Mode Change Protocols for Predictable Contract-Based Resource Management in Embedded Multimedia Systems

Transcription

1 Mode Change Protocols for Predctable Contract-Based Resource Management n Embedded Multmeda Systems Marsol García Valls Department of Telematcs Engneerng Unversdad Carlos III de Madrd Avda. de la Unversdad 30, Leganés Madrd (Span) mvalls@t.uc3m.es Aleandro Alonso, Juan A. de la Puente Department of Telematc Systems Engneerng ETSI Telecomuncacón Techncal Unversty of Madrd Cudad Unverstara s/n, Madrd, Span {aalonso, puente}@dt.upm.es Abstract Meda processng n Hgh-Qualty Multmeda Embedded Systems (HQMES) has real-tme constrants. Tmely processng and renderng of vdeo frames and audo samples s essental to meet user expectatons. The nature of ncomng meda suffers unforeseen varatons whch have dfferent resource requrements. Therefore, HQMES have to ntegrate polces for effcently and smoothly adaptng to these changes. Mode change protocols allow applcatons to swtch ther state (for nstance, to transton from one qualty level to another) by controllng the way n whch the applcaton tasks change from one state to another. Ths paper provdes a soluton for tmely mode change protocols based on a contract model between applcatons and the executon platform. A new mode change algorthm, progressve mode change protocol, s ntroduced for applcatons wth no tolerance to data loss durng ther transtons. The executon platform s based on a qualty of servce resource manager (QoSRM) that arbtrates the greedy executon of multmeda applcatons, and that s mplemented on top of the servces of a real-tme operatng system. A task model and a temporal characterzaton of multmeda applcaton tasks s also presented as the basc platform for the QoSRM operaton. Valdaton experments show stable executon of applcatons wth the proposed task characterzaton and progressve mode change protocol. 1. Introducton HQMES are user-orented systems that have to execute very effcently and cost-effectvely to delver the hghest qualty result possble to the customer. These systems, as set top boxes and dgtal ntegrated TV sets, have evolved not only n ther hardware structure but also n ther software platform. From former hardware-coded meda processng functons, we fnd nowadays software-coded functonalty ntegrated n an embedded structure. The transton from hardware to software has ntroduced a hgh degree of flexblty n these systems at the cost of hgher threats to predctablty, relablty, and performance. HQMES have requrements for real-tme operaton (as, for example, hgh-qualty vdeo renderng) whch need real-tme support from the underlyng platform. Not only the network protocols must be determnstc, but also the operatng system and dstrbuton mddleware. These systems are hghly demandng envronments that approprately mx determnstc lowlevel mechansms wth effcent hgh-level protocols and strateges. One wthout the other may result n useless solated effort [5,11]. Lower-level mechansms provde the bascs to buld system protocols that offer the requred real-tme support for applcaton operaton. These mechansms are resource schedulng, manly processor, memory, communcaton meda, and battery. Reconfguraton s also a key aspect of HQMES, snce ther applcatons may suffer sporadc changes n the amount of requred computaton resources. Ths mples that ther functonal structure and ther operaton should be flexble enough to adapt to these changes. Reconfguraton cannot tolerate operaton uncertanty. The system should be kept under predctable operaton condtons even n the event of state transtons. As a consequence, real-tme technques and predctable resource management technques have to be used. The basc theory for provdng true determnsm can rely on real-tme technques that have evolved and lost some of ther tradtonal restrctons n order to better sut the multmeda consumer doman. Such evoluton has

2 become effcent management of resources appled at operatng system level and, n some cases, at system archtectural level. Stll many problems of these systems reman, for nstance, handlng of unpredctable varatons n resource requrements and of state transtons. Ths paper puts nto context the tradtonal problems of these systems and proposes an approach for: controllng executon of the tradtonal greedy multmeda applcatons n a tme predctable way and performng effcent mode changes for applcatons wth no tolerance to data loss durng reconfguraton. The paper reles on a contract based approach for handlng nterference of applcatons. The approach extends the basc focus of [2] by ntroducng a progressve mode change protocol for applcatons wth no tolerance for data loss. Also, the paper gves a task characterzaton and temporal analyss for multmeda applcatons. The paper s structured as follows. Secton 2 offers an overvew of related work. Secton 3 presents the basc prncples for predctable resource management. Secton 4 revsts and extends the applcaton modelng of [2]. Secton 5 elaborates on the applcaton task model and the temporal analyss used by the QoSRM to assess predctablty. Secton 6 proposes a new mode change protocol for applcatons that do not tolerate data loss durng transtons. Secton 7 presents the valdaton experments that show the stable executon of applcatons wth the proposed modelng and mode change protocols. At last, secton 8 presents the conclusons of the work. 2. Background Resource management s a system wde concern. Nowadays, when applcatons are manly dstrbuted, resource guarantees are requred across the applcaton nodes. However, although end-to-end resource requrements may nfluence the executon of the applcaton at each node, t s mportant to note [11] that node-centered polces and mechansm for predctable resource management have to be set frstly. At node level, there are two basc approaches for resource management: Operatng system based resource reservatons schemes and schedulng polces, such as [1,3,7,8,9]. Archtectural solutons for developng ntermedaton agents as QoSRMs, as the ones descrbed n [2,4,6,12]. These enttes take advantage of the predctablty of an underlyng RTOS to buld the requred mechansms for predctable resource management. Resource management based on QoS technques has tradtonally been targeted at general purpose dstrbuted systems manly used for nternet-based vdeo conferencng systems. Ther requrements are not as hard as those of commercal products for the consumer market that have to offer hgh-qualty outputs. HQMES are hgh qualty vdeo processng and delvery systems targeted at a user that tolerates no mage freezes and no delays n operaton. Wth the ncreased trend n enhancng the software contaned n them (to make them more flexble), mechansms that provde support for predctablty are requred. Snce hardware s more relable than software, researchers need to attack all sdes of the development of HQMES, from the software engneerng parts, the mddleware, all the way down to the lower level determnstc executon mechansms and the RTOS. Also, other work appeared to mplement coordnaton enttes that would collaborate wth multmeda applcatons n a best effort way [4]. From a more ntegral perspectve, approaches as [6] offered layered archtectural vews for mplementng manager enttes n HQMES by means of defnng the approprate hooks to nclude determnstc resource management mechansms. One of the ntal deas on mode change protocols was [10] whch s very lmted for the actual requrements of HQMES reconfguraton. It consders dual prortes for tasks, a lower and upper prorty values. It calculates the tme lmt when a task has to be rased to ts upper prorty to fnsh on tme. Ths technque has no consderaton for applcaton semantcs regardng, for nstance, the nature of the processed meda. In HQMES, specfc values for a hgher level QoS characterzaton are needed. To fll n these gaps, ths paper focuses at the level of the ntermedaton enttes, bult on top of the RTOS. For these enttes, the followng s proposed: A characterzaton of task types and temporal analyss of multmeda applcatons. Ths characterzaton s bult on the bass of the applcaton model presented n [2]. In ths paper, we present perodc, contnuous, and mprecse tasks; we show how they are approxmated by perodc tasks. Based on [2], a new algorthm for progressve transtons s presented for multmeda applcatons wth no tolerance for data loss. Ths approach s based on the exstence of a RTOS that provdes support for executon predctablty. On top of t, the necessary abstractons for buldng a QoSRM entty are made. System operaton s based on a contract model to support executon solaton that guarantees predctablty.

3 3. Predctable resource management prncples 3.1. Fundamental operatons A QoSRM must perform the followng operatons: Admsson control. Resources are lmted and applcaton executon wll be checked aganst resource avalablty, as shown n fgure 1. Resource reservaton guarantees. The QoSRM has to gve the applcatons strct guarantees that the resource budgets contracted wll be avalable. Global optmzaton. It allows performng an approprate resource assgnment, n a way that the global qualty offered by applcatons together wth the global qualty perceved by the user s maxmzed. Handlng overload, faults, and alarms. The system must be able to flter out overload stuatons (whch are very frequent n the multmeda processng envronment), to recover from faults, and to handle alarms that may be trggered durng system operaton. Estmaton of resource requrements of applcatons. Resource requrements for meda processng algorthms on HQMES are estmated by applcaton experts. Snce resource demands are varable and data dependent, the average case s used [11]. Currently, there s no ntegrated soluton that s capable of fulfllng all these prncples. In fact, only a few solutons address satsfactory three (four, at most) of them n an ntegrated way. 3.2 Archtectural prncples for QoSRM mplementaton Fgure 1: Resource assgnment scheme Schedulng and management of resources. To guarantee suffcent resources, the system must nclude approprate resource schedulng polces. Resource usage montorng. It allows to determne the behavor of applcatons and to detect stuatons of over or nfra utlzaton as a frst step towards undertakng correctve actons. Dynamc adaptaton. At run tme, the system must be able to adapt to changes, for nstance, due to a sporadc varaton n the load generated by the ncomng data. Stablty. The system must be able to react n a stable way to any external or nternal event; reacton to them should not be a source of nstablty. Effcent transtons. Reconfguraton of applcatons (such as a swtch of qualty level) may be frequent, dependng on, for nstance, the user acton. Such changes determne a new confguraton of the system that nvolves a new dstrbuton of resource budgets among applcatons. These transtons should be smooth. The QoSRM that s consdered follows the archtectural prncples of HOLA-QoS [6], shown n fgure 2. Ths archtecture, centralzed n ts ntal verson, has also been ported to a multprocessor archtecture, and t s currently beng ported to a fully open dstrbuted envronment wth real-tme vrtual machne structure. Fgure 2: HOLA-QoS Archtecture Some of the characterstcs of the archtecture are: It has a herarchcal mult-level structure that allows workng at dfferent abstracton levels by adustng to the functonal nterfaces. Integratng a dfferent reconfguraton protocol requres only to code t n the approprate layer, precsely, layer 2. Its homogeneous layer structure (as shown n fgure 3) allows for easy replacement of components n the layers to experment wth dfferent resource management mechansms and

4 reconfguraton polces, whch s an addtonal detal related to the prevous characterstc. Its control s herarchcal: (1) upper layers perform less frequent control operatons although such operaton have most nfluence on the system as a whole, whereas (2) lower layers perform more automatc control mechansms that are executed wth hgher frequency (such as resource accountng and montorng, resource enforcement, and admsson control). Fgure 3: Layer Structure n HOLA-QoS 3.2. Contract-Based Executon Executon based on a contract model s a type of system operaton that nvolves a frm agreement between the QoSRM and the applcatons; ths operaton mantans at all tmes the followng system wde premses: The platform (QoSRM whch takes the basc servces of an RTOS) has to guarantee applcatons a gven budget for each resource that the applcatons need n order to delver the agreed qualty level, and Applcatons must provde a certan output qualty wth the agreed resource budgets. Under a contract model, applcaton codng s responsblty of the multmeda applcaton engneers. They have complete knowledge of the resource needs of the applcatons they program; ths s especally true n the case of hgh qualty vdeo applcatons [5]. The basc technque to mplement the contract model s the budget enforcement. To avod that applcatons nterfere wth one another due to ther greedy tasks, the system must offer budget solaton. Guaranteeng budgets to tasks s done by means of forcng tasks not to use more resources than they have contracted n ther budget. Ths way, even f greedy tasks of an applcaton are wllng to ncur n budget overruns, the QoSRM wll steel the processor from them whenever they have consumed the budget. If the system has avalable resources, the QoSRM can decde to let some budget overruns happen. The mechansm to guarantee budgets to approprately handle nterference s based on the followng key ponts: Resource usage montorng and accountng; ths s the basc mechansm for the QoSRM to obtan nformaton of the actual resource consumpton of applcatons; t allows to detect possble budget overruns. Prorzaton of applcatons; t s a basc decson tool to take approprate correctve actons f the system executon needs to be adapted. Also, t s a basc mechansm to provde sutable admsson protocols, based on basc temporal analyss and response tme calculatons. Fgure 4 shows the behavor of the budget enforcement mechansm as the bascs to mplement the contract model on the QoSRM sde. As executon progresses and nterference s forced, the QoSRM has to enforce the maxmum yet safe resource budget for all applcatons. Therefore, the total resource usage should not exceed the safe bounds n the system. Interference may be caused ether by user requests to swtch applcatons to a hgher qualty level or by a change of the ncomng meda that requres a hgh processng capacty (for nstance, a fast moton scene). Fgure 4: Contract-based executon and budget enforcement 4. Applcaton Model Ths secton presents the approach for modelng applcatons n HQMES on top of the basc model of [2]. The basc prncples for the applcaton model have been the followng: To adust to the natural structure of multmeda applcatons: (1) flter-based meda processng, and (2) to model the dfferent delvery output qualtes (qualty levels) that a multmeda applcaton may produce as results.

5 To ntegrate smoothly the hooks for performng system-wde and cross-applcaton resource management. Hgh qualty vdeo streamng applcatons have a ppelne and graph structure. Ther output qualty s drectly nfluenced by the number and complexty of the ntermedate flters to be appled to the data. Snce applcaton tasks are greedy, output qualty s related to the amount of resources that multmeda flters are granted. In our approach, applcatons have two man parts wth separate responsbltes: (1) control part for nteracton wth the QoSRM, and (2) functonal part that executes the meda processng algorthms. The functonal part of a typcal hgh-qualty vdeo applcaton s a ppelne of connected multmeda flters. Applcatons receve data (nput sgnal), process t and produce an output sgnal for the next flter n the ppelne. Such processng s carred out n a contnuous way,.e., for most multmeda flters/tasks, t s true that they execute n a greedy way for as long as they have nput data to process. The control part s an addtonal task that s n charge of recevng the control commands from the QoSRM and restructurng the functonal part as necessary. For nstance, a qualty level change may requre that the current task set s changed or parameterzed n a dfferent way snce the new qualty level may have dfferent computaton demands. The applcaton control part wll have to parameterse the code of the requred tasks; t wll change the structure of the functonal part,.e., the connectons between tasks and/or flters, f necessary. Fgure 5 presents the applcaton modellng approach. The system model wll be a collecton of the applcatons of the specfc HQMES. The QoSRM has the whole system nformaton n ts nternal repostory (n the case of HOLA-QoS, ths s the system profle data base). As explaned [2], the applcaton model follows these crtera: Each applcaton can delver dfferent output results or qualty levels. A qualty level may be mplemented wth dfferent resource combnatons, each called QLConfguraton (.e., an applcaton can be capable of delverng a full screen sze wth c processor percentage and y memory or compensatng memory wth processor as c + ν processor and y - υ memory). Each realzaton of a qualty level can be acheved by a dfferent set of applcaton tasks (Task). Tasks may be grouped (Cluster) n a way that they compensate one another n the usage of resources. Fgure 5: Applcaton charactersaton Each cluster, whch s a group of tasks wth smlar propertes for purposes of compensaton, can be realzed by assgnng a dfferent set of resource budgets (Budget) to t for each resource t uses. Ths s represented as a ClusterConfguraton. Also, a certan task can take dfferent versons or profles (TaskConfguraton) dependng on the nput data t has to process. Ths model shown n fgure 5 can be ether used n full as presented (whch wll allow fne control over applcatons) or n a smplfed form (whch allows easer formal modelng), as follows. In ts most smple form, an applcaton a s characterzed by the set of ts qualty levels, ts task set, and ts assocated mportance: ( Φ, τ, Ι (1) ) a The set of qualty levels of an applcaton may range from 1 to n. Each qualty level, ϕ s, contans a gven set of tasks: Φ s ϕ (2) s ϕ s s τ r r ϕ s s Φ and r [ 1, ] (3) The specfcaton of an applcaton task s done wth the standard parameters, so t can be easly handled by any real-tme operatng system based on a prortybased pre-emptve scheduler: ( C r, Tr, Dr, Pr ) (4) Dependng on the data nput type, a task wll requre a dfferent state (values) for ts parameters. The task class attrbutes are based on (4), however the dfferent states of ths task are ts TaskConfguraton set.

6 5. Task Model and Temporal Analyss Ths secton descrbes the proposed task model for hgh qualty multmeda embedded systems. Also, a formal characterzaton of the task model s presented as a means to perform the temporal analyss of the system based on the ndvdual analyss of the applcatons. For non-schedulable task sets, the QoSRM wll take approprate acton to avod system rsks: (1) to reect an applcaton, (2) to stop less mportant applcatons, or (3) to lower some applcaton s current qualty level, etc. On top of these basc tools, the contract model s gven. The system montors resource usage of applcatons and enforces the contracted budgets. If some spare computng capacty s avalable, the QoSRM may allow some applcaton to exceed ts contracted budgets. Ths ntroduces a safe executon envronment avodng executon nterference Task Model The proposed task model for applcatons of hgh qualty multmeda embedded systems has the followng characterstcs: Tasks are perodc or contnuous. Multmeda tasks are fundamentally of these two types. Perodc tasks are actvated at fxed tme ntervals, and they must fnsh executon before each new actvaton. Contnuous tasks are mostly actvated by the nput data; therefore, they execute constantly n a non-stop fashon as long as they receve nput data to process. Also, mprecse tasks may be present. They have man smlartes wth contnuous tasks. They are charactersed by the fact that ther output mproves proportonally to the amount of resources that they are assgned. They have two parts: a mandatory part and an optonal one. If they execute the mandatory part, the result s consdered to be acceptable; f the optonal part can also be executed, the result of the processng s sad to be precse. Assgnment of resource budgets. A task receves a utlzaton budget (resource budget) for each resource that t needs to execute. The task has to fnsh ts processng wthn the assgned budget; ths budget s always guaranteed by the contract model. Task groups or clusters. Clusters enable the groupng of tasks (at a lower abstracton level than an applcaton) n a way that a resource budget s assgned to the group as a whole. Ths allows compensatng for ndvdual deadlne msses and budget overruns. Perodc refll of resource budgets. Every start of actvaton perod, resource budgets are reflled by the QoSRM; therefore, schedulablty analyss and admsson control s based on the values of the budgets. Varous schedulng polces of a task cluster are possble: (1) non specfc (wth no pre-empton, so t may happen that a task s allocated the processor and others suffer starvaton), or (2) based on tme references (a task parameter, such as the computaton tme or the deadlne, ndcates when a task has to be pre-empted for the rest of the cluster to be executed) Temporal characterzaton Followng, the temporal characterzaton for applcatons that contan contnuous tasks s gven. The smplest characterzaton of a contnuous task s done as beng an mprecse task: τ α, β D, T, P ) (5) ( where α s the mandatory part and β s the optonal part. Ths specfcaton requres that the admsson test for applcatons be updated as follows: α (6) R = α + α ( hp( )) T To be schedulable, all tasks of an applcaton wll have a response tme, R, not greater that ther deadlne. They wll be checked wth the nterference of hgher prorty tasks, hp(). For all tasks of an applcaton, the fulflment of equaton (6) wll guarantee that all tasks are able to delver the acceptable output qualty. Through montorng, the system can detect that enough resources are avalable for greedy contnuous tasks to execute longer delvery an mproved qualty output. The system wll do the checkng wth equaton (7): α + β (7) R = ( α + β ) + ( α + β ) ( hp( )) T By approxmatng an mprecse contnuous task as perodc, the system has an ncreased flexblty for low-level mprovement of output qualty of tasks. Ths low-level control s more effcent snce t s done by the QoSRM over the RTOS. Combnng clusters and budgets, the schedulablty analyss s more flexble and powerful. Let us magne a smple multmeda applcaton wth four flters (τ n, τ flter1, τ flter2, τ out ), wth two strct perodc tasks (the τ n and τ out tasks) and two contnuous tasks whch are the meda processng flters. Fgure 6 shows the normal schedule for the whole set where only a fxed average case executon tme s consdered that allows tasks to provde an acceptable output qualty.

7 6. Mode Change Protocols Fgure 6: Normal Schedule Fgure 7: Modelng for Imprecse Computatons If the greedy contnuous tasks are modeled for mprecse computaton, the system ntroduces more flexblty to allow tasks to mprove the output qualty as shown n schedule of fgure 7. Actual optonal executon of a contnuous task, δ, s bounded by [0, β ]. δ s related to the deadlne of the entre applcaton ppelne, Δ, by the followng expresson: (8) δ 0, Δ α a x A frst smplfcaton for the run-tme system to enforce optonal parts s done through obtanng an average optonal part among all contnuous tasks of the applcaton: Δ α (9) a δ x 0, n where n s the number of task n the applcaton and Δ s the applcaton deadlne. The ncrease n the percentage of processor utlzaton s shown n (10): δ (10) ct( a ) Δ x a x 100 Eventually, response tmes of tasks wll have to be modeled as shown n (11): (11) Δ α R = ( hp( )) α + a x T a x n ( α + β ) + ( α + β ) Due to the user acton or to any nternal decson of the adaptaton polces of the QoSRM, the current system confguraton may have to be replaced by a new one. Ths occurs, for nstance, when: (1)the qualty level of one applcaton s changed, (2) a new applcaton s launched, (3) an applcaton s stopped, or (4) a change n the nput meda requres more computaton resources to be assgned to some applcaton. In ths paper, we refer to the current system confguraton as beng the complete set of task profles (set of TaskConfguraton obects) that are actve n the system. Swtchng the current confguraton of the system requres a mode change protocol that manages the transton n a smooth way, not annoyng the user. Dfferent multmeda applcatons have dfferent requrements for mode changes, manly dependng on whether they tolerate some data loss durng the change. Termnaton of tasks s also an mportant factor. In mode change algorthms for hard real-tme systems, t s usual practce that tasks that wll not be part of the new mode are allowed to termnate normally. Ths smplfes ther programmng. Our approach sets two termnaton crtera for tasks of the old mode. Such crtera depend on the applcaton type and ts degree of tolerance to data loss n the transton from the old mode to the new one. Whereas hard real-tme systems focus mode change protocols at task level, ths scheme falls short for HQMES snce t has no nformaton of any hgher level applcaton semantcs or structure. Followng, a set of basc consderatons has been dentfed: (1) applcatons have to be able to confgure at functonal level to change ther qualty level, and (2) the QoSRM shares wth each applcaton knowledge of the nternal task structure and ts resource consumpton for each of ther possble mplementatons of qualty levels. A generalzed mode change protocol was presented n [2]; t splts the responsblty for the transton between applcatons and the QoSRM. It assumes that only applcatons know the precse reconfguraton needs of the nternal structure (management of buffer contents and new connectons, etc.). An mmedate mode change algorthm for mmedate transtons s sutable for applcatons where t s more mportant a fast change than loosng some data n the transton (.e., channel change n a TV set). It s revsted n fgure 8. The parameters and functons presented n the algorthm of fgure 8 are: Ω: set of applcatons that change to a new system confguraton.

8 OM a: task set that mplements the old qualty level of applcaton a. for all a Ω for all τ a stop τ f τ OMa destroy τ for all τ NMa create τ for τ (conta NMa) set_params τ for all a Ω send_cmd_reconf(ql_new) to a wat_complete_reconf_ack() from a for τ (conta NMa) start τ Fgure 8: Immedate reconfguraton NM a: task set that mplements the new qualty level of applcaton a. Cont a: set of tasks that reman n the new qualty level; ther profle may have to change. send_cmd_reconf(ql_new): the QoSRM sends the reconfguraton trgger (command) to the applcaton. wat_complete_reconf_ack: wats untl the applcaton has fnshed ts complete functonal reconfguraton. A new algorthm s proposed for provdng progressve reconfguraton. In the progressve mode change algorthm, only tasks that do not stay n the new qualty level are deleted. Tasks that are present n the new mode may change ther parameters (for nstance, may receve a dfferent resource budget set). for all a Ω send_cmd_enter_safe_state() to a wat_safe_state_app_ack() from a for all τ a stop τ f τ OMa destroy τ for all τ NMa create τ for τ (NMa conta) set_params τ send_cmd_reconf_task_conectons(ql_new) to a wat_complete_reconf_ack() from a for τ (NMa conta) start τ Fgure 9: Progressve reconfguraton There are some applcatons that have very low tolerance for data loss at all tmes, even durng applcaton reconfguraton. For these applcatons, a progressve mode change protocol has been proposed. The semantcs of ths protocol requres that before the QoSRM ntates the coordnaton of the mode change, the applcaton enters a safe state. When the applcaton confrms ts safeness, the QoSRM creates the tasks of the new mode and sets ts parameters accordng to the system profle. It then starts to stop the tasks of the old mode. Afterwards, the QoSRM sets the new mode parameters for the tasks that contnue n the new mode. Later, t creates the tasks that appear n the new mode and sets ts parameters. Eventually, all tasks are started. The parameters and functons presented n the algorthm of fgure 9 are: send_cmd_enter_safe_state(): functon used by the QoSRM to notfy applcatons to prepare to reconfgure to a new qualty level. wat_safe_state_app_ack(): functon used by the QoSRM to block untl an applcaton enters a safe state (savng data buffers, etc.) to proceed wth the mode change protocol. cmd_reconf_task_connectons(ql_new): functon used by the QoSRM to nform an applcaton to perform the approprate ppelne connectons accordng to ts structure n the new mode. In the context of progressve mode changes, low overhead n the transton s not as mportant as performng safe changes n qualty levels,.e., wthout loosng data n the change and wthout annoyng user percepton. Applcaton tasks requre, n ths context, to nclude semantcs of the change. Therefore, the optonal part, β s taken not only as tme to mprove processng; t may also be used for preparaton for mode changes or fault tolerance procedures. 7. Valdaton Valdaton experments have been carred out that show the effcency of applyng the contract-based approach by mplementng the budget enforcement mechansms and the stablty of the mode change algorthms. Implementaton of the QoSRM follows the HOLA-QoS harness archtecture. Experences have been carred out n both, real vdeo processng and renderng applcatons and synthetc ones. The ntal mplementaton has been on a multprocessor archtecture runnng raw hgh qualty vdeo processng and renderng applcatons orgnally on TrMeda platforms (TM1000 and TM1100) from former Phlps Semconductors on the real-tme operatng system psosystem. The current harness archtecture and the above mentoned mechansms have been ported on a

9 x86 platform runnng Red Hat Lnux and ts real-tme patch for TmeSys real-tme Java vrtual machne. Fgure 10 shows experments on the multcore TrMeda 1100 embedded platform, whch s specfcally desgned for multmeda processng; they nclude dedcated coprocessors for specfc memoryand bus-ntensve multmeda processng operatons. App. Task Type Cluster A τ0 Perodc (50ms) QL (ms) Hgh Med. Low ς τ1 Contnuous ς τ2 Contnuous ς B τ3 Perodc ς3 4-3 (50ms) τ4 Contnuous ς4 4-4 C τ5 Perodc ς (50ms) τ6 Contnuous ς τ7 Contnuous ς Table 1: Synthetc applcatons wth hgh system load The experment presented n fgure 10 shows the behavor of applcaton applcatons descrbed n table 1. The experment runs the three synthetc applcatons descrbed n table 1. The experment shows the frame processng and renderng tmes for the applcaton set above whch can ntroduce very hgh load n the system. Despte the average processor load beng over 90%, the frame processng and renderng tmes that are obtaned are stable. Renderng tmes represent the tme taken by a frame that enters the applcaton processng ppelne untl the frame s ready to be rendered on screen. Applcaton qualty levels fluctuate durng the experment and no unstable behavor s caused. Ths s due to the effectveness of the budget enforcement mechansm. The feasblty of achevng predctable executon by means of the mplementaton of the contract model s, therefore, evdenced as a key step for achevng system dependablty. For these experments the full characterzaton of applcatons has been utlzed as shown n the applcaton model of secton 4. Resource budgets assgned by the system concde n ths case wth the requred computaton tme. Results show that budget enforcement mechansms keep deadlne fulfllment. Perodc peaks correspond to the hgh level montorng algorthms of the QoSRM mplemented n HOLA-QoS to maxmze the utlzaton of platform resources. Fgure 11 valdates mode change performance; t shows the tme taken to perform the swtchng among two applcaton qualty levels by exchangng the actual current task set. In the presence of hgh nterference, results show that mode change has an average tme penalty of approxmately 79,4 ms, beng ts maxmum value 82,1ms. Ths experment has been carred out n a standard sngle core PC platform wth no dedcated multmeda coprocessors. Results for both mode change protocols, mmedate and progressve show smlar benefts. Ths s the deal stuaton snce a system global strategy wll decde whch mode change to apply, manly based on the nherent characterstcs of the multmeda applcaton that wll be consdered Fgure 11: Mode change results Intal executon exhbts normal nstablty. The rest of peaks are produced by montorng nstants where the system gathers nformaton on resource usage of applcaton tasks. Even n such a case a maxmum value of 82,1ms s acheved. Experments show that executon stablty s preserved even n the event of system confguraton transtons. 8. Conclusons Fgure 10: Frame Renderng and Processng Tmes Achevng tmely state transtons s one of the many problems that predctable executon n hgh qualty multmeda systems has. It s a complex problem wth many sdes to be solved. Another one of

10 these sdes s keepng compatblty among the costeffectve usage of resources n a hgh load envronment, whereas preservng tme predctablty and non nterference of applcatons at all tmes. Exstng approaches to predctable executon reman at a too pessmstc level for multmeda embedded systems; usually, they come from the real-tme feld and apply worst-case executon-tme technques where multmeda requres an average case. Other approaches leave predctablty out the pcture; ths s the case of most general purpose traffc-based QoS schedulng only concentratng on the network resource. Ths paper has presented an approach for achevng predctable mode changes n HQMES. Dfferent protocols have been presented over the past to adust to the dfferent nature of multmeda applcatons. Here, a new algorthm progressve mode change protocol, has been proposed. The operaton model of the system has been realzed on the bass of a contract-model for predctable executon and a complete applcaton model to allow havng a QoSRM that can arbtrate applcaton executon and coordnate mode changes. Experments have been ntegrated and mplemented n a QoSRM based on the archtecture harness of HOLA- QoS. The paper proposes an applcaton task characterzaton and temporal analyss; these are used by the QoSRM for admsson control and as the bass for resource management. Controllng executon of the tradtonal greedy multmeda applcatons n a tme predctable way and performng effcent mode changes for transtons among dfferent qualty levels of applcatons s acheved as experments show. Valdaton results have been presented for multmeda applcatons n hgh load executon condtons. Results show applcaton executon stablty s preserved at all tmes, even durng reconfguraton. The basc budget enforcement mechansms keep deadlne fulfllment and, therefore, applcaton executon stablty. 9. Bblography [1] C. Steger, H. Walder, M. Platzner. Operatng Systems for Reconfgurable Embedded Platforms: Onlne Schedulng of Real-Tme Tasks. IEEE Transactons on Computers, vol. 53, no. 11. ISSN IEEE Computer Socety [2] García-Valls, M., Alonso Muñoz, A., de la Puente, J. A. Tme-Predctable Reconfguraton wth Contract-Based Resource Management. In Proc. 4 th Internatonal IEEE Servce Orented Archtectures n Convergng Networked Envronments. Bradford, UK. May [3] L. Rzvanovc, D. Isovc, and G. Fohler. Integrated Global and Local Qualty-of-Servce Adaptaton n Dstrbuted, Heterogeneous Systems. Internatonal IFIP Conference on Embedded and Ubqutous Computng (EUC-07), LNCS Lecture Note, Tape, Tawan, December, 2007 [4] Chu, H., Nahrstedt, K., CPU Servce Classes for Multmeda Applcatons. In Proc. Of IEEE Internatonal Conference on Multmeda Computng Systems [5] Gabran, M., Hetschel, C., Steffens, L., and Brl, R. Dynamc Behavour of Consumer Multmeda Termnals: Vdeo Processng Aspects. In Internatonal Conference on Multmeda and Expo (ICME). Toko, [6] García Valls, M., Alonso Muñoz, A., Ruíz Martínez, J., Groba, A. An Archtecture of a QoS Resource Manager for Flexble Multmeda Embedded Systems. In Proc. of 3rd Internatonal Workshop on Software Engneerng and Mddleware. LNCS vol [7] Pavan, A., Jha, R., Graba, L., Cooper, S., Carde, I., Gomal, V., Parthasarathy, S., Bedros, S., Real- Tme Adaptve Resource Management. In Computer Journal. Vol 34 (7). Pp ISSN: July [8] Rakumar,R., Lee, C., Lehoczky, K, and Seworek, D. A QoS-based Resource Allocaton Model. In Proceedngs of the IEEE Real-Tme Systems Symposum. December [9] Mercer, C., and Rakumar, R. An Interactve Interface and RT-Mach Support for Montorng and Controllng Resource Management. In IEEE Real-Tme Technology and Applcatons Symposum [10] Davs, R., and Wellngs, A. Dual Prorty Schedulng. In 16 th IEEE Real-Tme Systems Symposum [11] Otero, C., Steffens, L., van der Stok, P., van Loo, S., Alonso, A., Ruz, F., Brl, R., García Valls, M. Ambent Intellgence: Impact on Embedded Systems Desgn. On QoS-Based Resource Management for Ambent Intellgence. Kluwer Academc Publshers [12] García Valls, M. QoS n Multmeda Embedded Systems through Dynamc Resource Management. PhD Thess. Techncal Unversty of Madrd. July In Spansh.