply with the requeted data iediately Indirect ode Otherwie, the throwbox replie an etiation about how long it will take to get the requeted data fro DTN, and the

4 Data or index: a trade-off in obile delay tolerant network 333 probability. Then, the node can ake a deciion whether to fetch the data via cellular network right now. 3 Data contact prediction In thi ection, we introduce the data contact prediction algorith. The data contact prediction include two part: hitory record collecting and future contact prediction. Table Data ite Contact hitory record Contact tie t 2nd kth Data t t 2 t k Data 2 T 2 t 22 t 2k Data i t i t i2 t ik Data M t M t M2 t Mk 3. Hitory record collecting When a obile node carrying data ite i contact with a throwbox, we conider thi contact event a a data contact of ite i. Throwboxe will record the nae of the data and the current tie. Then, throwboxe ue thee record to build a data contact table. The data contact table i tored a an index file in the big buffer. Table give an exaple. Then, the tie pan in contact table can be ued a input to predict the tie of the next data contact. 3.2 Future contact prediction We introduce a novel algorith to predict future data contact: tie-window-baed predict algorith. Figure 2 how an exaple about one data ite contact tieline (a row in the data contact table), where the tie pot i denoted a t and t k repreent the tie pot of the k th data contact. The offline tie i denoted a T. Tie-window-baed prediction ue the forer k offline tie to predict the k th offline tie T k. J = {T, T 2,, T i,, T k } repreent the et of one data ite offline tie fro the firt data contact to the k th. We conider the axiu offline tie in et J i T Max, T Max > T i J and we take Δt T a the iniu decreae eta, where t = Max. Then we ue Δt to build an arithetic progreion K = {Δt, 2Δt,, iδt,, kδt}. Every ite in K i a candidate predicted offline tie. By coparing the candidate predicted offline tie with every hitorical offline tie, we can find a ot reliable value. (4) ue thee candidate of K a an input to calculate the reliability R(iΔt) of each candidate predicted offline tie: k 0 a = i t T Ri ( t) =, a =, i [, k] k i t > T k (4) where a i an indicator and equal to only when the candidate i larger than the offline tie T. Then, we copare R(iΔt) with a threhold R th, and take the iniu R(iΔt) of all R(iΔt) that larger than the threhold a R : { th} Rin = in R( i t) R( i t) > R, i [, k] (5) The threhold R th can be ued to control the preferred R(iΔt), we take the R th = 0.5 here. Under thi etting, the calculated iδt i cloe to the edian value of all the offline tie T i. We take the iδt whoe reliability i R in a the final predicted offline tie PT k : k { ( ) in} PT = i t R i t = R (6) In reality, the data encounter frequency can change dynaically becaue the obile node do not hold the data ite all the tie, the total copie of one data ite i not tatic. To quickly adapt to uch dynaic factor, we iprove the baic ethod by a tie-window technique. It principle i to egent the whole tieline into a erie of aller tie window and to place the highet ephai on the ot recent record while gradually decreaing the ephai on the preceding one. Suppoe the tieline wa divided into tie window, and the et of the data ite offline tie alo wa divided into all et: { T, T,..., Tk},{ Tk + Tk,..., T( + ) k },...,{ T( ) k, T( ) k, , T k }, and the accuracy calculated of the th tie window i expreed a: ( + ) k a k = 0 ( ) + i t T R i t =, a = k i t > T Now, (4) can be iproved and expreed a a weighted average of R (iδt) over tie window: Ri ( t) = ω R ( i t) + ω R ( i t) ω R ( i t) 2 2 = ω R ( i t) = where ω i the weight of the tie window. Different weight-election ethod (e.g., linearly or exponentially decreaing weight) would dicard the hitory data at different rate. Here, we iply give the th tie window the weight of: ω i= (7) (8) = (9) i Lot of prediction algorith accuracy rate grow extreely lowly after they have enough hitorical record, which ean there i a convergence tate. Through tet and analyi, we find that the convergence accuracy of the tie-window-baed prediction i 80% and the convergence ize of the index i 40 (ore detail will be hown in Section 5).

5 334 H. Yao et al. Figure 3 Table 2 Para. c c c d t r t t 2 t d Data fetching tieline Syte paraeter Explanation Traniion cot of cellular network Traniion cot of DTN The tie of uer generate a data requet The tie of uer eet a throwbox The tie of uer fetch a data fro throwbox 4 Buffer pace allocation The deadline of a data requet Becaue of the liited buffer ize, a large index file ean le pace to tore data ite. In order to achieve a better yte perforance, an efficient buffer pace allocation trategy i needed iinently to conider the trade-off. In thi ection, we propoe a buffer pace allocation echani to anage the buffer pace in throwboxe. 4. Data fetching proce Coplete proce of one ucce data fetching i hown in Figure 3. All the paraeter are lited in Table 2. Baed on the network and delivery odel, a coplete proce of data fetching could be any one of the following five ituation: Cae : If obile node could not encounter any throwbox before the deadline, which ean it ipoible to fetch the data via DTN. The bet choice i to download the data via cellular network iediately. So, the total cot in thi cae i A = t r ζ + c c. Cae 2: If obile node chooe not to fetch the data via cellular network at t r, then encounter a throwbox before the requet deadline at t. Once the throwbox buffer tore the requeted data, obile node can coplete thi traniion by downloading it fro the throwbox. So, the total cot in thi cae i A 2 = t ζ + c d. Cae 3: If obile node eet a throwbox at t but the throwbox doe not have the data. Then, throwbox will reply a tie prediction which i t 2, and let obile node to chooe waiting for throwboxe to fetch it, or fetching it via cellular network iediately. If obile node chooe not to wait, then the total cot of thi data fetching i A 3 = t ζ + c c. Cae 4: After eeting the throwbox for the firt tie, the obile node could wait and continue oving. At tie t 2, obile node fetche the data via DTN fro another throwbox in indirect ode uccefully. Then, the total cot i A 4 = t 2 ζ + c d. Cae 5: Siilar to cae 4, obile node chooe to wait to fetch the data in indirect ode. However, a wrong tie prediction ake it could not fetch the data via DTN before the deadline. Mobile node ha to fetch the data via cellular network at deadline t d with the total cot A 5 = t d ζ + c c. 4.2 Utility function optiiation By analying the data fetching progre, we preent the optial ize of the index file to achieve the axiu utility. Theore : Suppoe the ize of the index buffer pace i denoted a, the optial ize achieved the axiu utility can be found and can be changed under different network condition. To a requet of data i, the utility i the reaining benefit when the traniion i finihed. Thu, the yte total benefit of ucce data fetching for a certain tie can be preented a: ( ) (0) U = W a total = where repreent the th data fetching. Since obile node requet the data randoly, the acce probability of each data i M i equal. Due to the ditribution for the initial benefit of different data follow the truncated noral ditribution with a ean value W, the u of ucce data fetching initial benefit can be calculated a W = W. Then (4) can be changed into: = total U = W a () = So, our obective can be converted to iniiing the total cot = a. Baed on the five data fetching cae, the total cot of one ucce fetching proce a rando data i can be preented a: a = P0A+ ( P0) ( PA 2 + ( P) Ax ) (2) where P 0 i the probability that the data requet deadline coe before obile node encountering a throwbox, and P i the probability that requeted data i exiting in the buffer of throwboxe. If requeted data i not in the data buffer, then the cot A x can be preented a:

6 Data or index: a trade-off in obile delay tolerant network 335 A = PA + ( P) A (3) x 2 y 2 3 where P 2 i the probability that the requeted data i exiting in the index file of throwboxe, in other word, a predicted t i can be delivered. A y i the cot after the predicted t i i given and A y can be preented a: Ay = P3( P4A3 + ( P4) A4) + ( P3) A5 (4) where P 3 i the accuracy of the predicted offline tie and P 4 i the probability that predicted data contact delay i within the requet deadline. Siultaneouly conidering (4), (5) and (6), the average total cot of one ucceful data downloading can be preented a: a = P0A+ ( P0)( PA 2 + ( P) { P2{ P3( P4A3 + ( P4) A4) + ( P3) A5 + ( P2) A3}) (5) In order to calculate the tie cot and traniion cot ynthetically, we tranfor all the cot into the for of c d. Suppoe that: t = c, t = c, t = c, t = c cc = 0cd r d 2 d 2 3 d 4 4 d (6) where 0,, 4 are controllable paraeter, by changing the value of 0,, 4, the yte can odify the weight of tie and traniion cot in the total cot and adapt the delay-enitive or the traniion-cot-enitive environent. Then, we can get: A = 0cd A2 = ( 2 + ) cd A3 = ( 2 + 0) c A4 = ( 3 + ) cd A5 = ( 4 + 0) c d d (7) Siultaneou (7) and (9), we can change the proble into calculating the iniied coefficient of c d. The ize of data index eta i k (a we explained in Section 3) and uppoe the ize of the index buffer pace are denoted a. So, P and P 2 can be preented a: B * P =, P2 =, ( 0, ) (8) M Mk where * = in{b, Mk} and it enure that there i at leat one pace to tore the data ite. P 0, P 3 and P 4 are known contant. Suppoe that F() repreent the coefficient function of (9): ai F () = (9) c d Then after erging iilar ter, F() can be preented a: α β (20) 2 F () = + + γ where α, β, γ are fored by paraeter B, M, k, P 0, P 3, P 4, 0,, 2, 3, 4. The derivative of F() can be preented a: F () = 2α + β (2) So, when α 0, F() achieve the iniu if: = β 2α o we can know that the optial atifie: β β, 0 < < 2α 2α β = 0, 0 > 2α * β *, > 2α and when α < 0, F() achieve the axiu if: = β 2α o we can know that the optial atifie: β 0, > 2α 2 = β, 2α 2 * * * * (22) (23) (24) (25) With all the paraeter entioned above, the utility function can evaluate the yte total utility, and give the optial index file ize. 4.3 Buffer pace anageent algorith Bae on the theoretical analyi above, we develop the index-baed buffer pace anageent algorith, a hown in Algorith. The index-baed buffer pace anageent guarantee that throwboxe will chooe the bet way to allocate the buffer pace to ake ure the yte total cot i the iniu. Index-baed buffer pace anageent include four phrae: trategy-chooing phrae, fill-up phrae, adutent phrae and tatic phrae. Buffer pace anageent algorith: Input: Syte paraeter: M, B, k, P 0, P 3, P 4, 0,, 4 ; : With all the paraeter, calculate the uing (6); 2: According to different α, copare the and * to deterine the optial ; 3: for each data i contact event do 4: if optial = 0 then 5: if b data < B then 6: if data i b data then 7: fetch data i into the buffer; 8: end if

7 336 H. Yao et al. 9: ele 0: break; : end if 2: ele 3: if b data + < B then 4: record thi contact inforation into index file; 5: if i b data then 6: fetch data i into the buffer; 7: end if 8: ele 9: if < then 20: delete the data ite with the lowet initial benefit and record thi contact inforation; 2: ele 22: delete the oldet contact inforation and tore thi new one; 23: end if 24: end if 25: end if 26: end for 4.3. Strategy-chooing phrae At the very beginning of the yte operation, throwboxe ut deterine the torage trategy. Step and 2 calculate the uing (24) according to the correponding paraeter, then coparing the and * to chooe the optial which achieve the axiu yte benefit, and ue the optial to guide the later phrae Fill-up phrae Step 4 to 9 how that if the optial = 0, then throwboxe will tore the data ite into the buffer until it i full, intead of recording any contact inforation. After the buffer i full of data, the yte goe to the tatic phrae. If the optial = * or = β, then whenever a obile node holding 2 α oe data ite encounter a throwbox, throwbox will record the data contact inforation into index file, and fetch the data ite into the buffer if thee ite have no copie in the buffer (tep 0 4). Thi procedure will continue until the buffer i full, after that, yte goe to the next phrae Adutent phrae Once the buffer i full, yte uing tep 6 to 9 to delete one data ite and ue the epty pace to tore the upcoing data contact inforation. After a while, the epty pace will be ued up and another data ite will be deleted a before. Thi phrae will end a long a the index file reache the ize of optial and yte will go to the tatic phrae Static phrae In thi phrae, the proportion of data buffer and the index file will not change anyore. The replaceent trategy of new data contact record and new data ite are ae a the trategy in adutent phrae. 5 Evaluation and dicuion In thi ection, we preent our iulation to evaluate the perforance of buffer pace allocation algorith under variou etting. The evaluation ethod, etting, and reult are preented a follow. 5. Siulation etting and etric We ue two type of trace to conduct our iulation. The firt trace i generated by the ONE iulator in Keranen et al. (2009). We deploy 00 obile node in a all area of a real city: Helinki, Finland. Mobile node perfor hortet path ap-baed oveent pattern on the road. The econd trace i a large-cale dataet of real GPS trace fro around 320 taxie operational in the urban area in Roe, Italy. In the iulation, the virtual throwboxe are deployed in the treet in every two kiloetre. Each obile node ha a buffer to tore five data ite, and generate a requet of a rando data ite fro the et M. At the initiate tage of the yte, obile node tore five data ite randoly elected fro the et M and throwboxe have a hort tie to war up recogniing the baic inforation of the whole network. We run the iulation under two different nuber of data, M = 300, 400. Then we take P 4, B and k a our ain obect of obervation. Deadline i deterined by the initial benefit, the initial benefit W follow the truncated noral ditribution with the ean value W = 20,000. In order to iplify the iulation, we et different requet deadline to repreent the initial benefit. We et the default index eta ize a 0.05 while the ize of a data ite i et a. We cobine all throwboxe buffer a one big buffer ized fro B = 55 to B = 00 becaue of the full connection. In order to evaluate the effect of the index-baed buffer pace anageent algorith, we alo ipleent a traditional buffer anageent echani called data-only buffer pace anageent, where throwboxe ue all torage pace to tore the data ite. Table 3 Evaluation etting Paraeter nae Default Range Nuber of obile node N n Nuber of data M Deadline 20,000 5,000 45,000 Throwboxe buffer ize B Index eta ize k

8 Data or index: a trade-off in obile delay tolerant network Reult and dicuion Firtly, to evaluate the accuracy of the tie-window-baed prediction, we run oe tet and reult are hown a Figure 4. We record every encounter tie of a rando data ite i and repeat the iulation with different nuber of contact record for 00 tie each. Figure 4 how that the prediction accuracy i increaing a the hitorical record grow up until the index record about 40 tie contact inforation. Then, the prediction accuracy tay around the 80%. So, in the following iulation, throwboxe index only record 40 latet contact inforation. Figure 5 Syte average offloading ratio under generated trace, (a) offloading ratio v. ize of throwbox buffer (b) offloading ratio v. deadline (c) offloading ratio v. ize of index eta (ee online verion for colour) Figure 4 Prediction accuracy under different nuber of hitorical record (ee online verion for colour) (a) 5.2. Effect of the throwbox buffer ize Figure 5(a) and Figure 7(a) how the offloading ratio under different throwbox buffer ize. We can ee that when the ize of the throwbox buffer increae, the offloading ratio of two algorith will increae and the offloading ratio of index-baed algorith i alway higher than the data-only algorith. And we alo notice that the yte perforance i different under different nuber of data ite M = 300 and M = 400. More data ite ean ore diverity data requet, which will reduce the requet hit rate in the throwbox buffer. Figure 6(a) and Figure 8(a) give the average delay of all the data fetching. A we had expected, the average data fetching delay of index-baed algorith i uch lower than the data-only algorith. Thi i due to the future contact prediction algorith. (b) (c)

9 338 H. Yao et al. Figure 6 Syte average delay under generated trace, (a) delay v. ize of throwbox buffer (b) delay v. deadline (c) delay v. ize of ize of index eta (ee online verion for colour) Figure 7 Syte average offloading ratio under real trace, (a) offloading ratio v. ize of throwbox buffer (b) offloadingratio v. deadline (c) offloading ratio v. ize of index eta (ee online verion for colour) (a) (a) (b) (b) (c) (c)

10 Data or index: a trade-off in obile delay tolerant network 339 Figure 8 Syte average delay under real trace, (a) delay v. ize of throwbox buffer (b) delay v. deadline (c) delay v. ize of ize of index eta (ee online verion for colour) (a) rate of the data-only algorith i very low and increaing rate of the index-baed algorith i uch higher at the beginning and gradually low down. To the data-only algorith, due to lack of network global inforation, data ite in throwboxe buffer do not change ince the buffer i full. It can increae the hit rate in throwboxe buffer but the efficiency i quite low. When the deadline i long enough for ot data requet can be fetched fro other obile node, the increaing rate reduce. The initial benefit influence to average delay i repreented in Figure 6(b) and Figure 8(b). A we can ee, when the deadline i hort, the gap between the two algorith i quite narrow. But a the deadline increaed, the gap i wider and wider. The reaon i that when the deadline i hort, obile node can hardly have chance to eet the throwboxe ore than once, o the index-baed algorith can barely help obile node to fetch data. But when the deadline enlarge, the advantage of index-baed algorith how up and lot of requet were offloaded before the deadline coing. However, a longer deadline cannot give the data-only algorith the ae benefit, o the gap becoe wider. (b) Effect of the index eta ize Figure 5(c) and Figure 7(c) how that a the ize of the index eta becoe larger, the offloading ratio i reducing. Thi i becaue when the ize of index eta i all (e.g., k = 0.0), replacing a data ite can tore 00 ore data index into the buffer and the pace of three data ite can tore all the data index if the nuber of data i 300, thi kind of replacing i very efficient. When the ize of index eta i increaing, replacing data ite with index i till ueful but not that ignificantly. The average delay howed in Figure 6(c) and Figure 8(c) alo give the ae reult. A aller index eta ize give throwboxe ore pace to tore data ite and it can bring a horter delay. (c) Effect of the deadline Figure 5(b) and Figure 7(b) how the offloading ratio under different initial benefit. Initial benefit deterined the deadline of each data requet, o we chooe to change the deadline to oberve the yte perforance. The increaing 6 Related work Throwboxe-baed DTN are firt propoed in Zhao et al. (2006). In the later work in Ibrahi et al. (2007, 2009), iulation reult and real deployent have deontrated that iporting a nuber of throwboxe into the DTN can indeed iprove the routing perforance and overall throughput. Beide, oe other tudie focuing on analytical odel for delay ditribution in Gu et al. (200) and deigning/evaluating routing trategie in Gu et al. (200) for throwbox-baed DTN are alo preented. Meanwhile, Baneree et al. (200) conider the proble about energy efficiency of each throwbox node for throwbox-baed DTN. The ain difference between our work and previou work i that we ipleent a contact prediction echani on throwboxe, by acrificing oe data torage, and treat throwboxe a both data buffer and forecat equipent. To the bet of our knowledge, thi i the firt work that ake throwboxe becoe ultifunctional.

11 340 H. Yao et al. In exiting prediction-baed chee, obile node obility and contact i etiated baed on a hitory of obervation. A repreentative cae i uing utility-routing in Lindgren et al. (2003) and Zhang et al. (2007), where obile node conider the utility value a the predictor of two node future likelihood of encounter. Deng and Chang (204) propoe a ulticat routing chee baed on ocial difference (SDMR), which conider the ocial difference between node, including both the iilarity and the centrality difference. LeBrun et al. (2005) propoe a routing algorith for VANET that ue the current poition and traectorie of node to predict their future poition and calculate the ditance to the detination. Yeh et al. (204) reveal a yte perforance prediction and analyi ethod for ulti-core yte by adopting electronic yte-level (ESL) deign ethodology. In Burn et al. (2005), they propoe a prediction chee that ue pat frequencie of contact, a well a the pat contact. Another prediction-baed generic algorith for DTN routing i MobySpace in Leguay et al. (2006), which ue a highdienional Euclidean pace contructed upon node obility pattern. The aor difference between our approach and previou work i we take the data a our target of prediction. 7 Concluion In thi paper, we introduce a novel throwbox deign by adding an index file into the buffer, which odifie the throwbox fro a pure data buffer into a data tranfer helper with future prediction. Aiing at the trade-off between data and index, we propoe a utility function to evaluate the yte perforance under different cobination of variable. Theoretical analyi how that replacing oe data ite with an index file in the buffer can reduce the total cot effectively in ot cae. Siulation reult alo prove that the index-baed prediction play an iportant role in reducing the traniion cot of data fetching. Beide, iulation further how that the index-baed buffer pace allocation echani outperfor the iple index-added echani. Our future work will ainly focu on two apect. The firt i to extend current yte odel to enable data traniion aong obile node. Secondly, we will bring in real-world trace into iulation to evaluate the yte perforance. Acknowledgeent Thi reearch wa upported by the NSF of China (Grant No , , , ), the China Potdoctoral Science Foundation funded proect (Grant No. 204M562086), the Fundaental Reearch Fund for National Univerity, China Univerity of Geocience, Wuhan (Grant No. CUG4065, CUGL50829), the Provincial Natural Science Foundation of Hubei (Grant No. 205CFA065). Reference Baneree, N., Corner, M.D. and Levine, B.N. (200) Deign and field experientation of an energy-efficient architecture for DTN throwboxe, IEEE/ACM Tranaction on Networking, Vol. 8, No. 2, pp Burn, B., Brock, O. and Levine, B.N. (2005) MV routing and capacity building in diruption tolerant network, in IEEE INFOCOM. Cico Viual Networking Index (Cico VNI) Forecat and Methodology, White Paper [online] Deng, X. and Chang, L. (204) A tie-conidered ulticat routing chee baed on ocial difference in delay-tolerant network, in International Journal of Ebedded Syte, Vol. 6, No., pp Fall, K. (2003) A delay tolerant network architecture for challenged internet, in ACM SIGCOMM. Gu, B., Hong, X., Wang, P. and Borie, R. (200) Latency analyi for thrown box baed eage dieination, in IEEE Globeco. Ibrahi, M., Al Hanbaliand, A. and Nain, P. (2007) Delay and reource analyi in MANET in preence of throwboxe, Perforance Evaluation, Vol. 64, No. 9 2, pp Ibrahi, M., Nain, P. and Carrera, I. (2009) Analyi of relay protocol for throwbox-equipped DTN, in WiOPT. Jereie, L., Tiur, F. and Vania, C. (2006) Evaluating obility pattern pace routing for DTN, in IEEE INFOCOM. Keranen, A., Ott, J. and Karkkainen, T. (2009) The ONE iulator for DTN protocol evaluation, in Siutool. LeBrun, J., Chuah, C. and Ghoal, D. (2005) Knowledge baed opportunitic forwarding in vehicular wirele ad hoc network, IEEE VTC, Vol. 4, pp Lee, K., Lee, J., Yi, Y., Rhee, I. and Chong, S. (203) Mobile data offloading: how uch can WiFi deliver?, IEEE/ACM Tranaction on Networking, Vol. 2, No. 2, pp Leguay, J., Friedan, T. and Conan, V. (2006) Evaluating obility pattern pace routing, in IEEE INFOCOM. Lindgren, A., Doria, A. and Schelen, O. (2003) Probabilitic routing in interittently connected network, ACM SIGMOBILE Mobile Coputing and Counication Review, Vol. 7, No. 3, pp Meheti, F. and Spyropoulo, T. (204) I it worth to be patient? Analyi and optiization of delayed obile data offloading, in IEEE INFOCOM. Spyropoulo, T., Pouni, K. and Raghavendra, C.S. (2006) Perforance analyi of obility-aited routing, in ACM MobiHoc. Yeh, J.C., Lin, C.H. and Liu, C.N. (204) Multi-core yte perforance prediction and analyi at the ESL, in International Journal of Coputational Science and Engineering, Vol. 9, No. 2, pp Zhang, X., Neglia, G., Kuroe, J. and Towley, D. (2007) Perforance odeling of epideic routing, Coputer Network, Vol. 5, No. 0, pp Zhao, W., Chen, Y., Aar, M., Coer, M.D., Levine, B.N. and Zegura, E. (2006) Capacity enhanceent uing throwboxe in DTN, in IEEE MASS.