The major source of errors in B-ISDN/ATM systems is expected to be buffer overflow during congested conditions, resulting in lost packets. A single lost or errored ATM cell will cause retransmission of the entire packet data unit (PDU) that it belongs to. The performance of the end-to-end system can be made much less sensitive to cell loss by means of forward error correction. In this paper, we present the results of a simulation study for an ATM network where forward error correction is performed at both the cell level and the PDU level. The results indicate that (i) cell losses are highly correlated in time, and analytical models ignoring this fact will not yield accurate results, (ii) the correlation of cell losses is similar to burst errors in digital communication, and similar code interleaving techniques should be used, (iii) coding cells and PDUs separately provides this interleaving effect, and this joint code outperforms coding only at the cell level or only at the PDU level in almost all cases simulated

Oguz Nihat Cem, Ayanoglu Ender

Bilkent University Institutional Repository

A Simulation Study of Two-Level Forward Error Correction for Lost Packet Recovery in B-ISDNIATM Nihat Cem O#uz Electrical and Electronics Eng. Dept., Bilkeni Uniuersitg, Ankara, 06533, Tbrkey Abstract The major source of errom in B-ISDN/ATM syrtenu is expected to be buffer overflow during congested conditions, resulting in lost packets. A single lost or errored ATM cell will cause retrans- w o n  of the entire packet data unit (PDU) that it belolags to. The performance of the end-bend system can be made much less sensitive to cell low by mema of forward error correction. In thia paper, we present the results of a aimulation study for an ATM network where forward error correction is performed at both the cell level and the PDU level. The results indicate that (i) cell losses are highly correlated in time, and analytical mod& ignoring thia fact wil l  not yield accurate results, (ii) the correlation of cell losses is similar to burst errors in digital com- munication, and similar code interleaving techniques should be used, (iii) coding cells and PDIJs separately provides this inter- leaving effect, and this joint code outperform coding only at the cell level or only at the PDU level in almost all cases simulated. 1 Introduction In high-speed integrated packet-switched networks such 88 the Broadband Integrated Services Digital Network (E ISDN) with the Asynchronous Zhnsfer Mode (ATM) packet protocoi, the end-bend propagation delay for a typical con- nection will be much larger than the duration of a packet. Consequently, retransmissions associated with the conven- tional error detection and Automatic Repeat nQuest (ARQ) mechanisms will cause degradation in the delay-throughput performance. In ARQ, each retransmission increments the delay of a packet by approximately the round-trip propaga- tion time. This is intolerable for many high-speed applica- tions, mpecially for those sensitive to both loss and delay, such as distributed proceseing and interactive computing. The problem of a large propagation delay with respect to the packet size is present in satellite and deep-space com- munications, where error correction techniques are employed to increase reliability. In a similar manner, it has been sug- gested to use Forward Error Correction (FEC) to improve reliability without increasing the end-bend delay in high- speed networks (11-[7]. The basic idea in FEC is to add redundant information to the original data so that the receiver can recover lost infor- mation using this redundancy, and hence, avoid retransmis- sions. In competition with this recovery capability, however, there is an oppoeite effect of FEC at work: adding redun- 1843 0-7803-o950-?J93/$3.WlW3IEEE Ender A yonojlu AT&T Bell Laboratories Holmdel, NJ, 077sS-30S0, USA dancy to the original data increases the load in the network, and in turn, the loea rate. FEC can be useful only when the former effect prevails. In this work, we simulated a long-distance connection through an ATM network, and quantified the improvement in delay-throughput performance achieved by using FEC. In ATM, the basic unit of transport, switching, and queue- ing is a 53-byte cell: 48 bytes of payload and 5 bytes of header.Cells are grouped into variable size packets, also known as Packet Data Units (PDUs), at  the ATM adap tation layer. While passing through the network, some of the cella are lost at congested switches. Therefore, some of the PDUs arrive at  the destination with missing cells. By transmitting parity cells along with the information-bearing ones, cell losses in some PDUs can be recovered. A PDU is considered lost if its missing cells cannot be recovered. Normally, the transmitter is informed of the lost PDUs, and they are retransmitted. Our principal motivation is the fact that the burstiness in cell losses strongly affects the perfor- mance of FEC. Therefore, in addition to coding over consec- utive cells, which is effective when cell losses are dispersed evenly or are “random,” we prop- coding over PDUs. Our results indicate this is quite effective in the case of burst cell loeseS. 2 Proposed FEC Technique In coding over consecutive cells, the encoder appends MA independent parity cells for each group of NA consecutive information-bearing cells. The receiver determines the pcr sition of loaaes in this block of NA + MA cells by means of sequence numbers. Hence, the end-t-nd connection can be viewed as an erasure channel. It is then possible to de- sign an optimal, maximumdistance code so that the decoder can recover the whole block provided that it arrives with lesa than or equal to MA erased cells [SI. For example, in [9], Ayanoglu et al. considered an optimal, maximum distance separable code baaed on either a Fourier-Galois transform or a Reed-Solomon code for self-healing communication n e t  works. We consider this block of NA + MA cells as a PDU. We call a PDU coded if MA > 0 and uncoded otherwise. Due to the statistical multiplexing in ATM networks, queues at the switching nodes may occasionally be con- gested, during which time cells are subject to a high prob- ability of low. In such caae~, it is possible that more than MA erasures hit a coded PDU. To resolve this difficulty, in addition to coding over consecutive ccllr, we employ a lim- ilar code over PDUs: each block of N p  information-bearing PDUs, coded or not, is followed by M p  independent parity PDUs. Then, similarly to the case of cell coding, it suffices for the decoder to receive any N p  PDUs out of N p  + M p  to recover the whole coding block. We call this block of N p  + M p  PDUs a codirp block. Observe that there are k = NPMA + MpN,  + MPMA parity cells used for NpN,  information-bearing cells. The optimal code with the same parameters is the one that can rccovcr any pattern of up to k erased cells out of ( N p  + MP)(NA + M A ) .  However, the decoding delayo may then be too large. With the propoeed technique, the re- covery capability is structurally distributed over subblocks (PDUs) in the whole coding block, and hence, we take the advantage of fsster decoding at the expense of losing decod- ing flexibility. 3 Simulation Model We consider a long-distance Vidual Channel (VC) connec- tion through an ATM network. The VC ~ ~ n ~ i s t s  of 4 inter- mediate nodes and 6 links of length equivalent to 2048 ulofu, where a dot is the unit time needed to oerve a cell at any standard ATM t ran"ion speed. In each one of the in- termediate nodes, there is a non-blocking 8 x 8 ATM switch capable of transporting all the simultaneous input cells to the requested output porta in zero time. We consider two oufppuf queueing techniquea. In the first technique, there is a reaerved buffer of capacity B cella for each output port (complete partitioning). In the second technique, all the cells to be queued share a common buffer pool of capacity 8B cells regardless of the output requesta (complete slar- mg). We consider cell lasees due to buffer overflows only. Although complete partitioning avoids interaction of traf- fic streams destined for different output porta, and yields smaller queueing delays M compared to complete sharing, the latter technique is expected to provide saving in cell l o "  when the traffic is buraty [lo]. We concentrate on the forward t r a c  flowing from the source to the destination through the VC, and perform FEC on this fogged t r d c .  At intermediate nodes, the tagged traffic interferes with the vnfeggtd cells belonging to other VCs. We a u m e  that PDUs of NA cells arrive at the tagged and untsgged sour- continuously according to independent Poieaon processsa with rate ~ / N A ,  where p is the normalised load offered by a source. The cella of a PDU are transmitted caneecutively. The untagged PDUs join the tagged VC with probability 1/8, and the untagged cells that join the tagged VC depart at the downstream nodes independently with probability 7/8. The tagged and untaggd celle are served at the same priority level. The lost tsglled PDUs are retrammitted upon negative acknowl- edgement messages or timeouts. The transmiwions of new tagged PDUs are governed by an end-bend flow control mechanism with PDU permits [ll]. Finally, we amume that there is a cell level memory at the destination. In other words, the suceeseful cells are stored at the receiver although the PDUs that they belong to are lo&. Obviourly, thio feature itwlf baa a strong impact on the overall network performance M the work left for the suuc- cemive retrammimion cycles decreasee from one cycle to the next. 4 Simulation Results We Axed the parameters N A  and N p  aa 16 and 256, ream- tively, and performed various simulatione to optimise MA and M p  separately for the c ~ c g  of completely partitioned and completely shared output buffers of capacity B = 16, 64, und 266. In them simulations, we memured the aver- age PDU d e l q  M a function of p, where p took valuer up to [(1+ MA/NA)(~ + Mp/lVp)]- l .  The average PDU de- lay WM defined 8s the average time (in slots) that a tagged PDU rpent in the network. In the PDU coded c-, the aver- were computed over information-bearing PDUs IK) as to make a meaningful comparison with the uncoded case. While optimizing MA, we kept M p  = 0, and tried MA = 0, 1, 2, 3,4,6,8, and 12. The results of them simuls- tions yielded MA = 4 as the best choice with an acceptable throughput limitation for both output queueing techniques. In the optimization of M p ,  we tried M p  = 0, 2, 4, 6, 8, 10, 12, 14, 16, 24, and 32, this time keeping MA = 0, and obtained M p  = 4 and 16 as the best choices for complete partitioning and complete sharing, respectively. The simuls- tion model and the results of thaw aimulatione for complete partitioning are discussed in detail in (121. In this paper, we compare the results of the uncoded, only cell coded, only PDU coded, and both cell and PDU coded casee with cod- ing parameters, MA and M p ,  chosen as above. In Figure 1, we compare the reeults for complete parti- tioning. For B = 16, it is observed that PDU coding doee not provide ap i f icmt  improvement in the delay-throughput performance for any p, and cell coding is superior to PDU coding for all p ,  Due to the bursty traffic characteristics, the buffers of such emall capacity are alm& always sat- urated even for low p. Therefore, cells are lost randomly with high probabilities, and conaequently, cell coding out- perfom PDU coding over the whole range of p. Ae the buffer capacitiw increaee to B = 64 and 256, PDU coding starts to provide gain, and in fact for low p, yields better delay-throughput performance as compared to cell coding. For such large buffer capacities and low loads, cells an! lo& in rare bursts, and PDU coding exhibits gain. A8 the effec- tive normalised load, p(1+ M p / N p ) ,  8pproeches unity, the frequency of burst cell losses increases, and many cells from distinct connections interfere at the output buffem resulting in random cell lasees. Therefore, the PDU coding gain de- c r e w  with increwsing p, and cell coding starts to perform better for high p. The joint code outperforms only cell cod- ing or only PDU coding for almost all p, except for a small degradation around p = 0.45 when B = 256, which is due to the individual performance degradation in cell coding. 1844 In comparison of the results for complete sharing, de- picted in Figure 2, with those of complete partitioning, it ia observed that complete sharing yields better delay- throughput performance for low p, where the input traffic is bursty. This is in accordance with the a priori expec- tation that complete sharing would be effective for bursty t r a c .  In particular, when B = 16, the gain of complete sharing is quite significant, and the critical load after which retransmiasions begin is shifted to about p = 0.35 from very small values. In fact, for low p, complete sharing with B = 16 achieves the performance of complete partitioning with B = 64. This sharing gain diminishes with increasing B.  The important difference between the results for the two queueing techniques with regard to coding is observed in the case of PDU coding when B = 16. Itecall that, for complete partitioning with B = 16, cells are lost randomly with high probabilities even for low p, and hence, PDU coding provides no significant gain. Complete sharing with the same B, however, saves a significant fraction of cell losses when p is low, resulting in bursty cell loss characteristics. This, in turn, makes PDU coding effective. Comparison of the performance for the uncoded and coded casea yields similar trade-offs for both queueing techniquea when B = 64 and 256. In general, for low loads, cell losses occur in rare bursts, and consequently, PDU coding outperforms cell coding. For higher loads, the picture changes, and cell coding starts to perform better as cells tend to be lost randomly with high probabilities. Complete sharing, on the other hand, outper- forms complete partitioning for low loads where the traffic is bursty. However, for high loads, we observe the reverse situation since the frequency of burst input cells increase re- sulting in a heavy load. Also, in comparison with complete partitioning, complete sharing makes PDU coding more ef- fective especially for small B since it increases the burstiness of the cell loss process. The two coding techniques act in- dependently, exhibiting gain and loss by means of different mechanisms. The joint code exhibits the advantages and the disadvantages of the individual contributions, in most casea with a net gain. 5 Summary and Conclusions We have presented the results of a simulation study, showing that the use of forward error correction improves the per- formance of broadband networks. We have concentrated on the performance over a virtual circuit connection through an ATM network. We have considered both completely parti- tioned and completely shared output buffers at the switch- ing nociles. The FEC technique is based on transmitting parity packets, which are constructed by using an erasure channel code, along with information-bearing packets. Al- though this may increase the network load, leading to higher packet loss rates and limit the network throughput, retrans- missions are avoided provided that sufficiently many packets reach the destination. In particular, we have considered two types of coding: coding over consecutive cells and coding over consecutive fixed-length PDUs. The Simulation results obtained have confirmed our a priori expectation that cod- ing over PDUs would be effective for burst cell l o“ .  This effect of PDU coding is comparable to that of an interleav- ing or a buffer management technique which can be used to combat burst cell lossee. Our results indicate that, by employing FEC with correct parameters, it is poeaible to reduce the average PDU delays approximately to the extent of a half. References [l] N. F. Maxemchuk, “Dispersity routing,” Proc. ICC ’75, pp. 41.10-41.13, 1975. [2] N. Shacham, “Packet recovery and error correction in high-speed widearea networks,” Proc. MILCOM ’89, p. 29.5.1, May 1989. [3] T. Kitami and I. Tokizawa, “Cell loss compeneetion schemes employing error correction coding for asyn- chronous broadband ISDN,” Proc. INFOCOM ’90, pp. 116-123, San Francisco, CA, June 1990. [4] A. J. McAuley, “Reliable broadband communications using a burst erasure correcting code,” Proc. ACM SIG- COMM ’90, pp. 287-306, Philadelphia, PA, September 1990. [5] E. Ayanoglu, et al., “Protocols for error/loss recovery in broadband ISDN,” Proc. 7th Int’l. Teletrafic Congr. Sem., Morristown, NJ, October 1990. [6] L. Zhang and K. W. Sarkiea, “Modeling of a virtual path and its applications for forward error recovery coding schemes in ATM networks,” Proc. SICON ’91, Singa- pore, September 1991. [7] E. W. Biersack, “A simulation study of forward error correction in ATM networks,” Computer Communico- tions Review, Vol. 22, January 1992. [8] R. E. Blahut, Theory and Practice of Error Control Codes, Addison-Wesley Publishing Company, Inc., M a s  sachusetts 1983. [9] E. Ayanoglu, et al. “Diversity coding: using error con- trol for self-healing in communication networks,” Pro- ceedings of INFOCOM’SU, pp. 95-104, San Francisco, CA, June 1990. (To be published, IEEE %ns. Comm.) 101 M. G. Hluchyj and M. J. Karol, “Queueing in high- performance packet switching,” IEEE J. Select. Anas  in Commun., Vol. 6, no. 9, pp. 1587-1597, December 1988. 111 D. Bertsekas and R. Gallager, Data Networks, Prentice- Hall, Inc., Englewood Cliffs, New Jersey 1987. [12] N. C. Oguz and E. Ayanoglu, “A simulation study of forward error correction for lost packet recovery in E ISDN/ATM,” Proc. BILCON’92, pp. 70-80, Ankara, Turkey, July 1992. 1845 - 8 1 5  - 8 a010 - 3 a, m .  e 3 5 -  ............. E -  16 I .  I 0.0 0.2 0.4 0.6 0.8 1 .o Throughput e10000 01 m e $ 5  0 0.0 0.2 0.4 0.6 0.8 1 .o Throughput *loo00 201 1 t . 1 ’ 7 ’ 1 / l’ I 0.0 0.2 0.4 0.6 0.8 t .o Throughput Figure 1: Comparison of the uncoded (O,O), only cell coded (4,0), only PDU coded (0,4), and both cell and PDU coded (4,4) casea for complete partitioning. Averagea were com- puted over 512 coding blocks. &12 e 3 6  0 0.0 0.2 0.4 0.6 0.8 1 .o Throughput e10000 4 5 1  . ! ’ ............. 0 (0,161 (4,161 327 - e ,  0 2 9 -  0 , 0.0 0.2 0.4 0.6 0.8 1 .o Throughput Figure 2: Comparison of the uncoded (O,O), only cell coded (4,0), only PDU coded (0,16), and both cell and PDU coded (4,16) cases for complete rharing. Averages were computed over 512 coding blocks. 1846 

Simulation study of two-level forward error correction for lost packet recovery in B-ISDN/ATM

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Simulation study of two-level forward error correction for lost packet recovery in B-ISDN/ATM

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