Detection and Avoidance Deadlock for Resource Allocation in Heterogeneous Distributed Platforms

Transcription

1 Internatonal Journal of Coputer Scence and Telecouncatons [Volue 6, Issue 2, February 2015] 1 ISSN Detecton and Avodance Deadlock for Resource Allocaton n Heterogeneous Dstrbuted Platfors Ha Huy Cuong Nguyen 1 and Van Son Le 2 1 Departent of Inforaton Technology, QuangNa Unversty, Ta Ky Cty, Vet Na 2 Departent of Inforaton Technology, Da Nang Unversty of Educaton, Da Nang, Vet Na 1 nguyenhahuycuong@gal.co, 2 levansupha2004@yahoo.co Abstract In a heterogeneous dstrbuted platfors large proble s dstrbute aong the processors (such as aong the coputers of dstrbuted coputng syste or aong the coputers of parallel coputng syste etc.) to ake t cost effectve and less te consung nstead of a coputer syste wth sngle processor. There are ore general types of resource allocaton probles than those we consder here. In ths paper, we present an approach for provng detecton and avodance algorth, to schedule the polces of resource supply for resource allocaton on heterogeneous. We propose an algorth for allocatng ultple resources to copetng servces runnng n vrtual achnes platfors. Index Ters Cloud Coputng, Resource Allocaton, Heterogeneous Dstrbuted Platfors, Deadlock Detecton and Avodance Deadlock R I. INTRODUCTION ECENTLY, there has been a draatc ncrease n the popularty of cloud coputng systes that rent coputng resources on-deand, bll on a pay-as-you-go bass, and ultplex any users on the sae physcal nfrastructure. These cloud coputng envronents provde an lluson of nfnte coputng resources to cloud users that they can ncrease or decrease ther resources. In any cases, the need for these resources only exsts n a very short perod of te. The ncreasng use of vrtual achne technology n data centers, both leadng to and renforced by recent nnovatons n the prvate sector aed at provdng low-antenance cloud coputng servces, has drven research nto developng algorths for autoatc nstance placeent and resource allocaton on vrtualzed platfors[1], [2], ncludng our own prevous work. Most of ths research has assued a platfor consstng of hoogeneous nodes connected by a cluster. However, there s a need for algorths that are applcable to heterogeneous platfors. Heterogenety happens when collectons of hoogeneous resources forerly under dfferent adnstratve doans are federated and lead to a set of resources that belong to one of several classes. Ths s the case when federatng ultple clusters at one or ore geographcal locatons e.g., grd coputng, sky coputng. In ths work we propose vrtual achne placeent and resource allocaton deadlock detecton algorths that, unlke prevous proposed algorths, are applcable to vrtualzed platfors that coprse heterogeneous physcal resources. More specfcally, our contrbutons are: We provde an algorthc approach to detect deadlock and resource allocaton ssues n the vrtualzaton platfor heterogenety. Ths algorth s n fact ore general, even for heterogeneous platfors, and only allowed to allocate nal resources to eet QoS arbtrary force. Usng ths algorth, we extend prevously proposed algorths to the heterogeneous case. We evaluate these algorths va extensve sulaton experents, usng statstcal dstrbutons of applcaton resource requreents based on a real-world dataset provded by Google. Most resource allocaton algorths rely on estates regardng the resource needed for vrtual achne nstances, and do not refer to the ssue of detectng and preventng deadlocks. We studed the pact of estaton errors and propose dfferent approaches to tgate these errors, and dentfy a strategy that works well eprcally. II. RELATED WORKS Resource allocaton n cloud coputng has attracted the attenton of the research county n the last few years. Srkantaah et al. [8] studed the proble of request schedulng for ult-tered web applcatons n vrtualzed heterogeneous systes n order to nze energy consupton whle eetng perforance requreents. They proposed a heurstc for a ultdensonal been packng proble as an algorth for workload consoldaton. Garg et al. [10] proposed near optal schedulng polces that consder a nuber of energy effcency factors, whch change across dfferent data centers dependng on ther locaton, archtectural desgn, and anageent syste. Warneke et al. [11] dscussed the challenges and opportuntes for effcent data processng n cloud envronent and presented a data Journal Hoepage:

2 Ha Huy Cuong Nguyen and Van Son Le 2 processng fraework to explot the dynac resource provsonng offered by IaaS clouds. Wu et al. [12] propose a resource allocaton for SaaS provders who want to nze nfrastructure cost and SLA volatons. Adds et al. [13] proposed resource allocaton polces for the anageent of ult-ter vrtualzed cloud systes wth the a to axze the profts assocated wth ultple class SLAs. A heurstc soluton based on a local search that also provdes avalablty, guarantees that runnng applcatons have developed. Abdelsale et al. [14] created a atheatcal odel for power anageent for a cloud coputng envronent that prarly serves clents wth nteractve applcatons such as web servces. The atheatcal odel coputes the optal nuber of servers and the frequences at whch they should run. Yazr et al. [15] ntroduced a new approach for dynac autonoous resource anageent n coputng clouds. Ther approach conssts of a dstrbuted archtecture of NAs that perfor resource confguratons usng MCDA wth the PROMETHEE ethod. Our prevous works anly dealt wth resource allocaton, QoS optzaton n the cloud coputng envronent. There are ore general types of resource allocaton probles than those we consder here. For nstance: 1. We consder the possblty that user ght be wllng to accept alternatve cobnatons of resources. For exaple, a user ght request eleentary capacty CPU,, HDD rather than a specfc. 2. We consder the possblty that resources ght be shared. In ths case, soe sharng s typcally pertted; for exaple, two transactons that need only to read an obect can be allowed concurrent access to the obect. 3. We begn by defnng our generalzed resource allocaton proble, ncludng the deadlock detecton proble as an nterestng specal case. We then gve several typcal solutons. III. SYSTEM MODEL RESOURCE ALLOCATION IN HETEROGENEOUS DISTRIBUTED PLATFORMS Resource allocaton n cloud coputng has attracted the attenton of the research county n the last few years. Cloud coputng presents a dfferent resource allocaton paradg than ether grds or batch schedulers [2]. In partcular, Aazon C2 [10], s equpped to, handle ay saller coputer resource allocatons, rather than a few, large request as s norally the case wth grd coputng. The ntroducton of heterogenety allows clouds to be copettve wth tradtonal dstrbuted coputng systes, whch often consst of varous types of archtecture as well. Lke tradtonal dstrbuted syste before we can see a heterogeneous dstrbuted syste conssts of a set of processes that are connected by a councaton network. The councaton delay s fnte but unpredctable [21], [22]. A). The Applcaton A heterogeneous dstrbuted progra s coposed of a set of n asynchronous processes p 1, p 2,,p n that councates by essage passng over the councaton network. We assue that each process s runnng on a dfferent processor. The processor does not share a coon global eory and councate solely by passng essages over the councaton network. There s no physcal global clock n the syste to whch processes have nstaneous access. The councaton edu ay delver essages out of order, essages ay be lost garble or duplcated due to teout and retranssson, processors ay fal and councaton lnks ay go down. The syste can be odeled as a drected graph n whch vertces represent the processes and edge represent undrectonal councaton channels. We use the platfor graph, for the grd platfor. We odel a collecton of heterogeneous resources and the councaton lnks between the as the nodes and edges of an undrected graph. See an exaple n Fg. 1 wth 8 processors and 11 councaton lnks. Each node s a coputng resource (a processor, or a cluster, or node). P8 P3 P5 P1 P6 P4 Fg. 1. An exaple sple platfor A process can be n two states: runnng or blocked. In the runnng state (also called actve state), a process has all the needed re and s ether executng or s ready for executon. In the blocked state, a process s watng to acqure soe resource. B). The Archtecture The target heterogeneous platfor s represented by a drected graph, the platfor graph. There are p nodes P 1, P 2,, P n that represent the processors. In the exaple of fgure 1 there at eght processors, hence n = 8. Each edge represents a physcal nterconnecton. Each edge e : P P s labeled by value c, whch represents the te to transfer a essage of unt length between P and P, n ether drecton: we assue that the lnk between P and P s bdrectonal and syetrc. A varant would be to assue two undrectonal lnks, one n each drecton, wth possbly dfferent label values. If there s no councaton lnk between P and P we let c, = +, so that c, < + eans that P and P are neghbors n the councaton graph. C). Wat For Graph (WFG) In dstrbuted systes, the sate of the syste can be odeled by drected graph, called a wat for graph (WFG) [21] [25]. In a WFG, nodes are processors and there s a drected edge fro node P 1 to ode P 2 f P 1 s blocked and s P2 P7

3 Internatonal Journal of Coputer Scence and Telecouncatons [Volue 6, Issue 2, February 2015] 3 watng for P 2 to release soe resource. A syste s deadlocked f and only f there exsts a drected cycle or knot n the WFG. Let us frst of all descrbe the deadlock condton proble ore precsely. A set S = {s 1, s 2, s k } of k > 1 enttes s deadlocked when the followng two condtons sultaneously hold: Each entty s S s watng for an event persson that ust be generated fro another entty n the set; No entty s S can generate a persson whle t s watng. If these two condtons hold, the enttes n the set wll be watng forever, regardless of the nature of the persson and of why they are watng for the persson ; for exaple, t could be because s needs a resource held by s n order to coplete ts coputaton. A useful way to understand the stuatons n whch deadlock ay occur s to descrbe the status of the enttes durng a coputaton, wth respect to ther watng for soe events, by eans of a drected graph W, called wat-for graph. Deadlock detecton can be represented by a Resource Allocaton Graph (RAG), coonly used n operatng systes and dstrbuted systes. A RAG s defned as a graph (V,E) where V s a set of nodes and E s a set of ordered pars or edges (v,v ) such that v,v V. V s further dvded nto two dsont subsets: P { p0, p1, p2,..., p } where P s a set of processor nodes shown as crcles n Fgure 1; and where Q s a set of resource nodes Q q0 q1 q2 q n {,,,..., } shown as boxes n Fgure 1. A RAG s a graph bpartte n the P and Q sets. An edge e =(p,q ) s a request edge f and only f p P, q Q. The axu nuber of edges n a RAG s n. A node s a snk when a resource (processor) has only ncong edge(s) fro processor(s) (resource(s)). A node s source when a resource (processor) has only outgong edge(s) to processor(s) (resource(s)). A path s a sequence of edges p 1 q 1 q 1 p 2 pk q k1 q s ps 1 {(, ),(, ),...,(, ),(, ) where E. If a path starts fro and ends at the sae node, then t s a cycle. A cycle does not contan any snk or source nodes. The focus of ths paper s deadlock detecton. For our vrtual achne resource allocaton on heterogeneous dstrbuted platfors deadlock detecton pleentaton, we ake three assuptons. Frst, each resource type has one unt. Thus, a cycle s a suffcent condton for deadlock [3]. Second, satsfes request wll be granted edately, akng the overall syste expedent [3]. Thus, a processor s blocked only f t cannot obtan the requests at the sae te. All proposed algorths, ncludng those based on a RAG, have O(n) n the worst case.. In ths paper, we propose deadlock detecton algorth wth O(n(,n)) based on a new atrx representaton. The proposed vrtual achne resource allocaton on heterogeneous dstrbuted platfors deadlock detecton algorth akes use of s and can handle ultple requests/grants, akng the proposed algorth faster than the O(n) algorth [16], [17]. IV. DEADLOCK DETECTION FOR RESOURCE ALLOCATION IN HETEROGENEOUS DISTRIBUTED PLATFORMS In ths secton, we wll frst ntroduce the atrx representaton of a deadlock detecton proble. The algorth s based on ths atrx representaton. Next, we present soe essental features of the proposed algorth. Ths algorth s, and thus can be apped nto a cloud archtecture whch can handle ultple requests/grants sultaneously and can detect ultple deadlocks n lnear te, hence, sgnfcantly provng perforance. A). Matrx Representaton of a Deadlock Detecton Proble In graph theory, any drected graph can be represented wth an adacency atrx [3]. Thus, we can represent a RAG wth an adacency atrx. However, there are two knds of edges n a RAG: grant edges, whch pont fro resources to processors, and request edges, whch pont fro processors to resources. To dstngush dfferent edges, we desgnate eleents n the adacency atrx wth three dfferent values as shown n Fgure 2. Ths Fgure shows the atrx representaton of a gven syste wth processors p 1, p 2,,p,...,p and resources q 1, q 2,,q,,q n. The leftost colun s the processors label colun. The top row s the resources label row. If there s a request edge (p,q ) n the RAG, correspondng eleent n the atrx s r. If there s a grant edge (q,p ) n the RAG. The correspondng eleent n the atrx s g. Otherwse, the value of the eleent s 0. Ths varant of the adacency atrx of a RAG (V,E) can be defned forally as follows: M [ ] n, (1, 1 n), where s the nuber of processors and n s the nuber of resources. {r,g,0} = r, f f ( p, q ) E = g, f f ( p, q ) E = 0, f otherwse Ths atrx provdes a teplate able to represent request and grant cobnatons. Note that each resource has at ost one grant, that s, there s at ost one g n a colun at any te. However, there s no constrant on the nuber of requests fro each processor. If there are deadlocks n a syste, there ust be at least one cycle n ts RAG, that s, there ust be a sequence of edges, {( p, q ),( q, p ),...,( p, q ),( q, p ),...,( p, q ),( q, p )} k k k k 1 s s s 1 E,where. In the atrx representaton, ths cycle s apped nto a sequence of atrx eleents { 1,,...,,,, } k k k 1 k s s 1 where are s requests(r s) and 2,,...,, k 1 k 1 s are grants (g s). By ths fact, we can detect deadlocks n a syste wth ts adacency atrx. Next, we wll present the new detecton algorth.

4 Ha Huy Cuong Nguyen and Van Son Le 4 B). Deadlock Detecton Algorth On ths bass of the atrx representaton, we propose a deadlock detecton algorth. The basc dea n ths algorth s teratvely reducng the atrx by reovng those coluns or rows correspondng to any of the followng cases: a row or colun of all 0 s; a source ( a row wth one or ore r s but no g s, or a colun wth one g and no r s); a snk ( a row wth one or ore g s but no r s, or a colun wth one r s but no g s); Ths contnues untl the atrx cannot be reduced any ore. At ths te, f the atrx stll contans row(s) or colun(s) n whch there are non-zero eleents, then there s at least one deadlock. Otherwse, there s no deadlock. The descrpton of ths ethod s shown n algorth. Algorth: Deadlock Detecton Algorth (CPU)* ()* Input: P ; P fro IaaS provder ; Step 1: calculate optal resource allocaton to (CPU) * () * provde VM. x, x Max{ U IaaS }; Step 2: Coputes new resource CPU (CPU) ( ) If C x, C x then CPU ( n1) CPU ( n) ( CPU ) CPU r ax{, r n( x C )}; ( n1) ( n) () r ax{, r n( x C )}; CPU ( n 1) ( n1) Return new resource r ; r Else Step 3: Intalzaton n M [ ], Where {r,g,0}, ( =1,, and =1,,n) = r f (p,q ) E. = g f (p,q ) E. = 0, otherwse. { M, 0}; Step 4: Reove all snk and sources DO { Reducble = 0; For each colun: f ( k, k, k {, 0}){ colun { 1, 2, 3,..., }, reducble 1; } else{} For each row: f ( k, k, k {, 0}){ row { 1, 2, 3,..., }, reducble 1; } else{} colun row; } UNTIL( reducble 0); Step 5: Detect Deadlock If ( 0 ), then return deadlock exts. If ( 0 ), then return no deadlock exts. CPU (n 1) (n1) Output: new resource r ; r The followng exaple llustrates how the algorth works, n each teraton of ths algorth; at least one reducton can be perfored f the atrx s reducble. Hence, t takes at ost n(,n) teratons to coplete the deadlock C). Our Algorth to Avodance Deadlock In heterogeneous dstrbuted platfors f there are n processes for each processor and resources the algorth wll be as follow: Step 1: In any of the processes of a processor usng one of the resources n a specfc te perod (.e., the perod-1) then no other requreents for the resources wll be allocated for the specfed te perod. Step 2: The resource occuped can be used by other processes wthn a specfc te perod (.e., the perod-2) only after the release by the process of step 1 by approxately te-1. Durng the perod-2 has no other process wll be able to use that resource. Step 3: In the sae way, a process of the processor s deterned n step 2 can use an O resources n a specfc te perod (.e., the perod-3) n the absence the other wll be able to use that resource. Step 4: The resources that were occuped n step 3 can be used by other processes defned n step 1 n a specfc te perod (.e., the perod-4) only after released by the process of step 3 by approxately-3. Durng the perod-4 has no other process wll be able to use that resource. D). Proof of the Correctness of DDA Exaple 2 State atrx representaton The syste n state shown n Fg. 2 (a) can be representaton n the atrx for show n (b). For the sake of better understandng, we wll descrbe t n the atrx representaton, shown n Fg. 3 (c) fro now on.

5 Internatonal Journal of Coputer Scence and Telecouncatons [Volue 6, Issue 2, February 2015] 5 p3 q2 p1 q1 p4 q3 p2 q4 p5 p6 q5 q6 rg0r00 00rg00 => M = 0000g0 000rgr 0000rg 00000r The frst case generated the request usng a noral dstrbuton of arrval te. Ths deternes the perforance of the algorths to handle the arrval of tasks n an exponentally ncreasng nuber of request. There were up 100 request generated and also these requests were assgned n randoly. => Fg. 2. Matrx representaton exaple Fg. 4. Message overheads by network latences usng the generated requests based on arrval te n noral dstrbuton Step 1 (a) The coparatve analyss of experental result can be seen n any tes, after task executon, although there were ndvdual te proved DDA algorth response te was not sgnfcantly less than optal te algorth, n ost cases, proved algorth s better than the optal te algorth, thus valdated the correctness and effectveness. VI. CONCLUSION Step 2 (b) Step 3 (c) Fg. 3. A saple sequence of reducton steps and deadlock detecton V. SIMULATION RESULTS AND ANALYSIS In ths paper, resource allocaton ethod based on proved DDA has been valdated on CloudS, the platfor s an open source platfor, we used Java language to progra algorth pleentaton class. Experents gve n tasks, by CloudS s own optzaton ethod and proved algorth. Deadlock s a hghly unfavorable stuaton that can occur n any ultprocessor syste. The occurrence of a deadlock can crpple parts of a ultprocessor syste. It s necessary to develop control polces that avod deadlocks by restrctng the freedo n resource allocaton. In ths paper we have presented a fast deadlock detecton and deadlock avodance ethodology that s easly applcable to heterogeneous dstrbuted platfors. Once a deadlock s detected, t ust be soehow resolved. In a heterogeneous dstrbuted platfors large proble s dstrbute aong the processors (such as aong the coputers of dstrbuted coputng syste or aong the coputers of parallel coputng syste etc.) to ake t cost effectve and less te consung nstead of a coputer syste wth sngle processor. But snce the large progra s dvded nto saller progras chances of occurrng deadlock becoes hgh. So, t s very necessary to apply deadlock avodance ethod n ultprocessor syste. In ths paper we have also provded the algorth whch sple and easy to understand. We can also pleent ths ethod everywhere n our coputatonal lfe as needed. REFERENCES [1]. Ha Huy Cuong Nguyen, Van Son Le, Thanh Thuy Nguyen, Algorthc approach to deadlock detecton for resource allocaton n heterogeneous platfors, Proceedngs of 2014 Internatonal Conference on Sart Coputng 3-5 Noveber, Hong Kong, Chna, pp

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