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INTERNET-DRAFT Sanjeev Rampal,
Expires June 20th 1997 IBM Corpn.
December 20th, 1996.
Flow Grouping For Reducing Reservation Requirements for
Guaranteed Delay Service
<draft-rampal-flow-delay-service-00.txt>
Status of this Memo
This document is an Internet-Draft. 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.''
To learn the current status of any Internet-Draft, please check the
``1id-abstracts.txt'' listing contained in the Internet- Drafts
Shadow Directories on ftp.is.co.za (Africa), nic.nordu.net (Europe),
munnari.oz.au (Pacific Rim), ds.internic.net (US East Coast), or
ftp.isi.edu (US West Coast).
Abstract
The guaranteed service class of the Integrated Services model
is based on the Weighted Fair Queueing model and requires
rate reservation in order to provide end-to-end delay guarantees.
Often, the amount of reservation needed to satisfy specified
delay bounds can be quite high leading to low network utilization.
This draft demonstrates a property of the Weighted Fair Queueing
formulation which enables grouping of flows (which use the
guaranteed service and are routed over the same path) in such a
way that a lower reservation is needed than would be required if
each flow were treated individually, and the delay bounds of each
flow can still be provably satisfied.
1.0 Introduction
This draft presents a technique for improving the bandwidth
utilization for connections/ flows belonging to the guaranteed
service class [1] of the integrated services (IntServ) internet
specification [2].
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The guaranteed service class ensures no packet loss and provides
a strict upper bound on the end-to-end delay that will be
experienced by any packet of a flow belonging to this class. This
service requires each network element in the path of a flow to
reserve a certain bandwidth for this flow. One problem with
supporting this service class is that the amount of bandwidth
reservation required can be quite high (and could be much greater
than even the peak data arrival rate of the flow). This results
in poor network utilization.
This draft addresses this utilization problem for guaranteed service
flows. A method is presented for reducing the amount of bandwidth
reservation needed to support such flows (thereby improving network
utilization). This is done while retaining the same delay guarantees
that the service already provides to each flow. The reduction in
reservation is achieved through grouping some of the guaranteed
service flows in a network in such a way that the amount of
bandwidth needed to be reserved for a group is less than the sum
of the reservations that would be required for each flow
individually.
In this draft, first, we outline how to perform this flow grouping.
We then show that utilization can be improved while still provably
satisfying delay guarantees for each flow. The main contribution
of this draft is to demonstrate this property of Weighted Fair
Queueing. We then outline an approach for implementing this
technique in an internetwork.
Note. The proposed flow grouping technique is completely
independent of the reservation merging using filters such as
"wild card filters" proposed in RSVP specifications.
2.0 Outline of Flow Grouping
The proposed approach works by forming groups from among flows
which use the guaranteed service and which are routed over the
same path in a network (that is flows which use the exact same
set of links for their path in the network). Current IP routing
algorithms do not account for dynamic link loads and in the absence
of failures, most or all traffic between any two nodes will usually
be routed over the same set of links. With the use of more QoS or
load sensitive routing algorithms in the future this technique can
still be used however, additional state will need to be maintained
in routers to indicate which flows are using the same path. This
draft does not concentrate on such implementaiton details at
this time.
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The reason for choosing only flows which use the same
path is that the delay bound calculated by the Guaranteed Service
is an end-to-end value. If we try to group flows whose paths share
some links initially but subsequently diverge for example, we will
need to recharacterize the traffic of each flow after the paths
diverge, possibly using reshaping and adding delay. We do not
address that problem. The main contribution of this draft is to
introduce the grouping technique. Even if grouping is restricted
only to flows which share the same path, this will always result
in some improvement in the utilization over existing approaches
which do not employ any grouping at all.
We show that by grouping some (but not all) of such flows
appropriately and assigning a bandwidth reservation to the entire
group instead of to the individual flows, we can reserve a lower
amount of bandwidth for the group than the total that would be
required if this grouping were not to be performed. Further we can
still satisfy the delay bounds that are provided for each flow
when such a grouping is not performed. For a given set of flows,
a simple test procedure is outlined using which the network
determines whether the reservation with grouping will be less than
without grouping. Accordingly flows will be grouped only if there
is some bandwidth savings as compared to assigning a separate
reservation for each flow as recommended by the specification [1].
2.1 Flow grouping technique
The achievable improvement in utilization using flow grouping is
explained first using some examples. Next a procedure for
implementing this in an internetwork is outlined.
Consider two flows(F1 and F2) using the guaranteed service class in
a network as defined in [1] and [2]. These two flows are between the
same source and receiver nodes and are routed over the exact
same set of links (which we denote as L1, L2 ... Ln where n is the
number of physical links/hops in the path). Let P denote the maximum
packet size allowed for any connection in the network and let Cj
denote the bandwidth of link Lj (j=1,2 ... n).
Let the traffic characterization of these two flows be given as
(b1, r1, P1) and (b2, r2, P2) respectively where the b term
is the bucket size and the r term is the token generation rate of
the leaky bucket characterizing the respective flows, while the P
terms are the maximum packet sizes. Let D1 and D2 be the maximum
tolerable delay for the respective flows as specified by the
application.
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Consider a network in which separate rate reservations of R1 and
R2 have been assigned to these two flows (we assume that
the reservation for a flow is greater than its token generation rate
which is a necessary condition for guaranteed service). The total
amount of bandwidth which needs to be reserved on each link in the
path is hence R1 + R2. In the guaranteed service formulation,
the delay bound is inversely related to the amount of the reservation.
Hence to minimize the amount of reservation for this case, the delay
guarantee provided by the network must equal that required by the
flow (since any lower reservation will increase the delay bound
provided by the network beyond the maximum tolerable limit
specified by the application).
Hence we have,
D1 = (b1/R1) + (n-1) * (P1/ R1) + (sum from j=1 to n) P/Cj (1)
D2 = (b2/R2) + (n-1) * (P2/ R2) + (sum from j=1 to n) P/Cj (2)
The quantities on the right hand sides of equations (1) and (2)
are the formulation of the end-to-end queueing delay bound as
specified in [4]. The formulation in [1] is slightly different but
is derived from the same. We restrict ourselves to the strict WFQ
type formulation from [4] in this draft. The actual delay bound would
equal the queueing delay bound plus the propagation delay. Given the
route of a flow, the propagation delay component is fixed and the
same for all flows using the same route. Hence without any loss
of generality, we restrict ourselves to queueing delay bounds in
this draft.
Now consider a flow created by grouping these two flows into one
flow group which is characterized by the traffic model
(b_g, r_g, P_g) (the bucket size, token generation rate and maximum
packet size repectively of the resultant flow after grouping). Let
this flow group be assigned a reservation of Rg. Physically, packets
from both flows are simply multiplexed first come first served into
one flow. Packets which arrive at the same instant are reordered
arbitrarily. If the scheduler uses separate queues for different
flows for example, then we simply send packets from all flows in a
flow group to the same queue.
Consider a set of traffic characterization parameters for the flow
group which are obtained as follows.
b_g = b1 + b2 (3)
r_g = r1 + r2 (4)
Pg = max{P1, P2} (5)
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In the appendix, we show that these values are sufficient to
characterize the traffic of the flow group (which is the aggregate
traffic consisting of packets from both flows). In other words, if
the individual flows are deemed conforming by a leaky bucket derived
from the individual traffic models, then the traffic of the flow
group will also be deemed conforming by a leaky bucket based on
traffic values for the flow group calculated as above.
The minimum value of the delay bound that can be guaranteed by
the network to this combined flow can be calculated given this
reservation. We note that if the worst case delay bound guaranteed
to the flow group is no more than the minimum of all delay bounds
guaranteed to each individual flow, then the delay seen by any
packet in the flow group is guaranteed to be less than the delay
bound of the group and hence less than the delay bound guaranteed
to its own flow.
The table below shows the minimum delay bound for the individual
and aggregate flows when Rg = R1 + R2 for two example values of
the traffic parameters (n=2 and P/Cj = 1, j=1,2 are assumed).
In the first case, the minimum delay bound that can be guaranteed
for the combined flow with Rg = R1 + R2 (denoted
as D_(1,2) is less than each of the bounds (D1 and D2) that can be
guaranteed for the flows individually, using separate reservations.
Hence a lower overall reservation (R') can be obtained
when the flows are grouped. As shown, this results in a reduction of
25 percent in the amount of bandwidth which needs to be reserved on
each link in the path of these flows. On the other hand, in the
second case, with Rg = R1 + R2, the minimum delay bound that
can be guaranteed for the combined flow is greater than that which
can be guaranteed for flow F1 with separate reservations. In order
for the combined flow to obtain a delay bound satisfactory for
both flows, a reservation of greater than R1 + R2 would be required.
Hence there is no gain in grouping for this case and better
utilization would be obtained by keeping the two flows separate and
maintaining individual reservations.
Table 1: Examples of gain (or loss) using flow grouping
(b1, r1, P1) (R1, D1) (b2, r2, P2) (R2, D2) D_(1,2) R' Percent
gain
------------ ------- ----------- ------- ------ - -------
(10, .5, 10) (1, 22) (10, .5, 10) (1, 22) 17 1.5 25
(10, .5, 10) (1, 22) (10, .5, 100) (1, 112) 62 - Loss
----------------------------------------------------------------------
n=2, P/Cj = 1, j=1,2
percentage gain is defined as 100 * (R1 + R2 - R')/(R1 + R2)
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2.2. A procedure for testing whether grouping should be performed.
As shown above, there may or may not be some gain in grouping
two flows together. The procedure to test whether two flows can
be grouped together is straightforward. The total reservations
required with and without grouping are compared. Grouping can be
performed only if it results in lower total reservation than the
sum of the reservations with no grouping.
Given the two flows F1 and F2, and their traffic parameters and
delay requirements as above, the procedure for testing whether
they should be combined into a group is as follows.
1. Calculate the total reservation required with grouping using
equation (6) (which simply inverts the standard delay bound
equation which has the form like equations (1) and (2)).
Rg = max {r_g, (b_g+(n-1)* P_g)/(D_g - (sum j=1 to N) P/Cj)} (6)
where r_g, b_g and P_g are calculated according to equations (3)
through (5).
D_g = min(D1, D2) (7)
2. Now calculate the total reservation required when grouping is not
performed. This is given by equation (8) below.
R_tot = R1 + R2 (8)
where
R1 = max{r_1, (b_1 + (n-1) * P_1)/(D1 - (sum j=1 to n) P/Cj)} (9)
R2 = max{r_2, (b_2 + (n-1) * P_2)/(D2 - (sum j=1 to n) P/Cj)} (10)
3. If the reservation with grouping (from equation (6)) is smaller,
grouping can be performed else it is better to provide individual
reservations.
4. If it is decided to group two flows, then the new parameters of
the resultant flow group are calculated exactly as in equations (3)
through (5) (and equation (7)).
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3.0 Implementing flow grouping in a network
In a network supporting guaranteed service, this technique is
implemented as follows. At each source, corresponding to each
receiver node r, and each unique path p between these two nodes
which has at least one guaranteed service flow, the following
information is maintained. The triplet (b_i, r_i, P_i) and the
delay requirement D_i is maintained for each such flow i. In addition,
for each flow group between these nodes and using this path p, a
list of flows is maintained which form this group. Flows that have
not been combined with any other flow are treated as groups containing
only one flow. For each flow group, an aggregated set of traffic
parameters as well as amount of reservation and the delay guarantee
(calculated according to equations (3), (4), (5) and (7) above) are
maintained. Note that the information needed to be maintained can
be greatly reduced if there is always only one path between any two
nodes as is the characteristic of most existing IP routing algorithms
which are not load sensitive.
We now consider three possible cases that can cause the amount of
reservation on a path to change.
1. A new flow enters the network.
When a new flow enters the network and is routed over a specific
path, it is tested whether it can be combined with each
existing flow group between the same source receiver pair and
using the same path (using the test outlined above). If it
cannot be successfully combined with any existing group, then
a separate reservation is created for this flow and a new group
is created containing only this flow. Else, it is combined with
that flow group which will result in the smallest overall
increase in reservation. on this path. Finally, the parameters
of the selected flow group are updated to reflect the addition
of the new flow to the group (again according to equations (3)
through (7)). Hence the test for grouping will be performed
with every existing flow group on the same path which in the
worst case equals the number of flows in the path.
2. An existing flow leaves the network.
In practice, this may occur because the reservation refresh
message for a particular flow was not received within a
specified timeout period or an explicit `disconnect' message
was received. Regardless of the disconnecting procedure
the same techniques apply.
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The parameters of the group to which this flow was assigned are
recalculated taking into consideration only the flows which
continue to exist in the group. The new token generation rate
r_g and bucket size b_g are calculated by subtracting out the
contribution of the flow which is leaving the group. The
new P_g and D_g can be calculated by recomputing the maximum
and minimum respectively over the remaining flows. An
improvement in efficiency can be obtained by using a heap data
structure (one each for the maximum packet size and tolerable
delay for flows in a flow group). This will speed up the
calculations required everytime a flow enters or leaves a
group.
3. An existing flow changes its traffic parameters or
delay requirements
The case of a change in the traffic parameters of a flow can
be treated simply as a combination of the above two cases
(it is equivalent to a flow with the old parameters leaving
the network and another flow with the new parameters
subsequently entering the network).
3.1 Performance control policies
In order to obtain maximal bandwidth reduction, the network
should always attempt to re-assign resources in any of the
three cases above so that overall reservation is kept as low
as possible. However, this requires performing the test for
grouping frequently. Each such test can involve O(m)
calculations where m is the number of flows in a path, since
in the worst case, we have to compare an incoming or changing
flow against all existing flows.
The network can implement several policies which reduce the
amount of calculations and resource re-allocations by
compromising on the achievable reduction in reservation. For
instance, if the only the tolerable delay for a flow increases,
it may continue in its current group (thereby avoiding any
resource re-allocation or calculations), even though a greater
reduction in the amount of reservation could have been achieved
if this flow was now assigned to another flow group. As another
example, a network may choose to always perform separate
reservations when a flow enters a network (in order to obtain
fast connection setup), but then, perform the calculations
for optimally performing the flow grouping in the background
once the flow has already been setup.
Several such policies can be defined but are not the
main focus of this draft. This contribution of this draft is
the flow grouping technique to show that it will always result
in some improvement in the utilization for guaranteed service
flows as compared to an implementation which does not perform
grouping.
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An additional comment is that the proposed scheme does not
claim to achieve the optimal grouping of flows resulting in
the absolute minimal possible reservation for a set of flows.
The main point of this contribution is that
use of this technique will result in a reservation which
is never greater and often lower than when it is not used.
3.2 Some Additional Issues
There is nothing in the flow grouping technique that restricts
it to be performed only in the case of source-initiated
reservation environments (such as ATM [5]) or in
receiver-initiated environments (such as RSVP signaling over
IP [3]). In any environment where the Guaranteed Service as
defined in [1] is provided, this technique can be used to
improve utilization.
Policing and Implementation Issues
Even though flows are grouped, policing should still be
performed on individual flows rather than on flow groups. This
ensures that a flow which violates its traffic specification
can be detected even if the combined traffic in a flow group may
still be in comformance with the calculated parameters for
the group.
An additional issue is that the Guaranteed Service additionally
includes two parameters in the traffic specification viz. a
minimum policed unit and a peak rate. These parameters are not
involved in the delay calculations [1], hence have not been
addressed in this draft. We note for the sake of completeness
that if needed the peak rate of a flow group should be calculated
as being the sum of the peak rates of the individual flows in it,
while the minimum policed unit should be calculated as the
minimum of the corresponding quantity from all flows in the group.
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4.0 References
[1] S. Shenker, C. Partridge, R. Guerin "Specification of Guaranteed
Service," draft-ietf-intserv-guaranteed-svc-06.txt,
Integrated Services Working Group, Internet Engineering Task Force (IETF),
August 1996.
[2] R. Braden, D. Clark, and S. Shenker, "Integrated Services
in the Internet Architecture: an Overview," RFC 1633, June 1994.
[3] R. Braden et. al., "Resource ReSerVation Protocol (RSVP) -
Version 1 Functional Specification,"
draft-ietf-rsvp-spec-14.txt, November 1996.
[4] A.K. Parekh and R.G. Gallager, "A Generalized Processor Sharing
Approach to Flow Control in Integrated Services Networks - The
Multiple Node Case," Proc IEEE Infocom '93 pp.521-530.
[5] The ATM Forum, "User-Network Interface (UNI) Specification
v3.1," September 1994.
5.0 Appendix
We show here that the traffic parameters calculated using equations
(3), (4), (5) and the delay bound of (7) are sufficient to
characterize a flow group formed from two individual flows. Consider
the flows F1 and F2 with traffic parameters (b1, r1, P1) and
(b2, r2, P2) and delay upper bounds D1 and D2 as above.
If flow F1 conforms to its traffic specification,
the amount of data provided by it to the source node over any time
interval (t1 , t2) is at most b1 + r1*(t2 - t1). Similarly the amount
of data provided by flow F2 in the same time interval cannot exceed
b2 + r2*(t2 - t1).
Now consider the flow obtained by grouping these two flows (Fg),
with traffic parameters (b_g, r_g, P_g) and delay bound
D_g, where these quantities are calculated according to
equations (3), (4), (5) and (7) above. Over time interval (t1, t2)
hence, the aggregate flow is required to generate no more
than b_g + r_g*(t2 - t1). However, this is easily true because when
equations (3) and (4) are true, we have
b_g + r_g*(t2 - t1) = (b1 + r1*(t2 - t1)) + (b2 + r2*(t2 - t1))
Also, the greater of P1 and P2 is clearly the
maximum packet size of the combined flow. Finally, if every packet
of the combined flow is guaranteed an end to end delay which is the
minimum of the tolerable delays of all flows making up the flow group,
clearly, every flow will see an acceptable delay even when it is
combined with other flows in a group. Hence equations (3), (4), (5)
and (7) represent valid parameter values for the flow obtained by
grouping flows F1 and F2.
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6.0 Author Information
Sanjeev Rampal
C305/B664,
IBM Networking Division,
Research Triangle Park, NC 27709.
Voice 919-254-4801
email sanjeev@raleigh.ibm.com
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