Cloud Service Reliability: Modeling and Analysis

Size: px
Start display at page:

Download "Cloud Service Reliability: Modeling and Analysis"

Transcription

1 Cloud Sevice eliability: Modeling and Analysis Yuan-Shun Dai * a c, Bo Yang b, Jack Dongaa a, Gewei Zhang c a Innovative Computing Laboatoy, Depatment of Electical Engineeing & Compute Science, Univesity of Tennessee, Knoxville, TN, USA b Collaboative Autonomic Computing Laboatoy, School of Compute Science Univesity of Electonic Science and Technology of China, Chengdu, China c Depatment of Industial and Infomation Engineeing, Univesity of Tennessee, Knoxville, TN, USA Abstact Cloud computing is a ecently developed new technology fo complex systems with massivescale sevice shaing, which is diffeent fom the esouce shaing of the gid computing systems. Cloud eliability analysis and modeling ae not easy tasks because of the complexity and lage scale of the system. This pape systematically analyzes cloud computing and models the eliability of the cloud sevices. Vaious types of failues ae inteleaved in the cloud computing envionment, such as oveflow failue, timeout failue, esouce missing failue, netwok failue, hadwae failue, softwae failue, and database failue. This pape investigates all of them to achieve a compehensive pictue about cloud sevice eliability, and models those failues in a holistic manne using Makov models, Queuing Theoy and Gaph Theoy. In accodance with the poposed model, a new evaluation algoithm is futhe developed in this pape integating the Bayesian appoaches togethe with the Gaph Theoy. Keywod Cloud computing, eliability modeling, Gaph theoy, Queuing theoy, Bayesian analysis

2 . Intoduction Cloud computing enables the massive-scale sevice shaing, which allows uses to access technology-enabled sevices without knowledge of, expetise with, o contol ove the technology infastuctue that suppots them. Cloud computing is diffeent fom but elated with gid computing, utility computing and tanspaent computing. Gid computing [] is a fom of distibuted computing wheeby a "supe and vitual compute" composed of a cluste of netwoked, loosely-coupled computes acts in concet to pefom vey lage tasks. Utility computing [2] is the packaging of computing esouces, such as computation and stoage, as a meteed sevice simila to a taditional public utility such as electicity. Tanspaent computing [3] means complex back-end sevices ae tanspaent to uses who only see a simple and easy-touse font-end inteface. The cloud computing deployments ae today poweed by gids, having tanspaent chaacteistics and billed like utilities; but cloud computing is athe a natual next step fom the gid-utility-tanspaent model. Based on this model, the cloud computing can athe ealize the sevice shaing than only the esouce shaing coined by gid computing. The cloud computing is thus moe sevice-oiented than esouce-oiented. Dai et al. [4] has aleady mentioned that the uses do not cae too much about the esouces of the gid system but ae moe concened with the sevices they ae using. Hence, the function of sevice shaing enabled by cloud computing will be moe inteesting to geneal uses than the esouces shaing of the gid computing. A vaiety of cloud sevices ae povided by the cloud system. The cloud system could become vey lage even all ove the whole Intenet. Uses can equest cloud sevices fom any cone of the wold. Some examples of commecial cloud sevices include Amazon EC2 [5], Xen [6], Google Cloud [7], IBM Cloud [8], and Micosoft Cloud [9]. The eliability of the cloud computing is vey citical but had to analyze due to its chaacteistics of massive-scale sevice shaing, wide-aea netwok, heteogeneous softwae/hadwae components and complicated inteactions among them. Hence, the eliability models fo pue softwae/hadwae o conventional netwoks [0-] cannot be simply applied to study the cloud eliability. Theefoe, this pape fist pesents an innovative eliability model fo cloud computing. The cloud eliability model is sevice oiented and hieachical, which is tactable and effective in addessing such a lage and complex system. This new model compehensively consides vaious types of failues that have significant influences on the success/failue of cloud sevices, 2

3 including oveflow, timeout, data esouce missing, computing esouce missing, softwae failue, database failue, hadwae failue, and netwok failue. The emaining of this pape is oganized as follows. Section 2 pesents a geneal achitectue of the cloud computing system and makes a thoough analysis of the cloud sevices. Section 3 builds a holistic model fo cloud sevice eliability and pesents a new evaluation algoithm. Section 4 concludes this pape and discusses the futue eseach. 2. Cloud Computing System and Failue Analysis Cloud computing is distinguished fom conventional distibuted computing by its focus on massive-scale sevice shaing. The chaacteistics of the cloud computing ae descibed in subsection 2., and then vaious failues in a cloud sevice ae analyzed in subsection Desciption of the cloud computing We ae developing a cloud computing system in the VGADS (Vitual Gid Application Development Softwae) poject sponsoed by National Science Foundation (NSF). This system has aleady been collaboating and integated with Amazon EC2 [5]. The achitectue of ou cloud sevice system is depicted in Fig., which is also a typical epesentation of most pesent o futue cloud sevice systems. Thee is a cloud management system (CMS) which is composed by a set of seves (eithe centalized o distibuted). The CMS mainly fulfills fou diffeent functions as shown in Fig. : ) To manage a equest queue that eceives job equests fom diffeent uses fo cloud sevices; 2) To manage computing esouces (such as PCs, Clustes, Supecomputes, etc.) all ove the Intenet; 3) To manage data esouces (such as Databases, Publicized Infomation, UL contents, etc.) all ove the Intenet; and 4) To schedule a equest and divide it into diffeent subtasks and assign the subtasks to diffeent computing esouces that may access diffeent data esouces ove the Intenet. 3

4 Use Cloud Sevices Uses Intenet Job equests equests Uses Cloud Management System (CMS) eq.queue Computing es. Man. Schedule Data es. Man. Schedule Subtasks esouces (Data & Comp) esults C D Netwok C2 C3 D2 D Comp. Intenet Comp. Data Data Data Intenet Intenet Fig.. Cloud Sevice System. When a use equests a cetain given cloud sevice, we apply a wokflow to descibe and manage the cloud sevice [2]. Fig. 2 depicts a wokflow template of a sevice that includes fou diffeent subtasks (S, S2, S3, S4) and thei inteelationship (data dependency), e.g. S3 needs the inputs that esult fom S and S2. It also shows the equied data esouces that the subtasks need to access, e.g., S needs to access data esouce D when unning, S2 needs D2 and D3, and S4 needs D4, but S3 needs nothing. With the given wokflow of a cloud sevice, the schedule in the CMS can assign these subtasks to diffeent computing esouces while allocating the data esouces, as shown in Fig. 2, e.g., the computing esouce C is assigned two subtasks, S and S3, to un, C5 is a data esouce offeing data D2, D3 and D4, and C3 is both computing esouce and data esouce to un subtask S2 while offeing data D and D3. Afte the computing esouces and data esouces eceive the commands/subtasks fom the CMS, they fom a netwok accoding to the connectivity o accessibility, e.g. C3 is diectly connected with C5, but cannot diectly communicate with C4 due to the connectivity (e.g. computes C3 and C4 may be both behind outes that tanslate thei oiginal IP addesses so that they cannot diectly build the TCI/IP connection, o they do not have access to each othe [3]). 4

5 Wokflow of a Sevice S D S3 S4 Schedule S2 D4 D2,D3 C S,S3 C2 C4 S2,S3 S4 C3 S2 D,D3 D2, D3,D4 C5 S D C6 Fig. 2. Wokflow of a Cloud Sevice and Scheduling The cloud netwok shown in Fig. 2 can be vey lage, and each link in Fig. 2 is actually a vitual link that may go though many components (outes/cables/optical fibes/machines) ove a long distance. Thus, the computing esouces will wok togethe via the netwok to un the subtasks while accessing necessay data fom the data esouces. When the job is finished, the esults will etun to the use who equests this sevice, as shown in Fig Failue Analysis of Cloud Sevice As Fig. and Fig. 2 show, thee ae a vaiety of types of failues that may affect the success/eliability of a cloud sevice, including Oveflow, Timeout, Data esouce missing, Computing esouce missing, Softwae failue, Database failue, Hadwae failue, and Netwok failue. We analyze these failues in moe details. Oveflow: The equest queue should have a limitation on the maximal numbe of equests waiting in the queue. Othewise, new equests have to wait fo too long a time in the queue, which could make the Timeout failues much moe dominant. Theefoe, if the queue is full when a new job equest aives, it is simply dopped and the use is unable to get sevice, which is called an oveflow failue. Timeout: The cloud sevice usually has its due time set by the use o the sevice monito. If the waiting time of the equest in the queue is ove the due time, the Timeout failue occus, see e.g. [4]. As a esult, those timeout equests will be dopped fom the queue so that not to affect othe following equests. Data esouce missing: In CMS, the data esouce manage (DM) egistes all data esouces. Howeve, it is possible that some peviously egisteed data ae emoved but 5

6 the DM is not updated. As a esult, if those data esouces ae assigned in a cetain job equest, they will cause the data esouce missing failue. Computing esouce missing: Similaly to the above data esouce miss, the computing esouce missing may also occu, such as PC tuns off without notifying the CMS. Softwae failue: The subtasks ae actually softwae pogams unning on diffeent computing esouces, which contain softwae faults, see e.g. [5]. Database failue: The database that stoes the equied data esouces may also fail, causing that the subtasks when unning cannot access the equied data. Hadwae failue: The computing esouces and data esouces in geneal have hadwae (such as computes o seves) which may also encounte hadwae failues. Netwok failue: When subtasks access emote data, the communication channels may be boken eithe physically o logically, which causes the netwok failue, especially fo those long time tansmissions of lage datasets, see e.g. [6]. The model fo cloud computing eliability has to conside all types of these failues, which would be vey complicated and existing eliability models cannot addess all of these concens in a holistic manne although each single topic has been studied. Moeove, these diffeent types of failues ae actually coelated with one anothe (i.e., not independent) in a cloud sevice which exhibits anothe eason why the cloud eliability model cannot simply utilize any one single existing model in each individual topic (such as softwae eliability, hadwae eliability, o netwok eliability). Fo example, failues of schedules may incease the waiting time, which could affect the timeout and the oveflow failues; a lage queue limit may educe the pobability of oveflow failue but may incease that of the timeout failue; a database failue may make a softwae unable to be finished due to lack of necessay data; netwok failues may block the equied communications among softwae pogams to get necessay inputs fom othes. With such coelations, it is obvious that a new holistic model has to be developed fo cloud eliability. 3. Cloud Sevice eliability Modeling and Evaluation In this section, we develop a holistic model fo Cloud Sevice eliability, which is defined as the pobability that a cloud sevice unde consideation can be successfully completed fo a use in a 6

7 specified peiod of time. In paticula, this equies that the job equest be successfully seved by the schedules in time, the set of subtasks contained by the sevice be completed, the computing/data esouces equied by the subtasks be available; and the netwok be opeational duing the communications. Fom the definition of cloud sevice eliability, it is clea that all types of failues we have discussed in section 2 will moe o less affect this pobability to povide a successful sevice. We classify the above failues in two goups:. equest Stage Failues: Oveflow and Timeout. 2. Execution Stage Failues: Data esouce missing, Computing esouce missing, Softwae failue, Database failue, Hadwae failue, and Netwok failue. The failues in Goup may occu befoe the job equest is successfully assigned to computing/data esouces; on the othe hand, the failues in Goup 2 may occu afte the job equest has been successfully assigned and duing the execution of subtasks. Theefoe, the two goups of failues could be deemed as independent. Nevetheless, failues within each goup ae stongly coelated. In summay, the modeling of cloud sevice eliability can be sepaated in two pats: modeling of equest Stage eliability and modeling of Execution Stage eliability. 3.. equest Stage eliabiliy This equest stage contains two types of failues: oveflow and timeout. The due time fo a specific sevice is the allowed time spent fom the submission of the job equest to the completion of the job. The due time can be set by the use o by the sevice monito. If a job equest is not seved by a schedule befoe the due time, it will be dopped. The dopping ate is denoted by µ d. Suppose the capacity of the equest queue is N (the maximal numbe of equests in the queue). We assume that the aival of submissions of job equests follow a Poisson pocess with the aival ate of λ a. Usually, thee ae multiple schedule seves to seve the equests. These schedule seves ae usually homogeneous with simila stuctues, schemes and equipments. Hee, we assume a total of S homogenous schedule seves ae unning simultaneously to seve the equests. The sevice time to complete one equest by each schedule seve is assumed to be an exponentially distibuted quantity with paamete µ. Thus, such pocess can be modeled by a Makov pocess 7

8 as depicted by Fig. 3, in which state n (n=0,,,n) epesents the numbe of equests in the queue. λ a λ a λ a 0 2 S- S S+ N- N µ + µ d 2 µ + 2µ d S µ + Sµ S µ d + ( S +) µ d S µ + Nµ d Fig. 3. Makov model fo the equest queue. In Fig. 3, the tansition ate fom state n to state n+ is λ a. At state N, the aival of a new equest will make the equest queue oveflow, so the equest is dopped and the queue still stays at state N. The sevice ate of a equest by a schedule seve is µ. If n S, then n equests can be immediately seved by the S schedule seves, so the depatue ate of any one equest is equal to nµ. If n > S, only S equests ae being simultaneously seved by schedule seves, so the depatue ate is Sµ. The dopping ate fo any one equest in the queue to each its due time is nµ d (n=,2,,n). Denote by q n the steady pobability fo the system to stay at state n (n=0,,,n). It is easy to deive q n by solving the following Chapman-Kolmogoov equations: And S n λ a N n n µ + p x) λa qn = ( n + ) µ qn+ + x= y= 0 a q0 µ q λ a λ = (2) ( p( n y) λaq y (n=,,s-) (3) ( p( n y) λaq y (n=s,,n-) (4) N n n µ + p x) λa qn = Sµ qn+ + x= y= 0 S q = N µ N y= 0 N n= 0 The pobability fo the oveflow failue NOT to occu is thus p( N y) λ q (5) a y q = (6) n N = oveflow q n n= 0 whee q n (n=0,,,n) can be obtained by solving equations (2)-(6)., (7) 8

9 To study the timeout failue, suppose the cuent length of the equest queue is n (n=0,,,n-) when the new sevice equest unde consideation aives. The pobability density function (p.d.f.) of waiting time to complete the n equests by S schedule seves is f ( t) = Sµ e n n S ( S t) ( n S)! Sµ t µ, t 0 and n S. (8) If the waiting time is longe than the due time T d, the timeout failue occus. Theefoe, the pobability fo the waiting time in completing the n+ equests to be less than T d is If T d P{ t < Td } = f n( t) dt n S (9) 0 n < S, then the new equest that has aived can be immediately seved without any waiting time. Theefoe, the pobability fo the timeout and oveflow failues NOT to occu (i.e. the equest Stage is eliable) is S N Td equest = n + qn 0 n= 0 n= S q f ( t) dt (0) whee f n (t) can be obtained by (8). The summation in (0) between [ 0, N ] contains a condition that the oveflow failue not to occu as analyzed by the (7). Thus, in (0) epesents the pobability without timeout o oveflow failues. n equest 3.2. Execution Stage A New Model To addess vaious types of failues duing the execution of a cloud sevice, we popose a new model hee. All types of execution stage failues ae integated in this new model, as illustated by a gaph model in Fig. 4. 9

10 Hadwae Failues Netwok Failues Netwok Failues D,D2 D2 D Database Failues Data/Comp es. Miss (a special HW failue) S D Hadwae Failues S2,S3 S2 Softwae Failues S3 Fig. 4. A gaph model integating diffeent types of failues at the execution stage. In this model, hadwae (such as a compute) is epesented by a solid-line node, so the chaacteistics egading the hadwae (such as hadwae failues, pocessing speed, etc.) can be associated with the node. The link of the netwok is epesented by a solid line which epesents a communication channel between two nodes, so the chaactes of the channel (such as link failue, bandwidths, etc.) can be associated with the link. Hadwae may contain database o softwae equied by the cloud sevice, so we suggest using vitual nodes to epesent database o softwae pogams, which ae dawn as dashed-line cicles. The idea of vitual nodes is diffeent fom pevious gaph models fo distibuted computing systems [7]. Those models only exhibit the softwae/database inside the hadwae node, which actually fits the physical stuctue (e.g. softwae does un inside the compute hadwae), but such physical epesentations could not epesent the heteogeneity of hadwae/softwae/databases so these models only used the node popety to incopoate all diffeent chaacteistics. Howeve, in cloud computing the heteogeneity is significant including vaious kinds of esouces, so these esouces should be teated espectively. The vitual nodes making physical stuctue inside-out can fulfill this equiement. As a esult, the chaacteistics with espect to the database (such as size of data uploaded/downloaded, database failues, etc.) and to the softwae (such as softwae failues, and the unning time of the softwae) can be associated with diffeent vitual nodes without intefeing the chaacteistics of hadwae (the solid-line node). This vitual link (dashed line) connects diffeent vitual nodes to thei hosted hadwae node. The vitual stuctue in Fig. 4, when exhibiting the heteogeneity, can also show 0

11 the failue coelation to accommodate to the pactice bette, e.g. if the hadwae fails, then all those vitual nodes (components inside this hadwae) ae isolated fom outside, which means unavailable at the same time to othe extenal components. Finally, this gaph model can also addess the data/computing esouces missing. Once the missing esouces ae included by the cloud schedule by mistakes, we can addess the missing in anothe way, i.e., the esouce fails at the beginning of the execution of the cloud sevice. Theeby, the missing of esouces can be incopoated in the hadwae popety, as a special type of hadwae failue. In summay, the new gaph model to be built as pe the above methodology can well addess those diffeent failues in a holistic manne fo a given cloud sevice duing the execution stage Paametes In accodance with the new model as depicted by Fig. 4, the paametes with espect to diffeent components ae discussed hee, which will be used in the poposed evaluation algoithm. Fo the i:th hadwae node ( i =,2,..., H ), denote by ps i its Pocessing Speed, e.g. in MIPS (Million Instuctions pe Second). Fo the j:th data esouce ( j =,2,..., J ), denote by sd j the Amount of Data downloaded/uploaded by emote softwae pogams, e.g., in MB (Mega Bytes). Fo softwae (such as a softwae pogam to complete a subtask), denote by wp ( k =,2,..., K ) the Wokload of the k:th softwae pogam, e.g. in NoI (Numbe of Instuctions) to be executed. Denote by sd ( i =,2,..., J, j =,2,..., J, i j ) the Amount of Data exchanged between the i:th ij subtask and the j:th subtask. Denote by communication link, e.g. in bps (bit pe second). bw ( m =,2,..., M ) the Bandwidth of the m:th m Any of the elements of hadwae/database/softwae/links may encounte failues. The failue ate [] is anothe paamete of inteest. As explained by [8], in the opeational phase of softwae, thee will be no modifications made on the softwae souce code, thus the softwae failue ate is a constant. Fo electonic hadwae, a constant failue ate is nomally obseved in the opeational phase as well. We thus denote by λ element ) the failue ate of the n:th element. ( n Theefoe, the eliability of each individual element can be deived as ) = exp{ λ ( element ) T ( element )}, () ( elementn n w n k

12 whee T element ) denotes the length of woking time of the n:th element in a cloud sevice, w( n which can be deived, espectively, as follows. The time that the k:th softwae pogam is unning on the i:th machine is Softwae Wokload wp T = The time that the m:th communication link is tansmitting data is k w( Softwae) = (2) Pocessing Speed psi Amount of Data sdij T w ( Communication) = = (3) Bandwidth bw The total woking time fo a hadwae element has two pats: unning softwae and tansmitting data, thus T w( Hadwae) = Tw( Softwae) + Tw( Communication) (4) Hadwae Hadwae which means the summation of the execution time of all softwae pogams unning on this hadwae and the communication time of all channels going though this hadwae. The woking time fo a data souce can be calculated as the summation of all communication times that access the data on the data souce. T ( DataSouce) = T ( Communication) (5) w Data With the woking time deived by equations (2)-(5), the eliability of individual element can be obtained fom (), which is moe ealistic and pactical than othe conventional methods [7] assuming the eliabilities of elements (nodes and links) ae constant, (e.g. a node is always 90% eliable, egadless of how long it woks). In fact, the eliability of individual element is affected by vaious conditions such as failue ate, amount of data, bandwidth, opeation time, etc. w m New Evaluation Algoithm Though the new gaph model and the paametes of elements ae moe ealistic and pactical, they also make the evaluation of oveall eliability much moe complicated so that the existing algoithms [7] could not be diectly applied hee. Fo instance, those conventional algoithms have one o some of the following assumptions that ae not applicable to evaluate the eliability given the above new model: ) the netwok topology is made up of physical nodes/links without consideing the vitual nodes/links; 2) the opeational pobabilities (eliabilities) of nodes o links 2

13 ae constant; 3) only hadwae failues of links and pocessos ae consideed without taking into account the softwae, data and esouce failues. Theefoe, we futhe pesent a new algoithm fo evaluating the oveall cloud sevice eliability consideing all diffeent factos duing the execution stage given the new gaph model and the above paametes. The new evaluation algoithm based on Gaph theoy and Bayesian theoem is pesented to deive the eliability, as follows. A. Minimal Subtask Spanning Tee (MSST) The set of all nodes and links involved in completing a specific subtask fom a Subtask Spanning Tee (SST). This SST can be consideed to be a combination of seveal minimal subtask spanning tees (MSSTs), whee each MSST epesents a minimal possible combination of available elements (nodes and links) that guaantees the success to execute this specific subtask (i.e., failue of any element in MSST leads to the subtask failue). By this definition of MSST, we can see that each MSST contains exactly one set of data esouces without any duplications, because any duplication could be educed to anothe smalle SST. Theefoe, fo any MSST, the data esouces and pecedent subtasks that povide cetain input fo the subtask ae also detemined. One can also obtain the woking times of diffeent elements by (2)-(5). Some elements inside one MSST can still belong to seveal paths if they ae involved in diffeent communications tasks, such as data tansmission o data esouce access. Note that all elements in the execution stage ae hot-standby although some elements/subtasks may be waiting fo the output of some othe subtasks. So duing the waiting peiod, those elements ae also possible to fail. Thus, we suppose that an MSST completes the entie sevice if all of its elements do not fail duing the maximal time allowed to complete all subtasks in executing which they ae involved. Theefoe, when calculating the element eliability in a given MSST, one has to use the coesponding ecod with maximal time. Assume thee ae a total of K elements in an MSST, and element i (i=,2,,k) denotes the i:th element in the MSST. Accodingly, the communication time of the i:th element is denoted by T w( element i) and λ ( elementi ) epesents its failue ate. The eliability of this single MSST can be simply expessed as K MSST = i= exp{ λ ( element ) T ( element )} (6) i w i 3

14 With this equation, the eliability of an MSST can be computed if the woking times of all the elements ae obtained. Hence, finding all the MSSTs and detemining the woking time of thei elements ae the fist step in deiving the execution eliability of a cloud sevice. To solve the gaph tavesal poblem, seveal classical algoithms have been suggested, such as depth-fist seach, beadth-fist seach, etc. These algoithms can find all MSSTs in an abitay gaph. Hee, we popose a depth-fist seach algoithm hee, which is biefly descibed as follows: Step. Given a pogam/subtask, say S m, stat fom a node that contains this pogam, to seach the equied data esouces and pecedent subtasks/pogams along the possible links, and ecod elements that compose the seaching oute and thei communication times. Step 2. Until all the equied data esouces and pecedent subtasks/pogams ae eached, an MSST is found, and ecod this MSST. Step 3. Then othe outes ae tied to seach othe MSSTs until all the MSSTs ae seached. Step 4. Change to anothe node that also contains the pogams m. epeat the above thee steps until all the nodes that have S m ae evaluated. Save all the MSSTs found associated with S m into the vecto MSST ( S m ). Step 5. Change to anothe pogam and epeat the above fou steps until all the pogams ae exploed. Then all the vectos of MSST S ) (m=,2, M) ae geneated. ( m B. Minimal Execution Spanning Tee (MEST) Simila to the MSST, a Minimal Execution Spanning Tee (MEST) epesents a minimal possible combination of available elements (nodes and links) that guaantees the success to execute the entie sevice. Thus, at least one MSST of each MEST S ) (m=,2, M) must be eliable, and then the subtask S m (m=,2, M) can be connected to those emote esouces and exchange data with them successfully though the netwok. If any set of the M subtasks ae successful, then the execution is eliable fo the cloud sevice to execute the equied set of subtasks, so the MEST ( m could be deived as the intesection of the above sets of MSSTs as I M m= In pactice, all MESTs could be geneated in the following steps: MEST = MSST( ) (7) Step : Select an MSST fom each set of MSST S ) whee (m=,2, M). S m ( m 4

15 Step 2: M MSSTs ae obtained and put them togethe to geneate the MEST. Fo each common element when intesecting tees togethe, ecod the geate woking time as the final woking time of this element in the MEST. Step 3: epeat Step -2 until all combinations ae tied to geneate all N MSSTs. Simila to (6), the eliability of a single MEST can be calculated by MEST = i MEST exp{ λ ( element ) T ( element )} (8) i w i C. Execution eliability Having the list of N MESTs and the coesponding task completion time, one can detemine the eliability of cloud sevice at the execution stage, as follows. = U N execute P MEST i (9) i= which means any one MEST out of the total N MESTs being succeeded will make the cloud sevice successfully executed in the execution stage. Denote event of the MEST j while E j the failue of the E j the successful opeation MEST j. Using the Bayesian theoem on conditional pobability, we can deive (9) to a summation of conditional pobabilities P = U N execute MEST i i= N i P = ( E ) P( E, E, E E ) j= P L (20) j 2, The pobability P ( E j ) can be diectly obtained fom (8) as (, E, ) E 2, L E j E j can be computed by the following two-step algoithm. j j MEST j and the pobability Step identifies the failues of all of the citical elements in a peiod of time duing which they lead to the failues of any one MEST fom pevious j- MESTs, but do not affect MEST j. Step 2 geneates all the possible combinations of the identified citical elements that lead to the event E, 2, E, L E j E by a binay seach, and computes the pobabilities of those j combinations. Thei summation is P{ E, E2, L E j Ej}. 5

16 When calculating the failue pobabilities of MESTs elements the maximal time fom the coesponding ecods in a list fo the given MEST should be used. Finally, if a cloud sevice needs to be successfully completed, both equest stage and execution stage should be eliable. Afte we deive the eliability fo both stages, we can heeby get the cloud sevice eliability whee Sevice as = Sevice equest execute (2) equest can be deived fom the eliability of equest stage by (0), and deived fom the eliability of execute stage by (20). execute can be 4. Conclusion and Discussion In this pape, eliability modeling and analysis of cloud sevice is conducted. We fist elaboate vaious types of possible failues in a cloud sevice, based on which a holistic eliability model is developed. A new algoithm is poposed to evaluate cloud sevice eliability based on the developed model. The developed cloud sevice eliability model and evaluation algoithm, howeve, is yet to be validated by simulation and eal-life data. This issue shall be addessed in ou futue eseach. Acknowledgement: This wok is suppoted by National Science Foundation (No ) of USA. This wok is suppoted by National Natual Science Foundation of China (No ) and Key Poject of Chinese Ministy of Education (No. 0938). efeences: [] I. Foste, C. Kesselman. The Gid 2: Bluepint fo a New Computing Infastuctue. Los Alios, Mogan-Kaufmann, [2] C.S. Yeo,. Buyya, M.D. de Assunção, et al. Utility Computing on Global Gids. Technical epot, GIDS-T , Gid Computing and Distibuted Systems Laboatoy, The Univesity of Melboune, Austalia, [3] Y. Zhang, Y. Zhou. Tanspaent computing: A new paadigm fo pevasive computing. Poceedings of the 3d Intenational Confeence on Ubiquitous Intelligence and Computing (UIC-06), LNCS 445,,

17 [4] Y.S. Dai, Y. Pan, X.K. Zou. A hieachical modeling and analysis fo gid sevice eliability. IEEE Tansactions on Computes, 56(5), 68-69, [5] [6] [7] [8] [9] [0] M.L. Shooman. eliability of Compute Systems and Netwoks: Fault Toleance, Analysis and Design. New Yok: John Wiley & Sons, Inc., [] M. Xie, Y.S. Dai, K.L. Poh. Computing System eliability: Models and Analysis. New Yok: Kluwe Academic Publishes, [2] L. Xing, Y.S. Dai, A new decision diagam model fo efficient analysis on multi-state systems, IEEE Tansactions on Dependable and Secue Computing, Accepted fo Publication, 2008, Publishes: IEEE Pess. [3] X. Zou, Y.S. Dai, Y. Pan, Tust and Secuity in Collaboative Computing, Wold Scientific, Hackensack, NJ, U.S.A., 2008, ISBN: [4] D. Abamson,. Buyya, J. Giddy. A computational economy fo gid computing and its implementation in the Nimod-G esouce boke. Futue Geneation Compute Systems, 8(8), , [5] Y.S. Dai, M. Xie, K.L. Poh. eliability of gid sevice systems, Computes & Industial Engineeing, 50(-2), 30-47, [6] Y.S. Dai, M. Xie, K.L. Poh, eliability Analysis of Gid Computing Systems, The 9th IEEE Pacific im Symposium on Dependable Computing (PDC2002), IEEE Compute Pess, 2002, pp [7] M. Xie, Y.S. Dai, K.L. Poh, Computing Systems eliability: Models and Analysis, (330 pages), Spinge: New Yok, U.S.A., ISBN: X. [8] B. Yang, M. Xie. A study of opeational and testing eliability in softwae eliability analysis, eliability Engineeing & System Safety, 70(3), ,

HEALTHCARE INTEGRATION BASED ON CLOUD COMPUTING

HEALTHCARE INTEGRATION BASED ON CLOUD COMPUTING U.P.B. Sci. Bull., Seies C, Vol. 77, Iss. 2, 2015 ISSN 2286-3540 HEALTHCARE INTEGRATION BASED ON CLOUD COMPUTING Roxana MARCU 1, Dan POPESCU 2, Iulian DANILĂ 3 A high numbe of infomation systems ae available

More information

Software Engineering and Development

Software Engineering and Development I T H E A 67 Softwae Engineeing and Development SOFTWARE DEVELOPMENT PROCESS DYNAMICS MODELING AS STATE MACHINE Leonid Lyubchyk, Vasyl Soloshchuk Abstact: Softwae development pocess modeling is gaining

More information

An Approach to Optimized Resource Allocation for Cloud Simulation Platform

An Approach to Optimized Resource Allocation for Cloud Simulation Platform An Appoach to Optimized Resouce Allocation fo Cloud Simulation Platfom Haitao Yuan 1, Jing Bi 2, Bo Hu Li 1,3, Xudong Chai 3 1 School of Automation Science and Electical Engineeing, Beihang Univesity,

More information

Concept and Experiences on using a Wiki-based System for Software-related Seminar Papers

Concept and Experiences on using a Wiki-based System for Software-related Seminar Papers Concept and Expeiences on using a Wiki-based System fo Softwae-elated Semina Papes Dominik Fanke and Stefan Kowalewski RWTH Aachen Univesity, 52074 Aachen, Gemany, {fanke, kowalewski}@embedded.wth-aachen.de,

More information

Questions & Answers Chapter 10 Software Reliability Prediction, Allocation and Demonstration Testing

Questions & Answers Chapter 10 Software Reliability Prediction, Allocation and Demonstration Testing M13914 Questions & Answes Chapte 10 Softwae Reliability Pediction, Allocation and Demonstation Testing 1. Homewok: How to deive the fomula of failue ate estimate. λ = χ α,+ t When the failue times follow

More information

The transport performance evaluation system building of logistics enterprises

The transport performance evaluation system building of logistics enterprises Jounal of Industial Engineeing and Management JIEM, 213 6(4): 194-114 Online ISSN: 213-953 Pint ISSN: 213-8423 http://dx.doi.og/1.3926/jiem.784 The tanspot pefomance evaluation system building of logistics

More information

Reliability of Cloud Computing Services

Reliability of Cloud Computing Services IOSR Journal of Engineering (IOSRJEN) ISSN (e): 2250-3021, ISSN (p): 2278-8719 Vol. 04, Issue 01 (January. 2014), V7 PP 51-60 www.iosrjen.org Reliability of Cloud Computing Services 1 anju Mishra & 2 dr.

More information

Chapter 3 Savings, Present Value and Ricardian Equivalence

Chapter 3 Savings, Present Value and Ricardian Equivalence Chapte 3 Savings, Pesent Value and Ricadian Equivalence Chapte Oveview In the pevious chapte we studied the decision of households to supply hous to the labo maket. This decision was a static decision,

More information

Comparing Availability of Various Rack Power Redundancy Configurations

Comparing Availability of Various Rack Power Redundancy Configurations Compaing Availability of Vaious Rack Powe Redundancy Configuations By Victo Avela White Pape #48 Executive Summay Tansfe switches and dual-path powe distibution to IT equipment ae used to enhance the availability

More information

ON THE (Q, R) POLICY IN PRODUCTION-INVENTORY SYSTEMS

ON THE (Q, R) POLICY IN PRODUCTION-INVENTORY SYSTEMS ON THE R POLICY IN PRODUCTION-INVENTORY SYSTEMS Saifallah Benjaafa and Joon-Seok Kim Depatment of Mechanical Engineeing Univesity of Minnesota Minneapolis MN 55455 Abstact We conside a poduction-inventoy

More information

Comparing Availability of Various Rack Power Redundancy Configurations

Comparing Availability of Various Rack Power Redundancy Configurations Compaing Availability of Vaious Rack Powe Redundancy Configuations White Pape 48 Revision by Victo Avela > Executive summay Tansfe switches and dual-path powe distibution to IT equipment ae used to enhance

More information

INITIAL MARGIN CALCULATION ON DERIVATIVE MARKETS OPTION VALUATION FORMULAS

INITIAL MARGIN CALCULATION ON DERIVATIVE MARKETS OPTION VALUATION FORMULAS INITIAL MARGIN CALCULATION ON DERIVATIVE MARKETS OPTION VALUATION FORMULAS Vesion:.0 Date: June 0 Disclaime This document is solely intended as infomation fo cleaing membes and othes who ae inteested in

More information

Effect of Contention Window on the Performance of IEEE 802.11 WLANs

Effect of Contention Window on the Performance of IEEE 802.11 WLANs Effect of Contention Window on the Pefomance of IEEE 82.11 WLANs Yunli Chen and Dhama P. Agawal Cente fo Distibuted and Mobile Computing, Depatment of ECECS Univesity of Cincinnati, OH 45221-3 {ychen,

More information

Database Management Systems

Database Management Systems Contents Database Management Systems (COP 5725) D. Makus Schneide Depatment of Compute & Infomation Science & Engineeing (CISE) Database Systems Reseach & Development Cente Couse Syllabus 1 Sping 2012

More information

Financial Derivatives for Computer Network Capacity Markets with Quality-of-Service Guarantees

Financial Derivatives for Computer Network Capacity Markets with Quality-of-Service Guarantees Financial Deivatives fo Compute Netwok Capacity Makets with Quality-of-Sevice Guaantees Pette Pettesson pp@kth.se Febuay 2003 SICS Technical Repot T2003:03 Keywods Netwoking and Intenet Achitectue. Abstact

More information

Tracking/Fusion and Deghosting with Doppler Frequency from Two Passive Acoustic Sensors

Tracking/Fusion and Deghosting with Doppler Frequency from Two Passive Acoustic Sensors Tacking/Fusion and Deghosting with Dopple Fequency fom Two Passive Acoustic Sensos Rong Yang, Gee Wah Ng DSO National Laboatoies 2 Science Pak Dive Singapoe 11823 Emails: yong@dso.og.sg, ngeewah@dso.og.sg

More information

Automatic Testing of Neighbor Discovery Protocol Based on FSM and TTCN*

Automatic Testing of Neighbor Discovery Protocol Based on FSM and TTCN* Automatic Testing of Neighbo Discovey Potocol Based on FSM and TTCN* Zhiliang Wang, Xia Yin, Haibin Wang, and Jianping Wu Depatment of Compute Science, Tsinghua Univesity Beijing, P. R. China, 100084 Email:

More information

Hubs, Bridges, and Switches

Hubs, Bridges, and Switches Hubs, Bidges, and Switches Used fo extending LANs in tems of geogaphical coveage, numbe of nodes, administation capabilities, etc. Diffe in egads to: m collision domain isolation m laye at which they opeate

More information

Power Monitoring and Control for Electric Home Appliances Based on Power Line Communication

Power Monitoring and Control for Electric Home Appliances Based on Power Line Communication I²MTC 2008 IEEE Intenational Instumentation and Measuement Technology Confeence Victoia, Vancouve Island, Canada, May 12 15, 2008 Powe Monitoing and Contol fo Electic Home Appliances Based on Powe Line

More information

Over-encryption: Management of Access Control Evolution on Outsourced Data

Over-encryption: Management of Access Control Evolution on Outsourced Data Ove-encyption: Management of Access Contol Evolution on Outsouced Data Sabina De Capitani di Vimecati DTI - Univesità di Milano 26013 Cema - Italy decapita@dti.unimi.it Stefano Paaboschi DIIMM - Univesità

More information

Give me all I pay for Execution Guarantees in Electronic Commerce Payment Processes

Give me all I pay for Execution Guarantees in Electronic Commerce Payment Processes Give me all I pay fo Execution Guaantees in Electonic Commece Payment Pocesses Heiko Schuldt Andei Popovici Hans-Jög Schek Email: Database Reseach Goup Institute of Infomation Systems ETH Zentum, 8092

More information

Research on Risk Assessment of the Transformer Based on Life Cycle Cost

Research on Risk Assessment of the Transformer Based on Life Cycle Cost ntenational Jounal of Smat Gid and lean Enegy eseach on isk Assessment of the Tansfome Based on Life ycle ost Hui Zhou a, Guowei Wu a, Weiwei Pan a, Yunhe Hou b, hong Wang b * a Zhejiang Electic Powe opoation,

More information

9:6.4 Sample Questions/Requests for Managing Underwriter Candidates

9:6.4 Sample Questions/Requests for Managing Underwriter Candidates 9:6.4 INITIAL PUBLIC OFFERINGS 9:6.4 Sample Questions/Requests fo Managing Undewite Candidates Recent IPO Expeience Please povide a list of all completed o withdawn IPOs in which you fim has paticipated

More information

Uncertain Version Control in Open Collaborative Editing of Tree-Structured Documents

Uncertain Version Control in Open Collaborative Editing of Tree-Structured Documents Uncetain Vesion Contol in Open Collaboative Editing of Tee-Stuctued Documents M. Lamine Ba Institut Mines Télécom; Télécom PaisTech; LTCI Pais, Fance mouhamadou.ba@ telecom-paistech.f Talel Abdessalem

More information

An Epidemic Model of Mobile Phone Virus

An Epidemic Model of Mobile Phone Virus An Epidemic Model of Mobile Phone Vius Hui Zheng, Dong Li, Zhuo Gao 3 Netwok Reseach Cente, Tsinghua Univesity, P. R. China zh@tsinghua.edu.cn School of Compute Science and Technology, Huazhong Univesity

More information

Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local Generation

Data Center Demand Response: Avoiding the Coincident Peak via Workload Shifting and Local Generation (213) 1 28 Data Cente Demand Response: Avoiding the Coincident Peak via Wokload Shifting and Local Geneation Zhenhua Liu 1, Adam Wieman 1, Yuan Chen 2, Benjamin Razon 1, Niangjun Chen 1 1 Califonia Institute

More information

Distributed Computing and Big Data: Hadoop and MapReduce

Distributed Computing and Big Data: Hadoop and MapReduce Distibuted Computing and Big Data: Hadoop and Map Bill Keenan, Diecto Tey Heinze, Achitect Thomson Reutes Reseach & Development Agenda R&D Oveview Hadoop and Map Oveview Use Case: Clusteing Legal Documents

More information

Optimizing Content Retrieval Delay for LT-based Distributed Cloud Storage Systems

Optimizing Content Retrieval Delay for LT-based Distributed Cloud Storage Systems Optimizing Content Retieval Delay fo LT-based Distibuted Cloud Stoage Systems Haifeng Lu, Chuan Heng Foh, Yonggang Wen, and Jianfei Cai School of Compute Engineeing, Nanyang Technological Univesity, Singapoe

More information

Ilona V. Tregub, ScD., Professor

Ilona V. Tregub, ScD., Professor Investment Potfolio Fomation fo the Pension Fund of Russia Ilona V. egub, ScD., Pofesso Mathematical Modeling of Economic Pocesses Depatment he Financial Univesity unde the Govenment of the Russian Fedeation

More information

PAN STABILITY TESTING OF DC CIRCUITS USING VARIATIONAL METHODS XVIII - SPETO - 1995. pod patronatem. Summary

PAN STABILITY TESTING OF DC CIRCUITS USING VARIATIONAL METHODS XVIII - SPETO - 1995. pod patronatem. Summary PCE SEMINIUM Z PODSTW ELEKTOTECHNIKI I TEOII OBWODÓW 8 - TH SEMIN ON FUNDMENTLS OF ELECTOTECHNICS ND CICUIT THEOY ZDENĚK BIOLEK SPŠE OŽNO P.., CZECH EPUBLIC DLIBO BIOLEK MILITY CDEMY, BNO, CZECH EPUBLIC

More information

Scheduling Hadoop Jobs to Meet Deadlines

Scheduling Hadoop Jobs to Meet Deadlines Scheduling Hadoop Jobs to Meet Deadlines Kamal Kc, Kemafo Anyanwu Depatment of Compute Science Noth Caolina State Univesity {kkc,kogan}@ncsu.edu Abstact Use constaints such as deadlines ae impotant equiements

More information

Things to Remember. r Complete all of the sections on the Retirement Benefit Options form that apply to your request.

Things to Remember. r Complete all of the sections on the Retirement Benefit Options form that apply to your request. Retiement Benefit 1 Things to Remembe Complete all of the sections on the Retiement Benefit fom that apply to you equest. If this is an initial equest, and not a change in a cuent distibution, emembe to

More information

STUDENT RESPONSE TO ANNUITY FORMULA DERIVATION

STUDENT RESPONSE TO ANNUITY FORMULA DERIVATION Page 1 STUDENT RESPONSE TO ANNUITY FORMULA DERIVATION C. Alan Blaylock, Hendeson State Univesity ABSTRACT This pape pesents an intuitive appoach to deiving annuity fomulas fo classoom use and attempts

More information

Towards Realizing a Low Cost and Highly Available Datacenter Power Infrastructure

Towards Realizing a Low Cost and Highly Available Datacenter Power Infrastructure Towads Realizing a Low Cost and Highly Available Datacente Powe Infastuctue Siam Govindan, Di Wang, Lydia Chen, Anand Sivasubamaniam, and Bhuvan Ugaonka The Pennsylvania State Univesity. IBM Reseach Zuich

More information

A framework for the selection of enterprise resource planning (ERP) system based on fuzzy decision making methods

A framework for the selection of enterprise resource planning (ERP) system based on fuzzy decision making methods A famewok fo the selection of entepise esouce planning (ERP) system based on fuzzy decision making methods Omid Golshan Tafti M.s student in Industial Management, Univesity of Yazd Omidgolshan87@yahoo.com

More information

Efficient Redundancy Techniques for Latency Reduction in Cloud Systems

Efficient Redundancy Techniques for Latency Reduction in Cloud Systems Efficient Redundancy Techniques fo Latency Reduction in Cloud Systems 1 Gaui Joshi, Emina Soljanin, and Gegoy Wonell Abstact In cloud computing systems, assigning a task to multiple seves and waiting fo

More information

High Availability Replication Strategy for Deduplication Storage System

High Availability Replication Strategy for Deduplication Storage System Zhengda Zhou, Jingli Zhou College of Compute Science and Technology, Huazhong Univesity of Science and Technology, *, zhouzd@smail.hust.edu.cn jlzhou@mail.hust.edu.cn Abstact As the amount of digital data

More information

An Efficient Group Key Agreement Protocol for Ad hoc Networks

An Efficient Group Key Agreement Protocol for Ad hoc Networks An Efficient Goup Key Ageement Potocol fo Ad hoc Netwoks Daniel Augot, Raghav haska, Valéie Issany and Daniele Sacchetti INRIA Rocquencout 78153 Le Chesnay Fance {Daniel.Augot, Raghav.haska, Valéie.Issany,

More information

Modeling and Verifying a Price Model for Congestion Control in Computer Networks Using PROMELA/SPIN

Modeling and Verifying a Price Model for Congestion Control in Computer Networks Using PROMELA/SPIN Modeling and Veifying a Pice Model fo Congestion Contol in Compute Netwoks Using PROMELA/SPIN Clement Yuen and Wei Tjioe Depatment of Compute Science Univesity of Toonto 1 King s College Road, Toonto,

More information

AN IMPLEMENTATION OF BINARY AND FLOATING POINT CHROMOSOME REPRESENTATION IN GENETIC ALGORITHM

AN IMPLEMENTATION OF BINARY AND FLOATING POINT CHROMOSOME REPRESENTATION IN GENETIC ALGORITHM AN IMPLEMENTATION OF BINARY AND FLOATING POINT CHROMOSOME REPRESENTATION IN GENETIC ALGORITHM Main Golub Faculty of Electical Engineeing and Computing, Univesity of Zageb Depatment of Electonics, Micoelectonics,

More information

Approximation Algorithms for Data Management in Networks

Approximation Algorithms for Data Management in Networks Appoximation Algoithms fo Data Management in Netwoks Chistof Kick Heinz Nixdof Institute and Depatment of Mathematics & Compute Science adebon Univesity Gemany kueke@upb.de Haald Räcke Heinz Nixdof Institute

More information

Evaluating the impact of Blade Server and Virtualization Software Technologies on the RIT Datacenter

Evaluating the impact of Blade Server and Virtualization Software Technologies on the RIT Datacenter Evaluating the impact of and Vitualization Softwae Technologies on the RIT Datacente Chistophe M Butle Vitual Infastuctue Administato Rocheste Institute of Technology s Datacente Contact: chis.butle@it.edu

More information

THE DISTRIBUTED LOCATION RESOLUTION PROBLEM AND ITS EFFICIENT SOLUTION

THE DISTRIBUTED LOCATION RESOLUTION PROBLEM AND ITS EFFICIENT SOLUTION IADIS Intenational Confeence Applied Computing 2006 THE DISTRIBUTED LOCATION RESOLUTION PROBLEM AND ITS EFFICIENT SOLUTION Jög Roth Univesity of Hagen 58084 Hagen, Gemany Joeg.Roth@Fenuni-hagen.de ABSTRACT

More information

Channel selection in e-commerce age: A strategic analysis of co-op advertising models

Channel selection in e-commerce age: A strategic analysis of co-op advertising models Jounal of Industial Engineeing and Management JIEM, 013 6(1):89-103 Online ISSN: 013-0953 Pint ISSN: 013-843 http://dx.doi.og/10.396/jiem.664 Channel selection in e-commece age: A stategic analysis of

More information

est using the formula I = Prt, where I is the interest earned, P is the principal, r is the interest rate, and t is the time in years.

est using the formula I = Prt, where I is the interest earned, P is the principal, r is the interest rate, and t is the time in years. 9.2 Inteest Objectives 1. Undestand the simple inteest fomula. 2. Use the compound inteest fomula to find futue value. 3. Solve the compound inteest fomula fo diffeent unknowns, such as the pesent value,

More information

Firstmark Credit Union Commercial Loan Department

Firstmark Credit Union Commercial Loan Department Fistmak Cedit Union Commecial Loan Depatment Thank you fo consideing Fistmak Cedit Union as a tusted souce to meet the needs of you business. Fistmak Cedit Union offes a wide aay of business loans and

More information

An Analysis of Manufacturer Benefits under Vendor Managed Systems

An Analysis of Manufacturer Benefits under Vendor Managed Systems An Analysis of Manufactue Benefits unde Vendo Managed Systems Seçil Savaşaneil Depatment of Industial Engineeing, Middle East Technical Univesity, 06531, Ankaa, TURKEY secil@ie.metu.edu.t Nesim Ekip 1

More information

How to recover your Exchange 2003/2007 mailboxes and emails if all you have available are your PRIV1.EDB and PRIV1.STM Information Store database

How to recover your Exchange 2003/2007 mailboxes and emails if all you have available are your PRIV1.EDB and PRIV1.STM Information Store database AnswesThatWok TM Recoveing Emails and Mailboxes fom a PRIV1.EDB Exchange 2003 IS database How to ecove you Exchange 2003/2007 mailboxes and emails if all you have available ae you PRIV1.EDB and PRIV1.STM

More information

ENABLING INFORMATION GATHERING PATTERNS FOR EMERGENCY RESPONSE WITH THE OPENKNOWLEDGE SYSTEM

ENABLING INFORMATION GATHERING PATTERNS FOR EMERGENCY RESPONSE WITH THE OPENKNOWLEDGE SYSTEM Computing and Infomatics, Vol. 29, 2010, 537 555 ENABLING INFORMATION GATHERING PATTERNS FOR EMERGENCY RESPONSE WITH THE OPENKNOWLEDGE SYSTEM Gaia Tecaichi, Veonica Rizzi, Mauizio Machese Depatment of

More information

Towards Automatic Update of Access Control Policy

Towards Automatic Update of Access Control Policy Towads Automatic Update of Access Contol Policy Jinwei Hu, Yan Zhang, and Ruixuan Li Intelligent Systems Laboatoy, School of Computing and Mathematics Univesity of Westen Sydney, Sydney 1797, Austalia

More information

College of Engineering Bachelor of Computer Science

College of Engineering Bachelor of Computer Science 2 0 0 7 w w w. c n u a s. e d u College of Engineeing Bachelo of Compute Science This bochue Details the BACHELOR OF COMPUTER SCIENCE PROGRAM available though CNU s College of Engineeing. Fo ou most up-to-date

More information

A formalism of ontology to support a software maintenance knowledge-based system

A formalism of ontology to support a software maintenance knowledge-based system A fomalism of ontology to suppot a softwae maintenance knowledge-based system Alain Apil 1, Jean-Mac Deshanais 1, and Reine Dumke 2 1 École de Technologie Supéieue, 1100 Note-Dame West, Monteal, Canada

More information

Alarm transmission through Radio and GSM networks

Alarm transmission through Radio and GSM networks Alam tansmission though Radio and GSM netwoks 2015 Alam tansmission though Radio netwok RR-IP12 RL10 E10C E10C LAN RL1 0 R11 T10 (T10U) Windows MONAS MS NETWORK MCI > GNH > GND > +E > DATA POWER DATA BUS

More information

Office of Family Assistance. Evaluation Resource Guide for Responsible Fatherhood Programs

Office of Family Assistance. Evaluation Resource Guide for Responsible Fatherhood Programs Office of Family Assistance Evaluation Resouce Guide fo Responsible Fathehood Pogams Contents Intoduction........................................................ 4 Backgound..........................................................

More information

Research Article A Reputation-Based Identity Management Model for Cloud Computing

Research Article A Reputation-Based Identity Management Model for Cloud Computing Mathematical Poblems in Engineeing Volume 2015, Aticle ID 238245, 15 pages http://dx.doi.og/10.1155/2015/238245 Reseach Aticle A Reputation-Based Identity Management Model fo Cloud Computing Lifa Wu, 1

More information

Optimal Peer Selection in a Free-Market Peer-Resource Economy

Optimal Peer Selection in a Free-Market Peer-Resource Economy Optimal Pee Selection in a Fee-Maket Pee-Resouce Economy Micah Adle, Rakesh Kuma, Keith Ross, Dan Rubenstein, David Tune and David D Yao Dept of Compute Science Univesity of Massachusetts Amhest, MA; Email:

More information

Converting knowledge Into Practice

Converting knowledge Into Practice Conveting knowledge Into Pactice Boke Nightmae srs Tend Ride By Vladimi Ribakov Ceato of Pips Caie 20 of June 2010 2 0 1 0 C o p y i g h t s V l a d i m i R i b a k o v 1 Disclaime and Risk Wanings Tading

More information

Energy Efficient Cache Invalidation in a Mobile Environment

Energy Efficient Cache Invalidation in a Mobile Environment Enegy Efficient Cache Invalidation in a Mobile Envionment Naottam Chand, Ramesh Chanda Joshi, Manoj Misa Electonics & Compute Engineeing Depatment Indian Institute of Technology, Rookee - 247 667. INDIA

More information

Model-Driven Engineering of Adaptation Engines for Self-Adaptive Software: Executable Runtime Megamodels

Model-Driven Engineering of Adaptation Engines for Self-Adaptive Software: Executable Runtime Megamodels Model-Diven Engineeing of Adaptation Engines fo Self-Adaptive Softwae: Executable Runtime Megamodels Thomas Vogel, Holge Giese Technische Beichte N. 66 des Hasso-Plattne-Instituts fü Softwaesystemtechnik

More information

How to create RAID 1 mirroring with a hard disk that already has data or an operating system on it

How to create RAID 1 mirroring with a hard disk that already has data or an operating system on it AnswesThatWok TM How to set up a RAID1 mio with a dive which aleady has Windows installed How to ceate RAID 1 mioing with a had disk that aleady has data o an opeating system on it Date Company PC / Seve

More information

Self-Adaptive and Resource-Efficient SLA Enactment for Cloud Computing Infrastructures

Self-Adaptive and Resource-Efficient SLA Enactment for Cloud Computing Infrastructures 2012 IEEE Fifth Intenational Confeence on Cloud Computing Self-Adaptive and Resouce-Efficient SLA Enactment fo Cloud Computing Infastuctues Michael Maue, Ivona Bandic Distibuted Systems Goup Vienna Univesity

More information

Define What Type of Trader Are you?

Define What Type of Trader Are you? Define What Type of Tade Ae you? Boke Nightmae srs Tend Ride By Vladimi Ribakov Ceato of Pips Caie 20 of June 2010 1 Disclaime and Risk Wanings Tading any financial maket involves isk. The content of this

More information

Strength Analysis and Optimization Design about the key parts of the Robot

Strength Analysis and Optimization Design about the key parts of the Robot Intenational Jounal of Reseach in Engineeing and Science (IJRES) ISSN (Online): 2320-9364, ISSN (Pint): 2320-9356 www.ijes.og Volume 3 Issue 3 ǁ Mach 2015 ǁ PP.25-29 Stength Analysis and Optimization Design

More information

Referral service and customer incentive in online retail supply Chain

Referral service and customer incentive in online retail supply Chain Refeal sevice and custome incentive in online etail supply Chain Y. G. Chen 1, W. Y. Zhang, S. Q. Yang 3, Z. J. Wang 4 and S. F. Chen 5 1,,3,4 School of Infomation Zhejiang Univesity of Finance and Economics

More information

METHODOLOGICAL APPROACH TO STRATEGIC PERFORMANCE OPTIMIZATION

METHODOLOGICAL APPROACH TO STRATEGIC PERFORMANCE OPTIMIZATION ETHODOOGICA APPOACH TO STATEGIC PEFOANCE OPTIIZATION ao Hell * Stjepan Vidačić ** Željo Gaača *** eceived: 4. 07. 2009 Peliminay communication Accepted: 5. 0. 2009 UDC 65.02.4 This pape pesents a matix

More information

867 Product Transfer and Resale Report

867 Product Transfer and Resale Report 867 Poduct Tansfe and Resale Repot Functional Goup ID=PT Intoduction: This X12 Tansaction Set contains the fomat and establishes the data contents of the Poduct Tansfe and Resale Repot Tansaction Set (867)

More information

Reduced Pattern Training Based on Task Decomposition Using Pattern Distributor

Reduced Pattern Training Based on Task Decomposition Using Pattern Distributor > PNN05-P762 < Reduced Patten Taining Based on Task Decomposition Using Patten Distibuto Sheng-Uei Guan, Chunyu Bao, and TseNgee Neo Abstact Task Decomposition with Patten Distibuto (PD) is a new task

More information

Continuous Compounding and Annualization

Continuous Compounding and Annualization Continuous Compounding and Annualization Philip A. Viton Januay 11, 2006 Contents 1 Intoduction 1 2 Continuous Compounding 2 3 Pesent Value with Continuous Compounding 4 4 Annualization 5 5 A Special Poblem

More information

Spirotechnics! September 7, 2011. Amanda Zeringue, Michael Spannuth and Amanda Zeringue Dierential Geometry Project

Spirotechnics! September 7, 2011. Amanda Zeringue, Michael Spannuth and Amanda Zeringue Dierential Geometry Project Spiotechnics! Septembe 7, 2011 Amanda Zeingue, Michael Spannuth and Amanda Zeingue Dieential Geomety Poject 1 The Beginning The geneal consensus of ou goup began with one thought: Spiogaphs ae awesome.

More information

An application of stochastic programming in solving capacity allocation and migration planning problem under uncertainty

An application of stochastic programming in solving capacity allocation and migration planning problem under uncertainty An application of stochastic pogamming in solving capacity allocation and migation planning poblem unde uncetainty Yin-Yann Chen * and Hsiao-Yao Fan Depatment of Industial Management, National Fomosa Univesity,

More information

Chris J. Skinner The probability of identification: applying ideas from forensic statistics to disclosure risk assessment

Chris J. Skinner The probability of identification: applying ideas from forensic statistics to disclosure risk assessment Chis J. Skinne The pobability of identification: applying ideas fom foensic statistics to disclosue isk assessment Aticle (Accepted vesion) (Refeeed) Oiginal citation: Skinne, Chis J. (2007) The pobability

More information

883 Brochure A5 GENE ss vernis.indd 1-2

883 Brochure A5 GENE ss vernis.indd 1-2 ess x a eu / u e a. p o.eu c e / :/ http EURAXESS Reseaches in Motion is the gateway to attactive eseach caees in Euope and to a pool of wold-class eseach talent. By suppoting the mobility of eseaches,

More information

Multiband Microstrip Patch Antenna for Microwave Applications

Multiband Microstrip Patch Antenna for Microwave Applications IOSR Jounal of Electonics and Communication Engineeing (IOSR-JECE) ISSN: 2278-2834, ISBN: 2278-8735. Volume 3, Issue 5 (Sep. - Oct. 2012), PP 43-48 Multiband Micostip Patch Antenna fo Micowave Applications

More information

The Role of Gravity in Orbital Motion

The Role of Gravity in Orbital Motion ! The Role of Gavity in Obital Motion Pat of: Inquiy Science with Datmouth Developed by: Chistophe Caoll, Depatment of Physics & Astonomy, Datmouth College Adapted fom: How Gavity Affects Obits (Ohio State

More information

Adaptive Queue Management with Restraint on Non-Responsive Flows

Adaptive Queue Management with Restraint on Non-Responsive Flows Adaptive Queue Management wi Restaint on Non-Responsive Flows Lan Li and Gyungho Lee Depatment of Electical and Compute Engineeing Univesity of Illinois at Chicago 85 S. Mogan Steet Chicago, IL 667 {lli,

More information

Load Balancing in Processor Sharing Systems

Load Balancing in Processor Sharing Systems Load Balancing in ocesso Shaing Systems Eitan Altman INRIA Sophia Antipolis 2004, oute des Lucioles 06902 Sophia Antipolis, Fance altman@sophia.inia.f Utzi Ayesta LAAS-CNRS Univesité de Toulouse 7, Avenue

More information

Load Balancing in Processor Sharing Systems

Load Balancing in Processor Sharing Systems Load Balancing in ocesso Shaing Systems Eitan Altman INRIA Sophia Antipolis 2004, oute des Lucioles 06902 Sophia Antipolis, Fance altman@sophia.inia.f Utzi Ayesta LAAS-CNRS Univesité de Toulouse 7, Avenue

More information

Timing Synchronization in High Mobility OFDM Systems

Timing Synchronization in High Mobility OFDM Systems Timing Synchonization in High Mobility OFDM Systems Yasamin Mostofi Depatment of Electical Engineeing Stanfod Univesity Stanfod, CA 94305, USA Email: yasi@wieless.stanfod.edu Donald C. Cox Depatment of

More information

SUPPORT VECTOR MACHINE FOR BANDWIDTH ANALYSIS OF SLOTTED MICROSTRIP ANTENNA

SUPPORT VECTOR MACHINE FOR BANDWIDTH ANALYSIS OF SLOTTED MICROSTRIP ANTENNA Intenational Jounal of Compute Science, Systems Engineeing and Infomation Technology, 4(), 20, pp. 67-7 SUPPORT VECTOR MACHIE FOR BADWIDTH AALYSIS OF SLOTTED MICROSTRIP ATEA Venmathi A.R. & Vanitha L.

More information

Transmittal 198 Date: DECEMBER 9, 2005. SUBJECT: Termination of the Existing Eligibility-File Based Crossover Process at All Medicare Contractors

Transmittal 198 Date: DECEMBER 9, 2005. SUBJECT: Termination of the Existing Eligibility-File Based Crossover Process at All Medicare Contractors anual ystem Depatment of ealth & uman evices (D) entes fo edicae & Pub 100-20 One-Time Notification edicaid evices () Tansmittal 198 Date: DEEBE 9, 2005 hange equest 4231 UBJET: Temination of the Existing

More information

YARN PROPERTIES MEASUREMENT: AN OPTICAL APPROACH

YARN PROPERTIES MEASUREMENT: AN OPTICAL APPROACH nd INTERNATIONAL TEXTILE, CLOTHING & ESIGN CONFERENCE Magic Wold of Textiles Octobe 03 d to 06 th 004, UBROVNIK, CROATIA YARN PROPERTIES MEASUREMENT: AN OPTICAL APPROACH Jana VOBOROVA; Ashish GARG; Bohuslav

More information

An Introduction to Omega

An Introduction to Omega An Intoduction to Omega Con Keating and William F. Shadwick These distibutions have the same mean and vaiance. Ae you indiffeent to thei isk-ewad chaacteistics? The Finance Development Cente 2002 1 Fom

More information

A Capacitated Commodity Trading Model with Market Power

A Capacitated Commodity Trading Model with Market Power A Capacitated Commodity Tading Model with Maket Powe Victo Matínez-de-Albéniz Josep Maia Vendell Simón IESE Business School, Univesity of Navaa, Av. Peason 1, 08034 Bacelona, Spain VAlbeniz@iese.edu JMVendell@iese.edu

More information

Modal Characteristics study of CEM-1 Single-Layer Printed Circuit Board Using Experimental Modal Analysis

Modal Characteristics study of CEM-1 Single-Layer Printed Circuit Board Using Experimental Modal Analysis Available online at www.sciencediect.com Pocedia Engineeing 41 (2012 ) 1360 1366 Intenational Symposium on Robotics and Intelligent Sensos 2012 (IRIS 2012) Modal Chaacteistics study of CEM-1 Single-Laye

More information

Secure Smartcard-Based Fingerprint Authentication

Secure Smartcard-Based Fingerprint Authentication Secue Smatcad-Based Fingepint Authentication [full vesion] T. Chales Clancy Compute Science Univesity of Mayland, College Pak tcc@umd.edu Nega Kiyavash, Dennis J. Lin Electical and Compute Engineeing Univesity

More information

STOCHASTIC MARKOV MODEL APPROACH FOR EFFICIENT VIRTUAL MACHINES SCHEDULING ON PRIVATE CLOUD

STOCHASTIC MARKOV MODEL APPROACH FOR EFFICIENT VIRTUAL MACHINES SCHEDULING ON PRIVATE CLOUD Intenational Jounal on Cloud Comuting: Sevices and Achitectue(IJCCSA,Vol., No.3,Novembe 20 STOCHASTIC MARKOV MODEL APPROACH FOR EFFICIENT VIRTUAL MACHINES SCHEDULING ON PRIVATE CLOUD Hsu Mon Kyi and Thinn

More information

Unveiling the MPLS Structure on Internet Topology

Unveiling the MPLS Structure on Internet Topology Unveiling the MPLS Stuctue on Intenet Topology Gabiel Davila Revelo, Mauicio Andeson Ricci, Benoit Donnet, José Ignacio Alvaez-Hamelin INTECIN, Facultad de Ingenieía, Univesidad de Buenos Aies Agentina

More information

The impact of migration on the provision. of UK public services (SRG.10.039.4) Final Report. December 2011

The impact of migration on the provision. of UK public services (SRG.10.039.4) Final Report. December 2011 The impact of migation on the povision of UK public sevices (SRG.10.039.4) Final Repot Decembe 2011 The obustness The obustness of the analysis of the is analysis the esponsibility is the esponsibility

More information

Analyzing Ballistic Missile Defense System Effectiveness Based on Functional Dependency Network Analysis

Analyzing Ballistic Missile Defense System Effectiveness Based on Functional Dependency Network Analysis Send Odes fo Repints to epints@benthamscience.ae 678 The Open Cybenetics & Systemics Jounal, 2015, 9, 678-682 Open Access Analyzing Ballistic Missile Defense System Effectiveness Based on Functional Dependency

More information

Top K Nearest Keyword Search on Large Graphs

Top K Nearest Keyword Search on Large Graphs Top K Neaest Keywod Seach on Lage Gaphs Miao Qiao, Lu Qin, Hong Cheng, Jeffey Xu Yu, Wentao Tian The Chinese Univesity of Hong Kong, Hong Kong, China {mqiao,lqin,hcheng,yu,wttian}@se.cuhk.edu.hk ABSTRACT

More information

HIGH AVAILABILITY SOLUTION: RESOURCE USAGE MANAGEMENT IN VIRTUALIZED SOFTWARE AGING

HIGH AVAILABILITY SOLUTION: RESOURCE USAGE MANAGEMENT IN VIRTUALIZED SOFTWARE AGING Intenational Jounal o Compute Science & Inomation Technology (IJCSIT) Vol 4, No, June 0 HIGH AVAILAILITY SOLUTION: ESOUCE USAGE MANAGEMENT IN VITUALIZED SOFTWAE AGING Aye Myat Myat aing and Ni La Thein

More information

arxiv:1110.2612v1 [q-fin.st] 12 Oct 2011

arxiv:1110.2612v1 [q-fin.st] 12 Oct 2011 Maket inefficiency identified by both single and multiple cuency tends T.Toká 1, and D. Hováth 1, 1 Sos Reseach a.s., Stojáenská 3, 040 01 Košice, Slovak Republic Abstact axiv:1110.2612v1 [q-fin.st] 12

More information

Real Time Tracking of High Speed Movements in the Context of a Table Tennis Application

Real Time Tracking of High Speed Movements in the Context of a Table Tennis Application Real Time Tacking of High Speed Movements in the Context of a Table Tennis Application Stephan Rusdof Chemnitz Univesity of Technology D-09107, Chemnitz, Gemany +49 371 531 1533 stephan.usdof@infomatik.tu-chemnitz.de

More information

Questions for Review. By buying bonds This period you save s, next period you get s(1+r)

Questions for Review. By buying bonds This period you save s, next period you get s(1+r) MACROECONOMICS 2006 Week 5 Semina Questions Questions fo Review 1. How do consumes save in the two-peiod model? By buying bonds This peiod you save s, next peiod you get s() 2. What is the slope of a consume

More information

Electricity transmission network optimization model of supply and demand the case in Taiwan electricity transmission system

Electricity transmission network optimization model of supply and demand the case in Taiwan electricity transmission system Electicity tansmission netwok optimization model of supply and demand the case in Taiwan electicity tansmission system Miao-Sheng Chen a Chien-Liang Wang b,c, Sheng-Chuan Wang d,e a Taichung Banch Gaduate

More information

An Immunological Approach to Change Detection: Algorithms, Analysis and Implications

An Immunological Approach to Change Detection: Algorithms, Analysis and Implications An Immunological Appoach to Change Detection: Algoithms, Analysis and Implications Patik D haeselee Dept. of Compute Science Univesity of New Mexico Albuqueque, NM, 87131 patik@cs.unm.edu Stephanie Foest

More information

Chapter 2 Valiant Load-Balancing: Building Networks That Can Support All Traffic Matrices

Chapter 2 Valiant Load-Balancing: Building Networks That Can Support All Traffic Matrices Chapte 2 Valiant Load-Balancing: Building etwoks That Can Suppot All Taffic Matices Rui Zhang-Shen Abstact This pape is a bief suvey on how Valiant load-balancing (VLB) can be used to build netwoks that

More information

The Binomial Distribution

The Binomial Distribution The Binomial Distibution A. It would be vey tedious if, evey time we had a slightly diffeent poblem, we had to detemine the pobability distibutions fom scatch. Luckily, thee ae enough similaities between

More information

Peer-to-Peer File Sharing Game using Correlated Equilibrium

Peer-to-Peer File Sharing Game using Correlated Equilibrium Pee-to-Pee File Shaing Game using Coelated Equilibium Beibei Wang, Zhu Han, and K. J. Ray Liu Depatment of Electical and Compute Engineeing and Institute fo Systems Reseach, Univesity of Mayland, College

More information