Optical routing of asynchronous, variable length ... - Semantic Scholar

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 18, NO. 10, OCTOBER 2000

Optical Routing of Asynchronous, Variable Length Packets Lubo Tanˇcevski, Member, IEEE, Siva Yegnanarayanan, Gerardo Castanon, Student Member, IEEE, Lakshman Tamil, Member, IEEE, Francesco Masetti, and Tom McDermott, Member, IEEE

Abstract—We discuss the introduction/implementation of optical IP routers, then we introduce a novel scheduling algorithm incorporating void filling and aimed at optical routing of asynchronous, variable packet length packets. We describe its structure and discuss the complexity issues. Albeit introduced with the purpose of cancelling the expensive optical synchronization, we argue that this approach represents the most viable all-optical approach for implementing packets-over-SONET (IP-centric scenario). We also present simulations under self-similar traffic conditions which point to the inefficiency of optical buffering to combat the effects of self-similarity, and we outline alternative strategies for proper buffer dimensioning. Index Terms—Optical packet switching, optical routing, selfsimilar traffic.

I. INTRODUCTION

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RESENT-DAY communication networks are being characterized by the explosive growth of the Internet and Internet-related services, as well as the widespread deployment of WDM transmission capabilities. The former has created a tremendous bandwidth bottleneck to the point where the term "broken network" has emerged; the latter has provided bandwidth solution for the bottleneck courtesy of the terabit WDM transmission systems. However, the available bandwidth usually comes in large wavelength pipes, and utilizing the potential to the fullest requires complex and often massively parallel electronic IP routers [1]. All-optical packet switching, on the other hand, stands to deliver terabit switching capacity, transparency, scalability, as well as natural integration within the WDM transmission framework [2]–[9], [17]. The majority of the approaches center on implementing an optical ATM switch, operating in synchronous regime, and using SDH/SONET as a data link layer transporting fixed length cells, with the usual overhead associated with the ATM/SONET transport [5]. Its realization, however, has been hindered by the complexity and high cost of the optical hardware and by the lack of sophisticated optical memories, to the point where it becomes important

Manuscript received October 21, 1999; revised May 5, 2000. L. Tanˇcevski, G. Castanon, and F. Masetti are with Alcatel Corporate Research Center, Richardson, TX 75081 USA (e-mail: [email protected]). S. Yegnanarayanan was with Alcatel Corporate Research Center, Richardson, TX 75081 USA. He is now with Cognet Microsystems. L. Tamil was with Alcatel Corporate Research Center, Richardson, TX 75081 USA. He is now with Yotta Networks, Inc. T. McDermott was with Alcatel Corporate Research Center, Richardson, TX 75081 USA. He is now with Chiaro Networks. Publisher Item Identifier S 0733-8716(00)09027-2.

to direct efforts toward reducing the optical hardware requirements by innovative, if not somewhat radical, solutions. In this paper, we identify optical packet synchronization as one of the most arduous and complex tasks. In the electronic domain, synchronizers are usually associated with electronic memories capable of storing packets for any desired amount of time. Optical memories, however, are based on fiber delay lines (FDLs) which delay the packets on-the-fly and are very inflexible compared to their electronic counterparts [4]. This results in the need to build complex optical synchronizers: one for every wavelength of every input fiber, each comprising many delay lines and optical switches. Two synchronizers were developed in KEOPS [10], [11]: a coarse one comprising five slow switches, and a fine one comprising three fast switches. Each incoming signal will have to traverse both synchronizers. At the same time, in the broadcast-and-select architecture (developed within KEOPS [9] but also investigated elsewhere [7]), a switches from input to output, where signal will traverse is the buffer depth. For moderate buffer depths – , it turns out that the hardware overhead for performing synchronization is nearly 50%. Abolishing the input synchronization substantially reduces the cost, but it requires more complex scheduling algorithms, able to schedule new arrivals on an asynchronous basis. In a sense, this represents a shift in complexity away from the optical domain and more into the electronic/software domain. In addition, FDL buffers work well under time-slotted operation, but exhibit excess losses when operated under asynchronous conditions. It is the purpose of this paper to introduce the terminology and requirements for scheduling algorithms capable of asynchronous and/or variable packet length operation, and to describe one particular algorithmic realization, named void filling, aimed at reducing the excess losses in asynchronous/variable length operation. The organization of the paper is as follows. In Section II, we introduce the basic terminology and we investigate the main issues arising in asynchronous operation. We identify the excess load as a main loss mechanism in asynchronous operation. In Section III, we describe a scheduling algorithm incorporating void filling aimed at reducing the excess load and improving the performance. We argue that intelligent scheduling can help improve the performance markedly, almost restoring the performance to the levels of synchronous operation. Section IV is divided into two subsections where we discuss practical realization issues. The first subsection is concerned with the complexity of the scheduler, and we outline methods which can help reduce the complexity. The second subsection deals with the issue of buffer dimensioning under realistic traffic conditions, where we present cal-

0733–8716/00$10.00 © 2000 IEEE

ˇ TANCEVSKI et al.: OPTICAL ROUTING OF ASYNCHRONOUS, VARIABLE LENGTH PACKETS

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Fig. 1. Logical diagram of the routing switch.

culations made under self-similar traffic. We point to the inefficiency of optical buffering to combat the effects of selfsimilarity, and outline alternative strategies such as nondegenerate buffers, massive multiserver queues, traffic shaping, reducing the traffic load, and implementing multiple-path routing schemes. Finally, we give a brief conclusion. II. ASYNCHRONOUS OPERATION Fig. 1 depicts a generic model of an all-optical router used throughout. Input packets arrive at many wavelengths at many input fibers asynchronously. Their arrivals are sensed, the headers separated from the payloads, and the packets are time-stamped. Simultaneously, fixed delay lines are inserted into the payload path to compensate for the time required to process the header. (The header could be processed electronically—for all-optical tag switching, see [12].) Processing the header assumes performing address lookup to determine the output fiber, performing scheduling to determine the time and wavelength to leave, and performing switch control for possible reconfiguration of the switch. A packet is transported into the buffer by means of a strictly nonblocking space switch only after these processing operations are completed. The packet is transported out of the buffer again using a strictly nonblocking architecture. The only assumption made is that every packet within the buffer should have a distinct wavelength, so that full internal speedup factor in wavelengths is assumed. Thus, the number of internal wavelengths within the switch is higher than the number of external or transport wavelengths per fiber (the speedup in wavelength can always be partially offset by speedup in space [9]). While in electronic routers the switching matrix can assume various forms such as high-speed bus, shared memory, or crossbar, only the crossbar option is viable in optical switching. Further, while the output cards in electronic routers can perform scheduling, in the optical domain the scheduling will have to be performed before the packet is admitted to the buffer. Finally, note the apparent absence of input and output synchronizers. Reducing the entire optical switch to nonblocking parts and a buffer, as done in Fig. 1, helps describe the relations in terms of a link scheduler. The problem, then, is to develop a link scheduler capable of fast scheduling of optical packets. and arriving at times Assume two packets with lengths and , and contending for the same output, as depicted in

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Fig. 2. Output relations of a 2 2 switch with one wavelength per fiber, in case of asynchronous operation. t is arrival times; L is packet lengths; is fixed processing overhead; is amount of delay in the optical FDL buffer.

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Fig. 2 for a 2 2 switch. will have to be delayed in the FDL . buffer for an amount which can only be If the inequality holds (true in most cases due to asynchronous arrivals), the output distribution of the packets features a gap or void between the two packets. If nothing is done to access that stretches all the way void, it will appear as if the first packet to the second packet, and hence as if the traffic load has been increased. Thus, the process of creation of voids in the output distribution results in excess load. This phenomenon has also been postulated in [13]–[15], and it is one of the most important loss mechanisms in asynchronous operation, impairing the performance sizably. It should be stressed that the effect occurs solely due to the large granularity of the optical FDL buffer—electronic buffers operate on a much finer granularity and can delay the packet for almost an arbitrary amount, hence no voids are present. Before evaluating numerically the excess load and the impairment it induces in the system performance, a few early observations are in order. The size of the voids, and therefore the associated excess load, depends on the distribution of packet lengths , and on the distribution of interarrival times , both of which are crucial traffic parameters. On the other hand, it depends on the amount of delay which is intimately connected to the granularity of the FDL optical buffer, and is therefore a switch parameter. Any attempt to minimize the excess load must therefore take into account some kind of matching between the traffic parameters and the switch parameters or, in other words, any change of traffic characteristics in the future will impact the switch performance. In order to test numerically the asynchronous performance, the usual bursty traffic model was used with source burstiness [17], [18]. The traffic is modeled as a superposition of many ON/OFF sources, one per every input channel. Each source is a succession of ON and OFF periods, with the duration of both periods obeying the geometric distribution. ON periods correspond to bursts of many IP packets, OFF periods to interarrival times. Within the ON period, all the packets are assumed to be going to

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Fig. 4.

(a)

(b)

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Fig. 3. Traffic performance of a 4 4 switch with 4 wavelengths per fiber, under bursty traffic with burstiness 4 and traffic load 0.74: (a) probability of packet loss versus the buffer depth for synchronous operation (dashed line), asynchronous operation (full line), and synchronous operation taking into account the excess load in (b) (dotted line); (b) excess load versus the buffer depth in case of asynchronous operation.

the same destination, but are scheduled independently. ON periods on a same source are assumed to be uniformly distributed among output fibers. A parameter in this model is the burstiness, which is defined as an average duration (in time slots) of the ON/OFF periods. Throughout, burstiness of 4 was assumed. In order to obtain an asynchronous model, the duration of the OFF periods was allowed to drift in both directions with uniform distribution. ON periods were assumed to be always 400 bytes in length. The simulated switch was a 4 4 fibers nonblocking switch with four wavelengths per fiber and a WDM buffer acting logically as output queue. The traffic load was 0.74. The results of the simulation are depicted in Fig. 3. On Fig. 3(a), the dashed curve represents the probability of packet loss versus buffer depth (number of delay lines in the FDL buffer) for the case of time-slotted operation where the packet durations are always 400 bytes, the basic delay line unit in the FDL buffer (buffer granularity) is also 400 bytes worth and arrivals are synchronized. The curve with full line represents the same in the case of asynchronous traffic. The conditions are exactly the same, only the packet arrivals are allowed to drift randomly, with granularity of 1 byte. Note the sizable deterioration in performance indicative of the additional losses which are present in asynchronous traffic. The computed excess load, defined as a ratio of the generated voids over the total number of transmitted packets,

Same as Fig. 2 with void filling.

is presented in Fig. 3(b)—it can measure as high as 0.3 and is one of the main reason for the incurred losses. To test this hypothesis, we have computed the probability of packet loss for the synchronous case taking into account the excess load in Fig. 3(b), represented with dotted line in Fig. 3(a) (when calculating dotted curve on Fig. 3, whenever the total load was 1, it was clipped to 1 to represent output conditions). Note that the curves for asynchronous (dashed line) and synchronous operation taking into account the excess load (dotted line) are very close, demonstrating that the excess load is the dominating loss mechanism in asynchronous operation. From above considerations, it is obvious that asynchronous operation will result in unacceptably high losses. Thus, the attempt to simplify the optical hardware requirements by abolishing synchronization will only make sense if procedures are installed to reduce the loss amount and improve the performance. We next show how intelligent scheduling algorithms can be employed to this end. III. THE VOID FILLING SCHEDULING ALGORITHM It is possible to reduce the amount of void space by scheduling packets to appear in the empty spaces, thereby filling the voids. This can best be understood by inspecting Fig. 4. The situation is exactly the same as the one depicted in Fig. 2, except that a third arrival at time (packet length ) contends for the same output. In this scenario, is transported undelayed and it appears at the (which is being delayed for ) such that the output before and is being partially filled. This amounts void between to reducing the void space, and it should result in reduction of the excess load. It also amounts to breaking the sequence of the packets, as the packet which arrived later, , is being transported ahead of the previous arrival, . However, the entire operation could be structured such that it is still FIFO preserving on a per flow basis, without noticeable consequences. We call any class of such intelligent scheduling algorithms void filling. We proceed in describing one possible realization. Fig. 5 outlines one particular realization of the void filling algorithm being implemented and tested here. Virtual wavelength fields are created for each output fiber storing the time relations among the packets destined for that output. The start time, the end time, and the wavelength of any present void is stored in memory (electronic). When a new packet arrival is sensed, it is time-stamped. The address lookup determines the output link to which that particular packet needs to be directed. After that, the virtual wavelength fields for all the wavelengths on that particular output are recreated and the packet is tested for filling any


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(a)

Fig. 5.

Block diagram of the void filling scheduling algorithm.

of the existing voids. This usually assumes testing whether the packet can be delayed such as to fit into a void. If successful, the packet is assigned time to leave and is transported into the buffer. If not, a conventional scheduling commences such that the algorithm searches for a virtual wavelength field with minimum duration and tries to schedule the packet for that field. If there is an available delay of sufficient length, the packet is given time to leave and transported into the buffer; but also, the characteristics of any new void created in this process are stored. If not, the packet is dropped. Evidently, the process involves two separate phases: filling the voids is given priority; and failing to fill a void, conventional scheduling is commenced (the conventional scheduling was used for the calculations in Fig. 3 in the previous section). Better understanding can be gained from Fig. 6. Consider a new packet arrival at time labeled current time. Fig. 6(a) depicts the virtual wavelength fields for the particular output fiber. In the example, there are 4 wavelengths per fiber and the buffer depth is 3. The delay lines in the FDL buffer are depicted as . The existing voids are labeled as and, as an example, in Fig. 6 there is memory space for 4 voids. First, a check is required whether there is delay line (including delay line of length 0) to advance the packet such that it coincides with a void. On can place the packet within and delay Fig. 6(a), delay line can place it within . Hence, voids and are inline accessible and need not be considered further. The next step involves checking whether the new packet can fit within either or and is depicted in Fig. 6(b). In Fig. 6(b) the new packet can fit within . The packet is then assigned wavelength to leave , time to leave and is then transported into the buffer to be delayed for . Further, the void information needs to be updated. Because all the memory positions have already been occupied (there is space for 4 voids and 4 voids have been

(b)

(c) Fig. 6. Graphical representation of the virtual wavelength fields for a switch with buffer depth 3 and 4 wavelength per fiber. (a) General description before the packet arrival. (b) Scheduling according to the void filling part of the algorithm. (c) Scheduling according to the conventional part of the algorithm. V is stored voids; X available delay lines; current time is time of the new packet arrival; holding time is maximum delay line available.

recorded), there is a need to update the void information as outlined in Fig. 6(b). First, the void space between the start of and start of is being discarded—we call this discard mechanism 1. Then, the new void information is recorded. Suppose now that the new packet is very long so that it does or . In this case, the second phase of the not fit in either scheduling—the conventional scheduling—commences, as out-

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400 bytes (the size of the packet), void filling gives exactly the same results as conventional scheduling—voids are smaller in length than 400 bytes and no packet can be fitted. Again, there is a well-pronounced optimum which occurs at much larger delay line lengths (around 2000 bytes). After 2000 bytes, however, the increasing excess load due to the larger delay line lengths starts dominating over the efficiency of the algorithm to fill the voids, and therefore the performance deteriorates. Finally, note the distinctive submodulation occurring exactly at 400 bytes interval. This can be ascribed to the fact that although the OFF periods in the model randomly drift in both directions, the most probable value is still 400 bytes, facilitating the process of void filling. The existence of optimum delay line length in both curves confirms the early observation that the switch parameters (the delay line length) will have to be matched to the traffic parameters in order to arrive at an optimum performance point. Fig. 7. Spectral dependence of the probability of packet loss for buffer depth 10 for asynchronous traffic with packet length 400 bytes: dashed line indicates conventional scheduling; full line indicates void filling with electronic memory space for 40 voids; dotted line indicates void filling with electronic memory space for 200 packets.

lined in Fig. 6(c). The algorithm searches for a virtual wavelength field with minimum length, in this case . Next, it is checked whether there is at least one delay line larger than the minimum length. If so, the new packet is assigned time and wavelength to leave [for the case of Fig. 6(c), time and wavelength ] and is transported into the buffer. In the process, a new void is created and the parameters of the void need to be stored, possibly through overwriting an existing void space as indicated in the figure—we call this discard mechanism 2. If not, the packet is dropped. It should be stressed that the second part of the scheduler is very similar to the horizon scheduling [22] or the LAUC scheduler [23]. The outlined algorithm should strictly be understood as a skeleton upon which many possible realizations could be built. For instance, this particular realization assumes inspecting the toward , and many voids in round-robin fashion, from other variants are possible. Further, the strict memory limitations for storing voids impose some kind of discarding mechanism, and many variants are also possible. To demonstrate the effectiveness of the void filling scheduling algorithm, we present simulations under the same asynchronous traffic and switch parameters assumed in Fig. 3. As pointed out earlier, for an optimal performance, the router parameters will have to be matched to the traffic parameters. This translates into matching the length of the basic delay line in the FDL buffer (buffer granularity) to traffic parameters. In Fig. 7 we plot the so-called “spectral dependence,” that is, the dependence of the probability of packet loss on the length of delay line unit. The calculations are for buffer depth 10. Dashed line depicts the curve for asynchronous operation without void filling. Note the existence of an optimum delay line length around 200 bytes, after which the probability increases, mainly due to the fact that large delay lines will introduce larger amount of excess load. Shown with a full line is the calculation for the case when void filling is implemented. The electronic memory space is enough for 40 voids in this case. Note that for delays below

IV. PRACTICAL IMPLEMENTATION ISSUES In this section, we attempt to provide arguments pertinent to some of the practical issues which will arise in any implementation of the optical routers. Subsection A deals with some of the complexity issues of the void filling scheduling algorithm. Subsection B seeks to provide connection to realistic traffic conditions through discussion of the effects of the self-similarity of the Internet traffic on the performance of the optical router. These arguments fall into the general framework of buffer dimensioning and provisioning of the available optical resources. A. Complexity Issues It is of great importance to ensure that the resulting scheduling algorithm does not inflate the complexity beyond practical realization. As a standard criterion, one should take the complexity of the present-day address lookup algorithms which are capable of performing up to 40 million lookups per second [20]. (This is true for the case of longest prefix match; multiprotocol label switching, MPLS, further facilitates this operation.) The goal then would be to optimize the scheduling in such a way that it is capable of scheduling comparable number of packets per second. This usually assumes translating the algorithm into some kind of data structure and then optimizing the number of memory accesses, and it is a subject of current and future work. Rather, here we outline some guidelines which should be taken into consideration. The complexity of the algorithm depends on: 1) the number of transport wavelengths per fiber; 2) the number of stored voids, that is, the size of the electronic memory; 3) the number of distinct delay lines in the FDL buffer, that is, the optical buffer depth. Conditions 1 and 2 contribute to the complexity by increasing the number of voids which need to be inspected in each scheduling, and are in that sense interrelated. Condition 3 increases the checking time to determine whether there is available delay capable of delaying the packet such that it coincides with an existing void. Condition 1: As evident from Fig. 6, an essential part of the algorithm is interleaving among all the transport wavelengths at that particular output fiber. This represents implementing multiserver queues, and is a very effective method for improving the


performance in terms of probability of packet loss [9]. From that perspective, having a large number of transport wavelengths is extremely important. However, that translates into large number of voids which need to be filled, increasing the complexity. On the other extreme, parallelization to such an extent that there is one scheduler for every wavelength is possible and will increase the speed considerably, but will cancel any benefit stemming from the wavelength interleave and result in unacceptable performance. The most appropriate solution will likely be somewhere in the middle such that there is some degree of parallelism and each scheduler performs wavelength interleave over a subset of the available wavelengths. This falls well in line with the following considerations: a) introduction of different classes of services will likely necessitate some kind of bandwidth (and buffer) provisioning scheme, such that a separate scheduler is assigned per separate class of services operating only over a wavelength subset assigned to that particular class of service in conjunction with appropriate buffer management schemes; b) tunability of the wavelength converters over the entire set of transport wavelengths is very difficult to achieve, and the more immediate solution will be to provide limited tunability over a wavelength subset. Condition 2: Increasing the size of the electronic memory, such that many more voids can be stored, increases the complexity. On the other hand, it also improves the performance as the void filling becomes more effective in reducing the excess load. Again, there exists an optimum regarding the size of the electronic memory space. Fig. 7 provides support for these arguments. The full line represents the spectral dependence in the case of electronic memory space for 40 packets, and the dotted line represents space for 200 packets. Observe the improvement in performance, which is indicative of the fact that the discard mechanism 2 [outlined in Fig. 6(c)] is reduced. However, the discard mechanism 1 [indicated in Fig. 6(b)] still takes place, and is the predominant mechanism for reducing the efficiency of the void filling process. Obviously, further reduction in the excess load and improvement in performance can be obtained by modifying the discard mechanism 1 to take into account larger electronic storage space. Condition 3: The number of delay lines, or the buffer size, is likely to be determined by the traffic characteristics. Even though ideally one would like to implement as large an optical buffer as possible, and even though this would increase the complexity of the scheduler, it is likely that due to practical problems (some of which will be discussed in the next section), the number of delay lines will be fairly modest. B. Self-Similar Traffic Calculations In the calculations already presented, we assumed for clarity the usual bursty traffic model. However, recent measurements and observations have confirmed that Internet traffic is self-similar in nature, and its characteristics cannot be truly represented by conventional bursty traffic models [21], [24]. In order to provide a connection to more realistic conditions, we next discuss the optical switch performance under self-similar traffic conditions. In order to investigate the effects of self-similar traffic, we have implemented a self-similar traffic model based on superposition of many ON/OFF sources [15], [26]. It has been proven

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that superposition of many ON/OFF sources, each having infinite variance, can lead to a self-similar aggregate traffic [25]. One possible distribution for the length of the ON/OFF periods is the Pareto heavy tailed distribution where the duration of the ON bytes , and OFF periods is given by indiwhere is a random variable uniform on [0, 1], and cates the floor function. ON periods represent bursts of packets, OFF are interarrival times. However, individual packets within the burst (ON period) are not switched independently, as was the case in the bursty traffic models; rather, the entire burst is being treated as a single entity. Bursts are again distributed among all the outputs with uniform distribution. The parameter bytes represents the minimum duration of the periods and is chosen to be 400 bytes in our calculations. It also helps implement asynchronous, variable packet length operation. The parameter measures the heaviness of the tails of the distribution, and for [26]. The infinite variance it is necessary that measurement of the strength of fractal coupling is represented through a parameter called Hurst parameter , and it serves as a measure for the degree of self-similarity. For self-similar and the traffic is more self-similar as traffic, approaches 1. Measurements at Bellcore have established , albeit for Ethernet traffic [24]. Given such a traffic model, there is one-to-one relationship between the heaviness of the tails of the Pareto distribution and the Hurst parameter, [25]. Presented in Fig. 8(a) is the speci.e., tral dependence for buffer depth 10 obtained under self-similar , for a 16 16 switch traffic with Hurst parameter . Three cases were inwith 16 /fiber and traffic load vestigated. . In this 1) Synchronized traffic, obtained by fixing bytes scenario, the packets have variable sizes which are integer multiples of one time slot, and arrivals are synchronized to the beginning of a time slot, the delay line length granularity being one time slot as well. This type is represented with a dashed line as a floor for comparison purposes. 2) Asynchronous traffic without void filling is represented with a dotted line. 3) Asynchronous traffic with void filling is represented with a full line. Observe that void filling improves the performance and drives it very close to the floor of synchronized traffic. Depicted in Fig. 8(b) are calculations of the buffer depth dependence. Two features are visible. First, the performance is seriously degraded because of the self-similarity of the traffic and the probability of packet loss increases to unacceptably high levels. Second, the probability of packet loss decays very slowly with increasing the buffer depth. The same phenomenon has been observed when buffering packet in the electronic domain [27], and the results are well in line with calculations in [28]. The argument behind these observations is that since selfsimilarity means variability or burstiness at vastly different time scales, huge buffers are needed to smooth out the traffic at different time scales, as opposed to smoothing out Poisson traffic which is bursty only on the time scale defined by the arrival rate. Hence, the probability of packet loss decays exponentially with buffer depth in case of Poisson traffic, but it decays hyperbolically or it features heavy tails itself in the case of self-similar

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(a) (a)

(b) (b) Fig. 8. Self-similar simulation for Hurst parameter H = 0:9 and traffic load = 0:8 and (a) spectral dependence; (b) buffer depth dependence.

traffic. The simulations point to the fact that huge buffers, for the case depicted here in the range of several thousand delay lines, will be needed to improve the performance to acceptable levels. While expensive, this is still possible in the case of electronic memories. In the case of optical buffers this is, at present, clearly beyond any hope of practical implementation. As such, however, it points to a valuable argument, that optical routers will likely have small optical buffers (buffer depth of around 10 delay lines), and alternative mechanisms for combating the effects of self-similarity will likely have to be implemented. In the following, we outline some of the alternative strategies which fall into the category of traffic shaping, buffer dimensioning, and provisioning of the available optical resources. • It is possible to emulate large optical memories using a relatively small number of FDL lines (limited buffer depth) by using nonuniform distribution of the fiber delay lines [3], [5], [8], [19]. In effect, this results in buffers with large holding time, but it also results in voids in the output distribution of packets acting as an excess utilization even in the case of perfectly synchronized fixed length packets [19]. Hence, a scheduling algorithm similar to void filling will have to accompany such FDL buffers. As indicated in [19], when highly successful in filling the voids, the buffers, albeit with limited buffer depth, emulate buffers with much larger buffer depth. This could prove to be a very effective way of combating the effects of self-similarity, especially

Fig. 9. Self-similar simulation for Hurst parameter H = 0:7 and traffic load = 0:8: (a) spectral dependence and (b) buffer depth dependence.

in multistage architectures such as SLOB, as suggested by results in [29]. • Increasing the number of transport wavelengths per fiber, and interleaving the packets among the available wavelengths, that is, implementing massive multiserver queues, is a very effective way of improving the performance [9]. This is even more important in view of the argument that the buffer depth of the FDL buffer is likely to be small. However, in order to have successful implementation, tunable wavelength converters with fast tunability, good precision, and wide range of tuning are of crucial importance. While this subject remains under rather vigorous investigation, it needs to be stressed that providing massive multiserver queues is one of the most effective strategies available for combating the effects of self-similar traffic. • Another alternative avenue is to introduce mechanisms for reducing the degree of self-similarity. Before providing a discussion about possible means of achieving this, inspect Fig. 9. Depicted are calculations of the spectral and . Observe buffer dependence for Hurst parameter that the probability of packet loss in Fig. 9(b) is lower [Fig. 8(b)]. Althan the corresponding one for though the tail decay with buffer depth is still hyperbolical, it is steeper than the tail decay in Fig. 8(b), indicating a reduction in the buffer depth. Also observe that the optimum delay line length in the FDL buffer, for the case of void filling, is 2500 bytes [as opposed to 5000 bytes , Fig. 8(a)], and for the case when no void for


(a)

(b) Fig. 10. Traffic load influence: (a) Probability of packet loss versus traffic load for a self-similar traffic with Hurst H 0:9 and number of wavelengths per fiber as a parameter indicated with numbers. (b) Traffic load versus the Hurst parameter for 64 wavelengths per fiber and probability of packet loss 10 . An 8 8 switch is assumed with buffer depth 6 and delay line length 5000 bytes.

=

2

filling is applied it is 100 bytes [as opposed to 500 bytes in Fig. 8(a)]. This is a confirmation of the postulate stated in Section II that for an optimal performance, the switch parameters (delay line length) will have to be matched to the traffic parameters (Hurst parameter). As stated before, Ethernet traffic measurements have established Hurst pa[24]. However, there are some expecrameter tations that massive time multiplexing in order to arrive to a 10-Gb/s stream in the optical backbone will help disperse some of the correlations introduced by the TCP layer and responsible, in part, for such a high Hurst parameter, so that lower Hurst parameters might be observed in optical backbones. In addition, traffic shaping can be implemented at the edges of the network to reduce the Hurst parameter [30]. In the optical domain, traffic shaping is likely to take place in the form of creation of optical packets, which are an assemblage of many individual IP packets, and which can have either fixed duration in time (1.6 s as defined in KEOPS [10]), or can be assembled into bursts of variable length [22]. Even though the rationale for in-

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troducing the optical packet sublayer is to reduce the processing overhead in order to arrive to terabit switching capacity, its potential effect on traffic shaping could prove useful in driving the Hurst parameter to lower values. For an extensive discussion on traffic shaping techniques in relation to self-similar traffic, see [31]. • Further improvement in performance can be gained by decreasing the amount of traffic load per link. While this seems a rather trivial solution, it should be stressed that it is the current thinking among the ISPs and Telcos where overprovisioning network bandwidth and keeping the network lightly loaded is a common practice. Indeed, at present, links are operated at low utilization even at peak rates. From that perspective, dimensioning of the optical routers to effectively sustain 0.6–0.7 traffic load will already be a worthwhile undertaking. • The inability to deploy massive FDL buffers can be offset partially by buffering the packets in the network. This usually assumes either deflection routing, where packets are randomly deflected, or more intelligent schemes such as multiple-path routing, where the packets are given more than one path through the network [32]. The effects of some of the outlined strategies for combating the deleterious effects of the self-similar traffic are visible in Fig. 10. Simulations of the probability of packet loss as a function of the traffic load are presented in Fig. 10(a), with the number of wavelengths per fiber as a parameter. An 8 8 switch was assumed with buffer depth 6, delay line length of 5000 . bytes, and self-similar traffic with Hurst parameter From Fig. 10(a) it is evident that: 1) a large number of wavelengths improve the performance to a great extent; 2) reducing the traffic load is a very efficient way of attaining acceptable performance even in wildly self-similar traffic. Any change of the traffic parameters (the degree of self-similarity) can lead to change in the bandwidth utilization, as evident from Fig. 10(b), where 64 wavelengths per fiber are assumed and probability of is used as a parameter. Importantly, reducpacket loss of tion in the Hurst parameter can allow the lines to be utilized better. In summary, the self-similar nature of the Internet traffic will require massive buffers which cannot be sustained in the optical domain. From that perspective, it is likely that future all-optical switches will employ moderate FDL buffers (buffer depth ), and so, alternative strategies for combating the effects of self-similarity will have to be employed. These strategies include (but are not limited to): emulating large optical memories through the nondegenerate buffer paradigm; deploying massive multiserver queues (large number of transport wavelengths per fiber); reduction of the degree of self-similarity through some form of traffic shaping (such as massive time multiplexing or creation of optical packets or processes at the application layer); reducing the traffic load per link; and implementing intelligent routing schemes of the like of multiple-path routing. It needs to be stressed that the effects of the self-similar traffic are equally deleterious for time-slotted operation. At high traffic loads, the asynchronous operation exhibits similar performance as the time-slotted one because the losses are mainly due to the self-similar nature of the traffic. At moderate-to-lower traffic

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loads, the excess load in asynchronous operation will start dominating, and the performance will be worse than the time-slotted operation. For that reason, implementing the void filling scheduler becomes important. V. CONCLUSION All-optical routing could prove to be a viable alternative to electronic routing by providing terabit switching capacity. Simple translation of existing electronic solutions into the optical domain, however, may not be the most cost-effective and straightforward way, due to the specifics of the optical components/subsystems. More specifically, the cost of the existing optical hardware and the lack of sophistication on the part of existing optical memories (FDL buffers) makes the process of performing input/output synchronization a difficult and complex undertaking. Asynchronous operation, however, will result in excess load stemming from the unusually coarse granularity of optical FDL buffers, which will deteriorate the system performance markedly. In order to attain an acceptable performance, an intelligent scheduling algorithm is needed—an example of which (void filling) was described in this paper. Its applicability, however, extends beyond the asynchronous operation, as it can be used to reduce the excess load when buffers with nonuniform distribution of the delay lines are used even in time-slotted mode of operation with the purpose of emulating large optical memories. Further, the approach represents the most viable implementation of the packets-over-SONET (IP centric) scenario in optics. In conventional routers, IP packets are chopped in cells at the input interfaces, switched, and then reassembled at the output. Clearly, this implementation is not very straightforward in the optical domain, and hence asynchronous switching of IP packets is the more viable alternative. For the purpose of providing connection to real-time traffic parameters, we provide calculations under self-similar traffic conditions. The initial explorations, well in line with established observations in the electronic domain, confirm that massive buffers will have to be employed to combat the deleterious effects of self-similarity. In line with the clear impracticality of building massive FDL optical buffers, this conclusion represents an important guideline for buffer dimensioning—future all-optical routers will likely have small FDL buffers, and alternative strategies are likely to be employed. Briefly touching on the domain of buffer dimensioning and provisioning of available optical resources, we discuss alternative strategies for combating the effects of self-similarity, such as: implementing massive multiserver queues, reducing the degree of self-similarity by traffic shaping procedures, reducing the link load, and implementing multiple-path routing schemes. More serious work is needed to attest to the validity and applicability of each of these schemes. ACKNOWLEDGMENT The authors wish to acknowledge the help of J. Vanhoutte and G. Chiruvolu from Alcatel CRC. Numerous discussions with them have proven invaluable in preparing and presenting some of the arguments of this paper.

REFERENCES [1] . [Online]. Available: http://www.pluris.com [2] F. Masetti et al., “High speed, high capacity ATM optical switches for future telecommunication transport networks,” IEEE J. Select. Areas Commun., vol. 14, pp. 979–998, June 1996. [3] D. K. Hunter, W. D. Cornwell, T. H. Gilfedder, A. Franzen, and I. Andonovic, “SLOB: A switch with large optical buffers for packet switching,” J. Lightwave Technol., vol. 16, pp. 1725–1736, Oct. 1998. [4] D. K. Hunter, M. C. Chia, and I. Andonovic, “Buffering in optical packet switches,” J. Lightwave Technol., vol. 16, pp. 2081–2094, Dec. 1998. [5] C. Guillemot et al., “Transparent optical packet switching: The European ACTS KEOPS project approach,” J. Lightwave Technol., vol. 16, pp. 2117–2134, Dec. 1998. [6] A. Carena, M. D. Vaughn, R. Gaudino, M. Shell, and D. J. Blumenthal, “OPERA: An optical packet experimental routing architecture with label swapping capability,” J. Lightwave Technol., vol. 16, pp. 2135–2145, Dec. 1998. [7] A. Misawa, Y. Yamada, M. Tsukada, K. Sasayama, K. Habara, T. Matsunaga, and K. Yukimatsu, “A prototype broadcast-and-select photonic ATM switch with a WDM output buffer,” J. Lightwave Technol., vol. 16, pp. 2202–2211, Dec. 1998. [8] Z. Haas, “The staggering switch: An electronically controlled optical packet switch,” J. Lightwave Technol., vol. 11, pp. 925–936, May/June 1993. [9] S. L. Danielsen et al., “WDM packet switch architectures and analysis of the influence of tuneable wavelength converters on the performance,” J. Lightwave Technol., vol. 15, pp. 219–227, Feb. 1997. [10] P. Gambini et al., “Transparent optical packet switching: Network architecture and demonstrators in the KEOPS project,” IEEE J. Select. Areas Commun., vol. 16, pp. 1245–1259, Sept. 1998. [11] L. Zucchelli, D. Di Bella, G. Fornuto, P. Gambini, D. Re, F. Delorme, R. Kraehenbuehl, and H. Melchior, “An experimental optical packet synchroniser with 100 ns range and 200 ps resolution,” in Proc. ECOC’98, Madrid, Sept. 1998, pp. 587–588. [12] D. J. Blumenthal, A. Carena, L. Rau, V. Curri, and S. Humphries, “WDM optical IP tag switching with packet-rate wavelength conversion and subcarrier multiplexed addressing,” in Proc. OFC’99, San Diego, Feb. 1999, Paper ThM1. [13] S. L. Danielsen, P. B. Hansens, and K. E. Stubkjaer, “Wavelength conversion in optical packet switching,” J. Lightwave Technol., vol. 16, pp. 2095–2108, Dec. 1998. [14] P. B. Hansen, S. L. Danielsen, and K. E. Stubkjaer, “Optical packet switching without packet alignment,” in Proc. ECOC’98, Madrid, Sept. 1998, pp. 591–592. [15] L. Tanˇcevski, A. Ge, G. Castanon, and L. S. Tamil, “A new scheduling algorithm for asynchronous, variable length IP traffic with void filling,” in Proc. OFC’99, San Diego, Feb. 1999, Paper ThM7. [16] L. Tanˇcevski, G. Castanon, and L. Tamil, “Optical IP packete transport: A granularity perspective,” in Proc. OSA Photonics Switching’99, Santa Barbara, July 1999, pp. 61–63. [17] S. L. Danielsen, C. Jorgensen, B. Mikkelsen, and K. E. Stubkjaer, “Analysis of a WDM packet switch with improved performance under bursty traffic conditions due to tuneable wavelength converters,” IEEE/OSSA J. Lightware Technol., vol. 16, pp. 729–735, May 1998. [18] S. Liew, “Performance of various input-buffered and output-buffered ATM switch design principles under bursty traffic: Simulation study,” IEEE Trans. Commun., vol. 42, pp. 1371–1379, Feb./Mar./Apr. 1994. [19] L. Tanˇcevski, L. S. Tamil, and F. Callegati, “Non-degenerate buffers: An approach for building large optical memories,” IEEE Photon. Technol. Lett., vol. 11, Aug. 1999. [20] . [Online]. Available: http://www.juniper.net/leadingedge/whitepapers/backbone-routers.fm.html [21] M. E. Crovella, M. S. Taqqu, and A. Bestavros, “Heavy-tailed probability distributions in the world wide web,” in A Practical Guide to Heavy Tails: Statistical Techniques for Analyzing Heavy Tailed Distributions, R. A. Adler, R. Feldman, and M. S. Taqqu, Eds. Boston: Birkhauser, 1998. [22] J. S. Turner, “Terabit burst switching,” J. High Speed Networks, vol. 8, no. 1, pp. 3–16, Jan. 1999. [23] Y. Xiong, M. Vandenhoutte, and H. C. Cankaya, “Design and analysis of optical burst-switched networks,” in Proc. SPIE All-Optical Networking 1999: Architecture, Control, Management Issues, vol. 3843, Boston, Sept. 1999, pp. 112–119. [24] W. E. Leland, M. S. Taqqu, W. Willinger, and D. V. Wilson, “On the self-similar nature of ethernet traffic,” IEEE/ACM Trans. Networking, vol. 2, pp. 1–15, Feb. 1994. (extended version).


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Lubo Tanˇcevski (S’93–M’95) received the Ph.D. degree in electrical engineering from the University of Ljubljana, Slovenia, in 1995. Since March 1998, he has been with Alcatel Corporate Research Center, Richardson, TX. His research interests include: IP/WDM transport, optical switching/routing, and optical internetworking.

Siva Yegnanarayanan, photograph and biography not available at the time of publication.

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Gerardo Castanon (S’95) received the Bachelor of Science degree in physics engineering from the Monterrey Institute of Technology and Higher Education (ITESM), Mexico, in 1987. He received the Master of Science degree in physics (optics) from the Ensenada Research Centre and Higher Education, Mexico, in 1989. He also received the Master and Ph.D. degrees in electrical and computer engineering from the State University of New York (SUNY) at Buffalo in 1995 and 1998, respectively. His dissertation topic was on transmission and teletraffic evaluation performance of high-speed optical packet switched networks. He was with the ITESM University between 1989–1992 as an Assistant Professor in the Department of Physics. In 1992, he joined the Department of Electrical and Computer Engineering at SUNY at Buffalo where he was supported by the Fulbright scholarship through his Ph.D. studies. Since January 1998, he has been a Research Scientist working with Alcatel Corporate Research Center, Richardson, TX, where he is doing research on IP over WDM, dimensioning and routing strategies for next generation optical networks and the design of all-optical routers. He is a member of the IEEE Communications and Photonics societies with a research interests in optical communication, optical amplifiers, performance evaluation of networks, ATM, WDM and wireless networks.

Lakshman Tamil (S’83–M’88) received the Ph.D. degree in electrical engineering from the University of Rhode Island, Kingston, RI. He is Founder, President, and CEO of Yotta Networks, Inc., Richardson, TX. He is concurrently a Full Professor of Electrical Engineering at the University of Texas at Dallas. He was heading optics research in Alcatel Corporate Research Center in Richardson and was the manager for Advanced Technology Platform Program in Terabit IP Optical Routers during 1997–1999. He has published well over 100 articles in the field fiber optics, transmission, switching and routing.

Francesco Masetti received the degree in electronic engineering and the Ph.D. degree in electronic engineering and computer science from the University of Bologna, Italy, and a post-graduation Master in Information Technology, from the Polytechnic of Milan, Italy. He carried out research and coordinated projects in Europe on ultra-high speed switching nodes and networks, both circuit- and packet-based, implemented with electronic and optical technologies. He has been the Location Director of the Alcatel Corporate Research Center in Richardson, TX, from 1997 to end 1999 and is currently director of strategic research activities on future high-speed, high-capacity backbone Internet routers.

Tom McDermott (M’85), photograph and biography not available at the time of publication.