TSMR

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ITC 11, Minoru Akiyama (Editor)Elsevier Science Publishers B. V. (North-Holland)© lAC, 1985

USE OF A TRUNK STATUS MAP FOR REAL-TIME DNHR

Gerald R. Ash

AT T Bell LaboratoriesHolmdel, New Jersey

ABSTRACf

Dynamic nonhierarchical routing (D \TJIR) is a new routingtechnique that is currently being implemented in the AT &T

Communications network. DNHR incorporates a preplannedtime-of-day routing strategy that enables a significant increasein the efficiency of the AT&T-C network. Trunk status maprouting (TSMR) is an extension of the DNHR concept to acentralized trunk status map (TSM) that provides real-time 'routing decisions in the DNHR network. Variousimplementations of TSMR are investigated, and thecomparative advantages of several real-time dynamic routingalgorithms are illustrated. A simple implementat ion of TSMRwhich is a hybrid of time variable routing and fully dynamicrouting is shown to yield benefits comparable to morecomplicated schemes.

1. INTRODUCTION AND SUMMARY

Earlier work has described the design, optimization, andcontrol o f networks with dynamic routing [1-3]. The termdynamic routing frequently suggests a real-time search for theoptimal routing patterns based on current network loads. n itsinitial imple m entation, dynamic nonhierarchical routing(DNHR) 'l ses a preplanned timed-variable routing strategywith a limi ted amount of real-time control. Real-time, trafficsensitive routing is indeed the limiting case of preplannedtime-variable routing, and in this paper we investigate thefeasibility and benefits of such "true dynamic routing." Herewe inves tigate a central co nt ro l capability called trunk statusmap routing (TSMR), which greatly extends the real-timerouting capability of DNHR. TSMR uses a real-time networkstatus map to implement a dynamic routing strategy, and weexamine the interaction of TSMR with network operation. The

trunk status map (TSM) concept involves having an upd ate ofthe number of idle trunks in each DNHR trunk g rou p sent to anetwork data base every T seconds. These updates are sent byeach stored program control (SPC) switch only wh en the trunkgroup status has changed. n return, the TSM, whic h is loca tedwithin the common channel signaling network, p eriodicallysends to the SPC switch es or dered routin g sequenc es to be us eduntil the next update in T seconds. The se ro utb g sequencesare determined by the TSM in real time using the TSMRdynamic routing strategy. As T approaches zero seconds, theseupdates effectively are sent for every call arrival.

n this paper we investigate through simulation techniques anumber of approaches to TSMR. These TSMR strategiesrange from schemes that simply determine the single most idlerouting path (which is a one or two-link connection) between

each node pair in the network to more complex schemes thatperiodically reoptimize the entire network routing pattern bysolving a large mathematical program. The scheme thatappears to e the most attractive operates as follows. The firstchoice path determined by the design algorithm (the unified

algorithm or UA [1], as modified for TSMR [4]) is used if acircuit is available. This first choice path is updated once eachrouting interval or load-set period (LSP), which is typically onehour to several hours in duration. f the first path is busy, thesecond path is selected from the list of other paths determined

by the UA on the basis of having the greatest number of idlecircuits at the time. Hence the TSMR approach is a hybrid oftime variable routing and fully dynamic routing. A detailedimplementation strategy is described that stabilizes the routingpatterns through trunk reservation techniques, and also allowsautomatic routing controls to augment the TSMR strategyduring network overloads and failures.

TSMR provides uniformly better blocking performance thanthe current implementation of DNHR and a significantlyreduced number of crankback messages; both network blockingand crank back messages decrease as the status and routingupdates interval, T, decreases. Crankback messages aresignaling messages used to inform the originating SPC switchthat a DNHR call has been blocked on the second link of atwo-link path. An initial evaluation of TSM processing cost

and crankback cost as a function of the update interval T placesthe optimum value of T in the range of about two to eightseconds. The network congestion control strategy developedfor TSMR provides performance under overloads and failuresthat is significantly better than the performance of the currentimplementation of DNHR.

2. REVIEW OF DNHR CONCEl IS

DNHR brings three principal changes to the network plan.First, there is a new network configuration. With DNHR, theAT T Communications (AT&T-C) network will evolve fromits present multiple level structure to a structure consisting ofDNHR switches at the upper level with subtending hierarchicalswitches at the lower level. There is also a new routingtechnique. DNHR allows the choice of traffic paths to changewith time of day and is not constrained by a hierarchicalranking of the switches. This approach greatly expands theflexibility of network routing and thereby pennits a largeincrease in the efficient use of the network. That eff ciencyreduces the need to construct transmission facilities in thefuture. Finally, there is a new way of operating and designingthe network. DNHR network operations are more centralizedand more automated than they are today, and that increasesoperating efficiency and improves network performance.Several technical feasibility studies have shown that thesechanges brought about by DNHR are technically feasible, thatnetwork performance is comparable to that of the hierarchy,and, with a proper level of automation, that operation of aDNHR network is quite tractable [3].

Figure illustrates the network structure which incorporatesDNHR into the AT&T-C intercity network. TIle DNHRnetwork has only one class of switching system, and end-officeshome on DNHR tandem offices y way of exchange accessnetworks. The DNHR ~ r t o nof the AT&T-C intercitynetwork consists , o 4ESS switches (and possibly successor

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ITC 11 Kyoto September 1985

> DNHR TANDEM

o PRI MARY CENTER

e TOLL CENTER

TO EXCHANGEACCESS NETWORK 3

TO EXCHANGEACCESS NETWORK 4

_ . DNHR TRUNK GROUP

- - HIGH USAGE TRUNK GROUP

FINAL TRUNK GROUP

FIGURE 1DNHR NETWORK CONFIGURATION

ESS Thl switches) interconnected by the common channelsignaling (CCS) network. ' Dynamic routing rules are usedbetween pairs of DNHR switches, and conventionalhierarchical routing rules are used between all other pairs ofAT&T -C switches. Thes e hierarchical switching systems willhome directly or indirectly on DNHR switches. Traffic isconcentrated in the hierarchical network through the use of ,conventional homing configurations, as illustrated by tandemT3 in Figure 1. To the subtending hierarchical switches, the

DNHR switches appear as a large network of regional centers.The dynamic routing method illustrated in Figure 2, called

two-link dynamic routing with crankback, capitalizes on twofactors: selection of minimum cost paths, as given by the UAdesign, between originating and terminating switches, anddesign of optimal, time-varying routing patterns to achieveminimum cost trunking by capitalizing on Iloncoincidentnetwork busy periods. We achieve the dynamic, or timevarying, nature of the routing scheme by varying the routechoices with time. The routes, which consist of differentsequences of paths, are designed to satisfy a node-to-nodeblocking requirement. Each path consists of one or, at most,two links or trunk groups in tandem. Paths used for routes indifferent time periods need not be the same. In Figure 2, theoriginating switch at San Diego (SNDG) retains control over a

dynamically routed call until it is either completed to itsdestination at White Plains (WHPL) or blocked. The controlof a call overflowing the second leg of a two-link connection(for instance, the ALBY-WHPL link of the SNDG-ALBYWHPL path in routing sequence # 1) is returned to theoriginating switch (SNDG) for possible further alternate ,routing. Control is returned when the via switch (ALBY in theexample) sends a CCS crankback signal to the originatingswitch.

Since many of the intercity traffic demands change with ti me ina reasonably predictable manner, the routing also changes withtime to achieve maximum trunk utilization and minimumnetwork cost. Initially, ten DNHR time periods are being usedto divide up the hours of an average business day intocontiguous routing intervals called load-set periods (LSPs).

This real-time, traffic-sensitive component of DNHR usesreal-time paths for possible completion of calls that overflow

the engineered paths (see Figure 2). The engineered pathsare designed to provide the objective blocking performance.

The real-time paths, which are also determined by the centralforecasting system, can be used only if the number of idletrunks in a group is greater than a specified number of trunks-the reservation level--before the connection is made. Thisprevents calls that normally use a trunk group from beingswamped by real-time rou ted calls.

The third principal change brought about by DNHR is the way

the network is designed and operated. Several operationssystems provide centralized functions such as switch planning,trunk forecasting, trunk servicing, routing administration, andnetwork management. An overview of the operations systems ,used to support DNHR is given in Reference 3. Embeddedwithin the forecasting and servicing systems is the UA, whichsimultaneously determines the trunking and routing for theentire DNHR network [1].

3 TRUNK STATUS MAP ROUTING MEI HOD

The real-time routing method discussed in connection with thepresent implementation of DNHR is used to improve networkservice. Service improvement with real-time routing issignificant even with relatively simple procedures. As analternative to using real-time routing to improve service, wecould hold the node-to-node blocking (service) level fixed anduse the real-time routing scheme to reduce the number oftrunks required to provide that level of service. Thisalternative approach can produce additional network savings.,Furthermore, real-time dynamic routing can improve networkperformance in the event of network failures, especially whensome amount of reserve capacity is available for redirecting 'traffic flows from their usual patterns. Hence an increasedlevel of real-time decision making might be warranted in theDNHR network.

Trunk status map routing (TSMR) is an extension oi theDNHR concept that uses a centralized trunk status map (TSM)to provide real-time routing decisions in the DNHR network.As described in the introduction, the TSM receives, every Tseconds from each SPC switch, updates of the number of idletrunks in each DNHR trunk group . These updates are sentonly when the number of idle trunks in the trunk group haschanged. In return, the TSM periodically sends to the SPCswitches ordered routing sequences to be used until the nextupdate in T seconds. These routing sequences are determinedby the TSM in real time using the TSM dynamic routingstrategy (TSMR). TSMR therefore represents a much moredynamic routing method than the current implementation ofDNHR.

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FIGURE 2TWO LINK DYNAMIC ROUTING WITH CRANKBACK

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ITC Kyoto September 1985

In this section we investigate alternative approaches to TSMRas well as the appropriate value of the status and routingupdate interval (T). We also study an automatic networkcongestion control strategy that could be implemented by theTSM.

A call-by-call simulation model is used to measure theperformance of an engineered network under various routingstrategies: DNHR various alternative TSMR strategies, andTSMR combined with automatic congestion control strategies.A 25-node DNHR network model projected for 1986 is usedfor the simulation studies. The 25-node model is designed bythe DNHR and TSMR design algorithms [1,4] for 6 hoursthroughout the day (from 8 a.m. through p.m. ). Thebehavior of the network is investigated over a typical two-weekperiod consisting of 10 average business days. Low ~ ~

variations are applied to the load fo r each node-to-node pal mthe network simulation. In addition, a systematic dailyvariation of the total network load is superimposed on therandom load variation according to typical load patterns overan average business week.

3 1 Alternative Approaches to TSMR

Various techniques are invest igated to determine the mostefficient TSMR method. These methods include the following:

1) route each call on the least loaded path (the path havingthe greatest number of idle circuits) among all candidatepaths;

2) route each call first on the direct path, if it exists and isavailable, or else select the least loaded path;

3) route each call on the first path assigned by the UA ifavailable, or else sele:ct the least l .oaded path;

4) compute the UA routing sequences that maximizecarried traffic for a short-term estimate of the networkloads and then apply Method 3 using the new routingsequences.

Methods 1 and 2 do not provide adequate performance for thefollowing reasons. Method 1 favors the path having the largestavailable capacity, not necessarily the first path, and usually atwo-link path. This tendency to favor two-link paths results ina significant redistribution of flows and relatively poor networkperforman ce. Method 2 performs considerably better thanMethod 1 but falls short of the performance of Method 3,which we describe shortly. Method 2 has a problem similar tothat of Method 1: since it always selects the direct path as the :first choice, and since the UA does not always design the direct 'path to be the first choice, Method 2 makes the path order toodifferent from that designed by the UA. Hence Method 1 andMethod 2 performance is degraded because the actualrealization of network flows deviates too fa r from the networkflow patterns designed by the UA.

Method 3, however, performs quite well. It ref lectssufficiently accurately the design of the UA by assigning firstpath traffic to the design first path. Flow on the first choicepath accounts for about 80 to 90 percent of the total networktraffic flow and hence the routing of this flow must correspondwell to the placement of trunks for the network to behaveproperly. Flows on the second and higher-numbered paths arebetter assigned by a least-loaded selection method than by apreplanned sequential selection method. This statement issupported by the simulation results shown in Figures 3 and 4.

Figure 3 shows the 10-day average hourly blocking for TSMRMethod 3 (for status and routhlg update interval T equal to fiveseconds) and also for the current implementation of DNHR;Figure 4 shows the 99th percentile hourly node pair blockingfor TSMR and DNHR. These results were obtained with anetwork designed for DNHR and clearly demonstrate thebenefits of TSMR in comparison to the current implementationof DNHR. The details of the TSMR strategy used in thesesimulations will be described in Section 3.2, 3.3, and 3.4.

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FIGURE 3AVERAGE NETWORK BLOCKING FOR DNHR AND TSMR

(AVERAGE BUSINESS DAY LOADS)

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FIGURE 499TH PERCENTILE NODE-TO-NODE BLOCKING FOR DNHR AND TSMR

(AVERAGE BUSINESS DAY LOADS)

A simple intuitive explanation of why TSMR Method 3 mightcomplete more calls than the current implementation of DNHRis illustrated by the four-node example shown in Figure 5. The

current number of idle circuits in each trunk group is shown.f the DNHR routing sequence for A-D calls is A-D - A-C

D - A-B-D, then the next A-D call arrival will block link ACand link CD, and either an A-C or CoD call arrival will then beblocked. However, the TSMR routing sequence for A- D callsin this network state is A-D - A-B-D - A-C-D. Therefore thenext A-D call arrival under the TSMR strategy will not blockany additional links. As illustrated by this simple example,TSMR tends to leave capacity on links throughout the network,distributed as uniformly as possible. Because of this propertyof TSMR, calls arriving in various parts of the network willhave a greater chance of being completed than under thehypothesized DNHR routing sequence. Bulfer [5] hasestablished the optimality of the least loaded routing strategyfor a class of two stage concentraton.

FIGURE 5

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TSMR Method 4 has greater adaptivity to load shifts thanMethod 3 but is more complex to implement and as such musthave better performance to be justified. The details of Method4 are now discussed. To calculate optimum routing sequenceswith the VA as required by Method 4, we assume that theserouting patterns are computed in advance of their actual useand that the average load in the future LSP is known precisely.This second assumption of course is an idealization of realityand represents an upper limit on the possible performance ofMethod 4. We used two methods based on the VA todetermine the routing sequences that maximize network flow inthe existing network. For each method we find the minimumincremental network capacity required to carry the future LSPload given the existing trunks as available network capacity [2].That is we minimize

where la j are the augmentations above the existing linkcapacities a j , and L is the number of links in the network. Inthis formulation of the VA we set all incremental link costs toone in order to transform the objective function fromincremental network cost to incremental network capacity.

In the first method (which we will call Method 4A), themaximum node-to-node blocking grade of service (GaS) isheld at one percent, and the routing and capacity 'augmentations la· are determined which minimize theobjective function. W e implement the routing solution, but thecapacity augmentations la . produced by the optimizationcannot actually be added to the network. Hence the traffic thatwould have been carried on these augmentations will actuallybe blocked. But since we have minimized these hypotheticalcapacity augmentations, this routing solution approximates the'minimization of total blocked traffic. In the second method(Method 4B) the node-to-node blocking GaS is raised untilthere are zero capacity augmentations lai produced by theoptimization. This second solution approximates theminimization of the maximum node-to-node blocking.

A comparison of the average network blocking performance ofMethod 3, Method 4A, and Method 4B is shown in Figure 6.For these results the update interval T is five seconds, and thenetwork is designed for TSMR, as described in Reference 6.As can be seen there is no apparent improvement gained fromthe more complex methods over Method 3, which suggests thatMethod 3 may achieve nearly the maximum flow performance.TSMR Method 3 was therefore selected for further study todetermine the best switching control logic and TSM logic toimplement TSMR.

3.2 Implemental on Strategy for TSMR

Extensive simulation studies of TSMR Method 3 were used todetermine the implementation strategy discussed in this section.We describe the TSMR strategy found to perform the bestfrom these simulation studies.

The SPC switch maintains a TSMR route sequence for eachdestination. The route sequence stored in the SPC switch ismade up of two functional parts. The first part consists of asingle path, called the "first-choice path," which is updated bythe TSM once each LSP and is made to correspond to the UAselected first-choice path. The second and subsequent paths ofthe route sequence consist of the "least loaded routing (LLR)paths. t These LLR paths are updated every T secondsaccording . to a least loaded criterion applied to the current

network status.For

each route sequence that ne .eds tobe

updated, the TSM determines the paths in the current routesequence that need to be changed and transmits these changesto the SPC switch. the least loaded path differs from .thesecond-choice path currently in the SPC switch, the TSM sends

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FIGURE 6AVERAGE NETWORK BLOCKING FOR TSMR METHODS 3, 4A AND 4B

an appropriate message to the SPC switch that changes thecontents of the LLR paths- to reflect the new least loaded pathand also changes the position of the other paths in the route

sequence. We found from the simulations that it is sufficientfor small values o f T to have the TSM compute only the leastloaded path and put it second in a route rather than sort theentire route in least loaded order.

For each node pair for which the direct trunk group exists andis the first choice, the TSM applies a thresholding scheme todetermine whether a routing update is needed, as follows.Consider the typical case in which the direct path is the firstchoice and a two-link path ' is the second choice (case 1 inFigure 7). I f the total number of idle circuits on these twochoices is greater than a threshold number which is sufficient to

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CASE 1: FIRST-CHOICE PATH IS THE DIRECT PATH

CASE 2 : FIRST-CHOICE PATH IS A TWO-LINK PATH

FIGURE 7EXAMPLE CALCULATION OF TSM ROUTING

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permit completion of all calls likely to arrive over the T-secondupdate interval, then there is no need to reorder the route ·seque.nce since the calls can be completed without generatingany crankbacks. A threshold that works reasonably well isN/8 where N is the number of trunks on the direct trunk groupto the terminating switch. (If the direct group does not exist oris not the (irst choice, the thresholding scheme is not used).For

case 1 in Figure 7, this means that if the numberof

trunkson the direct group is less than 200, then no routing updatemessage will sent to the ~ P switch. For case 2 in Figure 7,the thresholdmg scheme 15 not used. Use of this logicconcen rates the. TSM processing capacity on those node pairsfor which a routmg update to the SPC switch is most beneficial.This logic also limits the number of node pairs requiringupdated LLR paths.

I f there is not a sufficient number of idle circuits according tothe thresholding scheme discussed above, and a routing upda te

is potentially required, the next step for the TsM is todetermine the current least loaded path. It does this by firstretrieving the LLR path choice candidates, for this node pair,from the routing data base memory. These candidates aretypically a subset of the one- and two-link paths between the

two nodes. In the simulations we find that discounting thenumber of idle circuits by a small fraction of the trunk groupsize protects large groups from being selected by adisproportionately large number of node pairs as a via-pathcandidate when these large groups have temporarily idletrunks. Large groups tend to have short period s with arelatively large number of idle trunks, and overselection ofthose groups for via traffic during these short periods can bedetrimental to the direct traffic routed on the large groups.The simulation studies indicate that discounting the number ofidle trunks by N/36 trunks, where N is the trunk group size,works reasonably well in protecting the direct traffic on thelarge groups. (Groups with fewer than 36 trunks are notaffected). Using the discounted idle trunk values, the TSMthen determines the number of idle circuits on each path choice

and selects the path having the greate st number of idle circu its(which we call the least loaded path). This discountingprocedure is applied only in the TSM path ordering logic and isnot applied in the SPC switch path selection logic.I f the new least loaded path is the same as the old path or ifthere are no idle circuits en any candidate path, then a routingupdate is not sent to the SPC switch because there is noadvantage in doing so. Simu lations of this logic in combinationwith the idle circuit thresholds described above predict thatonly about 10-15 percent o f node pairs need routing updatesreturned to the SPC swit ch, in the busy hour, for an updateinterval T of five se.conds. This TSM logic therefore tends tohold the use of CCS and SPC switch resources down toreasonable levels.

When the least loaded path does change, then a message is sentto the SPC switch changing the contents of the routing seque:1ce.in the SPC switch. As an example, consider case 2 in Figure 7.In the figure the idle trunk quantities are the quantitiesdiscounted by N/36 trunks. The current route to switch B has amaximum of four path choices, of which three are LLR pathcandida tes - A-C-B, A-D-B, and A-B - in addition to the twolink, first-choice path A- E B determined by the UA. The T SMfirst determines that the second LLR path candidate, A-D-D,has become the least-loaded path, and then the TSM sendsJ.,LR path choices one and two to the SPC switch in the orderA-D-B and A-C-B. Path choice A-B is not sent to the SPCswitch since it remains the third LLR path choice. We call thisa "push-down" logic since the new least loaded path replacesthe old least loaded path, and the remaining path choices arepushed down one slot. The SPC switch replaces its current"LLR path choices one and two with the new paths and leavesthe current third LLR path choice unchanged. Hence this logicplaces the least loaded path in the second-choice position butdoes not necessarily leave the remaining path.s in the order oftheir available capacity. According to the simulation results,

for an update interval T of five seconds, the TSM transmits anaverage of about four entries in the SPC path sequence witheach routing update.

With this implementation of TSMR, the SPC switch does notrequire any time-varying routing capability of its own, as nowimplemented for DNHR [6]. All such dynamic routingcapabilities are controlled by the TSM, which changes the

first-choice path every LSP and also controls the LLR paths ina fully dynamic manner . The SPC switch, however, is the onlyplace where individual trunks are selected and assigned to aparticular call. The SPC switch sets up all calls over theselected paths using the present DNHR two-link routingprocedure with crankback. The number of crankbacks,however, is greatly reduced by the use of TSMR.

3 3 Status and Routing Update Interval T

Four 10-day simulations were made with values of the statusand routing update interval, T equal to 2, 5 , 10, and 30seconds. For these four values of T Figure 8 compares theTSMR results on the basis of three performance measures.The first measure is average network blocking, which is the10-day total number of blocked calls divided by the 10-day total

numb er of originating attempts; the second measure is averagenumber of crank backs per originating attempt, which is the 10-day total number of simulated crankbacks divided by the 10-day total number of originating attempts; and the thirdmeasure is the TSM workload, which is the daily total numberof least loaded path searches averaged over the 10 days. Wecan see from the results that the status and routing updateinterval should be as short as possible within the limitations of

SPC switch and TSM processing if we wish to maximizecompletions and minimize crankbacks.

There is approximately a two percent penalty in SPC switchcapacity due to the real time needed to process crank backmessages associated with the implementation of DNHR in the4ESS switch [3]. I f we apply this penalty to the currentforecast of switches in the mid-1990's, and if we assume that

the switch cost penalty for the TSMR strategy can be allocatedin direct proportion to the total number of crankbacksgenerated , then we obtain the crank back cost as a functionof T which is shown in Figure 9. Also shown in Figure 9 isthe total cost of processors needed to support the TSMprocessing level shown in Figure ·8, under the assumption thattwo processors are needed to support a five-second updateinterval for a 180-node TSMR network. Here we haveassumed that each processor costs $100,000. As shown inFigure 9, no fewer than four processors are required since theTSM is duplicated, because of reliability considerations, as aresignal transfer points in the CCS network, and at least twoprocessors are required at each TSM, also for reliabilitypurposes. The results shown in Figure 9 suggest that an updateinterval T in the range of two to eight seconds will minimize

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FIGURE 9 PROCESSING a CRANKBACK COSTvs UPDATE INTERVAL

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the total cost. The tradeoff analysis pictured in Figure 9assumes that the SPC switch real-time processing load requiredin addition to the crankback load is not a strong function of theupdate interval T. f future investigations show that this is notthe case, then the optimum value of T will need to bereevaluated.3 4 Network Congestion Control StraJegy for TSMR

In the face of network overloads, failures, or other causes ofnetwork congestion, the TSM needs to adjust its routingstrategy to best accommodate such conditions. Here weinvestigate the use of automatic trunk reservation (ATR)controls, busy path removal (BPR) controls, and extendedrouting logic (ERL) controls that could be implemented by theTSM to help alleviate network congestion. ATR is used toprotect the direct trunk group of overloaded node pairs fromexcess overflow from other node pairs. For traffic subjected totrunlC reservation, access to trunks on the direct trunk group isallowed only if the number of idle trunks in the group isgreater than a specified number called the reservation level.BPR controls eliminate paths through congested parts of thenetwork when heavy overload conditions exist. ERL allowsoverloaded node pairs to search out excess capacity available in

the network to complete the excess calls. Our simulationstudies have investigated a range of ATR, BPR, and ERL strategies; we present here the strategies that we found toperform best.

ATR is triggered automatically for a node-to-node pair if theaverage node-to-node blocking over a five minute interval isgreater than five percent and at least two calls are blockedduring the five-minute interval. f ATR is triggered, thenATR is applied to that node pair for the next five minutes.Once triggered, ATR operates in the following manner.Traffic attempting to alternate route over the direct trunkgroup of a triggered node pair is subjected to trunk reservation.(We used a reservation level of approximately five percent ofthe number of trunks in each trunk group). This actionptotects traffic on the direct trunk group of the triggered node

. pair if it exists) from interference from traffic on other nodepairs. Reservation is applied at both the TSM and the SPCswitch. Reservation at the TSM is iIitplemented by having theTSM subtract the number of trunks reserved from the n u m ~ r

idle in the process of determining the least loaded path. Inno

case is trunk reservation applied at the TSM or SPC switch fora one-link (direct) path.

BPR controls are triggered on total network blocking, and,once triggered, BPR removes all busy two-link paths from allroute sequences. That is, when the average network blockingover a five minute period exceeds three percent, those two-linkpaths (excluding the first path) that have zero fret circuits areremoved from the SPC switch route patterns for the next fivesecond ·interval. This strategy results in a uniformly appliedrestrictive control on the network; all node pairs are triggeredat once and are prevented from routing calls through congestedparts of the network. BPR controls are also used when an SPCswitch signals the TSM that it is in congestion or has failed. Inthe case of SPC switch congestion, the TSM removes the nodeas a via point in all routing patterns, and in the case of SPCswitch failure the TSM removes both direct and via routing tothe failed node.

With the ERL logic, extended searches for idle capacity aretriggered for a node-to-node pair whenever the blocking for thepair exceeds one percent over a five-minute period. When thetotal network blocking threshold used for BPR is triggered,

however, then the ERL logic is used only when the node-tonode blocking over a five-minute interval exceeds five percent,with a minimum of two blocked calls. When ERL is triggered,the search for the least loaded path for the triggered node pairis extended to include a larger set of candidate paths.

We simulated the ATR, BPR, and ERL controls over the threehour morning busy period for an average daily load, as well asfor 10, 20, and 30 percent general overloads in which eachnode-to-node traffic load was increased by the overloadpercentage. We also considered a focused overload on the

·White Plains switch in which each load to White Plains wasincreased by a factor of three. Finally, we considered twofailure situations which involved a Dallas-Wayne (DLLSWAYN) trunk group failure and an Anaheim-White Plains(ANHM-WHPL) trunk group failure. The results are given in

Table .1, in which the measures used reflect averages over theTABLE 1

PERFORMANCE COMPARISON OF TSMR . AND DNHR

99th CRKBSOVERWAD AVG PERCENI'ILE PER

ROUTING ORFAIWRE BLKG BLKG CALL

DNHR 0 .00044 .00215 01131TSMR 0 .00002 .00010 .00257

DNHR 10 .01382 .03330 .03462TSMR 10 .00479 .01230 00931

DNHR 20 .05753 11558 .08038TSMR 20 .03016 .13793 .01855

DNHR 30 .10745 .18454 .12002TSMR 30 .06524 .22876 .05332

DNHR FOCUS .01860 20361 .04878TSMR ONWHPL .00808 12265 .02865

DNHR DLLS-WAYN 00101 .00806 .01556TSMR FAILURE .00004 .00055 .00314

DNHR ANHM-WHPL .00187 01651 .03012TSMR FAILURE 00001 .00000 .00167

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three hours of the simulation: the average network blocking isthe total number of blocked attempts in three hours divided bythe total number of originating attempts; the 99th percentileblocking is the 99th percentile node pair blocking, where eachnode pair blocking is averaged over the three simulation hours;and the average number of crankbacks per originating t t e m p ~

is the total simulated number of crankbacks over the threesimulation hours divided by the total number of originat ing

attempts. For comparison, we have L'lc1uded results for thecurrent implementation of DNHR. The results indicate thatTSMR (with automatic congestion controls) provides imp rovf daverage blocking performance and comparable or better 99thpercentile blocking performance for all the cases studied. Thenumber of crankback messages is also significantly lower withTSMR.

As another indication of peak load pe rformance, Figure 10shows the hourly blocking performance for TSMR and thecurrent implementation of DNHR under an average Mondayload pattern (these loads are normally the highest loads of theweek). These results also demonstrate the ability of TSMRcongestion controls to increase network flow in comparison toDNHR. Both DNHR and TSMR performance would be

. mproved further by automatic network management controlspresent in the SPC switch and in the network managementsupport system.

( )

zu0...J(D

0 .006

0 .005

0 .004

0 .003

0 .002

0 .001

0

FIGURE 10AVERAGE NETWORK BLOCKING FOR DNHR AND TSMR

AVERAGE MONDAY LOADS

4 ON WSION

11

Our conclusions from these studies are that 1) TSMR providesuniformly better blocking performance than the currentimplementation of DNHR and a significantly reduced numberof crank back messages; both network blocking and the numberof crankback messages decrease as the status and routingupdate interval, T, decreases, 2) an initial evaluation of TSMprocessing cost and crankback cost as a function of the updateinterval T places the optimum value of T in the range of two toeight seconds; and 3) init ial studies show that the TSM canimplement effective automatic congestion control strategies .

. 5. ACKNOWLEDGEMENTS

B. B. Oliver of AT&T Communications first suggested the useof a trunk status map for DNHR. I also benefited greatly fromthe insights .of A. F. Bulfer of AT &T Communications whofirst suggested investiga tion of LLR strategies for TSMR.A. H. Kafker of AT&T Bell Laboratories was instrumental inthe design of the TSM implementation strategy described inSection 3.2.

REFERENCES

1. Ash, G. R., Cardwell, R. H., Murray, R. P., Designand Optimization of Networks with Dynamic Routing,BSTJ, Vol. 60, No. 8, October, 1981.

2. Ash, G. R. Kafker, A. H., Krishnan, K. R., Servicingand Real-Time Control of Networks with .DynamicRouting, BSTJ, Vol. 60, No. 8, October, 1981.

3. Ash, G. R., Kafker, A. H., Krishnan, K. R., IntercityDynamic Routing Architecture and Feasibility,Proceedings of the Tenth International TeletrafficCongress, Montreal, Canada, June, 1983.

4. Ash, G. R., forthcoming BLTJ paper on TSMR.

5. Bulfer, A. F., Blocking and Routing in Two-StageConcentrators, National TelecommunicationsConference, December 1-3, 1975, New Orleans, La.

6. Carroll, J. J., DiCarlo-Cottone, M. J., Kafker, A. H.,"4ESSl Switch Implementation of DynamicNonhierarchical Routing, GLOBECOM 1983,November 28 - December 1, 1983, San Diego, Ca.

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