Deterministic protocols for real-time communication in multiple ...

S. Norden et al. / Computer Communications 22 (1999) 128–136 131Table 1Node and channel status table (MDCR)Time N 1 N 2 N 3 N 40 (5, 17) (2, 6) (2, 9) (2, 12)1 C C C C2 N (5, 17)3 X (5, 17)4 X (5, 17) D (2, 6)5 X (5, 17)7 X (5, 17) D (2, 9)8 I I9 N (2, 12)10 X (2, 12)11respect to its predecessor, and modifying the laxity of itssuccessor. Messages with negative laxity are removed fromthe queue.The LDCR protocol consists of three phases, namely,contention mode, collision resolution (CR) mode, andleast laxity first (LLF) mode, which are described below.This combination of CR mode and LLF mode defines anepoch in the LDCR protocol as contrasted to the DCR preorder and MDCR protocols wherein an epoch is the CRmode alone.1. Contention mode (when channel is idle)(a) Each node examines the message at the head of itsqueue. If the laxity of the message is negative, themessage is dropped.(b) Otherwise, it attempts to transmit notifier for themessage.(c) If the notifier transmission is successful, themessage is transmitted.(d) If a collision occur during notifier transmission, allnodes enter into CR mode by traversing the CR tree inpre order.Table 2Node and channel status table (LDCR). C: Collision; N: Notifier; X: Transmit;D: Drop; L: Laxity; I: IdleTime N 1 N 2 N 3 N 40 (5, 17) (2, 6) (2, 9) (2, 12)1 C C C C2 N (5, 17)3 Defer (L 1 ˆ 9) C C4 (L 1 ˆ 8) N (2, 6)5 (L 1 ˆ 7) X (2, 6)7 (L 1 ˆ 5) N (2, 9)8 X (2, 9)10 (L 1 ˆ 2) N (2, 12)11 X (2, 12)12 LLF mode – (L 1 ˆ 0): X (5, 17)172. Collision resolution mode(a) When a node n i gets its turn in the CR mode, ittransmits its notifier. Thus every other node is informedof the message requirements of node n i(b) If the laxity of a message (first message at queue ofn i ) is less than a threshold (but non-negative), then themessage is transmitted, else the message is deferred andper order traversal continues. It two or more messageshave the laxity less than or equal to the threshold value,the preference is given to message with shorter servicetime. This minimizes the time that the channel isblocked, thereby improving the chances of successfultransmission for subsequent messages.(c) Even after the CR tree is completely traversed, ifsome deferred messages are still to be transmitted, theprotocol enters into the LLF mode.3. LLF mode(a) In the LLF mode, all the deferred messages aretransmitted, based on the least laxity order of messagesamong nodes. This phase is required to enable thosemessages, that arrived in the current epoch, to be transmittedbefore the next epoch. By doing this, the overheadincurred as result of collision between messages oftwo different epochs is eliminated.(b) If all the messages are either transmitted or dropped,the next epoch begins.Note that the threshold value mentioned in Step 2(b) isfixed, in our protocol, to be one. The importance of thisvalue, is brought out in a subsequent section, when comparingthis protocol with another representative protocol.3.4.2. Illustrative examplesIn this section, we demonstrate the effectiveness of theLDCR over MDCR with an illustrative example. The exampleconsiders a LAN with 4 nodes. Tables 1 and 2 depict theworking of MDCR and LDCR, respectively. The first entry(at time 0) in these tables is the initial status of the queue ateach node (each node has a single message to transmit). Forexample, node N 1 has a message having deadline of 17 andrequiring 5 slots for transmission. In this example, the preorder traversal of CR tree (binary tree), as shown in Fig. 1, isin the order of N 1 ,N 2, N 3, and N 4.Let us trace a few steps in the MDCR protocol shown inTable 1. At time 1, all nodes attempt to transmit their notifierwhich results in collision, thus all nodes enter the CRmode. At time 2, N 1 (root of the CR tree) transmits itsnotifier, and proceeds to transmit its message from timeslot 3 onwards, for 5 time slots. Thus all nodes back offfor a period of 5 slots. Even though the laxity of thismessage is very large (10), compared to the laxity of othermessages, it is still transmitted. As result, the other nodes allend up having negative laxity, when they get their turn. Bytime 8, two nodes in the left subtree (N 2 and N 3 ) would droptheir messages, as their laxities become negative at the end

132S. Norden et al. / Computer Communications 22 (1999) 128–136Fig. 1. Mapping of nodes into vertices of CR tree.of slot 4 and 7, respectively. At time 9, the node in the rightsubtree (N 4 ) will transmit its notifier successfully, and transmitsits message successfully before the deadline.For the LDCR protocol, the threshold used for defermentis taken to be 1. The behaviour of LDCR protocol is similarto MDCR up to time 2, i.e., after transmission of the notifierof message at N 1 . After transmission of the notifier, theLDCR computes the laxity for this message and finds thatthe laxity is greater than threshold, hence defers themessage. At time slot 4, N 2 transmits its notifier, and findsthat the laxity of the message is zero, hence the message istransmitted immediately. The protocol proceeds in thismanner.From the above example, it can be noted that the LDCRprotocol transmits all the messages successfully, while theMDCR protocol can transmit only 50% of the messages.The key aspect that contributes to the improved performancein LDCR is the deferment of the message at N 1 ,which has a large laxity. This allows more critical messagesat N 2 , N 3 , etc., to be transmitted before their deadlines.4. Simulation studiesTo study the effectiveness of the proposed protocols, wehave conducted extensive simulation studies. For eachsimulation run, 10000 messages were generated for theentire system. For the performance results, 95% confidenceintervals were obtained. The performance metrics used, andthe simulation model are defined below:4.1. Simulation model and parameters• N: Number of nodes on the network.Table 3Simulation parametersParameter Explanation Value when varied (fixed)N Number of nodes 5…30 (10)M Average message length 7…20 (20) slotsa Laxity parameter 2…25 (10)Load l M N 0.1…1 (0.6)P/Nt Packet to Notifier ratio 2…10 (10)• M: Average message length (or service time).• a: Laxity parameter which decides the deadline ofmessages, directly proportional to deadline. The deadlineis uniformly chosen in the interval [C i ,a*C i ].• l: Mean message arrival rate at a node. Message arrivalat each node follows Poisson distribution with mean arrivalrate l.• L: Load on the network is defined as the product ofnumber of nodes (N), mean message length (M), andthe arrival rate, i.e., L ˆ (l * M * N).• (P/Nt): Packet to notifier ratio. As mentioned earlier, slotis a basic unit of transmission in which one packet can betransmitted. We fix a normalized value of packet slot tobe 10 time slots, and from this ratio, we can determinethe number of slots used by transmission of a notifier,relative to this normalized value of a packet slot.The simulation parameters and their ranges are given inTable 3.4.2. Performance metrics• Success Ratio (SR): This is defined as the ratio of thetotal number of messages transmitted successfully to thetotal number of messages that arrived in the system. TheSR is an important metric which reflects the throughputof the network.• Effective Channel Utilization (ECU): This is the ratio ofthe time slots used for successful transmission to thenumber of time slots that elapsed until all messageswere transmitted or dropped. A higher value of ECUwould imply that the channel utilization, as result ofsuccessful message transmission, is large compared tothe net overhead as result of collision and notifier transmission.• Normalized Transmission Length (NTL): This is theratio of the mean length of the transmitted messages tothe mean length of the generated messages. The closer itsvalue to one, the less bias towards longer or shortermessages. In other words, when the NTL offered by aprotocol is one, the protocol behaves independent ofmessage service time.4.3. Results and discussionIn this section, we compare the performance of theproposed protocols (MDCR and LDCR) with a recentlyproposed protocol called PBCSMA. The PBCSMA protocolis chosen for comparison because it can support multipacketmessages, and has been reported to perform better than theVTCSMA and CSMA based protocols [15]. It is a modifiedversion of p-persistent CSMA with support for differentpriority levels of traffic. Note that the MDCR, LDCR, andPBCSMA are best effort protocols, which means that theyadmit all the messages arriving in the system, withoutguaranteeing that these messages will be transmitted

S. Norden et al. / Computer Communications 22 (1999) 128–136 133Fig. 2. Effect of load on (a) SR,(b) ECU,(c) NTL.successfully. In the simulation plots, these protocols arelabelled as with an extension BE to indicate ‘‘Best Effort’’.For the sake of completeness, we describe the PBCSMAprotocol as given below:The PBCSMA protocol• A message is characterized as critical, if its laxity is lessthan a predefined threshold, otherwise it is classified asnon-critical.• Transmission of a critical message begins with the broadcastof a notifier, similar to our protocol.• When a new message arrives and is classified as eithercritical or non-critical, and the channel is idle, themessage is sent. Otherwise (i.e., the channel is busy),if the message currently being transmitted is not critical,it is preempted to allow a critical message to besent.• Transmission of a non-critical message from a node isnot possible as long as the channel is busy. Also, themessage is not sent right after the channel becomesidle. The node waits for one slot, and if the channelremains idle, the message is sent.• Following a collision, a non-critical message issuspended for the duration of a slot, and if that slot isnot occupied by a critical message, the non-criticalmessage is retransmitted with probability P i .• If a critical message collides, it is retransmitted immediatelywith probability P i .From the Figs. 2(a)–5(a), it can be observed that the SRoffered by LDCR is better than the other two protocols ofwhich the MDCR is better than PBCSMA. From Figs. 3(b)–5(b), the ECU obtained using LDCR is higher (better) thanthe other two because of its SR. Similarly, the NTL offeredby LDCR is closer to one as compared to the other protocols.The reasons for these observations are discussedbelow:• LDCR is better than PBCSMA: The reasons, why LDCRis an improvement over PBCSMA, are as follows. In thecase of the notifier of a critical message colliding with thenotifier transmission of another critical message,PBCSMA will retransmit the interrupted message withcertain probability. When the threshold is large, onecould have several critical messages which require tobe transmitted. Repeated attempts at retransmission withoutproper arbitration in the CSMA fashion will lead toseveral collisions utilizing several slots which in turnleads to missing of message deadlines. Whereas inLDCR-BE, by forcing the threshold for critical messagesto be one, the protocol restricts the number of criticalmessages; in the event of collision, the arbitration isdone as per the pre order traversal of the CR treeFig. 3. Effect of a on (a) SR, (b) ECU, (c) NTL.

134S. Norden et al. / Computer Communications 22 (1999) 128–136Fig. 4. Effect of N on (a) SR,(b) ECU,(c) NTL.allowing one of the nodes to transmit in subsequent slotswithout wasting the bandwidth. Further, in LDCR, whentwo critical messages have laxities less than the thresholdvalue, the smaller message is transmitted whichimproves the chances of subsequent messages. AsPBCSMA is a preemption based protocol, if a non-criticalmessage is preempted as result of the presence ofseveral critical messages, the assumption made in [15]is that the non-critical message will have a large enoughdeadline so as to still be transmitted after all the criticalmessages. This will not hold especially when the thresholdis large and there are a large number of criticalmessages waiting for channel access. The subsequentdelay incurred by the non-critical message may make itcritical, leading to degradation in the protocol as thenumber of critical messages steadily increases. Anotherinteresting observation about PBCSMA that reinforcesthe above point, also made by the author in [15], is thatthe SR will degrade when the threshold is increasedbeyond a certain value, as the number of criticalmessages (with varying degree of criticality) increases.This results in increased number of collisions betweenthese messages, thereby reducing the SR. The increasednumber of collisions will also result in a lower ECUvalue. In addition, it may also result in priority inversion,as high laxity (non-critical) messages would contend forthe channel along with low laxity (critical) messages.The increased number of collisions will also resultin a lower ECU value. This situation will not arisein LDCR, as it defers the non-critical messages to aseparate mode (LLF), thus avoiding collisions betweenmessages with high and low laxities. This will reducethe number of overall collisions. These deferredmessages are transmitted in the LLF mode, usinglaxity based ordering. This systematic way of collisionresolution and message deferment results in improvedSR and ECU. The superiority of the LDCR protocolover PBCSMA, can be clearly seen, from all the simulationgraphs.• LDCR is better than MDCR: The relatively poor performanceof MDCR is owing to its blind transmission ofmessages as per the static position of nodes in the CR treewithout taking into account the laxity of messages amongthe nodes. Thus higher priority (lower laxity) messageswill be treated in the same way as lower priority (largelaxity) messages. This will lead to missing of messagedeadlines. Further, a large number of messages with tighterlaxity, having small service times, could be dropped ifa message with larger laxity, and having larger servicetime, is transmitted. This scenario is brought out by thehigh NTL values, shown by the MDCR protocol, in Figs.2(c)–5(c). From the Figs. 2(a)–5(a), which study theFig. 5. Effect of P/Nt ratio on (a) SR,(b) ECU,(c) NTL.

S. Norden et al. / Computer Communications 22 (1999) 128–136 135effect of the different input parameters, on SR, we canconclude the following:• SR vs Load: In Fig. 2(a), as load increases, there is apredictable fall in SR values for all the three protocolsas more number of messages are generated and morenumber of collisions, thus reducing SR.• SR vs a: In Fig. 3(a), as the laxity factor increases, thedeadline associated with every message increases,resulting in an increase in the number of messagesthat are transmitted successfully, hence increasing SR.• SR vs N: In Fig. 4(a), as the number of nodesincreases, the SR falls. This is the result of an increasein the number of messages, as well as a larger epochtime, which leads to more messages missing theirdeadlines.• SR vs P/Nt: In Fig. 5(a), as P/Nt is decreased, theperformance will fall expectedly, as a smaller ratioimplies a larger overhead as result of notifier transmission,compared to actual packet transmission.An interesting observation from the graphs is that theECU is not always influenced by the SR. Normally, onewould expect that as SR decreases, the ECU will alsodecrease since less number of slots are used for successfultransmission. Sometimes, this relation may not hold wheneven if less number of messages are transmitted, thecombined service times may exceed those of the droppedmessages, which will still increase the ECU (see Fig. 2(a)and (b)). This explanation is supported by the increasingNTL values (in Fig. 2(c)) with increasing load, for all theprotocols, implying that messages with larger service timesare transmitted.5. ConclusionsIn this article, we have identified the need for real-timeprotocols to support multipacket real-time message transmissionwhich is the form of communication in a typicalreal-time system. We have highlighted the inadequacy ofthe existing protocols to support this requirement. As a solutionto the problem, we have proposed protocols with besteffort service for multiple-access networks, namely, theLDCR and MDCR protocols. The MDCR is an extensionof DCR protocol while the LDCR protocol is based on theconcept of message deferment.We have demonstrated the effectiveness of our best effortprotocols through simulation, for a wide range of parametersfor multiple performance metrics, by comparingthem with a protocol (PBCSMA) recently proposed forthe same problem. Our simulation results reveal that theLDCR protocol performs better than the PBCSMA andMDCR for all the three performance metrics – successratio, effective channel utilization, and normalized transmissionlength. We are currently studying the effect of dynamicallyassigning more than one vertex in the CR tree to anode, allowing additional messages to be sent in the sameepoch.References[1] K. Arvind, K. Ramamritham, J.A. Stankovic, Window MAC protocolsfor real-time communication services, Technical Report, Universityof Massachusetts, USA, 1992.[2] J.I. Capetanakis, Tree algorithm for packet broadcast channels, IEEETrans. on Communications 27 (10) (1979) 1476–1484.[3] D.E. Comer, D.L. Stevens, Internet working with TCP/IP-Volume 2,Prentice-Hall International Inc, Englewood Cliffs, NJ, USA, 1994.[4] Intel Corp., CSMA/DCR deterministic access LANs, PresentationViewgraphs, Folsom Microcomputer Group, Feb. 1988.[5] K.H. Kim, C. Serro, Robustness of real-time local area network protocols,Computer Communications 20 (1997) 169–176.[6] L. 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Finkel, A Reservation-based CSMA protocolfor integrated manufacturing networks, IEEE Trans. on Systems, Manand Cybernetics 24 (8) (1994) 1247–1257.[13] K. Ramamritham, Channel characteristics in local-area hard real-timesystems, Computer Networks and ISDN Systems 13 (1987) 3–13.[14] J.A. Stankovic, K. Ramamritham, Hard real-time systems, ComputerSociety Press of IEEE, 1730, Massachussets Avenue, Washington,DC, 1993.[15] O. Ulusoy, Network access protocol for hard real-time communicationsystems, Computer Communications 18 (12) (1995) 943–948.[16] V. Upadhya, Design and Analysis of Real-time LAN protocols, M.S.Thesis, Department of Computer Science and Engineering, IndianInstitute of Technology, Madras, Jan. 1996.[17] W. Zhao, K. Ramamritham, Virtual time CSMA protocols for hardreal-time communication, IEEE Trans. on Software Engineering 13(8) (1987) 938–952.Samphel Norden obtained his B.Tech degree in Computer Science andEngineering from the Indian Institute of Technology, Madras, in 1998.Currently, he is a research student at the Computer Science Department,University of Washington at St. Louis, USA. His research areas ofinterests are real-time networks and active networks.S. Balaji obtained his B.Tech degree in Computer Science and Engineeringfrom the Indian Institute of Technology, Madras, in 1998.Currently, he is a research student at the Computer Science Department,University of Illinois at Urbana Champaign, USA. His researchareas of interest are parallel and distributed computing and computernetworks.

136S. Norden et al. / Computer Communications 22 (1999) 128–136G. Manimaran obtained his B.E. degree in Computer Science andEngineering from Bharathidasan University, Thiruchirappalli, in1989, his M.Tech. in Computer Technology from the Indian Instituteof Technology, Delhi, in 1993 and his Ph.D. in Computer Science andEngineering from the Indian Institute of Technology, Madras, in 1998.His research interests are resource management in parallel and distributedreal-time systems, real-time networks and fault-tolerantcomputing.C. Siva Ram Murthy obtained his B.Tech. degree in Electronics andCommunications Engineering from the Regional Engineering College,Warangal, in 1982, his M.Tech. in Computer Engineering from theIndian Institute of Technology (IIT), Kharagpur, in 1984 and hisPh.D. in Computer Science from the Indian Institute of Science(IISc), Bangalore, in 1988. From March to September, 1988, he workedas a Scientific Officer in the Supercomputer Education and ResearchCentre at IISc. He subsequently joined IIT, Madras, as a Lecturer ofComputer Science and Engineering. He became an Assistant Professorin August 1989, and is currently an Associate Professor at the sameplace. He has held visiting positions at the German National ResearchCentre for Information Technology (GMD), Sankt Augustin, Germany,the University of Washington, Seattle, USA, and the University of Stuttgart,Germany. He is a recipient of the Seshagiri Kaikini Medal for thebest Ph.D. thesis and also of the Indian National Science AcademyMedal for Young Scientists.