Delay Analysis and Time-Critical Protocol Design for In-Vehicle Power Line Communication Systems

Transcription

1 Delay Analyss and Tme-Crtcal Protocol Desgn for In-Vehcle Power Lne Communcaton Systems Zhengguo Sheng, Daxn Tan, Vctor C.M. Leung and Gaurav Bansal Abstract Wth the emergng automated tasks n vehcle doman, the development of n-vehcle communcatons s ncreasngly mportant and subjected to new applcatons. The use of vehcular power lnes has been a promsng alternatve to nvehcle communcatons because of elmnaton of extra data cables. In ths paper, we focus on the latest HomePlug Green PHY (HPGP) and explore ts opportunty to support tmecrtcal n-vehcle applcatons. Specfcally, we apply Network Calculus to evaluate the worst access and queung delay of varous prorty flows n vehcle bus networks. In order to maxmze the bandwdth utlty and satsfy the end-to-end hard delay requrements, we further propose a bandwdth effcent far rate schedulng and delay senstve traffc shaper. Performance evaluaton supplemented by numercal and smulaton results s also provded to show the advantage of HPGP and the proposed traffc shaper over the exstng ndustry solutons. Index Terms Vehcular power lne communcatons, Home- Plug GP, end-to-end worst delay, traffc shaper, Network Calculus. I. INTRODUCTION In modern vehcles, electroncs has become one of the most mportant components and s expected to ncrease exponentally wth the development of advanced and connected vehcles [1]. Today s vehcles have more than, wres wth the weght of to 5 Klograms. The challenge to ncrease the number of n-vehcle electronc systems has put consderable pressure on automotve communcaton networkng to accommodate ncreasng n-vehcle nformaton flows. Communcaton networks n modern vehcles use several communcaton buses to support control, safety and multmeda servces, etc. Future applcatons, such as advanced drver assstance systems (ADAS), connected and autonomous vehcles, demand a hghly dynamc and msson-crtcal n- and nter-vehcle communcaton envronment. In practce, a number of legacy n-vehcle communcaton buses, such as controller area network (CAN) [] and local nterconnect network (LIN) [3], are hghly applcaton specfc and usually nterconnected n heterogeneous networks va Ths research was sponsored by The Engneerng, and Physcal Scences Research Councl (EPSRC) (EP/P586/1), Royal Socety-Newton Moblty Grant (IE169), Asa Brggs Vstng Fellowshp from Unversty of Sussex and The Natonal Natural Scence Foundaton of Chna under Grant Nos , U15641 and (Correspondng Author: Daxn Tan). Z. Sheng s wth Department of Engneerng and Desgn, Unversty of Sussex, UK. E-mal: z.sheng@sussex.ac.uk. D. Tan s wth School of Transportaton Scence and Engneerng, Behang Unversty, Bejng 1191, Chna. E-mal: dtan@buaa.edu.cn. V. Leung s wth the Department of Electrcal and Computer Engneerng, Unversty of Brtsh Columba, Canada. E-mal: vleung@ece.ubc.ca G. Bansal s wth Toyota InfoTechnology Center, USA. E-mal: gbansal@us.toyota-tc.com. gateways. To cope wth the ncreasng bandwdth demand of future applcatons, a number of recent studes use Ethernet wth IEEE 8.1 audo vdeo brdgng (AVB) [4], [5] as nvehcle network to delver multmeda servces. The on-gong research of AVB towards tme-senstve networkng (TSN) [6] wll further extend ts capablty to support strngent realtme vehcle applcatons. However, the applcaton of dfferent network technologes and pont-to-pont lnks leads to an nflexble network archtecture and a complex cable harness n vehcles, due to wrng complexty that affects mantenance, relablty, weght, and costs, etc. The use of vehcular power lne communcatons (VPLC) s promsng to n-vehcle applcatons. So far, latest research efforts have been focused on the development of LIN, CAN and Ethernet based protocols over power lne [7], [8]. Also n our recent work [9], we adopted a cross-layer approach to ntegrate VPLC physcal layer characterstcs wth medum access control (MAC) and proposed a mult-channel CANbased MAC protocol for VPLC networkng. However, ndustry PLC solutons have been developng for more than a decade. For example, the HomePlug has dfferent specfcatons to support a varety of applcatons, rangng from hgh speed HDTV to low energy smart meter applcaton. The latest HomePlug Green PHY (HPGP) has been promoted by major automotve manufacturers as the common communcaton nterface to facltate the ntegraton of electrc vehcles nto smart grd applcatons, and t wll be capable to support Internet protocols nto vehcles and thus enable connected vehcles. However, HomePlug, whch s desgned for non-crtcal applcatons n home envronment, has never been consdered n tme-crtcal vehcle envronment. Hence there s a lack of understandng of fundamental lmts of standard HPGP n supportng n-vehcle traffc flows wth varous prortes and delay requrements. In ths paper, we are seekng answers to the fundamental queston: whether HPGP can support crtcal delay requrements of n-vehcle applcatons and how well they can be supported? Moreover, consderng that n-vehcle networks are expected to contnue growng n both sze and complexty, we make novel contrbutons to desgn new VPLC protocols and mechansms for managng communcatons and, n partcular, for ensurng end-to-end qualty-of-servces (QoS). By dong that, we frstly employ a determnstc modelng approach, that s Network Calculus (NC) [1], [11], to characterze the worst delay performance of real-tme n-vehcle transmsson usng HPGP. NC has been recently developed as a powerful tool to model and analyze congeston control of swtch ethernet, cellular networks, machne-to-machne and IEEE 8.11 net-

2 works [1] [15]. However, there s no such a work on the analyss of contenton based access protocol for n-vehcle networks. Specfcally, by dervng the arrval and servce processes of prorty flows over a multple access channel, hard delay bounds can be obtaned, whch n turn can help us understand the sutablty of standard HPGP n supportng n-vehcle applcatons. Provdng only access control cannot ensure delay requrement from an end-to-end (EE) pont of vew, partcularly when a message needs to be queued and forwarded from one subsystem to another. The IEEE 8.1 AVB over swtch Ethernet s beng actvely consdered as a promsng soluton to automotve tme-senstve applcatons [4]. Gven the nvehcle flow data (.e., prorty, cycle rate, data rate and sze) and statc topology (e.g., tree-topology), the contenton problem has been shfted to a congeston problem on swtch ports. Snce the AVB reles on a coordnated share network to delver predctable performance, the challenge to ncorporate AVB wth HomePlug for n-vehcle applcatons s to ensure an access method wth bounded delay, whch can be solved by the NC based analytcal results. Moreover, the EE delay of tme-crtcal n-vehcle applcatons are often wth hard requrements, whch cannot be fully satsfed by the current AVB. A new delay-senstve traffc shaper ncorporatng delay deadlne and prorty wll be devsed to ensure the EE delay requrements. The followng summarzes our contrbutons and key results: We analyze the worst delay performance of HPGP over a shared power lne bus usng NC tool. Such obtaned results relatng to prorty, data rate and delay can provde useful gudelnes n determnng the optmal frame length and schedulng strategy for bandwdth effcent HPGP n vehcle envronment. By further consderng the data congeston on swtch ports, we characterze the queung delay for each prorty flow and propose a delay senstve credt-based traffc shaper to ensure the EE delay requrements. A mathematcal framework s also supplemented to analyze the worst delay performance of the proposed protocol under realstc data modelng. The analytcal results show that the HPGP can acheve compettve performance compared wth the exstng ones, and the proposed solutons can mantan a satsfactory hard delay performance for all prorty flows. The rest of the paper s organzed as follows. In secton II, we revew the state-of-arts and emphasze the motvaton and mportance of our work. In Secton III, we descrbe the n-vehcle network topology, delay defnton and data modelng of HPGP. Secton IV provdes the prelmnary result of delay bound obtaned by NC tool, whereas n Secton V, we present the mathematcal analyss of the worst access delay and the proposed prorty-weghted far rate schedulng. We further analyze queung delay n Secton VI and ntroduce the delay senstve traffc shaper to ensure EE delay performance. The performance evaluaton s provded n Secton VII, and concludng remarks are gven n Secton VIII. II. RELATED WORK Vehcular communcatons have been wdely deployed for supportng dverse vehcle applcatons. Most of n-vehcle applcatons wth tme crtcal nature, such as brake and engne controls, are preferrng dedcated wred networks for relable and secure transmsson. Accordng to [16], the growth of automotve electroncs s n the order of n where n s the number of electronc control unt (ECU). Ths paper s motvated by the emergng VPLC technology that can support vehcle communcatons, especally future vehcles wth hghly sophstcated electronc systems, wth reduced data wrng and cost. Understandng the characterstcs of power wres n vehcle as a communcaton channel has been the drve for many measurement campagns [17] [19]. The fndngs show that vehcle power lnes consttute a harsh and nosy transmsson medum wth both tme and frequency-selectve channel, colored background nose, and perodc and aperodc mpulsve nose. The measurements n [], [1] have confrmed that the physcal transmsson of PLC n vehcle s feasble. However, the emergng new challenges come wth a surge n networkng technology (MAC layer and above) to acheve tme-crtcal and relable applcatons, whch s very lmted n the exstng lterature. The tme crtcal applcatons can be fundamentally dfferent from the general applcatons for whch current MAC protocols are desgned []. In wreless sensor networks, most exstng MAC protocols are energy effcent, e.g., IEEE and W-F. These protocols are typcally not sutable for vehcular read-tme applcaton. Although there are advantages to use wreless transmsson [3], n-vehcle wreless devces stll requre connectons to the power source, whch mtgates ths advantage [4]. There are also concerns wth securty n wreless networks, such as eavesdroppng on a n-vehcle network and reverse engneerng to jam false data [5]. Ths partcularly mportant, snce the n-vehcle network s safetycrtcal and t s mperatve to avod securty problems whch lead to dsastrous safety mplcatons. The exstng MAC protocol desgn for VPLC s prmarly based on the legacy n-vehcle bus protocols. LIN, whch has been appled over PLC [3], [7], s a low cost seral bus network used for dstrbuted body control electronc systems n vehcle. It s a sngle master/multple slave archtecture. As t s tme trggered, message latency s guaranteed. However, snce the speed s only Kbps, t s consdered to be most approprate for less tme crtcal applcatons, such as controllng doors or seats. CAN [] s a prorty-based bus whch uses carrer sense multple access wth collson detecton and resoluton (CSMA/CDR). A more recent work [9] proposed a cross-layer approach to multplex tme and frequency varaton of physcal medum nto CAN desgn for VPLC networkng. However, the use of bt-wse arbtraton scheme ntrnscally lmts the bt rate of CAN as the bt tme must be long enough to cover the

3 3 propagaton delay on the whole network. It supports speeds up to 1 Mbps, whch s sutable for real tme control applcatons. The adopton of HomePlug nto vehcle communcatons has been consdered untl recently [6] [8], n whch the authors proposed modfed HomePlug and IEEE 191 protocols for n-car PLC. However, t s not clear what s the fundamental lmt of the soluton n handlng tme-crtcal nvehcle data transmsson. Moreover, gven the complexty of n-vehcle topology, ts EE worst delay analyss has never been nvestgated. There are exstng lteratures n analyzng the congeston delay usng NC. The authors n [9] frstly used the NC to analyze the queung delay of Ethernet swtch networks. Later on, the smlar approach has been extended to the n-vehcle network scenaros and the authors n [3], [31] analyzed the congeston delay of Ethernet and AVB based n-vehcle networks. The authors n [3] dscussed the traffc shaper of AVB n vehcle networks for multmeda servces. However, all of these work are Ethernet based and prmarly focus on multmeda servces n vehcles. Our contrbuton n ths paper s to analyze the worst delay performance of HPGP n vehcle envronment, and further propose new desgns of schedulng and traffc shapng to better utlze the bandwdth resource and guarantee a hard delay performance for msson-crtcal n-vehcle communcatons. III. IN-VEHICLE NETWORK TOPOLOGY AND DATA MODELING A. In-Vehcle Network Topology and Delay Defnton Fg. 1 (a) shows the herarchcal structure of n-vehcle power system, and ts power lne communcaton topology can be generalzed as Fg. 1 (b). The n-vehcle networks are usually composed of a number of systems, such as nfotanment and powertran systems. Each of these systems may also nclude several subsystems whch nclude a number of sensors or ECUs. We dvde the whole n-vehcle networks nto the followng three domans: Subsystem doman: ECU s an embedded system and plays as a hub to control a subsystem n a transport vehcle. Sensor devces are drectly connected to the ECU as source nputs. Hence the star-topology s prmarly consdered n subsystems. Bus-system doman: In order to delver effcent communcatons, multple ECUs are connected over bus-based networks and each ECU may send or receve a message wth a pre-confgured prorty. Cross-system doman: Once a message needs to be sent across domans, a swtch or gateway s needed to forward the message. The swtch s confgured wth prorty queues. Messages wth the same prorty need to be queued followng the Frst-n-Frst-out (FIFO) rule. In ths paper, we focus on the delay ncurred n the transmsson process, ncludng schedulng, transmttng and queung. Consderng the speed of swtch processng s much faster than that of message queung and transmsson, we assume that when one message arrves at the swtch, t wll Parameter N C BP F f() L s A (t) A h (t) α (t) α h (t) σ ρ ρ h R β (t) R T d d max L max N P B R IS R SS η = R IS R SS t acc R β (t) T d DEE TABLE I PARAMETERS USED FOR DATA MODELING Descrpton Number of prorty flow or contendng node n a collson-free scenaro Beacon perod of HPGP Transmsson frequency of prorty Cycle rate of the prorty flow Frame length of short MPDU Arrval flow of prorty flow untl tme t Cumulatve arrval flow wth prorty hgher than untl tme t Arrval curve of prorty flow untl tme t Cumulatve arrval curve of flow wth prorty hgher than untl tme t The maxmum burst data sze of prorty flow The average rate of prorty flow Cumulatve average rate of flow wth prorty hgher than Channel capacty Servce curve of prorty flow on channel Servce rate of prorty flow on channel Latency component of servce curve on channel Access delay of prorty flow The maxmum delay deadlne of prorty flow The maxmum frame length supported by the proposed HPGP The maxmum number of physcal blocks supported by HPGP Idle-slope n the credt-based traffc shaper Send-slope n the credt-based traffc shaper Forwardng effcency of SR class Tme duraton of accumulatng credt Servce rate of prorty flow on swtch Servce curve of prorty flow on swtch Latency component of servce curve on swtch queung delay of prorty flow End-to-end delay of prorty flow be mmedately released on to a queue for forwardng wth a neglgble processng tme [33]. Also, the propagaton delay s neglgble compared wth other delay components. Therefore, the EE delay s defned as D EE = d access + d trans + d queue. (1) It s noted that (1) plays as a bass for the delay analyss and can be appled to more complex network scenaros, e.g., mult-hops networks. B. Data Modelng Table I summarzes all parameters defned n the paper. The cycle length of HPGP (or beacon perod) s defned as C BP = 4 ms, whch s preconfgured by the central coordnator (CCo) to match a cycle frequency of 5 Hz based on the network tme base. {1,,..., N} denotes the prorty level of flows and N corresponds to the lowest prorty. The HPGP defnes 4 prorty levels, thus we have N = 4. The transmsson frequency of a prorty flow can be defned as F = f() C BP, whch means that a new transmsson can

4 4 Throttle poston ( sgnal wres) Man battery Hgh current Battery Juncton Engne Motor etc. Battery montorng system Body Control system ECU Room Lght Door lock Ar temp sensor ( sgnal wres) Speed sensor (3 sgnal wres) 1. Subsystem sensors sensors... sensors Inputs Battery ECU Output Swtch. Bus system... ECU Battery Juncton Wper/washer system Powertran Control system Front/rear lght... ECU ECU... etc. Access delay Transmsson delay Queung delay (a) Wrng dagram of a typcal n-vehcle power system (b) In-vehcle data network topology Fg. 1. Mappng from n-vehcle power wrng harness to data network topology be scheduled every F tme. The f() s the cycle rate of the prorty flow. For example, f we consder a case that a hgher prorty flow needs to be transmtted more frequently, we may have f() =. Snce all flows are sent n a cyclc manner, the least common multple (lcm) of transmsson frequences of all prorty flows s F = lcm{f 1, F,..., F N }. It s noted that the cycle tme of real n-vehcle traffc can be vared from 1 ms up to 5 ms dependng on the applcatons [34]. In ths paper, the predefned traffc pattern of HPGP for all prorty levels can be appled for control traffc class n vehcles [4],.e., 1 1 ms. TABLE II DATA TRAFFIC REQUIREMENTS FOR IN-VEHICLE APPLICATIONS Traffc class Max delay Data rate Control & Management 1 ms [34] Kbps-1 Mbps Safety data (audo) 33 ms [35] 64 Kbps-1.4 Mbps Infotanment data 15 ms [36] 1.5 Mbps The general n-vehcle traffc requrement s categorzed n Table II, whch should be compled by exstng n-vehcle communcaton buses. For example, the LIN bus, whch s prmarly used n the body and comfort domans, can support 8 byte data wth low safety requrement. The CAN bus, whch s used n powertran and drver assstant control domans, can support up to 8 byte data but wth strngent delay and transmsson rate requrements. Therefore, gven a typcal nvehcle frame length of up to 8 byte, we consder the same case [6] where the short MAC protocol Data Unt (MPDU) wth only frame control (18 bts) s employed by HPGP for n-vehcle communcatons purposes. Fg. shows the MAC schedule of HPGP. By further employng the Mn- ROBO transmsson rate of 3.8 Mbps, we can have the total transmsson tme of such a frame as µs, whch ncludes prorty resoluton slots (35.84 µs per slot), an average of 3.5 backoff slots (35.84 µs per slot), one control frame (11.48 µs), one response nterfame space (RIFS) (a default beacon CIFS Fg.. PRS PRS1 Prorty resoluton Beacon perod BACKOFF (contenton wndow) Frame RIFS ACK Data transmsson HomePlug Green PHY CSMA/CA medum access value of 14 µs 1 ), one acknowledgement (11.48 µs) and one contenton nterframe space (CIFS) (a default value of 1 µs). Therefore, the equvalent total frame length of short MPDU can be derved as as L s = 5 bts, whch ncludes the aforementoned protocol overhead and data frame. IV. PRELIMINARIES: ACCESS DELAY BOUNDS OF HPGP A. Arrval curve The actual HPGP medum access s performed cyclc, a successful transmsson depends on ts own prorty and contenton from other flows. Accordng to the defnton n [1], the arrval flow of a message type wth prorty s a cumulatve functon and can be derved as the step functon t A (t) = L, () The cumulatve arrvals wth prorty hgher than can be derved as 1 1 t A h (t) = A (t) = L, (3) =1 F =1 In order to ease the analyss of the determnstc performance of networks, the upper bounded arrval curve (3) can be characterzed by the well known token bucket controller concept whch s defned as α (t) = σ + ρ t, where σ s the maxmum amount of flow that can arrve n a burst and ρ s the average rate of flow. Addtonally, the data arrval rate s 1 Snce the HPGP s a subset of HomePlug standard, the default value can ensure the compatblty wth other HomePlug standard, e.g., AV. F...

5 5 lmted by the lnk capacty whch s denoted as R. Thus the arrval curve can be defned as α (t) = mn {R t, σ + ρ t}, (4) In essence, the arrval curve for a partcular prorty flow can be characterzed by (R, σ, ρ ). In our case, the burst of each prorty flow can be assumed as σ = L, whch means that an mmedate transmsson can happen at t =. The average rate of a flow can be defned as ρ = L F. Consequently, the lnear expresson of cumulatve arrvals wth prorty hgher than can be obtaned as α h (t) = mn {R t, σ h + ρ h t}. (5) where σ h = ( 1) L and ρ h = 1 L j j=1 F j. We can observe that α h(t) Ah (t) when t 675 µs, whch means the derved upper arrval curve holds for almost entre network observaton and thus can satsfy all constrants of an affne arrval curve n network calculus. B. Servce curve After we have the arrval curve for the ncomng flow over a shared channel, we need to determne the servce curve to reflect the communcaton behavor of HPGP. The outgong flow, whch s served by the communcaton channel, can be modeled by a famly of smple servce curve called the rate-latency servce curve β(t) = R (t T ) +. Consder the prorty of ndvdual flow and the non-preemptve nature of transmsson mechansm, we derve the servce curves for each strct prorty (SP) traffc as follows. 1) Hghest prorty: It can always grant channel access to the hghest prorty traffc, unless there s a lower prorty frame n transmsson. Thus the rate-latency curve s β 1 (t) = R 1 (t T 1 ) +. (6) where R 1 = R and T 1 = max{l...n} R whch s the maxmum transmsson latency of a lower prorty data. For example, f we consder to assgn L s for all prorty flows, then T 1 = µs. ) Mddle prorty: Accordng to the SP prncple, any lower prorty flow needs to wat untl all hgher prorty flows are served. So there s an addtonal latency for processng the ntal burst mposed from hgher prorty flows. Accordng to the aggregate traffc modelng of non-preemptve prorty flows [9], the equvalent servce rate s lmted to R 1 j=1 ρ j. Thus the servce curve s derved as β (t) = R (t T ) +. (7) 1 j=1 σj R where R = R 1 j=1 ρ j and T = + T 1. The result can be appled to characterze the second and thrd prorty flows n HPGP. 3) Lowest prorty: The only latency mposed for ths flow s the watng tme to serve all hgher prorty flows, so we can derve the servce curve for the lowest prorty flow as β N (t) = R N (t T N ) +. (8) N 1 where R N = R N 1 =1 ρ =1 and T N = σ R N. We can observe that the servce curve of one flow hghly depends on other flows. Partcularly, wth lower prorty of a flow, ts servce curve tends to decrease. C. Delay bound Theorem 1: The maxmum access delay bound for each prorty flow n HPGP s d T + σ (R R ) (R ρ ) R. (9) Proof : Accordng to the defnton n [1], the delay bound of a flow s the maxmum horzontal devaton between ts arrval curve α and servce curve β. Thus we have d sup{nf{τ : α (t) β (t + τ)}} t d sup{ nf {mn {R t, σ +ρ t τ : t} = R (t+τ T ) + }}, (1) Accordng to mn-plus algebra, the dstrbutvty of sup and nf wth respect to operators (max) and (mn) can lead (1) nto d sup{ nf {R t = β (t+τ)} nf {σ +ρ t τ : τ : t = β (t+τ)}, (11) Snce we know that when t σ R ρ, R t σ + ρ t, we can further derve (11) as d sup { nf {R t = R (t + τ T ) + }} t t τ : sup{ nf {σ + ρ t = R (t + τ T ) + }}, t t τ : (1) where t = σ R ρ denotes the curvng pont of arrval curve. For t T τ, (1) leads to 1 d sup { nf {τ = =1 ρ t + T }} t t τ : R sup{ nf {τ = σ + ( t t τ : =1 ρ R) t + T }}. R (13) Due to the lnear ncreasng and decreasng of nner equatons wth respect to t n (13), the result s obtaned when t = t. It represents the nterval from the tme when a frame reaches the head-oflne and ready for transmsson to the begnnng of the successful transmsson.

6 6 D. Drect applcaton n subsystem doman From Secton III-B, t s not dffcult to observe that the orgnal HPGP can accommodate up to 4 collson-free schedulng,.e., 4 prortes. Although the number of supported con-current transmsson s lmted, t stll can be appled nto some of the subsystem scenaros, such as n Fg. 1 (b) n whch each sensor node may have a few data wrngs connected to the ECU. Table III shows an example of data wrng specfcaton of sensor nodes connected to DTA S8Pro ECU [37]. It s worth notng TABLE III AN EXAMPLE OF INPUT WIRING HARNESS OF S8PRO ECU S8Pro ECU Inputs No. of sgnal wres Speed sensor 3 Cam poston sensor 3 Ar temperature sensor Ol pressure sensor 1 Throttle poston sensor that each of these sgnal wres needs a dedcated data cable. For example, besdes the power cable, the throttle poston sensor needs addtonal two cables to provde throttle poston and dlng sgnals. Gven most of sensor devces requre no more than 4 sgnal cables, the orgnal HPGP can be drectly appled to schedule sensor level communcatons wth ECU usng only power wrng. Result 1: The upper bound of maxmum access delay by usng HomePlug GP for n-vehcle transmsson wth a frame sze up to 8 bytes s.1 ms. Proof : The delay performance s deterorated wth a decreasng prorty level. Therefore, the worst delay performance can be expected when the transmsson s assgned wth the lowest prorty. Accordng to (9), we can derve the maxmum delay as d 4 T 4 + σ 4 (R R 4 ) (R ρ 4 ) R 4 = 3 L s R ρ h + L s ρ h (R ρ )(R ρ h ). (14) can be where ρ h = 3 L s j=1 F. The maxmum value of d 4 obtaned when ρ h and ρ are the maxmum, that s, when F s the smallest. Snce F = f() C BP, we can have all prorty flows wth the hghest frequency of transmsson F 1 = F = F 3 = F 4 = C BP, whch leads to the result. E. Lmtatons of HPGP Result 1 ndcates that HPGP can satsfy the maxmum delay requrement partcularly for control traffc class defned n Table II,.e., 1 ms. However, as observed from Fg. 4, the total bandwdth utlty of HPGP s qute low wth only about 3.4% (.13 Mbps/3.8 Mbps). There s a sgnfcant potental to better utlze HPGP to accommodate more nodes on a sharng bus or cope wth bandwdth demandng applcatons, such as nfotanment and multmeda. Moreover, recall from Secton I, the deployment of new sensors or applcatons n a vehcle has sgnfcantly ncreased the number of ECUs over a sngle bus system. More than 1 ECUs s qute common n today s hgh-speed vehcle networks. Due to the lmtaton of HPGP, a maxmum of 4 prorty flows cannot ensure collson-free transmsson when more than 4 nodes are sharng the sngle bus. In the followng, we wll propose a compatble soluton of HPGP to enable more collson-free communcatons over a sngle bus, and maxmze the bandwdth utlty wthout volatng delay requrements. V. COLLISION-FREE AND BANDWIDTH EFFICIENT TRANSMISSION BASED ON HPGP A. The Proposed Collson-Free Soluton Motvated by the CAN bus that nodes use a n-bt random arbtraton regster (RAR) to avod collson and prortze ther access to the medum, the MAC mechansm of HPGP can thus be converted to support more collson-free transmsson. As shown n Fg., HPGP uses slots for prorty resoluton followed up to 7 slots for backoff n a contenton wndow. All these tme slots are wth dentcal length,.e., µs per slot. In practse, the backoff slots can be merged nto prorty resoluton slots, dependng on the number of nodes on a sngle bus. Hence the total number of prorty can be sgnfcantly ncreased to cope wth a large number of ECUs,.e., 9 = 51 ECUs. For example, f there are 1 ECUs sharng a sngle bus, only backoff slots need to be merged wth the prorty resoluton slots, whch s capable of supportng up to N = 4 = 16 ECUs. Therefore, n the followng, only prorty resoluton slot s consdered before frame transmsson. Table IV shows the updated data model when the proposed soluton s appled. It s worth notng that the proposed soluton does not ncrease the complexty of frame overhead and can coexst wth standard HPGP. TABLE IV UPDATED DATA MODEL FOR COLLISION-FREE TRANSMISSION WHEN N > 4 BASED ON HPGP N No. of prorty slots Total transmsson tme of a frame (µs) Equvalent frame length (L s) 4 < N <= < N <= < N <= Result : Gven a hard delay deadlne of a msson-crtcal transmsson d max, the maxmum frame length that can be supported by the proposed HPGP s defned n (16). Proof : Accordng to (14), the lowest prorty flow experences the longest transmsson delay. Therefore, n order to ensure a hard delay requrement n prorty based access channel, a transmsson should be consdered wth lowest prorty n the worst scenaro. Assume there are a total of N contentng nodes 3, the worst delay performance s when F 1 = F... = F N = C BP, thus we can obtan (15). Snce the maxmum total transmsson rate cannot excess the channel capacty, that s, NLmax C BP R, the maxmum frame length (16) can be obtaned. 3 In ths paper, we use N to denote both the number of prorty flow and the number of contendng node, snce they are dentcal n collson-free scenaros.

7 7 d max = (N 1)xC BP R (N 1)x + (N 1)x C BP (R x)(r (N 1)x) (N 1)d max x (NRd max + (N 1)C BP R)x + R d max = x = NRd max + (N 1)C BP R ± (N 4N + 4)R d max + (N 1) C BP R + N(N 1)R d max C BP (N 1)d max, where x = L max /C BP (15) L max = mn { Nd max RC BP + (N 1)CBP R } ((N )d max RC BP + (N 1)RCBP ) + 4(N 1)d max R CBP 3, RC BP. (N 1)d max N (16) Result can be used to calculate the maxmum number of physcal block (PB) for one physcal protocol data unt (PPDU). Recall from Secton III that the L s s the equvalent protocol overhead and the short MPDU (preamble and frame control), the maxmum number of PBs that can be supported by the n-vehcle HPGP s Lmax L s N PB =. (17) where the PB136 (136 bytes per physcal block) s consdered for Mn-ROBO mode. In prorty based mult-access transmsson, delay and transmsson rate are two mportant crtera to evaluate the effectveness of transmsson schedulng. Hence, n the followng, we explore the nter-relatons between these two and propose a rate-adaptve schedulng scheme. Lemma 1: For each non-hghest prorty flow, the transmsson rate ρ s proportonal to ts maxmum access delay d max, and has R ρ 1 d max. Proof : Accordng to (9), we can derve the transmsson rate as ρ = R (d max L ρ h T1 ) (R ρh ) 1 j=1 L. (18) j where T1 = T 1 when N, otherwse T1 =. ρ h = 1 j=1 ρ j. Lemma 1 tells that there s a tradeoff between the transmsson rate of prorty flow and ts delay performance. Accordng to the defnton of transmsson rate ρ n (4), a large transmsson rate ndcates a hgher frequency of transmsson, whch means that contentons wth other prorty traffc wll be ncreased. Lemma : For each non-hghest prorty flow, the way to ncrease the transmsson rate wthout negatvely affectng ts worst delay performance s to reduce transmsson rate of any flow wth hgher prorty. Proof : Accordng to (18), ρ h s the summaton of hgher prorty transmsson rates. Hence, t s straghtforward to observe that wth a smaller value of ρ h, ρ can be ncreased. For the hghest prorty flow, snce d 1 max{l...n} R, ts transmsson rate ρ 1 has no effect on ts own delay performance, but wll mpact the performance of lower prorty flows. Therefore, combng Lemma 1 and, we conclude that a conservatve rate schedulng for hgh prorty flow s favorable for low prorty flow. Hence we propose the followng prorty-weghted far rate schedulng algorthm to maxmze the bandwdth utlty and mantan delay deadlne by mposng the farness feature nto consderaton. Algorthm 1: Prorty-Weghted Far Rate Schedulng Input: delay requrement D = {d N}, channel capacty R, beacon perod C BP, transmsson frequency f = {f() N}. Output: rate schedulng ρ = {ρ N}. Intalzaton: 1) Identfy the number of con-current transmsson N; ) Rank ther delay requrements wth d d j, when < j; 3) Calculate the prorty weght w = d N =1 d. for (each prorty flow to N) do ρ = R w, L = ρ C BP f(); f L > L max n (16) then L = L max // cope wth schedulng dynamcs; f ρ > ρ (L, d ) n (18) then ρ = ρ (L, d ) // wthout volatng max. delay; Confgure N PB () n (17) to accommodate physcal blocks packagng. VI. QUEUING DELAY ANALYSIS ON SWITCH PORT So far, the worst delay of medum access over a sngle bus has been shown a bounded performance by usng the NC. The calculaton of transmsson delay s straghtforward by havng d trans = L /R. However, message exchange between bus systems are usually needed n vehcle system, and thus

8 8 the delay ssue has been shfted from channel contenton to congeston on swtch port. The IEEE 8.1 Audo Vdeo Brdgng (AVB) [38] s beng actvely consdered as a promsng soluton to automotve tme-senstve applcatons. One of the key mechansms to ensure EE delay performance s to use the traffc shaper to regulate prorty flows on swtch port. Therefore, n ths secton, we characterze the queung delay on swtch and further propose an effectve shapng soluton to guarantee the EE delay performance usng HPGP. A. Traffc shaper n IEEE 8.1 AVB The traffc shapng algorthm n IEEE 8.1 AVB defnes two stream reservaton (SR) classes whch are wth hgher prorty than the tradtonal strct prorty (SP) 4 traffc class. Each SR class defnes both dle-slope R IS whch s the rate of ganng credt, and send-slope R SS whch s the rate of reducng the credt, and has R SS = R IS R, (19) where R s the capacty of the channel. However, dfferent to the standard approach whch s orgnally used for multmeda servces n Ethernet, the number of SR class for the mssoncrtcal vehcle applcaton s determned by the number of nvehcle messages requrng guaranteed EE delay. Thus, we assume the number of SR class s dentcal to N. Result 3: The rato η = R IS R SS defnes forwardng effcency of SR class and has η = { 1, Less burst data transmtted than SP. > 1, More burst data transmtted than SP. Proof : We denote t acc as the tme duraton of accumulatng credt and R IS as the servce rate of a SR class. Accordng to the credt-based traffc shaper polcy defned by the AVB, the total amount of data accumulated and forwarded by a SR class can be expressed as ρ acc = R IS t acc, ρ fwd = R IS t acc η. () When η 1, ρ fwd ρ acc, the total accumulated queung data may not be fully forwarded by swtch and the queue s expected to ncrease. The amount of burst data pushed onto the channel s no larger than SP. When η > 1, ρ fwd > ρ acc, the swtch allows more queung data to be forwarded, partcularly when the SR s wth strngent delay deadlne but more congested data on the queue. The SR wll generate more burst data over the channel. The result shows that the prncple of the traffc shaper s to lmt the amount of burst data pushed onto the channel, whch affects the delay performance of other prorty flows. In the followng, we propose a delay senstve shapng algorthm to dynamcally adjust the forwardng speed of each queue accordng to ts prorty and resdual delay tme. 4 The strct prorty (SP) class has been used to characterze access delay. B. Delay Senstve Traffc Shaper Our objectve s to fnd a strategy that determnes η for each ncomng flow and ensures ts EE delay performance. It s worth notng that both dle-slope and send-slope of a flow also affect the performance of other flows. When multple queues are competng on a swtch port, we expect the overall delay requrements can be satsfed. To reflect the resdual tme budget of a prorty flow and adjust the correspondng servce rate to satsfy ts delay requrement when t arrves at swtch, we defne the forwardng effcency of flow as η = T consumed T consumed =, (1) T resdual T target T consumed The ratonal behnd (1) s to satsfy a global delay requrement by reshapng the servce curves, partcularly for those flows wth lower prorty and resdual delay budget. By keepng the same servce rate R as defned n Secton IV-B for each prorty flow, we defne the dle-slope R IS for prorty as R IS = R, () Hence the correspondng send-slope R SS can be defned as R SS = R IS η. (3) The delay analyss has now been shfted from a contenton problem over a sngle bus to a congeston problem on swtch port. We can stll apply the approach n Secton IV-B to obtan the rate-latency servce curve for each prorty flow. 1) Hghest prorty: The hghest prorty traffc can always be scheduled for forwardng, unless there s a lower prorty frame n transmsson. Thus the rate-latency curve s β 1 (t) = R 1 (t T 1 ) +. (4) where R 1 = R and T 1 = max{l...n} R whch s the maxmum transmsson delay of a low prorty data. ) Lower prorty: For any lower prorty flow usng SR class, ts delay T s hghly related to the delay tme from all hgher SR prorty flows. The tme perod of send-slope RSS can be expressed as t SS = T R + offset R SS, (5) where R = R, RSS = R η and offset = RSS L R s the one maxmum frame that can be transmtted when the credt of s closed to, whch brngs the total credt goes to negatve. Thus, we can obtan the delay 1 T = T 1 + t j SS = T 1 1 T j R j + offset j +, (6) j=1 j=1 Therefore, the servce curve s derved as R j SS β (t) = R (t T ) +. (7)

9 Credt Cumulatve data (bt) L R t T s + r t Maxmum delay d b IS Arrval curve (upper bound) + = R ( t-t) Servce curve (Lower bound) Tme (ms) Maxmum access delay (ms) delay for f(1),f(),f(3),f(4)=1,,3,4 delay for f(1),f(),f(3),f(4)=4,3,,1 rate for f(1),f(),f(3),f(4)=1,,3,4 rate for f(1),f(),f(3),f(4)=4,3,,1 6 4 Average transmsson rate (Kbps) 1 R IS R SS 1 R IS RSS 3 R IS 3 RSS ( R, R IS ) SS Prorty level Fg. 4. Maxmum delay and transmsson rate for orgnal HPGP Output of swtch 1 T max{ L, > 1} R Fg tss L L 1 1 L1 tss L1, max L L L, max L3 3 tss L 3, max Queung delay of SR based transmsson on swtch Tme (ms) 3) Maxmum queung delay: The derved Theorem 1 can stll be appled to derve the bounded queung delay for each prorty, thus the queung delay bound s d T + σ (R R ) (R ρ ) R. (8) Fg. 3 llustrates the SR based transmsson on swtch port. It s noted that the SP based traffc class can coexst wth SR class, and serve prorty flows whch mss the delay deadlne. In such a case, a best-effort approach wll be adopted. C. End-to-end Delay Combne the access, transmsson and queung delay that we have analyzed so far, the worst EE delay of prorty can be derved as D EE d + L R + d, (9) The result can be further generalzed to a more complex network scenaros wth multple bus systems crossng the same swtch or cascaded networks. Thus the worst EE delay can be derved as n ˆD EE (d h + L R + ( d h η = max{η k }, k = 1...m) ). h=1 (3) where n s the number of hops, each hop s composed of a communcaton bus and a swtch. m s the number of bus systems crossng one swtch. The flows wth the same prorty are scheduled on the same queue when they arrve at the same swtch port. By choosng a maxmum η among dfferent systems, the lower bound servce curve can be guaranteed for all prorty flow crossng the same swtch. VII. PERFORMANCE EVALUATION In ths secton, we provde evaluaton results usng the system parameters provded n Secton III. A. Orgnal HPGP Fg. 4 shows the maxmum delay and transmsson rate for each prorty flow, respectvely, wth two sets of cycle rates and dentcal frame length,.e., L = L s, 1...N. The general delay performance of all flows algns wth Result 1. We can also observe that the delay performance s negatvely affected by the decreasng prorty. Moreover, f hgher prorty flows tend to ncrease ther cycle rate (or reduce ther transmsson rate), the delay of lower prorty flows wll be mproved, whch s relevant to Lemma. We also compare the maxmum delay bounds (ncremented by transmsson delay) among four major solutons obtaned usng NC n Fg. 5(a). In the comparson, both LIN and CAN based solutons are usng the dentcal data sze of 8 byte and 4 prortes. The basc cycle length are the same as C BP = 4 ms, each prorty flow can be sent at a rate of f() C BP, where f() s an nteger value chosen by flow. Accordng to the standard specfcaton, the LIN bus [3] uses the master-slave perodcal transmsson wth date rate of Kbps, whereas the CAN [] bus uses prorty-based contenton detecton and resoluton (CDR) wth date rate of 5 Kbps. The latest Multchannel CAN (M-CAN) [9] s based on the hgh-speed CAN (5 Kbps) but wth two frequency selecton. Ther delay bounds are derved n Appendx A. The smulaton s also supplemented by havng 4 collson-free nodes over a sngle bus wth dfferent prorty, randomly selected cycle frequency and destnatons. The result s collected as the worst delay over 1 beacon perods. It can be seen that the HPGP shows clear advantage over the LIN, but wth compettve performance aganst CAN based protocols. Snce HPGP ntroduces extra overhead compared wth other solutons, Fg. 5(b) shows a far comparson by averagng the delay performance,.e., delay

10 Maxmum delay (ms) Lowest prorty Hghest prorty Max. 3.4ms Smulaton result of the worst delay Total number of prorty slots needed 3 1 Collson free Collson Maxmum access delay (ms) No. of prorty slots needed 6 4 Maxmum access delay (ms) LIN Orgnal HPGP CAN M CAN Total Number of Nodes (a) Delay performance for transmttng one 8-Byte control data: LIN (18 bts), Orgnal HPGP (5 bts), CAN and M-CAN (136 bts) Fg. 6. No. of prorty slots needed and ts maxmum access delay under dfferent network sze Maxmum delay per bt (ms) Max..8ms Smulaton result of the worst delay LIN Orgnal HPGP CAN M CAN (b) Average delay performance for transmttng one 8-Byte control data Fg. 5. Maxmum delay comparsons for 4 prortes tme per bt. The HPGP shows the superor performance than CAN based protocols. Table V shows the result of the scheduled transmsson rate and achevable delay performance by applyng Algorthm 1 for orgnal HPGP and CAN, respectvely. In ths example, we smply confgure F 1 = F = F 3 = F 4 = C BP. As can be seen, the derved result can keep the actual delay performance wthn the targeted delay deadlne. Moreover, by adjustng the payload sze, adaptve transmsson rates can be acheved to support more data type, e.g., multmeda, n order to maxmze the bandwdth utlty. The farness ndex (ρ/d target ) ndcates that the proposed soluton can successfully mantan a global farness by allocatng more bandwdth to low prorty flows. Moreover, we should note that gven the same prorty and delay requrements, HPGH can support much hgher transmsson rate and more payload than the CAN soluton. B. Collson-Free HPGP Fg. 6 shows the relatons between the number of nodes on a sngle bus, prorty tme slots needed and ther maxmum access delay performance. All nodes are transmttng usng the dentcal frame length,.e., L = L s, 1...N. The result can be used to determne the maxmum number of collson-free nodes and ts prorty slots confguraton when delay requrement s known. We further compare the maxmum delay bounds (ncremented by transmsson delay) among the same solutons n Fg. 7(a). The benchmark solutons are usng the same data model and cycle rate assumed n Fg. 5(a). Accordng to Table IV, the collson-free HPGP for N = 1 uses L s = 96 bts. We notce that the worst delay of the lowest prorty flow usng the proposed collson-free HPGP s worse than that of CAN bus, whereas n Fg. 5(a), such delay s better than CAN. The result ndcates that due to the large overhead and exchange complexty of HPGP, ts performance tends to worse than CAN when the number of node ncreases over a sngle bus. However, the average delay performance of collson-free HPGP n Fg. 7(b) s stll the best among all solutons. By further applyng the Algorthm 1 nto the collson-free HPGP and CAN to cope wth more ECUs sharng on the same bus, Table VI shows the optmzed transmsson rate and delay performance. It s clear that the proposed far schedulng works well for both collson-free HPGP and CAN. It s also nterestng to observe that for prorty 1 and, the maxmum payload of HPGP s 16 bytes, whch means that only control frame s used for data transmsson. The result s also algned wth the general practse that tme-crtcal control messages are usually assgned wth hgher prorty but small data sze, whereas for less-crtcal data transmsson, hgh data rate and large packet sze s allowed but wth lower prorty. The data rate and maxmum payload spreads even wder when more prorty flows are transmttng, HPGH stll acheves a better performance than the CAN soluton.

11 11 TABLE V PRIORITY-WEIGHTED FAIR RATE SCHEDULING FOR ORIGINAL HPGP AND CAN Orgnal HPGP CAN Prorty level Targeted access delay (ms) Acheved delay (ms) Transmsson rate (Mbps) Maxmum payload (Byte) Bandwdth utlty 94.% (3.58 Mbps/3.8 Mbps) 93.6% (34 Kbps/5 KBps) Jan s farness 97.16% 97.15% TABLE VI PRIORITY-WEIGHTED FAIR RATE SCHEDULING FOR COLLISION-FREE HPGP AND CAN Collson-Free HPGP CAN Prorty level Targeted access delay (ms) Acheved delay (ms) Transmsson rate (Mbps) Maxmum payload (Byte) Bandwdth utlty 97.8% (3.7 Mbps/3.8 Mbps) 97.% (43 Kbps/5 Kbps) Jan s farness 96.3% 96% C. End-to-end Delay Analyss In ths secton, we further ncorporate queung delay nto analyss. We assume that a bus system s composed of 7 prorty nodes, and bus systems are connected by swtches. All nodes n a bus are transmttng usng the dentcal frame length,.e., L = 16 bts, 1...N, accordng to Table IV. In order to derve the worst delay, the transmsson frequency s assumed to be the same for all prorty flows, that s, F = C BP, 1...N. In order to compare and analyze the access and queung delay, we start wth a smple scenaro where only one bus system s drectly connected wth one swtch, e.g., Fg. 1 (b). Fg. 8 shows the breakdown of EE delay when a frame s transmtted over the bus, arrved and forwarded by the swtch. It shows that the prorty and 3 usng the proposed tme senstve shaper on swtch have a lower delay than SP over the bus, whereas for the prorty 4-7, such delay s worse than SP. Ths s because after the SP transmsson over the bus, the prorty flows and 3 have lower resdual delay budget compared wth other prortes. Hence, accordng to the proposed delay senstve shaper, t wll allocate more transmttng tme (wth a relatvely small send-slop) when prorty and 3 are engaged for forwardng. Such adaptve changes wll ncrease the delay of lower prorty flows, however, the proposed tme senstve shaper can stll mantan ther worst delay performance wthn the deadlne. Furthermore, because the dynamc adjustment of traffc consders both consumed and resdual delay budgets, the proposed soluton can mantan a global farness among all prorty flows n order to avod mssng the deadlne of any prorty flow. The Jan s farness ndex (d acheved /d target ) n Fg. 8 can reach to 9.46%. Fg. 9 further compares the EE delay performance by usng dfferent shaper solutons on swtch port, such as SP, IEEE 8.11 AVB [38] 5 and weghted round robn [3]. It shows that under the same network assumpton and delay deadlne, the proposed soluton s the only one that can manage to keep the EE delay wthn the target delay deadlne. Table VII also shows the statstcs of delay performance. The value wth * ndcates the volaton of delay deadlne. TABLE VII STATISTICS OF ACHIEVED END-TO-END DELAY PERFORMANCE Prorty level Targeted EE delay (ms) Proposed delay senstve shaper (ms) SP (ms) * AVB (ms) * 6.5* RR (ms) 8* 8.6* 9.* 9.8* 1.5* In order to show the delay performance n a more complex n-vehcle network scenaro, we consder a network topology n Fg. 1 n whch the bus network A s transmttng to D, B s transmttng to A, and C s transmttng to D, smultaneously. Transmttng nodes n both B and C are wth the same delay deadlnes, whereas A s wth more relaxed deadlne due to the mult-hop transmsson. The result n Fg. 11 shows that the actual delay of all flows can be mantaned wthn the deadlne by usng the proposed shaper method. It s also nterestng to observe that the system C performs worse than B although they have the same delay constrants. Ths s because the network C s competng wth A on swtch when A has relatvely lower resdual budget compared tself on swtch 1, thus the proposed delay senstve shaper allocates more transmsson tme for A on swtch, whch leads to a worse delay performance for C. However, B has the advantage to compete wth A on swtch 1 when both A and B have adequate delay budget. 5 In the standard AVB, only two SR classes are consdered and lower prorty flows are usng SP.

12 1 Maxmum delay (ms) Lowest prorty Hghest prorty Max. 75.6ms Smulaton result of the worst delay End to end delay (ms) Targeted delay deadlne SP Proposed delay senstve shaper AVB shaper Round robn 4 LIN Collson Free HPGP CAN M CAN (a) Delay performance for transmttng one 8-Byte control data: LIN (18 bts), Collson Free HPGP (96 bts), CAN and M-CAN (136 bts).1 Fg Prorty level Comparson of end-to-end delay usng dfferent traffc shaper Maxmum delay per bt (ms) Lowest prorty Hghest prorty Maxmum.7ms Smulaton result of the worst delay LIN Collson Free HPGP CAN M CAN Fg. 1. B Delay deadlne for Bus AàD Prorty Deadlne (ms) A Swtch 1 Swtch Delay deadlne for Bus BàA, CàD Prorty Deadlne (ms) A mult-hop and cross-doman scenaro wth traffc delay constrants C D (b) Average delay performance for transmttng one 8-Byte control data End to end delay (ms) Fg. 7. Maxmum delay comparsons for 1 prortes Targeted delay deadlne Acheved delay Queung delay: Delay senstve shaper Access delay: Strct prorty (SP) End to end delay (ms) Targeted delay deadlne for A Acheved delay of A Targeted delay deadlne for B and C Archeved delay of B Archeved delay of C Fg Prorty level Breakdown of end-to-end delay n a sngle bus and swtch scenaro Prorty level Fg. 11. End-to-end delay comparson n a mult-hop and cross-doman scenaro usng the proposed delay senstve shaper

13 13 VIII. CONCLUSIONS We have shown that HPGP s able to meet hard delay requrement of n-vehcle communcatons. Even n the condton of hgh workload, the performance of the ntegrated desgn of contenton and congeston control s adequate and promsng for n-vehcle power lne networks. Compared wth the ndustry solutons, the HPGP based approach s promsng to replace the legacy LIN and low/medum speed CAN. The results can be used to help vehcle and networkng engneers desgn HPGP-based msson crtcal applcatons and future network nfrastructure n vehcular envronments to ntegrate every object (e.g., n-vehcles sensors, passengers smart phones, nfrastructures) and form an ntellgent transportaton system. The n-vehcle communcatons dscussed n ths paper can be used to connect n-vehcle components wth the external world, whch wll ncrease the support of human and machne communcatons n connected vehcles. A. LIN APPENDIX A DELAY CALCULATION FOR EXISTING SOLUTIONS It s a sngle master/multple slave archtecture. One node, termed the master, possesses an accurate clock and drves the communcaton by pollng the other nodes, the slaves, perodcally. A master can handle at most 15 slaves (there are 16 dentfers by class of data length). As t s tme trggered, message latency s guaranteed. The transmsson rate s Kbps and the data length s 8 bytes. Sync Break Message Header Sync Feld PID Feld 14 bts 1 bts 1 bts Message Response Data 1... Data n Checksum 1-8 bts 1 bts Fg. 1. Tme schedule of LIN bus transmsson [3] Fg. 1 shows the tme schedule for transmttng a LIN message. The message header takes 34 bts (14 bts+1 bts+1 bts) and the response takes 74 bts (8 8 bts+1 bts). The total number of bt s 18 bts (34 bts+74 bts). Therefore, the transmsson delay s: D t = 18 = 5.4 ms, (31) Kbps A tme reserve of up to 4% s gven for transmsson of a LIN message, that s, nterbyte space. Hence the delay for transmttng one message s D t = D t 1.4 = 7.56 ms. (3) Therefore, the maxmum delay for the frst scheduled node (or wth the hghest prorty) s DLIN h = 7.56 ms, whereas the maxmum delay for the last node (or wth the lowest prorty N) s DLIN l = N 7.56 ms. B. CAN CAN s a prorty-based bus whch allows to provde a bounded communcaton delay for each message prorty. The MAC protocol of CAN uses CSMA/CDR wth bt by bt nondestructve arbtraton over the ID feld (Identfer). In our case, we consder that the dentfer s coded usng 11 bts (CAN.A) and t also serves as prorty. Hgher prorty messages always gan access to the medum durng arbtraton. The data sze s also consdered as 8 bytes and transmsson rate s 5 Kbps. Fg. 13. CAN frame structure [] Fg. 13 shows the CAN frame structure, the equvalent maxmum frame sze of CAN s 136 bts (13 bts maxmum frame sze plus 6 bts carrer sensng tme). Snce CAN s also a prorty based protocol, we can use the smlar result from Theorem 1 and obtan the delay performance as follows. The data length s L = 136 bts, the cycle rate for all prorty flows s set at ts maxmum F = 4 ms, and R = 5 Kbps. Therefore, the maxmum delay for the hghest prorty node s DCAN h = L R = 136 = 1.88 ms. (33) 5 Kbps The maxmum delay for the lowest prorty node depends on the number of prortes N, and can be derved as D l CAN = (N + 1)L R ρ h = (N + 1) Kbps (N 1) 136/4 ms. (34) It s worth notng that CAN bus has 11 prorty bts, whch means that t can theoretcally cope wth 48 prorty levels. C. Mult-channel CAN [9] The result of Mult-channel CAN (M-CAN) can be derved drectly from the standard CAN bus. We consder the hghspeed CAN wth a total transmsson rate of 5 Kbps. Snce the M-CAN employs two frequency channels characterzed by power lnes, the maxmum delay results can be obtaned as DM CAN h = L R = 136 =.544 ms. (35) 5 Kbps It s noted that the effectve data rate for each channel s R = 5 Kbps and the hghest prorty flow (wth the mnmum delay) can have the prvlege to domnate a sngle channel. The maxmum delay for the lowest prorty node depends on the number of prortes N, and can be derved as DCAN l = NL N 136 R ρ h = 5 Kbps (N ) 136/4 ms. (36) Snce there are always two channels avalable, the worst delay happens when up to N 1 nodes sharng a sngle channel.