Traffic Engineering Working Group Wai Sum Lai Internet Draft - Updates 3564 AT&T Labs Document: January 2004 Category: Informational Bandwidth Constraints Models for Differentiated Services-aware MPLS Traffic Engineering: Performance Evaluation Status of this Memo This document is an Internet-Draft and is in full conformance with all provisions of Section 10 of RFC2026. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet- Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." The list of current Internet-Drafts can be accessed at http://www.ietf.org/ietf/1id-abstracts.txt The list of Internet-Draft Shadow Directories can be accessed at http://www.ietf.org/shadow.html. This document is available in both .txt and .pdf formats. Abstract The Differentiated Services (Diffserv)-aware MPLS Traffic Engineering Requirements RFC 3564 specifies the requirements and selection criteria for Bandwidth Constraints Models. Two such models, the Maximum Allocation and the Russian Dolls, are described therein. This document complements RFC 3564 by presenting the results of a performance evaluation of these two models under various operational conditions: normal load, overload, preemption fully or partially enabled, pure blocking, or complete sharing. Conventions used in this document The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC-2119. Table of Contents Lai Category - Expiration [Page 1] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 Status of this Memo................................................1 Abstract...........................................................1 1. Introduction....................................................2 2. Bandwidth Constraints Models....................................3 3. Performance Model...............................................4 3.1 LSP Blocking and Preemption....................................5 3.2 Example Link Traffic Model.....................................6 3.3 Performance Under Normal Load..................................7 4. Performance Under Overload......................................8 4.1 Bandwidth Sharing Versus Isolation.............................9 4.2 Improving Class 2 Performance at the Expense of Class 3.......10 4.3 Comparing Bandwidth Constraints of Different Models...........11 5. Performance Under Partial Preemption...........................12 5.1 Russian Dolls Model...........................................13 5.2 Maximum Allocation Model......................................14 6. Performance Under Pure Blocking................................14 6.1 Russian Dolls Model...........................................14 6.2 Maximum Allocation Model......................................15 7. Performance Under Complete Sharing.............................16 8. Implications on Performance Criteria...........................17 9. Conclusions....................................................17 10. Security Considerations.......................................18 11. References....................................................18 12. Acknowledgments...............................................19 13. Author's Address..............................................19 Full Copyright Statement..........................................19 1. Introduction Differentiated Services (Diffserv)-aware MPLS Traffic Engineering (DS-TE) mechanisms operate on the basis of different Diffserv classes of traffic to improve network performance. Requirements for DS-TE and the associated protocol extensions are specified in references [1, 2], respectively. To achieve per-class traffic engineering, rather than on an aggregate basis across all classes, DS-TE enforces different Bandwidth Constraints (BCs) on different classes. Reference [1] specifies the requirements and selection criteria for Bandwidth Constraints Models (BCM) for the purpose of allocating bandwidth to individual classes. This document presents a performance analysis for the two BCMs described in [1]: (1) Maximum Allocation Model (MAM) - the maximum allowable bandwidth usage of each class, together with the aggregate usage across all classes, are explicitly specified. (2) Russian Dolls Model (RDM) - specification of maximum allowable usage is done cumulatively by grouping successive priority classes recursively. Lai Category - Expiration [Page 2] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 The following criteria are also listed in [1] for investigating the performance and trade-offs of different operational aspects of BCMs: (1) addresses the scenarios in Section 2 (of [1]) (2) works well under both normal and overload conditions (3) applies equally when preemption is either enabled or disabled (4) minimizes signaling load processing requirements (5) maximizes efficient use of the network (6) minimizes implementation and deployment complexity The use of any given BCM has significant impacts on the capability of a network to provide protection for different classes of traffic, particularly under high load, so that performance objectives can be met [3]. This document complements [1] by presenting the results of a performance evaluation of the above two BCMs under various operational conditions: normal load, overload, preemption fully or partially enabled, pure blocking, or complete sharing. Thus, our focus is only on the performance-oriented criteria and their implications for a network implementation. In other words, we are only concerned with criteria (2), (3), and (5); we will not address criteria (1), (4), or (6). Related documents in this area include [4, 5, 6, 7, 8]. In the rest of this document, the following acronyms are used: BC Bandwidth Constraint BCM Bandwidth Constraints Model MAM Maximum Allocation Model RDM Russian Dolls Model 2. Bandwidth Constraints Models To simplify our presentation, we use the informal name "class of traffic" for the terms Class-Type and TE-Class defined in [1]. We assume that (1) there are only three classes of traffic, and (2) all label-switched paths (LSPs), regardless of class, require the same amount of bandwidth. Furthermore, the focus is on the bandwidth usage of an individual link with a given capacity; routing aspects of LSP setup are not considered. The concept of reserved bandwidth is also defined in [1] to account for the possible use of overbooking. Rather than getting into these details, we assume that each LSP is allocated 1 unit of bandwidth on a given link after establishment. This allows us to express link bandwidth usage simply in terms of the *number of simultaneously established LSPs*. Link capacity can then be used as the aggregate constraint on bandwidth usage across all classes. Suppose that the three classes of traffic assumed above for the purpose of this document are denoted by class 1 (highest priority), class 2, and class 3 (lowest priority). When preemption is enabled, Lai Category - Expiration [Page 3] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 these are the preemption priorities. To define a generic class of BCMs for the purpose of our analysis in accordance with the above assumptions, let Nmax = link capacity, i.e., the maximum number of simultaneously established LSPs for all classes together, Nc = the number of simultaneously established class c LSPs, for c = 1, 2, and 3, respectively. For MAM, let Bc = maximum number of simultaneously established class c LSPs. Then, Bc is the Bandwidth Constraint for class c, and we have Nc <= Bc <= Nmax, for c = 1, 2, and 3, N1 + N2 + N3 <= Nmax, B1 + B2 + B3 >= Nmax. For RDM, the BCs are specified as: B1 = maximum number of simultaneously established class 1 LSPs, B2 = maximum number of simultaneously established LSPs for classes 1 and 2 together, B3 = maximum number of simultaneously established LSPs for classes 1, 2, and 3 together. Then, we have the following relationships: N1 <= B1, N1 + N2 <= B2, N1 + N2 + N3 <= B3, B1 < B2 < B3 = Nmax. 3. Performance Model Reference [8] presents a 3-class Markov-chain performance model to analyze a general class of BCMs. The BCMs that can be analyzed include, besides MAM and RDM, also BCMs with privately reserved bandwidth that cannot be preempted by other classes. The Markov-chain performance model in [8] assumes Poisson arrivals for LSP requests with exponentially distributed lifetime. The Poisson assumption for LSP requests is relevant since we are not dealing with the arrivals of individual packet within an LSP. Also, LSP lifetime may exhibit heavy-tail characteristics. This effect should be accounted for when the performance of a particular BCM by itself is evaluated. As the effect would be common for all BCMs, we ignore it for simplicity in the comparative analysis of the relative performance of different BCMs. In principle, a suitably chosen hyperexponential distribution may be used to capture some aspects of Lai Category - Expiration [Page 4] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 heavy tail. However, this will significantly increase the complexity of the non-product-form preemption model in [8]. The model in [8] assumes the use of admission control to allocate link bandwidth to LSPs of different classes in accordance with their respective BCs. Thus, the model accepts as input the link capacity and offered load from different classes. The blocking and preemption probabilities for different classes under different BCs are generated as output. Thus, from a service provider's perspective, given the desired level of blocking and preemption performance, the model can be used iteratively to determine the corresponding set of BCs. To understand the implications of using criteria (2), (3), and (5) in the Introduction Section to select a BCM, we present some numerical results of the analysis in [8]. This is to gain some insight to facilitate the discussion of the issues that can arise. The major performance objective is to achieve a balance between the need for bandwidth sharing so as to gain bandwidth efficiency, and the need for bandwidth isolation so as to protect bandwidth access by different classes. 3.1 LSP Blocking and Preemption As described in Section 2, the three classes of traffic used as an example are class 1 (highest priority), class 2, and class 3 (lowest priority). Preemption may or may not be used and we will examine the performance of each scenario. When preemption is used, the priorities are the preemption priorities. We consider cross-class preemption only, with no within-class preemption. In other words, preemption is enabled so that, when necessary, class 1 can preempt class 3 or class 2 (in that order), and class 2 can preempt class 3. Each class offers a load of traffic to the network that is expressed in terms of the arrival rate of its LSP requests and the average lifetime of an LSP. A unit of such a load is an erlang. (In packet-based networks, traffic volume is usually measured by counting the number of bytes and/or packets that are sent or received over an interface, during a measurement period. Here we are only concerned with bandwidth allocation and usage at the LSP level. Hence, the erlang as a measure of resource utilization in a link-speed independent manner is an appropriate unit for our purpose [9].) To prevent Diffserv QoS degradation at the packet level, the expected number of established LSPs for a given class should be kept in line with the average service rate that the Diffserv scheduler can provide to that class. Because of the use of overbooking, the actual traffic carried by a link may be higher than expected, and hence QoS degradation may not be totally avoidable. However, the use of admission control at the LSP level helps to *minimize* QoS degradation by enforcing the BCs established for the Lai Category - Expiration [Page 5] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 different classes, according to the rules of the BCM adopted. That is, the BCs are used to determine the number of LSPs that can be simultaneously established for different classes under various operational conditions. By controlling the number of LSPs admitted from different classes, this in turn ensures that the amount of traffic submitted to the Diffserv scheduler is compatible with the targeted packet-level QoS objectives. The performance of a BCM can therefore be measured by how well the given BCM handles the offered traffic, under normal or overload conditions, while maintaining packet-level service objectives. Thus, assuming the enforcement of Diffserv QoS objectives by admission control as a given, the performance of a BCM can be expressed in terms of *LSP blocking and preemption probabilities*. Different BCMs have different strengths and weaknesses. Depending on the BCs chosen for a given load, a BCM may perform well in one operating region and poorly in another region. Service providers are mainly concerned with the utility of a BCM to meet their operational needs. Regardless of which BCM is deployed, the foremost consideration is that the BCM works well under the engineered load, such as the ability to deliver service-level objectives for LSP blocking probabilities. It is also expected that the BCM handles overload "reasonably" well. Thus, for comparison, the common operating point we choose for each BCM is that they meet specified performance objectives in terms of blocking/preemption under given normal load. We then observe how their performance varies under overload. More will be said about this aspect later in Section 4.2. 3.2 Example Link Traffic Model As an example, consider a link with a capacity that allows a maximum of 15 LSPs from different classes to be established simultaneously. All LSPs are assumed to have an average lifetime of 1 time unit. Suppose that this link is being offered a load of 2.7 erlangs from class 1, 3.5 erlangs from class 2, and 3.5 erlangs from class 3. We now consider a scenario whereby the blocking/preemption performance objectives for the three classes are desired to be comparable under normal conditions (other scenarios are covered in later sections). To meet this service requirement under the above given load, the BCs are selected as follows: For MAM: up to 6 simultaneous LSPs for class 1, up to 7 simultaneous LSPs for class 2, and up to 15 simultaneous LSPs for class 3. For RDM: up to 6 simultaneous LSPs for class 1 by itself, Lai Category - Expiration [Page 6] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 up to 11 simultaneous LSPs for classes 1 and 2 together, and up to 15 simultaneous LSPs for all three classes together. Note that the driver is service requirement, independent of BCM. The above BCs are not arbitrarily picked; they are chosen to meet specific performance objectives in terms of blocking/preemption (detailed in the next section). An intuitive "explanation" for the above set of BCs may be as follows. Class 1 BC is the same (6) for both models, as class 1 is treated the same way under either model with preemption. However, MAM and RDM operate in fundamentally different ways and give different treatments to classes with lower preemption priorities. In can be seen from Section 2 that while RDM imposes a strict ordering of the different BCs (B1 < B2 < B3) and a hard boundary (B3 = Nmax), MAM uses a soft boundary (B1+B2+B3 >= Nmax) with no specific ordering. As to be explained in Section 4.3, this allows RDM to have a higher degree of sharing among different classes. Such a higher degree of coupling means that the numerical values of the BCs can be relatively smaller when compared with those for MAM, to meet given performance requirements under normal load. Thus, in the above example, the RDM BCs of (6, 11, 15) may be thought of as roughly corresponding to the MAM BCs of (6, 6+7, 6+7+15). (The intent here is just to point out that the design parameters for the two BCMs need to be different as they operate differently - strictly speaking, the numerical correspondence is incorrect.) Of course, both BCMs are bounded by the same aggregate constraint of the link capacity (15). The BCs chosen in the above example are not intended to be regarded as typical values used by any service provider. They are used here mainly for illustrative purposes. The method we used for analysis can easily accommodate another set of parameter values as input. 3.3 Performance Under Normal Load In the example above, based on the BCs chosen, the blocking and preemption probabilities for LSP setup requests under normal conditions for the two BCMs are given in Table 1. Remember that the BCs have been selected for this scenario to address the service requirement to offer comparable blocking/preemption objectives for the three classes. Table 1. Blocking and preemption probabilities BCM PB1 PB2 PB3 PP2 PP3 PB2+PP2 PB3+PP3 MAM 0.03692 0.03961 0.02384 0 0.02275 0.03961 0.04659 RDM 0.03692 0.02296 0.02402 0.01578 0.01611 0.03874 0.04013 In the above table, PB1 = blocking probability of class 1 Lai Category - Expiration [Page 7] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 PB2 = blocking probability of class 2 PB3 = blocking probability of class 3 PP2 = preemption probability of class 2 PP3 = preemption probability of class 3 PB2+PP2 = combined blocking/preemption probability of class 2 PB3+PP3 = combined blocking/preemption probability of class 3 First, we observe that, indeed, the values for (PB1, PB2+PP2, PB3+PP3) are very similar one to another. This confirms that the service requirement (of comparable blocking/preemption objectives for the three classes) has been met for both BCMs. Then, we observe that the (PB1, PB2+PP2, PB3+PP3) values for MAM are very similar to the (PB1, PB2+PP2, PB3+PP3) values for RDM. This indicates that, in this scenario, both BCMs offer very similar performance under normal load. From column 2 of the above table, it can be seen that class 1 sees exactly the same blocking under both BCMs. This should be obvious since both allocate up to 6 simultaneous LSPs for use by class 1 only. Slightly better results are obtained from RDM, as shown by the last two columns in Table 1. This comes about because the cascaded bandwidth separation in RDM effectively gives class 3 some form of protection from being preempted by higher-priority classes. Also, note that PP2 is zero in this particular case, simply because the BCs for MAM happen to have been chosen in such a way that class 1 never has to preempt class 2 for any of the bandwidth that class 1 needs. (This is because class 1 can, in the worst case, get all the bandwidth it needs simply by preempting class 3 alone.) In general, this will not be the case. It is interesting to compare these results with those for the case of a single class. Based on the Erlang loss formula, a capacity of 15 servers can support an offered load of 10 erlangs with a blocking probability of 0.0364969. Whereas the total load for the 3-class BCM is less with 2.7 + 3.5 + 3.5 = 9.7 erlangs, the probabilities of blocking/preemption are higher. Thus, there is some loss of efficiency due to the link bandwidth being partitioned to accommodate for different traffic classes, thereby resulting in less sharing. This aspect will be examined in more details later in the section on Complete Sharing. 4. Performance Under Overload Overload occurs when the traffic on a system is greater than the traffic capacity of the system. To investigate the performance under overload conditions, the load of each class is varied separately. Blocking and preemption probabilities for each case are Lai Category - Expiration [Page 8] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 not shown separately: they are added together to yield a combined blocking/preemption probability. 4.1 Bandwidth Sharing Versus Isolation Figures 1 and 2 show the relative performance when the load of each class in the example of Section 3.2 is varied separately. The three series of data in each of these figures are, respectively, class 1 blocking probability ("Class 1 B"), class 2 blocking/preemption probability ("Class 2 B+P"), and class 3 blocking/preemption probability ("Class 3 B+P"). For each of these series, the first set of four points is for the performance when class 1 load is increased from half of its normal load to twice its normal. Similarly, the next and the last sets of four points are when class 2 and class 3 loads are correspondingly increased. The following observations apply to both BCMs: 1. The performance of any class generally degrades as its load increases. 2. The performance of class 1 is not affected by any changes (increases or decreases) in either class 2 or class 3 traffic, because class 1 can always preempt others. 3. Similarly, the performance of class 2 is not affected by any changes in class 3 traffic. 4. Class 3 sees better (worse) than normal performance when either class 1 or class 2 traffic is below (above) normal. In contrast, the impact of the changes in class 1 traffic on class 2 performance is different for the two BCMs: being negligible in MAM and significant in RDM. 1. While class 2 sees little improvement (no improvement in this particular example) in performance when class 1 traffic is below normal when MAM is used, it sees better than normal performance under RDM. 2. Class 2 sees no degradation in performance when class 1 traffic is above normal when MAM is used. In this example, with BCs 6 + 7 < 15, class 1 and class 2 traffic are effectively being served by separate pools. Therefore, class 2 sees no preemption, and only class 3 is being preempted whenever necessary. This fact is confirmed by the Erlang loss formula: a load of 2.7 erlangs offered to 6 servers sees a 0.03692 blocking, a load of 3.5 erlangs offered to 7 servers sees a 0.03961 blocking. These blocking probabilities are exactly the same as the corresponding entries in Table 1: PB1 and PB2 for MAM. 3. This is not the case in RDM. Here, the probability for class 2 to be preempted by class 1 is nonzero because of two effects. (1) Through the cascaded bandwidth arrangement, class 3 is protected somewhat from preemption. (2) Class 2 traffic is sharing a BC Lai Category - Expiration [Page 9] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 with class 1. Consequently, class 2 suffers when class 1 traffic increases. Thus, it appears that while the cascaded bandwidth arrangement and the resulting bandwidth sharing makes RDM works better under normal conditions, such interaction makes it less effective to provide class isolation under overload conditions. 4.2 Improving Class 2 Performance at the Expense of Class 3 We now consider a scenario in which the service requirement is to give better blocking/preemption performance to class 2 than to class 3, while maintaining class 1 performance at the same level as in the previous scenario. (The use of minimum deterministic guarantee for class 3 is to be considered in the next section.) So that the specified class 2 performance objective can be met, class 2 BC is appropriately increased. As an example, BCs (6, 9, 15) are now used for MAM, and (6, 13, 15) for RDM. For both BCMs, as shown in Figures 1bis and 2bis, while class 1 performance remains unchanged, class 2 now receives better performance, at the expense of class 3. This is of course due to the increased access of bandwidth by class 2 over class 3. Under normal conditions, the performance of the two BCMs is similar in terms of their blocking and preemption probabilities for LSP setup requests, as shown in Table 2. Table 2. Blocking and preemption probabilities BCM PB1 PB2 PB3 PP2 PP3 PB2+PP2 PB3+PP3 MAM 0.03692 0.00658 0.02733 0 0.02709 0.00658 0.05441 RDM 0.03692 0.00449 0.02759 0.00272 0.02436 0.00721 0.05195 Under overload, the observations in Section 4.1 regarding the difference in the general behavior between the two BCMs still apply, as shown in Figures 1bis and 2bis. Some frequently asked questions about the operation of BCMs are as follows. For a link capacity of 15, would a class 1 BC of 6 and a class 2 BC of 9 in MAM result in the possibility of a total lockout for class 3? This will certainly be the case when there are 6 class 1 and 9 class 2 LSPs being simultaneously established. Such an offered load (with 6 class 1 and 9 class 2 LSP requests) will not cause a lockout of class 3 with RDM having a BC of 13 for classes 1 and 2 combined, but will result in class 2 LSPs being rejected. If class 2 traffic were considered relatively more important then class 3 traffic, then RDM would perform very poorly when compared with MAM with BCs of (6, 9, 15). Should MAM with BCs of (6, 7, 15) be used instead so as to make the performance of RDM look comparable? The answer is that the above scenario is not very realistic when the offered load is assumed to be (2.7, 3.5, 3.5) for the three classes, as stated in Section 3.2. Treating an overload of (6, 9, x) as normal operating condition is incompatible with the engineering of BCs according to needed bandwidth from different classes. It would Lai Category - Expiration [Page 10] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 be rare for a given class to need so much more than its engineered bandwidth level. But if the class did, the expectation based on design and normal traffic fluctuations is that this class would quickly release unneeded bandwidth toward its engineered level, freeing up bandwidth for other classes. Service providers engineer their networks based on traffic projections to determine network configurations and needed capacity. All BCMs should be designed to operate under realistic network conditions. For any BCM to work properly, the selection of values for different BCs must therefore be based on the projected bandwidth needs of each class, as well as the bandwidth allocation rules of the BCM itself. This is to ensure that the BCM works as expected under the intended design conditions. In operation, the actual load may well turn out to be different from the design. Thus, an assessment of the performance of a BCM under overload is essential to see how well the BCM can cope with traffic surges or network failures. Reflecting this view, the basis for comparison of two BCMs is that they meet the same or similar performance requirements under normal conditions, and how they withstand overload. In operational practice, load measurement and forecast would be useful to calibrate and fine-tune the BCs so that traffic from different classes could be redistributed accordingly. Dynamic adjustment of the Diffserv scheduler could also be used to minimize QoS degradation. 4.3 Comparing Bandwidth Constraints of Different Models As pointed out in Section 3.2, the higher degree of sharing among the different classes in RDM means that the numerical values of the BCs could be relatively smaller, when compared with those for MAM. We now examine this aspect in more details by considering the following scenario. We set the BCs so that, (1) for both BCMs, the same value is used for class 1, (2) the same minimum *deterministic* guarantee of bandwidth for class 3 is offered by both BCMs, and (3) the blocking/preemption probability is minimized for class 2. We want to emphasize that this may not be the way service providers select BCs. It is done here to investigate the *statistical* behavior of such a deterministic mechanism. For illustration, we use BCs (6, 7, 15) for MAM, and (6, 13, 15) for RDM. In this case, both BCMs have 13 units of bandwidth for classes 1 and 2 together, and dedicate 2 units of bandwidth for use by class 3 only. The performance of the two BCMs under normal conditions is shown in Table 3. It is clear that MAM with (6, 7, 15) gives fairly comparable performance objectives across the three classes, while RDM with (6, 13, 15) strongly favors class 2 at the expense of class 3. They therefore cater to different service requirements. Table 3. Blocking and preemption probabilities BCM PB1 PB2 PB3 PP2 PP3 PB2+PP2 PB3+PP3 Lai Category - Expiration [Page 11] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 MAM 0.03692 0.03961 0.02384 0 0.02275 0.03961 0.04659 RDM 0.03692 0.00449 0.02759 0.00272 0.02436 0.00721 0.05195 By comparing Figures 1 and 2bis, it can be seen that, when being subjected to the same set of BCs, RDM gives class 2 much better performance than MAM, with class 3 being only slightly worse. This confirms the observation in Section 3.2 that, when the same service requirements under normal conditions are to be met, the numerical values of the BCs for RDM can be relatively smaller than those for MAM. This should not be surprising in view of the hard boundary (B3 = Nmax) in RDM versus the soft boundary (B1+B2+B3 >= Nmax) in MAM. The strict ordering of BCs (B1 < B2 < B3) gives RDM the advantage of a higher degree of sharing among the different classes, i.e., the ability to reallocate the unused bandwidth of higher-priority classes to lower-priority ones, if needed. Consequently, this leads to better performance when an identical set of BCs is used as exemplified above. Such a higher degree of sharing may necessitate the use of minimum deterministic bandwidth guarantee to offer some protection for lower-priority traffic from preemption. The explicit lack of ordering of BCs in MAM together with its soft boundary implies that the use of minimum deterministic guarantees for lower-priority classes may not need to be enforced when there is a lesser degree of sharing. This is demonstrated by the example in Section 4.2 with BCs (6, 9, 15) for MAM. For illustration, Table 4 shows the performance under normal conditions of RDM with BCs (6, 15, 15). Table 4. Blocking and preemption probabilities BCM PB1 PB2 PB3 PP2 PP3 PB2+PP2 PB3+PP3 RDM 0.03692 0.00060 0.02800 0.00032 0.02740 0.00092 0.05540 Regardless of whether deterministic guarantees are used or not, both BCMs are bounded by the same aggregate constraint of the link capacity. Also, in both BCMs, bandwidth access guarantees are necessarily achieved statistically because of traffic fluctuations, as explained in Section 4.2. (As a result, service-level objectives are typically specified as monthly averages, under the use of statistical guarantees, rather than deterministic guarantees.) Thus, given the fundamentally different operating principles of the two BCMs (ordering, hard versus soft boundary), the dimensions of one BCM should not be adopted to design for the other. Rather, it is the service requirements, and perhaps also the operational needs, of a service provider that should be used to drive how the BCs of a BCM are selected. 5. Performance Under Partial Preemption In the previous two sections, preemption is *fully enabled* in the sense that class 1 can preempt class 3 or class 2 (in that order), Lai Category - Expiration [Page 12] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 and class 2 can preempt class 3. That is, both classes 1 and 2 are preemptor-enabled, while classes 2 and 3 are preemptable. A class that is preemptor-enabled can preempt lower-priority classes designated as preemptable. A class not designated as preemptable cannot be preempted by any other classes, regardless of relative priorities. We now consider the three cases shown in Table 5 when preemption is only partially enabled. Table 5. Partial preemption modes preemption modes preemptor-enabled preemptable "1+2 on 3" (Fig. 3, 6) class 1, class 2 class 3 "1 on 3" (Fig. 4, 7) class 1 class 3 "1 on 2+3" (Fig. 5, 8) class 1 class 3, class 2 In this section, we evaluate how these preemption modes affect the performance of a particular BCM. Thus, we are comparing how a given BCM performs when preemption is fully enabled versus how the same BCM performs when preemption is partially enabled. The performance of these preemption modes is shown in Figures 3 to 5 for RDM, and Figures 6 to 8 for MAM, respectively. In all of these figures, the BCs of Section 3.2 are used for illustration, i.e., (6, 7, 15) for MAM and (6, 11, 15) for RDM. However, the general behavior is similar when the BCs are changed to those in Sections 4.2 and 4.3, i.e., (6, 9, 15) and (6, 13, 15), respectively. 5.1 Russian Dolls Model Let us first examine the performance under RDM. There are two sets of results, depending on whether class 2 is preemptable or not: (1) Figures 3 and 4 for the two modes when only class 3 is preemptable, and (2) Figure 2 in the previous section and Figure 5 for the two modes when both classes 2 and 3 are preemptable. By comparing these two sets of results, the following impacts can be observed. Specifically, when class 2 is non-preemptable, and when compared with the case of class 2 being preemptable, then the behavior of each class is: 1. Class 1 generally sees a higher blocking probability when class 2 is non-preemptable. As the class 1 space allocated by the class 1 BC is shared with class 2, which is now non-preemptable, class 1 cannot reclaim any such space occupied by class 2 when needed. Also, class 1 has less opportunity to preempt - being able to preempt class 3 only. 2. Class 3 also sees higher blocking/preemption when its own load is increased, as it is being preempted more frequently by class 1, when class 1 cannot preempt class 2. (See the last set of four points in the series for class 3 shown in Figures 3 and 4, when comparing with Figures 2 and 5.) 3. Class 2 blocking/preemption is reduced even when its own load is increased, since it is not being preempted by class 1. (See the Lai Category - Expiration [Page 13] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 middle set of four points in the series for class 2 shown in Figures 3 and 4, when comparing with Figures 2 and 5.) Another two sets of results are related to whether class 2 is preemptor-enabled or not. In this case, when class 2 is not preemptor-enabled, class 2 blocking/preemption is increased when class 3 load is increased (the last set of four points in the series for class 2 shown in Figures 4 and 5, when comparing with Figures 2 and 3). This is because both classes 2 and 3 are now competing independently with each other for resources. 5.2 Maximum Allocation Model Turning now to MAM, the significant impact appears to be only on class 2, when it cannot preempt class 3, thereby causing its blocking/preemption to increase in two situations. 1. When class 1 load is increased (the first set of four points in the series for class 2 shown in Figures 7 and 8, when comparing with Figures 1 and 6). 2. When class 3 load is increased (the last set of four points in the series for class 2 shown in Figures 7 and 8, when comparing with Figures 1 and 6). This is similar to RDM, i.e., class 2 and class 3 are now competing with each other. When comparing Figure 1 (for the case of fully enabled preemption) with Figures 6 to 8 (for partially enabled preemption), it can be seen that the performance of MAM is relatively insensitive to the different preemption modes. This is because when each class has its own bandwidth access limits, the degree of interference among the different classes is reduced. This is in contrast with RDM, whose behavior is more dependent on the preemption mode in use. 6. Performance Under Pure Blocking This section covers the case when preemption is completely disabled. We continue with the numerical example used in the previous sections with the same link capacity and offered load. 6.1 Russian Dolls Model For RDM, we consider two different settings: "Russian Dolls (1)" BCs: up to 6 simultaneous LSPs for class 1 by itself, up to 11 simultaneous LSPs for classes 1 and 2 together, and up to 15 simultaneous LSPs for all three classes together. "Russian Dolls (2)" BCs: up to 9 simultaneous LSPs for class 3 by itself, Lai Category - Expiration [Page 14] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 up to 14 simultaneous LSPs for classes 3 and 2 together, and up to 15 simultaneous LSPs for all three classes together. Note that the "Russian Dolls (1)" set of BCs is the same as previously with preemption enabled, while the "Russian Dolls (2)" has the cascade of bandwidth arranged in *reverse* order of the classes. As observed in Section 4, the cascaded bandwidth arrangement is intended to offer lower priority traffic some protection from preemption by higher priority traffic. This is to avoid starvation. In a pure blocking environment, such protection is no longer necessary. As depicted in Figure 9, it actually produces the opposite, undesirable, effect: higher priority traffic sees higher blocking than lower priority traffic. With no preemption, higher priority traffic should be protected instead to ensure that they could get through when under high load. Indeed, when the reverse cascade is used in "Russian Dolls (2)," the required performance of lower blocking for higher priority traffic is achieved as shown in Figure 10. In this specific example, there is very little difference among the performance of the three classes in the first eight data points for each of the three series. However, the BCs can be tuned to get a bigger differentiation. 6.2 Maximum Allocation Model For MAM, we also consider two different settings: "Exp. Max. Alloc. (1)" BCs: up to 7 simultaneous LSPs for class 1, up to 8 simultaneous LSPs for class 2, and up to 8 simultaneous LSPs for class 3. "Exp. Max. Alloc. (2)" BCs: up to 7 simultaneous LSPs for class 1, with additional bandwidth for 1 LSP privately reserved up to 8 simultaneous LSPs for class 2, and up to 8 simultaneous LSPs for class 3. These BCs are chosen so that, under normal conditions, the blocking performance is similar to all the previous scenarios. The only difference between these two sets of values is that the "Exp. Max. Alloc. (2)" algorithm gives class 1 a private pool of 1 server for class protection. As a result, class 1 has a relatively lower blocking especially when its traffic is above normal, as can be seen by comparing Figures 11 and 12. This is of course at the expense of a slight increase in the blocking of classes 2 and 3 traffic. When comparing the "Russian Dolls (2)" in Figure 10 with MAM in Figures 11 or 12, the difference between their behavior and the associated explanation are again similar to the case when preemption is used. The higher degree of sharing in the cascaded bandwidth arrangement of RDM leads to a tighter coupling between the different Lai Category - Expiration [Page 15] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 classes of traffic when under overload. Their performance therefore tends to degrade together when the load of any one class is increased. By imposing explicit maximum bandwidth usage on each class individually, better class isolation is achieved. The trade- off is that, generally, blocking performance in MAM is somewhat higher than RDM, because of reduced sharing. The difference in the behavior of RDM with or without preemption has already been discussed at the beginning of this section. For MAM, some notable difference can also be observed from a comparison of Figures 1 and 11. If preemption is used, higher-priority traffic tends to be able to maintain their performance despite the overloading of other classes. This is not so if preemption is not allowed. The trade-off is that, generally, the overloaded class sees a relatively higher blocking/preemption when preemption is enabled, than the case when preemption is disabled. 7. Performance Under Complete Sharing As observed towards the end of Section 3, the partitioning of bandwidth capacity for access by different traffic classes tends to reduce the maximum link efficiency achievable. We now consider the case where there is no such partitioning, thereby resulting in full sharing of the total bandwidth among all the classes. This is referred to as the Complete Sharing Model. For MAM, this means that the BCs are such that up to 15 simultaneous LSPs are allowed for any class. Similarly, for RDM, the BCs are up to 15 simultaneous LSPs for class 1 by itself, up to 15 simultaneous LSPs for classes 1 and 2 together, and up to 15 simultaneous LSPs for all three classes together. Effectively, there is now no distinction between MAM and RDM. Figure 13 shows the performance when all classes have equal access to link bandwidth under Complete Sharing. With preemption being fully enabled, it can be seen that class 1 virtually sees no blocking, regardless of the loading conditions of the link. Since class 2 can only preempt class 3, class 2 sees some blocking and/or preemption when either class 1 load or its own load is above normal; otherwise, class 2 is unaffected by increases of class 3 load. As higher priority classes always preempt class 3 when the link is full, class 3 suffers the most with high blocking/preemption when there is any load increase from any class. A comparison of Figures 1, 2, and 13 shows that, while the performance of both classes 1 and 2 is far superior under Complete Sharing, class 3 performance is much better off under either MAM or RDM. In a sense, class 3 is starved under overload as no protection of its traffic is being provided under Complete Sharing. Lai Category - Expiration [Page 16] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 8. Implications on Performance Criteria Based on the previous results, a general theme is shown to be the trade-off between bandwidth sharing and class protection/isolation. To show this more concretely, let us compare the different BCMs in terms of the *overall loss probability*. This quantity is defined as the long-term proportion of LSP requests from all classes combined that are lost as a result of either blocking or preemption, for a given level of offered load. As noted from the previous sections, while RDM has a higher degree of sharing then MAM, both converge ultimately to the Complete Sharing Model as the degree of sharing in each of them is increased. Figure 14 shows that, for a single link, the overall loss probability is the smallest under Complete Sharing and the largest under MAM, with RDM being intermediate. Expressed differently, Complete Sharing yields the highest link efficiency and MAM the lowest. As a matter of fact, the overall loss probability of Complete Sharing is identical to loss probability of a single class as computed by the Erlang loss formula. Yet Complete Sharing has the poorest class protection capability. (We want to point out that, in a network with many links and multiple-link routing paths, analysis in [6] showed that Complete Sharing does not necessarily lead to maximum network-wide bandwidth efficiency.) Increasing the degree of bandwidth sharing among the different traffic classes helps to increase link efficiency. Such increase, however, will lead to a tighter coupling between different classes. Under normal loading conditions, proper dimensioning of the link so that there is adequate capacity for each class can minimize the effect of such coupling. Under overload conditions, when there is a scarcity of capacity, such coupling will be unavoidable and can cause severe degradation of service to the lower-priority classes. Thus, the objective of maximizing link usage as stated in criterion (5) of Section 1 must be exercised with care, with due consideration to the effect of interactions among the different classes. Otherwise, use of this criterion alone will lead to the selection of the Complete Sharing Model, as shown in Figure 14. The intention of criterion (2) in judging the effectiveness of different BCMs is to evaluate how they help the network to achieve the expected performance. This can be expressed in terms of the blocking and/or preemption behavior as seen by different classes under various loading conditions. For example, the relative strength of a BCM can be demonstrated by examining how many times the per-class blocking or preemption probability under overload is worse off than the corresponding probability under normal load. 9. Conclusions Lai Category - Expiration [Page 17] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 BCMs are used in DS-TE for path computation and admission control of LSPs by enforcing different BCs for different classes of traffic so that Diffserv QoS performance can be maximized. Therefore, it is of interest to measure the performance of a BCM by the LSP blocking/preemption probabilities under various operational conditions. Based on this, the performance of RDM and MAM for LSP establishment has been analyzed and compared. In particular, three different scenarios have been examined: (1) all three classes have comparable performance objectives in terms of LSP blocking/preemption under normal conditions, (2) class 2 is given better performance at the expense of class 3, and (3) class 3 receives some minimum deterministic guarantee. A general theme is shown to be the trade-off between bandwidth sharing to achieve greater efficiency under normal conditions, and robust class protection/isolation under overload. The general properties of the two BCMs are: RDM . allows greater sharing of bandwidth among different classes . performs somewhat better under normal conditions . works well when preemption is fully enabled; under partial preemption, not all preemption modes work equally well MAM . does not depend on the use of preemption . is relatively insensitive to the different preemption modes when preemption is used . provides more robust class isolation under overload Generally, the use of preemption gives higher-priority traffic some degree of immunity against the overloading of other classes. This results in a higher blocking/preemption for the overloaded class, when compared with a pure blocking environment. 10. Security Considerations No new security considerations are raised by the BCMs presented in this document; they are the same as in the DS-TE Requirements document [1]. 11. References Normative References 1 F. Le Faucheur and W.S. Lai, "Requirements for Support of Differentiated Services-aware MPLS Traffic Engineering," RFC 3564, July 2003. Informative References Lai Category - Expiration [Page 18] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 2 F. Le Faucheur (Editor), "Protocol extensions for support of Diff-Serv-aware MPLS Traffic Engineering," Internet-Draft, Work in Progress. 3 J. Boyle, V. Gill, A. Hannan, D. Cooper, D. Awduche, B. Christian, and W.S. Lai, "Applicability Statement for Traffic Engineering with MPLS," RFC 3346, July 2002. 4 F. Le Faucheur and W.S. Lai, "Maximum Allocation Bandwidth Constraints Model for Diff-Serv-aware MPLS Traffic Engineering," Internet-Draft, Work in Progress. 5 F. Le Faucheur (Editor), "Russian Dolls Bandwidth Constraints Model for Diff-Serv-aware MPLS Traffic Engineering," Internet- Draft, Work in Progress. 6 J. Ash, "Max Allocation with Reservation Bandwidth Constraint Model for MPLS/DiffServ TE & Performance Comparisons," Internet- Draft, Work in Progress. 7 F. Le Faucheur, "Considerations on Bandwidth Constraints Models for DS-TE," Internet-Draft, Work in Progress. 8 W.S. Lai, "Traffic Engineering for MPLS," Internet Performance and Control of Network Systems III Conference, SPIE Proceedings Vol. 4865, Boston, Massachusetts, USA, 30-31 July 2002, pp. 256- 267. 9 W.S. Lai, "Traffic Measurement for Dimensioning and Control of IP Networks," Internet Performance and Control of Network Systems II Conference, SPIE Proceedings Vol. 4523, Denver, Colorado, USA, 21-22 August 2001, pp. 359-367. 12. Acknowledgments Inputs from Jerry Ash, Jim Boyle, Anna Charny, Sanjaya Choudhury, Dimitry Haskin, Francois Le Faucheur, Vishal Sharma, and Jing Shen are much appreciated. 13. Author's Address Wai Sum Lai AT&T Labs Room D5-3D18 200 Laurel Avenue Middletown, NJ 07748, USA Phone: +1 732-420-3712 Email: wlai@att.com Full Copyright Statement "Copyright (C) The Internet Society (date). All Rights Reserved. This document and translations of it may be copied and furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may be prepared, copied, published Lai Category - Expiration [Page 19] Internet-Draft BC Models for Diffserv-aware MPLS TE Jan 2004 and distributed, in whole or in part, without restriction of any kind, provided that the above copyright notice and this paragraph are included on all such copies and derivative works. However, this document itself may not be modified in any way, such as by removing the copyright notice or references to the Internet Society or other Internet organizations, except as needed for the purpose of developing Internet standards in which case the procedures for copyrights defined in the Internet Standards process must be followed, or as required to translate it into languages other than English. The limited permissions granted above are perpetual and will not be revoked by the Internet Society or its successors or assigns. This document and the information contained herein is provided on an "AS IS" basis and THE INTERNET SOCIETY AND THE INTERNET ENGINEERING TASK FORCE DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Lai Category - Expiration [Page 20]