AJMONE MARSAN M.

BIANCO A.

LEONARDI E.

English

AJMONE MARSAN, Marco Giuseppe

BIANCO, ANDREA

LEONARDI, Emilio

PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino)

05 August 2020POLITECNICO DI TORINORepository ISTITUZIONALERPA: a Simple, Efficient and Flexible Policy for Input Buffered Switches / AJMONE MARSAN M.; BIANCO A.;LEONARDI E.. - In: IEEE COMMUNICATIONS LETTERS. - ISSN 1089-7798. - 1(1997), pp. 83-86.OriginalRPA: a Simple, Efficient and Flexible Policy for Input Buffered  SwitchesPublisher:PublishedDOI:Terms of use:openAccessPublisher copyright(Article begins on next page)This article is made available under terms and conditions as specified in the  corresponding bibliographic description inthe repositoryAvailability:This version is available at: 11583/1401850 since:IEEEIEEE COMMUNCATIONS LETTERS, VOL. 1, NO. 3, MAY 1997 83RPA: A Simple, Efficient, and Flexible Policyfor Input Buffered ATM SwitchesM. G. Ajmone Marsan, Senior Member, IEEE, A. Bianco, and E. LeonardiAbstract—Reservation with Preemption and Acknowledgment(RPA) is a simple, efficient, and flexible queuing discipline andscheduling algorithm for input buffered asynchronous transfer-mode (ATM) switches. This letter describes the RPA algorithms,and presents simulation results to demonstrate the effectivenessof the proposed approach.I. INTRODUCTIONTHE DESIGN of asynchronous transfer-mode (ATM)switches rests on three main elements: 1) the switchingfabric, i.e., the interconnection architecture used to transfercells from input ports to output ports; 2) the schedulingalgorithm used to arbitrate requests of cells that arrive atdifferent input ports, but must reach the same output port; and3) the queuing discipline at input and/or output ports, i.e., therule for the selection of the next cell to be handled.ATM switch designs with output buffers have been verypopular in recent years, mainly because they are not prone tothe well-known Head of the Line (HoL) blocking that mayadversely affect the performance of input buffered switches.However, a negative characteristic inherent in outputbuffered switches is the necessity for an internal cell transferrate times higher than the external link speed, being thatis the number of input (and output) ports.Since data rates on point-to-point fiber links keep growingvery rapidly and the number of ports of ATM switches followsa similar trend, providing the cell transfer rates required foroutput buffered designs within switching fabrics is becominga problem. Researchers have thus started reconsidering inputbuffered ATM switch designs.In order to either reduce or completely overcome the penaltyintroduced by the HoL blocking, that can limit the maximumachievable throughput to 60% of the output channel speed un-der uniform traffic conditions [1], separate queues are requiredat each input port for the storage of cells directed to differentoutput ports.Once cells have been sorted into separate queues, theperformance of an input-buffered ATM switch essentiallydepends on its queuing discipline and scheduling algorithm.Thus it is very important to search for simple but efficientManuscript received January 13, 1997. This work was supported in part bya research contract between Politecnico di Torino and CSELT, in part by theEC through the Copernicus Project 1463 ATMIN, and in part by the ItalianMinistry for University and Research. The associate editors coordinating thereview of this letter and approving it for publication were Dr. C. Siller andProf. Y. Bar-Ness.The authors are with the Dipartimento di Elettronica, Politecnico di Torino,10129 Torino, Italy (e-mail: ajmone@polito.it).Publisher Item Identifier S 1089-7798(97)04608-5.policies1 that must also be able to: 1) deal with the re-quirements of different traffic classes; 2) provide the meansto give priority to cells belonging to classes of traffic withmore stringent Quality of Service (QoS) requirements; and 3)support multicast addressing.Several policies were presented in the technical literatureto address some of these issues (mostly trying to overcomeHoL blocking) in input-buffered switches under uniform trafficconditions [2]–[5]. Most of them focus on architectures whereseparate queues are available at each input port, eachone storing cells directed toward a different output port.However, those policies do not succeed in providing themaximum achievable throughput under nonuniform trafficpatterns. Some of them can even lead to starvation in sometraffic scenarios.The first proposals of policies that lead to the optimal andfair exploitation of the switch bandwidth under every trafficpattern appeared very recently (see the maximum weightedmatching policies of [6] and [7]). Unfortunately, these policiesare not simple to implement, requiring a computational com-plexity , and they do not allow the managementof different traffic classes. As a consequence, they may not beadequate for the solution of all problems in the implementationof large high-speed ATM switches.In this letter, we propose a novel policy whose com-putational complexity is only and that leads to anefficient and fair exploitation of the switch bandwidth underall investigated load patterns that include several critical trafficconditions; at the same time, it can be extended to deal withdifferent traffic classes and multicast traffic (however, theseaspects are not addressed in this letter).II. THE RPA POLICYRPA stands for Reservation with Preemption and Acknowl-edgment. The name indicates that the queuing discipline andscheduling algorithm that we describe next are based on areservation round where sources can indicate their most urgentcell transfer needs, possibly overwriting less urgent requestsby other sources, and an acknowledgment round to allowsources to determine what cell they can actually transmit.The scheduling algorithm must be executed during every celltime to determine which cells must be transferred duringthe following cell time. It is thus very important to keepcomplexity to a minimum.1The term policy in this letter refers to the specific combination of queuingdiscipline and scheduling algorithm.1089–7798/97$10.00  1997 IEEE84 IEEE COMMUNCATIONS LETTERS, VOL. 1, NO. 3, MAY 1997Denote by the number of input and output ports ofthe switch, and label input and output ports with a subscript. We shall denote the th input and outputports by and , respectively,RPA requires, at each input port, the availability ofseparate first in–first out (FIFO) queues for the storage ofpackets directed to different output ports. More precisely, theth queue, denoted by , contains cells directed from theconsidered input port toward .In the description of RPA we concentrate on the case of asingle traffic class.RPA operates on an array where reservations are written byinput ports at each cell time. This reservation array will bedenoted by RES; it contains elements, denoted by RES( )with , that orderly refer to output ports [RES( )refers to ].Each RES( ) element contains three fields:RES the address of the input port trying toreserve a cell transmission to ;RES the urgency (by convention a value )of the cell transfer from RESto ; the urgency defines the importanceof the cell transfer; several approachesmay be adopted for the computation of theurgency values; multiple classes of trafficcan be managed with clever definitions ofthe urgency;RES is set to one during the acknowledgmentround by the input port being granted theright to transfer a cell to .The three fields are initialized to null values at the beginningof every reservation round.Input ports access array RES following a pre-establishedorder. For the description of the RPA operations, supposethat within some arbitrary cell time, is selected as the firstinput port in the access order; the other input ports follow, forexample, in ascending subscript order.In the reservation round, selects its most urgent cell (i.e.,the cell with the highest urgency among the cells at the headof its input queues ) and issues a reservation for a celltransfer toward the output port of this most urgent cell. If theoutput port to which the most urgent cell must be transferredis , port records its index in the RESfield, and the urgency of the selected cell in the RESfield.The reservation array is accessed next by , the input portfollowing in the access order (if the order is by increasingindex, ). Input port first evaluates a weightfunction for each output portwhere is the urgency of the cell at the head of queue .Then computes and records thevalue at which the function reaches its maximum. If, is allowed to issue a reservation for a celltransfer toward , writing its index in RESand in RES ; this implies that may over-write a previous reservation for a cell transfer toward ,thus preempting it. If , no reservation can beissued.The reservation round then continues: array RES is nextprocessed by input port , where , that executesthe same algorithm. After all input ports have processed arrayRES, the reservation round terminates.At this point, the acknowledgment round immediately starts,and array RES is processed for the second time by all inputports in the same order followed during the reservation round.First, checks whether its reservation toward hasbeen overwritten by any other input port with more urgentcell transfers toward . If the reservation has not beenoverwritten, is granted access to , and the RESfield is set to one. Otherwise, cannot transfer a cell to ;however, if at least one “idle” output port is found, i.e., anoutput port toward which no reservation has been made (thefield is zero), is allowed to transfer a cell towardany one of the idle output ports. In practice, selects theidle output port for which it has the most urgent cell, and setsto one the corresponding busy field. Note that in answitch, if a reservation has been overwritten, at least one idleoutput port exists. The same may not be true when the numberof output ports is smaller than the number of input ports.Next, port processes array RES to check whether itsreservation toward has been overwritten; if not, it can accessthe desired output port, and it sets the RES field toone. Otherwise, it checks whether any idle output port exists;if some idle output ports are found, is granted access towardthe output port for which it has the most urgent cell, and theappropriate busy field is set to one.This acknowledgment algorithm is executed in order by allinput ports; when all input ports have processed array RES,the scheduling algorithm terminates. One cell can now betransferred from each input port to the output port towardwhich it has been granted access.The ordering of input ports in their access to the reservationvector can either be the same in any cell time (in our examplethis means that always is the first input port, the second,and so on), or change; we call static the former version of thescheduling policy, and adaptive the latter. In this letter, for thesake of brevity, we do not consider adaptive policies, but anumber of those can be devised: we could envision a round-robin selection of the starting point of the cyclic rounds, arandom selection of the starting point of the cyclic rounds,or a completely random order. Each one of these alternativesprobably has pros and cons, but a careful investigation of thoseis left for future work. Of course, the static policy leads tosome unfairness (only for delays, not for throughputs), due tothe fact that input ports always have the same position withinthe round.Several metrics can be adopted to quantify the cell ur-gency. When just one class of traffic flows is present in theswitch, the number of cells stored in each input queue canbe chosen as the urgency for the cell at the head of eachqueue; this is the urgency metric we used in our simulationexperiments. When several classes of traffic flows are present,no significant modification to our scheduling policy is required,AJMONEMARSAN et al.: RPA—A POLICY FOR ATM SWITCHES 85and a straightforward generalization is sufficient; however, thedefinition of a suitable urgency metric is crucial for the supportof different types of QoS requirements. Moreover, in this caseeach input port may need a number of queues equal toto efficiently deal with traffic classes.III. COMPLEXITYThe complexity of the RPA scheduling algorithm is notdifficult to compute.During the reservation round, operations are requiredat each input port to compute for each ; in addi-tion, operations are required to determine the outputport for which is maximized; one operation issufficient to verify whether .The computational complexity of the reservation round isthus , since it is composed of sequential steps, eachone of complexity .During the acknowledgment round, operations arerequired at each input port to verify whether the reservationhas been overwritten; in addition, operations may benecessary to obtain the set of idle outputs and to determinethe one for which the input port has the most urgent cell.As a consequence, the computational complexity of theacknowledgment round is also .Hence, the total complexity of the scheduling algorithm is.IV. SIMULATION RESULTSWe briefly present in this section a small sample of thesimulation results that were obtained in the performanceinvestigation of RPA; we focus on the static version of thescheduling policy, but the general trends of the algorithmbehavior remain the same also when considering adaptiveversions.To begin with, in Fig. 1 we present average cell accessdelays versus the normalized load of the ATM switch, for theleast favored input port. The cell access delay is defined asthe time between the cell arrival at the input port and thesuccessful reservation of the cell transfer toward the desiredoutput port. The normalized load of the ATM switch is thefraction of slots that contain cells on all input ports. Resultsare obtained for an 8 8 switch configuration under uniformtraffic conditions, with queuing capacity at each input portequal to either 100 or 10 000 cells per input queue (a total ofeither 800 or 80 000 cells per input port). We report averagedelays for three types of input traffic.• Bernoulli input traffic (white square markers): cells arriveat input ports according to a Bernoulli process; thecell output ports are selected with random, independentchoices; the queue capacity is set to 100 cells for eachinput queue.• batch input traffic—case 1 (white round markers): cellscontinuously arrive at input ports during geometricallydistributed ON periods, whose average duration is tencells; no cells arrive during geometrically distributed OFFperiods, whose average duration is selected so as to obtainthe desired load (that cannot exceed on the average,Fig. 1. Average cell access delays for the static scheduling policy.TABLE IFIRST TRAFFIC SCENARIOsince the OFF period cannot be shorter than one cell); thecell output port is the same for all cells arriving duringone ON period, and is selected by random choice at thebeginning of the batch; the queue capacity is set to 10 000cells for each input queue.• batch input traffic—case 2 (white triangular markers):same as case 1 except that the average duration of ONperiods is 100 cells, so that the maximum achievableload grows to .Black markers with the same shape show the “optimal”performance that could be obtained with the same inputtraffic pattern in an output buffered switch with infinite queuelengths.Three main observations can be drawn from the simulationresults: 1) no throughput limitation can be observed in anyof the presented scenarios; 2) no losses were experienced;3) the presented delays are quite close to the “optimal”values. Note that even more complex scheduling policies (see[6], [7]) guarantee a full utilization of the switch bandwidthonly under asymptotic conditions, i.e., with infinite queuecapacities.The performance of RPA was studied also under trafficscenarios similar to those described in [6], [7]. Such conditionscan be easily proved to induce throughput limitations in all ofthe simple scheduling techniques proposed up to now (to thebest of our knowledge) and also in the maximum size matchingalgorithm described in [6], whose complexity is . Inorder to describe these input traffic patterns, we use a matrixnotation in Tables I–IV; rows are associated with input ports,columns with output ports; we report in the table the amountof traffic transmitted on average from the input port towardthe output port.We run simulations with different values of , scaling theinput load so as to avoid overload (in practice, the values86 IEEE COMMUNCATIONS LETTERS, VOL. 1, NO. 3, MAY 1997TABLE IISECOND TRAFFIC SCENARIOTABLE IIITHIRD TRAFFIC SCENARIOshown in the table were multiplied by 0.999), observing nothroughput limitation. This confirms our conjecture that thestatic version of RPA is close to being optimally efficient, inthe sense that, provided that: 1) the normalized offered loadof each input port is smaller than one and 2) the sum of thenormalized offered loads toward each output port is smallerthan 1, all of the input traffic can be successfully transferredto output ports.TABLE IVFOURTH TRAFFIC SCENARIOREFERENCES[1] M. Karol, M. Hluchyj, and S. Morgan, “Input versus output queuingon a space division switch,” IEEE Trans. Commun., vol. COM-35, pp.1347–1356, Dec. 1987.[2] M. Karol, K. Eng, and H. Obara, “Improving the performance of input-queued ATM packets switches,” presented at the IEEE INFOCOM’92,Firenze, Italy, May 1992.[3] T. Anderson, S. Owicki, J. Saxe, and C. Thacker, “High speed switchscheduling for local area networks,” presented at the 5th Int. Conf. Arch.Support for Programming Languages and Operating Systems, Oct. 1992.[4] N. McKeown and P. Varaiya, “Scheduling cells in an input-queuedswitch,” Electron. Lett., vol. 29, no. 25, pp. 2174–2175, Dec. 1993.[5] M. Chen, N. D. Georganas, and O. W. W. Yang, “A fast algorithm formulti-channel/port traffic assignment,” presented at the IEEE ICC’94,New Orleans, LA, May 1994.[6] N. McKeown, V. Anantharam, and J. Walrand, “Achieving 100%throughput in an input-queued switch,” presented at the IEEE INFO-COM’96, San Francisco, CA, Mar. 1996.[7] A. Mekkittikul and N. McKeown, “A starvation-free algorithm forachieving 100% throughput in an input-queued switch,” presented atthe ICCCN’96, Rockville, MD, Oct. 1996.

RPA: a Simple, Efficient and Flexible Policy for Input Buffered  Switches

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RPA: a Simple, Efficient and Flexible Policy for Input Buffered Switches

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