A Study on Performance of Explicit Rate Report based Congestion

Control under Coarse-grained Clock Management

Toshihiko Kato, Takumi Enda, Ryo Yamamoto and Satoshi Ohzahata

Graduate School of Informatics and Engineering, University of Electro-Communications,

1-5-1, Chofugaoka, Chofu, Tokyo 182-8585 Japan

Keywords: NDN, Congestion Control, Rate Control, MIRCC, Clock Management.

Abstract: Named Data Networking (NDN) is a widely adopted future Internet architecture for large scale content

retrieval. The congestion control in NDN is actively studied, and the rate-based congestion control method

is considered to be well suited. From the viewpoint of implementation, however, the rate-based method has

an issue that it requires the fine-grained clock management, which is hard to implement in off-the-shelf

computers. Among the rate-based congestion control methods, an approach in which intermediate nodes

report a maximum rate for a flow explicitly is considered to work well. In this paper we pick up MIRCC

(Multipath-aware ICN Rate-based Congestion Control) as an example of explicit rate report based scheme,

and examine the impact of system clock granularity of the performance of NDN rate based congestion control.

This paper provides the performance evaluation when consumers and NDN routers use the system clock with

long time interval.

1 INTRODUCTION

Resulting from a drastic increase in Internet traffic

(Cisco, 2020), there are many studies on the future

Internet architecture called Information Centric

Network (ICN), which is well suited for large scale

content retrieval. Named Data Networking (NDN)

(Jacobson et al., 2009) is a widely adopted platform

for the ICN researches. NDN relies on the name of

required content, not the address of hosts containing

the content, as a fundamental concept. NDN uses two

types of packets in all communications: an Interest

packet and a Data packet. A consumer that requests

a specific content sends an Interest packet containing

the content name. A producer that provides the

corresponding content data returns a Data packet to

the consumer. NDN routers transferring the Data

packet cache the packet for future redistribution.

The congestion control is one of the hot research

topics in NDN (Ren et al., 2016). Although it has

been also a hot topic in TCP, the mechanisms in TCP

congestion control are limited to the congestion

window management at data senders (Afanasyev et

al., 2010) and the simple explicit congestion

notification at intermediate routers (Ramakrishnan et

al., 2001). In contrast, various techniques can be

introduced to the NDN congestion control. One is a

receiver-driven window-based congestion control

approach. In this approach, a consumer maintains a

window size for Interest packet sending, just link a

sender in TCP. Congestion is detected by timeout

(Carofiglio et al., 2012) (Saino et al., 2013) or the

congestion notification (Zhang et al., 2014), and the

window for Interest packets are managed

heuristically, e.g., through an Additive Increase and

Multiplicative Decrease (AIMD) mechanism.

Another methods adopts CUBIC TCP mechanism

(Liu et al., 2016) or BIC TCP mechanism (Schneider

et al., 2016) in the window control. In NDN, the rate-

based congestion control approach is applicable. In

this approach, a consumer and routers maintain a rate,

in which Interest packets are transmitted contiguously.

The rate is determined heuristically by use of

congestion notification (Cheng et al., 2013) or by the

explicit rate reporting (Rozhnova and Fdida, 2014)

(Zhang et al., 2015) (Mahdian et al., 2016).

Among these methods, the rate-based method

with explicit rate reporting provides the best

performance. The overview of this method is as

follows. Each router monitors the total of data packet

traffic receiving over an individual link to an

upstream router or a producer, and calculates the

optimal Interest packet rate for each Interest-Data

Kato, T., Enda, T., Yamamoto, R. and Ohzahata, S.

A Study on Performance of Explicit Rate Report based Congestion Control under Coarse-grained Clock Management.

DOI: 10.5220/0009876200820088

In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications (ICETE 2020) - DCNET, OPTICS, SIGMAP and WINSYS, pages 82-88

ISBN: 978-989-758-445-9

flow. Each router sends this optimal rate in a Data

packet toward a consumer, and a consumer sends

Interest packets according to the reported rate.

Among the proposed explicit rate reporting methods,

the Multipath-aware ICN Rate-based Congestion

Control (MIRCC) specified in (Mahdian et al., 2016)

provides the most stable and highest performance.

From the viewpoint of implementation, however,

the rate-based congestion control approach has some

problems. Since the transmission speed in recent data

links becomes high, e.g., 10 Gbps in an access link,

the fine-grained clock management is required in the

rate-based congestion control. For example, if the

Data packet size is 10,000 bits and the link speed is

10 Gbps, the interval of Interest packet transmission

is 1 micro seconds (corresponding to 1 MHz) when

Interest packets are transmitted in a line speed. If the

rate is 5 Gbps or 3 Gbps, the Interest transmission

interval will be 2 micro seconds (500 KHz) or 3.33

micro seconds (300 KHz), respectively. In order to

handle these cases, it is supposed that higher precision

clock with shorter tick, such as 0.1 micro second (10

MHz), will be required to control the Interest packet

sending timing.

On the other hand, it is considered that the fine-

grained clock management is hard to implement in

off-the-shelf computers. For example, TCP

implementation uses 200 msec (5Hz) and 500 msec

(2Hz) clocks for the delayed acknowledgement and

retransmission, respectively (Fall and Stevens, 1994).

Therefore, implementing rate-based mechanism with

micro second order clock is extremely hard.

We pointed out this issue and discussed how a

coarse-grained clock system influences the NDN

rate-based congestion control, in our previous paper

(Kato et al., 2018). We adopted the Stateful

Forwarding (Cheng et al., 2013) as a target system of

the evaluation, and showed that the performance,

specifically the Data packet throughput, is degraded

largely when a coarse-grained clock is introduced.

Moreover, we proposed a method to send Interest

packets more smoothly even in the coarse-grained

clock environment.

However, the Stateful Forwarding is not the best

example of the NDN rate-based congestion control

methods. As stated above, the explicit rate reporting

methods, especially MIRCC, provide better

performance. In this paper, we examine how the

coarse-grained clock system influence the

performance of MIRCC.

The rest of this paper is organized as follows.

Section 2 gives the related work focusing on the

overview of NDN congestion control and MIRCC.

Section 3 describes the implementation of MIRCC

over the ndnSIM simulator (Afanasyev et al., 2012),

which is a widely used network simulator for NDN,

and the modification for the coarse-grained clock

system. Section 4 gives the performance evaluation

results. In the end, Section 5 concludes this paper.

2 RELATED WORK

2.1 Related Work on NDN Congestion

Control

As described above, the congestion control methods

in NDN are categorized as the window-based and the

rate-based methods. As for the window-based

methods, we can pick up the following three

examples. The Interest Control Protocol (ICP)

(Carofiglio et al., 2012) and the Content Centric TCP

(CCTCP) (Saino et al., 2013) are examples of the

traditional TCP like window-based methods. Here, a

consumer sends Interest packets continuously within

the window size, and the window size is changed

according to the AIMD mechanism triggered by Data

packet reception and congestion detected by timeout.

The Chunk-switched Hop Pull Control Protocol

(CHoPCoP) (Zhang et al., 2014) is another window-

based method. It introduces the explicit congestion

notification with random early marking instead of the

timeout-based congestion detection. Although these

use the AIMD mechanism, (Liu et al., 2016) proposes

a window control according to CUBIC TCP. The

Practical Congestion Control (PCON) scheme

(Schneider et al., 2016) uses the CoDel active queue

management scheme (Nichols and Jacobson, 2012),

which watches out the delay of packets in sending

queues, to detecting congestion. When congestion is

detected, a router signals it to consumers by explicitly

marking Data packets. In respond to this reporting,

the rate reducing is performed by consumers. PCON

follows AIMD or BIC TCP for the window control.

In the window-based methods, the window size itself

may not be optimal resulting from the Data packet

caching in different routers.

On the other hand, the rate-based methods are

classified into the non-deterministic scheme, which

uses the AIMD mechanism in determining the

Interest sending rate, and the explicit rate notification

scheme, in which intermediate routers report the

optimal Interest rate to a consumer. The Stateful

Forwarding (Cheng et al., 2013) is an example of the

former scheme. It introduces a negative

acknowledgment (NACK) packet as a response to an

Interest packet. It is sent back to a consumer when an

Interest packet is discarded in an intermediate router.

A Study on Performance of Explicit Rate Report based Congestion Control under Coarse-grained Clock Management

A consumer and a router manage the Interest sending

rate locally by AIMD, when a Data packet is received,

or a NACK packet is received / a timeout happens.

In contrast with those non-deterministic methods,

new methods have been introduced that enable

routers to report a maximum allowed Interest sending

rate. In the Hop-By-Hop Interest Shaping (HoBHIS)

(Rozhnova and Fdida, 2014), routers decide the

maximum allowed Interest sending rate

independently and accordingly shape Interest packet.

The maximum allowed rate is also reported to a

consumer and this allow a consumer to send Interest

packets without invoking congestion. In the Explicit

Congestion Notification (ECN) based Interest

sending rate control method proposed in (Zhang et al.,

2015), a consumer uses a minimum rate among the

reported rates from all intermediate routers. MIRCC

introduces a similar per-link Interest shaper at every

router and rate reporting to consumer. It takes

account of the case that a flow uses multipath transfer.

In those methods, the maximum allowed rate is

calculated from the parameters including link

capacity and utilization, queue size, inflated Interest

rate, and average round-trip time (RTT). They are

able to control Interest transmission so as to suppress

congestion, and as a result they can provide higher

throughput compared with other rate-based methods.

In spite of these merits, their implementation

requires the precise timing control for sending

Interest packets. However, the fine-grained clock is

hard to implement. There are some traditional rate-

based schemes, but they use some hardware

mechanism instead of the fine-grained clock. For

example, the Asynchronous Transfer Mode (ATM)

uses a kind of rate-based cell transfer (ITU-T, 1999),

but ATM uses null cells discarded at a receiving side

to regulate cell streams at a specific rate. (Yamamoto,

2008) introduced pause packets over Gigabit Ethernet,

corresponding to null cells in ATM, that are used only

between end nodes and switching hubs. Those

approaches are implemented by the MAC level

hardware, but NDN Interest packets are handled as a

higher level, which makes the hardware support

difficult.

2.2 Details of MIRCC

In MIRCC, consumers and routers that forward

Interest packets, called forwarders, maintain the

parameters indicated in Table 1. Each forwarder

calculates the Interest sending rate R(t) for individual

flows, at each interval T. R(t) is specified as the sum

of base_rate(t) and excess_rate(t), each of which is

given in the following way.

Table 1: List of MIRCC parameters.

In order to calculate base_rate(t), a forwarder

estimates the number of flows by equation (1).

𝑁

𝑚𝑎𝑥 𝐶,𝑦



𝑡



𝑅𝑡 𝑇



(1)

Then, base_rate(t) is computed as follows:

𝑏𝑎𝑠𝑒_𝑟𝑎𝑡𝑒𝑡 









(2)

Here, 𝛽𝑡 is given by

𝛽𝑡  𝑚𝑎𝑥0.1,













 (3)

As for excess_rate(t), the following equation is

used.

𝑒𝑥𝑐𝑒𝑠𝑠_𝑟𝑎𝑡𝑒𝑡  𝑅



𝑡𝑇





𝑦𝑡

𝑁



(4)

In order to avoid high-frequency oscillation, an

exponential weighted moving average (EWMA) is

applied to both base_rate(t) and excess_rate(t) with

weight 0.5. Finally, R(t) is given by the following

equation.

𝑅



𝑡



 𝑏𝑎𝑠𝑒_𝑟𝑎𝑡𝑒_𝑒𝑤𝑚𝑎𝑡 

𝑒𝑥𝑐𝑒𝑠𝑠_𝑟𝑎𝑡𝑒_𝑒𝑤𝑚𝑎𝑡 (5)

When a router receives a Data packet, it compares the

stamping rate included in the packet, and if the

included rate is larger than the computed R(t), then

R(t) is set in the Data packet.

DCNET 2020 - 11th International Conference on Data Communication Networking

3 MIRCC WITH

COARSE-GRAINED CLOCK

3.1 Implementation of MIRCC over

ndnSIM

In order to evaluate the performance of MIRCC

described in the previous section, we implemented it

over the ndnSIM simulator version 1.0. The reason

we used this version is that we reused the coarse-

gained clock implementation in our previous paper.

We implemented MIRCC in the following way.

(1) Add R(t) Parameter in Data Packet

In order to convey R(t) in a Data packet, we defined

the corresponding parameter, m_rate, and the

methods to access and modify it, in files

model/ndn-data.{h,cc}. Besides, the

methods for formatting a Data packet,

Serialize() and Deserialize(), is modified

in model/wire/ndnsim.cc.

(2) Implement a Method Calculating R(t)

A method called CalculateRate() is

implement-ed in utils/ndn-limits.cc. This

method is invoked every T interval, and calculates

R(t) according to equations (1) through (5) specified

above. Here, we need to mention that y(t) is given by

dividing the number of received Interest packets by T,

that the leaky bucket size is used as g(t), and that η=1

in this case.

(3) Add Various Functions in Interest/Data

Handling

Interest and Data packets are handled in file

model/fw/ndn-forwarding-strategy.cc.

We added the following functions in this file.

 Counting received Interest packets.

 Evaluating smoothed RTT at receiving Data

packets.

 Setting R(t) in a Data packet if the

corresponding value in the Data packet is larger

than the calculated R(t).

(4) Behaviour of Consumer

A consumer sends Interest packets according to the

reported R(t) in Data packets. We implemented this

kind of consumer as a new class called

ConsumerLi.

Figure 1: Implementation scheme of coarse-grained clock

system in a consumer.

3.2 Implementation of Coarse-grained

Clock based MIRCC

In the original NDN, the rate control in the consumer

is implemented as follows. The sending of Interest

packets with a specific rate is done in the

ScheduleNextPacket() method of the

ConsumerLi class. In this method, the

SendPacket() method of the Consumer class,

which is the superclass, is invoked periodically,

every 1.0/m_frequency seconds. The

SendPacket() method sends one Interest packet

actually.

We emulated a course-grained clock system in the

Consumer class in the following way (see Figure 1).

 A clock system with longer tick, such as 100

msec, is implemented in the ConsumerLi

class. It calls itself periodically with the

Schedule() method of the Simulator

class.

 We also introduced a queue storing Interest

packets temporarily. This queue is implemented

using the list class.

 In the SendPacket() method, Interest

packets are stored in the queue, instead of being

sent actually.

 When the longer clock tick is invoked, all the

queued Interest packets are transmitted actually.

In the router side in MIRCC, we implemented a

coarse-grained clock system, by assigning a large

value, such as 100 msec, in the interval T. Basically,

we assumed that the longer tick in a consumer and T

in a router take the same value. We also evaluate the

cases when the longer tick and T take different values.

1/m_frequency sec

queuing Interest packets

long term clock

sending queued

Interest packets

sending queued

Interest packets

A Study on Performance of Explicit Rate Report based Congestion Control under Coarse-grained Clock Management

Figure 2: Network configuration for performance

evaluation.

4 EXPERIMENT RESULTS

4.1 Experimental Setup

The network configuration used in this evaluation is

shown in Figure 2, which is a dumbbell configuration

where two consumers (C1 and C2) and two producers

(P1 and P2) are connected through two routers (R1

and R2). The bandwidth and delay between a

consumer and a router, and between a router and a

producer are 10Mbps and 50 msec, respectively.

Those between routers are 12Mbps and 100 msec,

respectively. The length of a Data packet is 1250

bytes, and so the link speed 10Mbps and 12Mbps

corresponds 1,000 packets/sec and 1,200 packets/sec,

respectively. The depth of a token bucket used for

policing the Interest packet flow is set to 200 packets

in consumers and routers.

Under these conditions, we evaluated the cases

that the coarse-grained clock has 100 msec, 250 msec,

500 msec and 750 msec interval values. In all the

evaluation runs, consumer C1 transmits Interest

packets to producer P1 between time 1 sec and 10 sec,

and consumer C2 sends Interest packets to producer

P2 between time 3 sec and 8 sec. In this evaluation,

cache is not used.

4.2 Results of Performance Evaluation

First of all, we evaluated the performance when the

longer tick in consumers and interval T in routers

have the same value. Figure 3 shows the results,

where the time interval value is set to 100 msec, 250

msec, 500 msec, and 750 msec. The graphs show the

Interest sending rate at consumers C1 and C2.

The result in Figure 3(a) corresponds to the case

that the time interval is 100 msec. In the beginning,

the Interest sending rate at C1 takes the value around

1,000 packets/sec although there is little fluctuations.

When C2 starts the communication the Interest

sending rates at C1 and C2 go to 600 packets/sec, with

some fluctuations. This result shows that two flows

from C1 and C2 share the bandwidth of the bottleneck

link evenly. It is considered that MIRCC performs

well, even if the time interval is relatively large.

(a) time interval = 100 msec. (b) time interval = 250 msec.

Figure 3: Results when longer tick and interval T are equal.

DCNET 2020 - 11th International Conference on Data Communication Networking

(a) interval T = 100 msec. (b) interval T = 250 msec.

Figure 4: Results when longer tick is set to 100 msec.

Figure 3(b) shows the result in the case that the

time interval is 250 msec. The result seems to be

similar with the case of 100 msec. The difference is

the convergence to 600 packets/sec when C2 starts

the communication takes larger period, around 2 sec.

In contrast these results, those in Figures 3(c) and 3(d)

show a catastrophic situation. Even if C2 starts its

session, the Interest sending rates in C1 and C2 keep

1,000 packets/sec as if the individual consumer

communicates alone. These results indicate that the

MIRCC mechanism does not work well. It should be

noted that the time interval values in those cases are

larger than RTT (400 msec) between the consumer

and the producer.

Next, we evaluated the performance when the

longer tick in consumers is set to 100 msec and

interval T in routes has large values. Figure 4(a) is

the result when T is 100 msec, and this is the same as

the result shown in Figure 3(a).

Figure 4(b) is the result when interval T is 250

msec. Comparing with the result in Figure 3(b), the

tendency of Interest sending rate is similar. In both

cases, the rates in two consumers are set to 600

packets/sec while C2 communicates with P2.

The results in Figures 4(c) and 4(d) are completely

different from those in Figures 3(c) and 3(d). When

the longer tick in consumers is set to 100 msec, the

MIRCC mechanism works well even if interval T in

routers is set to 500 msec or 750 msec.

5 CONCLUSIONS

In this paper, we showed the performance evaluation

of MIRCC, which is an effective rate-based

congestion control mechanism, under the condition

that the coarse-grained clock system is used in

consumers and routers. The congestion control

mechanism is an important issue in NDN, and the

MIRCC is considered as one of the effective

approaches. However, MIRCC requires a precise

system clock and it is an implementation issue for off-

the-shelf computers. We evaluated how the Interest

sending rate is realized when the coarse-grained

system clock is used in consumers and routers. The

evaluation results showed that a large clock interval

degrades the performance of MIRCC. The results

also showed that the clock granularity in consumers

for controlling Interest sending is more important

than the control interval used by MIRCC in routers.

Even if the interval values in routers is large, the

performance of MIRCC is kept well when the system

clock interval value is small in consumers.

A Study on Performance of Explicit Rate Report based Congestion Control under Coarse-grained Clock Management

REFERENCES

Cisco public White paper, 2020. Cisco Annual Internet

Report (2018-2023). https://www.cisco.com/c/en/us/

solutions/collateral/executive-perspectives/annual-

internet-report/white-paper-c11-741490.pdf.

Jacobson, V., et al., 2009. Networking Named Content. In

Proc. of CoNEXT ’09, pp. 1-12.

Ren, Y., Li, J., Shi, S., Li, L., Wang, G., Zhang, B., 2016.

Congestion control in named data networking - A

survey. Computer Communications, vol. 86, no. 15, pp.

1-11.

Afanasyev, A., Tilley, N., Reiher, P., Kleinrock, L., 2010.

Host-to-Host Congestion Control for TCP. IEEE

Commun. Surveys & Tutorials, vol. 12, no. 3, pp. 304-

342.

Ramakrishnan, K., Floyd, S., Black, D., 2001. The Addition

of Explicit Congestion Notification (ECN) to IP. IETF

RFC 3168.

Carofiglio, G., Gallo, M., Muscariello, L., 2012. ICP:

Design and Evaluation of an Interest Control Protocol

for Content-Centric Networking. In Proc. of IEEE

INFOCOM 2012, pp. 304-309.

Saino, L., Cocora, C., Pavlou, G., 2013. CCTCP: A

Scalable Receiver-driven Congestion Control Protocol

for Content Centric Networking. In Proc. of IEEE ICC

2013, pp. 3775-3780.

Zhang, F., Zhang, Y., Reznik, A., Liu, H., Qian, C., Xu, C.,

2014, A Transport Protocol for Content-Centric

Networking with Explicit Congestion Control. In Proc.

of IEEE ICCCN 2014, pp. 1-8.

Liu, Y., Piao, X., Hou, C., Lei, K., 2016. A CUBIC-Based

Explicit Congestion Control Mechanism in Named

Data Networking.In Proc. of IEEE CyberC 2016, pp.

360-363.

Schneider, K., Yi, C., Zhang, B., Zhang, L., 2016. A

Practical Congestion Control Scheme for Named Data

Networking. In Proc. of ACM ICN 2016, pp. 21-30.

Cheng, Y., Afanasyev, A., Moiseenko, I., Zhang, B., Wang,

L., Zhang, L., 2013. A case for stateful forwarding

plane, Computer Communications, vol. 36, no. 7, pp.

779-791.

Rozhnova, N and Fdida, S., 2014. An extended Hop-by-

Hop Interest shaping mechanism for Content-Centric

Networking. In Proc. of IEEE GLOBECOM 2014, pp.

1-7.

Zhang, J., Wu, Q., Li, Z., Kaafar, M., Xie, G., 2015. A

Proactive Transport Mechanism with Explicit

Congestion Notification for NDN. In Proc. of IEEE

ICC 2015, pp. 5242-5247.

Mahdian, M., Arianfar, S., Gibson, J., Oran, D., 2016.

Multipath-aware ICN Rate-based Congestion Control.

In Proc. of ACM ICN 2016, pp. 1-10.

Fall, K. and Stevens, W., 1994. TCP/IP Illustrated,

Volume1; The Protocols, Second Edition. Addison-

Wesley.

Kato, T., Osada, K., Yamamoto, R., Ohzahata, S., 2018. A

Study on How Coarse-grained Clock System Influences

NDN Rate-based Congestion Control. In Proc. of

IARIA ICN 2018, pp. 35-40.

Afanasyev, A., Moiseenko, I., Zhang, L., 2012. ndnSIM:

NDN simulator for NS-3. NDN, Technical Report

NDN-0005.

Nichols, K. and V. Jacobson, V., 2012. Controlling Queue

Delay. ACM Magazine Queue, vol. 10, issue 5, pp. 1-

15.

ITU-T, 1999. B-ISDN asynchronous transfer mode

functional characteristics, Series I: Integrated Services

Digital Nework, Recommendation I.150.

Yamamoto, Y., 2008. Estimation of the advanced TCP/IP

algorithms for long sistance collaboration. Fusion

Engineering and Design, vol. 83, issue 2-3, pp. 516-519.

NDN, Overall ndnSIM documentation; Forwarding

Strategies. http://ndnsim.net/1.0/fw.html.

DCNET 2020 - 11th International Conference on Data Communication Networking