Congestion Control in Named Data Networking

Congestion Control in Named Data Networking Daichi Tanaka

Masatoshi Kawarasaki

Graduate School of Library, Information and Media Studies University of Tsukuba Tsukuba, Japan [email protected]

Faculty of Library, Information and Media Science University of Tsukuba Tsukuba, Japan [email protected]

Abstract— The ICN (Information-centric networking) is a new network architecture that uses named information rather than IP address for content retrieval and delivery. Owing to the built-in multicast and in-network caching capabilities, ICN is expected to achieve efficient content delivery. Actually, however because the cache capacity of the router is limited, there is a possibility that ICN performance may not be as good as expected. This paper, taking NDN (Named Data Networking) as a study target, analyses the overload characteristics of NDN network and clarify performance deterioration mechanism caused by excessive content requests. Based on these results, it proposes the content caching control as well as the request forwarding control that adapt to the network state. By these controls, link congestion is mitigated and content acquisition time is significantly improved. It also reveals that the control effect varies considerably depending on the topological relationship between the location of the publisher and users.

data response performance, but in-network caching is not included in their model. Ref [9] performs the reality-check for the actual deployment of ICN and points out many constraints in such as the processing power and cache capacity of the router.

Keywords—NDN; performance; in-network caching; interest forwarding;

The rest of this paper is structured as follows: Section II provides a brief overview of the NDN. Section III describes simulation model and assumptions. Section IV analyses NDN network behavior under overload conditions and clarifies the performance degradation mechanism. Based on these, section V proposes congestion control methods and section VI evaluates their effectiveness. Section VII concludes this paper.

I. INTRODUCTION In recent years, research on the Information-centric Networking (ICN) has been actively conducted to evolve the Internet infrastructure from host-centric to information-centric paradigm. The ICN uses “named information” (or content or data) rather than IP address and contents are retrieved and delivered by its name [1] [2]. By using in-network caching, ICN natively supports multicast capability thus being expected to enable efficient content acquisition. Research projects such as CCN/NDN [3] and PRISM/PURSUIT [4] are driving forward ICN development. In this paper, we explore NDN (Named Data Networking) as a basis of the study. Although the concept of ICN is being embodied, its ability or benefits in content distribution are not still clear. Many of the researches about ICN performance focus on in-network caching. Ref [5] performed an exhaustive simulation to find that the cache tends to concentrate at the edge of the network and caching in the entire network is not so beneficial. But the network model is limited to one-source multi-user model. Ref [6] focused on the limitation in the router cache capacity and proposes a caching scheme that increases the diversity of contents in the router cache to improve cache hit rate. Ref. [7] proposes a caching scheme to reduce link congestion but it requires every router to know about the link state of the whole network. Ref [8] proposes the request forwarding method at each router based on the congestion state of adjacent links and 978-1-4673-9882-4/16/$31.00 ©2016 IEEE

This paper explores the behavior of the NDN network in overload situation and proposes the effective control methods that improve network efficiency as well as the user experience in terms of content acquisition time. By the simulation using a network model based on existing ISP topology, we clarify where the bottlenecks appear within a network and how they degrade the network performance. Based on these analysis, we propose two novel control methods that adapt to network state; namely, the data caching control and the request forwarding control. By simulation, we show that proposed methods can improve the content acquisition time significantly.

II. NDN OVERVIEW In this section, we provide a brief overview of NDN to facilitate understandings of the following sections. NDN uses two types of packets: Interest and Data. To retrieve Data, a user sends an Interest Packet to the network with the name of desired data in its header. Routers forward the Interest towards the data publisher using this data name, and the Data packet carrying the desired data is returned to the user with the name of the data in its header. Each NDN router maintains three kind of tables : Content Store (CS), Pending Interest Table (PIT) and Forwarding Information Base (FIB). The CS caches received Data Packet temporarily. The PIT records an Interest Packet that has been forwarded, waiting for the Data Packet to return. Each PIT entry includes the data name, the incoming interfaces of the Interest Packets and the outgoing interfaces to which the Interests have been forwarded. The FIB corresponds to the routing table in IP network except that it contains data name instead of IP address.

When a router receives an Interest Packet, it examines whether there is a matching data in its CS. If found, the Data is sent back to the incoming interface of the Interest packet. If not, the interest name is examined in the PIT entries. If the name exists in the PIT already, the incoming interface of this Interest is added to the existing PIT entry because Interests of other users have already asked for the same Data. If the name does not exist in the PIT, the Interest is added to the PIT and forwarded to the interface by looking up the FIB table. When a router receives a Data Packet, it looks up the PIT by its Data name. If a matching PIT entry is found, the router sends the Data Packet to the interfaces from which the Interests were received. Then the router caches the data in the CS and removes the PIT entry. If no PIT entry is found, the Data packet is discarded. It should be noted that the publisher needs to advertise his/her content name to the network beforehand. Advertisement is achieved by flooding the Advertise Packet within the network. When a router receives the Advertise Packet, it records the Data name and the receiving interface in its FIB table. III. SIMULATION We have developed a new NDN simulator for the performance analysis of NDN and the evaluation of proposed control methods. The simulation model, parameters and assumptions are described below. A. NDN Simulator The NDN project has already developed and published the NDN simulator “ndnSIM” [10] that runs on top of network simulator 3 (ns-3)[14]. However, the ndnSIM is specialized in the default NDN. For example, the caching policy is limited to LRU (Least Recently Used) that is the default of NDN. Therefore, we developed a new NDN simulator for this study. This simulator runs on the ns-3 and simulates the behavior of default NDN faithfully. It’s flexible enough to modify or expand default NDN. B. Simulation Model and Parameters We selected the parameters that affect the performance of NDN as listed in Table 1. The default values were set with

reference to Ref. [5]. 1) Content Model: The content parameter includes the number of content, content size, request popularity, request frequency, etc. Here, content popularity parameter (α) is explained. The popularity in HTTP content request is known to follow the zipf distribution [11,12], where the request probability of the i-th of popular content is proportional to 1/ iα. The degree of concentration changes according to this α. We applied the same distribution in NDN and set α to be 0.9 [5] as a default. We assumed that each content has a length of 2 Mbytes and accommodated in one Data Packet. Accordingly, the content and the Data packet will be one-to-one relationship. We also assumed that each user independently requests one content at a time according to the popularity distribution. When the requested content is received, the user will request the next one. 2) Network Model:. As the network topology, we adopted Geant 2012 (the number of nodes 40, the average node-degree 3.05) from the Web sites "The Internet Topology Zoo" [13] which provides a graphical representation of the backbone network around the world. The NDN network model is shown in Figure 1. Each node of the Geant 2012 corresponds to a NDN router, and fifty users are connected to each router. Therefore, the number of users of the entire network becomes 2000. We assumed five publishers in the entire network, and the location of the publisher (i.e., the location of router that the publisher is connected) was selected randomly for each simulation trial. The link bandwidth was assumed to be 1Gbps. In subsequent experiments, unless otherwise specified, each parameter shall have these default values. IV. NDN PERFORMANCE ANALYSIS We ran the simulations by changing the number of users from 1600 to 2000. In our model, as each user generates the content request with the same rate, the number of content requests is proportional to the number of users. NDN is expected to achieve more efficient content delivery owing to in-network caching than IP network. Actually, however, the

Table.1 Simulation Parameter Parameter Default Value Number of Contents 1000 Content Popularity Parameter 0.9 Content Size 2MB Network Topology Geant2012 Number of Users 2000 Location of Users 50 users per router Number of Publishers 5 Location of Publishers Randomly located Link Bandwidth 1.0Gbps Number of Routers 40

Fig. 1. Network topology model . (GEANT 2012)

Fig.5. Cache hit rate of Interest packets Fig.2. Content acquisition time and Number of Re-request

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Fig.3. Reference model of router and link

Fig.4. Time variation of congestion link utilization

router cache size is limited. We assumed that every router has the cache capacity that is 5% of the total amount of contents.[5] Regarding the performance metrics, we used the link utilization and cache hit rate from network view-point, and the content acquisition time (the Round Trip Time from request generation to content acquisition) from user view-point. A. Overload Characteristics of NDN Network Figure 2 shows the average value of the maximum content acquisition time for each user as well as the number of request retransmission in the case where the number of users is 1600 and 2000. We see that both of the content acquisition time and the number of re-request are extended with increase in the number of users. The timeout period for the user to retransmit the Interest was assumed to 5 seconds. To explain the simulation results, we use the notations as shown in Fig.3 where the router RA and router RB are connected by a bidirectional link. The link from RA to RB is LA,B and its usage rate is ρ (LA, B). Similarly, the link from RB to RA is LB,A and its usage rate is ρ (LB, A). If the utilization of a given link exceeds the threshold level (say, 80%), the link is referred to a congestion link. First, we examine the link utilization. When the number of users was 2000, the congestion links were L34,0, L35,2, L36,2, and

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Fig.6. Performance deterioration mechanism

L2,4. The time variation of the congested link utilization is shown in Figure 4. As the number of users increases, the link utilization also increases. Particularly, utilization of L2,4 remained at almost 100% during the simulation period. Owing to in-network caching, the increase of link utilization is not proportional to the increase in the number of users (or the number of content request). However, due to the limited router cache capacity, content that does not fit in the cache will be cached in the upstream router along the path. As a result, the utilization of the upstream link gradually rises. Link congestion is considered to be generated in this way. Next, we focused on the router whose incoming link is congested (e.g., Router RA with congestion link LB,A in Fig. 3). Routers corresponding to this condition were R0, R2 and R4. We measured at the router RA the cache hit rate of interest packets towards the link LA,B. (Note that data packets are expected to be returned over congested link LB,A). The results are shown in Figure 5. We can see that the cache hit rate is reduced as the number of user increases. B. Performance Deterioration Mechanism From the observation in the previous section, we can guess that the performance deterioration of NDN occurs in the following mechanism as shown in Figure 6. 1) When so many content requests occur, Interests may concentrate on specific routers within a network. 2) At the router RD where Interests are concentrated, a large amount of Data corresponding to the Interests are returned and cached. When the cache is full, the cache replacement occurs frequently and cache hit rate decreases. 3) By a decrease in cache hit rate, many Interests are forwarded to the outgoing link LD,U. 4) In response to these Interests, a large amount of Data flows into the incoming link LU, D. 5) When the link LU, D becomes congested, Data Packets are dropped. 6) Then timeout occurs on the user side, and the user retransmits the Interest to the network. 7) The user repeats re-request until the acquisition of the desired data. In this way, the performance of the NDN is degraded and the content acquisition time is extended.

V. CONGESTION CONTROL METHODS In this section, we propose congestion control methods in NDN based on the performance degradation mechanism described above. A. Control Policy To prevent performance degradation of the NDN network even during high load, it is essential to suppress link congestion as well as to improve the cache hit rate. Two possible ways are envisaged. First is the caching control. In the case when the link LU,D is congested, if Data from LU,D can be cached in higher priority at the router RD, the future Interests would not be forwarded to LD,U. This improves that the cache hit rate of the Interests towards LD,U and mitigates the congestion of link LD,U. Second is the Interest forwarding control. When the router RD detects congestion at the incoming link LU,D, it redirects the Interest to other interface than that of LD,U. By doing so, the congestion of link LU,D would be mitigated. The algorithm of these control methods are described in the next section. B. Proposed Method 1: Caching Control The objective of Method 1 is to improve the cache hit rate of the Interest toward the interface whose incoming link is congested. For this purpose, we modify the LRU (i.e., the least recently used data is replaced) that is the default caching policy of NDN. In the following, we explain the algorithm in the case where the router RD in Fig. 6 has received a Data Packet and the cache of router RD is full. 1) When the incoming link utilization ρ (LU, D) is less than the threshold (80%), the router RD applies the normal LRU. 2) When the incoming link utilization ρ (LU, D) is not less than the threshold value (80%), the router RD searches for the LRU data and examines whether it has been received from the congestion link LU, D. If so, the router RD searches for the next LRU data. C. Proposed Method 2: Interest Forwarding Control The objective of Method 2 is to reduce the usage rate of the congestion links. For this purpose, each router detects congestion in its incoming links and if it detects congestion, it does not forward the Interest to that interface and searches for alternate paths (i.e., the router selects alternate interface to forward the Interest). Default NDN [3] indicates the use of RTT (i.e., latency to receive the data packet) for the path selection in interest forwarding, while our Method 2 uses link utilization. The reason of using link utilization rather than RTT are as follows: Whereas RTT measurement is looking at the whole path to the Publisher, link utilization measurement looks at only the next one hop. Therefore, the interest forwarding control can react before link congestion occurs in the link utilization measurement, although it can react only after the occurrence of congestion in the RTT measurement.

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Fig.7. Interest forwarding control

In addition, the alternate path should be short and loop-free. For this purpose, Method 2 uses the number of hops to the Publisher at each router. We assume that content advertisement is made by flooding Advertise packet from the Publisher to the entire network. Upon receiving the Advertise, each router records the content name, receiving interface and the number of hops to the publisher that are written in the Advertise to the FIB. Then, the router adds 1 to the number of hops, and transmits the received Advertise downstream. In addition, the router measures the incoming link utilization regularly and records it in the FIB. In Method 2, the path (or interface) selection for interest forwarding is achieved in two phases, namely candidate interface selection and forwarding interface selection. The algorithm of Method 2 is explained below using Fig. 8. 1) Candidate Interface Selection Phase: The router selects candidate interface(s) for Interest forwarding based on the following conditions. a) Condition 1: The interface whose incoming link utilization is less than the threshold (80%). b) Condition 2: The interface having the minimum hop to the publisher, when the Forwarding Flag of the received Interest is ON. Here, the Forwarding Flag is an extension of the Interest packet header to prevent excessive routing. It is turned ON when the Interest packet experiences the alternate routing for the first time. In the example of Fig. 7, since the F1 is excluded by the condition 1, the candidate interface becomes the F2 and F3. 2) Forwarding Interface Selection Phase: Depending on the number of candidate interface N, the forwarding interface is selected as follows. a) N=0: The interface ranked #1 in the FIB. b) N=1: The candidate interface. c) N=2 or more: The interface having the minimum hop to the publisher among the candidate interfaces. If there are more than two interfaces having the minimum hop, select the interface whose incoming link utilization is the lowest. In the example of Fig. 8, the interface F2 is selected.

Fig.8. Content acquisition time (Caching control)

Fig.11. Cache hit rate of Interest packets (Caching control)

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Fig.12. Content acquisition time (Forwarding control) Fig.9. Location of Publisher and congestion links (Caching control, trial 4)

Fig.10. Congestion link utilization (Caching control)

VI. EVALUATION OF PROPOSED CONTROLS A. Evaluation Experiment of Caching Control To evaluate proposed caching control, we made four simulation trials by changing the location of Publisher. The threshold of link congestion was set to 0.8. Other parameters were set to the default values as shown in Table 1. 1) Experimental Results: Figure 8 shows the average value of the maximum content acquisition time for each trial. By control, the content acquisition time was reduced by 20.74% in maximum (trial 4) and 16.1% in average. In the following, we use the results of trial 4 to describe the behavior and effect of proposed caching control. First, with no control, we measured link utilization in the network. Congetion appeared at links L35,2, L36,2, and L2,4 whose locations in the network are shown in Fig.9. Figure 10 shows the transit characteristics of these congestion link utilization with and without control. From Fig.10, we can see that our control mitigates the congestion of L36,2 and L35,2 by 9.3% and 7.2% respectively.

Meanwhile in the link L2,4, the utilization had reached 100% even under control. Next, we measured the cache hit rate at the routers whose incoming links are congested. The results are shown in Figure 11. In the router R4, significant improvement in cache hit rate can be seen. But opposite effect was observed in R2. 2) Discussion: The proposed caching control was found to be effective in improving NDN performance by adjusting the caching policy to the congestion level of incoming links, but some links remained congested (e.g., the link L2,4 as shown in Fig. 10). Further, no improvement in the cache hit rate was observed in router R2 as shown in Fig. 12. Because the R2 was adjacent to two congestion links (L35,2 and L36,2), the control effect appeared to have faded. In fact, the proposed caching control was effective when the router is connected to a single congestion link. B. Evaluation Experiment of Forwarding Control We performed the simulation experiments four times by changing the location of the Publisher similar to the previous section. We used 0.7 as the threshold for determining the link congestion. (We performed some experiments by changing the threshold value and found 0.7 be the most effective.) As for the parameters, we used the default values of Table 1 except those relating to the forwarding control. 1) Experimental Results: Figure 12 shows the content acquisition time of each trial. By control, the content acquisition time was reduced by 30.1% in maximum (trial 4) and 24.2% in average. It can be seen that the acquisition time is reduced by proposed forwarding control. Thereafter, we describe the result of trial 4 in detail. Without our forwarding control, the congestion links were L12,15, L35,2, L27,28, L28,29 and L29,4 which are shown in Fig 13. The temporal characteristics of these congested link utilization is shown in Fig 14. Without

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Fig.13. Location of Publisher and congestion links (Forwarding control, trial4)

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Fig.14. Congestion Link Utilization (Forwarding Control)

control (Fig. 14 above), the utilization of the congestion links has remained around 80%. With control (Fig. 14 lower), it was improved by from 94.6% to 85.3%. We can see that the proposed forwarding control mitigates the link congestion. 2) Discussion: The experiments revealed that the proposed forwarding control mitigates link congestions and improves NDN performance. However, several seconds of control delay was observed. When we compare the caching control and the forwarding control, the latter was more effective. This is because the caching control mitigates link congestion indirectly by caching the data packet coming from congested link thus decreasing the interest packets that are forwarded to the outgoing link of the interface, while the forwarding control contributes more directly in decreasing the interest packets by redirecting them to other interfaces. Lastly, we investigate about the variation in the control effect among the trials. The control effects vary considerably according to the topological location of the publisher in NDN network. Figure 15 shows the relationship between the location of the publusher and congestion links in the case of trial 3 whose control effect was the lowest. In the trial 3, the publisher was located at node #4 (i.e., connected to the router R4). We can see that R4 is connected to many congestion links. We believe that this situation narrowed down the potential of alternate forwarding and resulted in insufficient control effect. VII. CONCLUSION In this study, we analyzed the overload characteristics of NDN network and clarified performance deterioration mechanism caused by excessive content requests. Further, based on these results, we proposed the content caching control

Fig.15. Location of Publisher and congestion links (Forwarding control, trial 3)

and the request forwarding control that adapt to the network state. By these controls, link congestion was mitigated and content acquisition time was significantly improved. It was also revealed that the control effect varies considerably depending on the topological relationship among the location of the publisher and users. Some issues were remained for further study. Regarding the caching control, improvement is needed when a router is connected to more than two congestion links. Relationship between the topological location of publisher and the control effect also needs to be investigated. Regarding the forwarding control, control delay was observed. Some proactive measures need to be investigated. Further, although the proposed caching control and forwarding control are two independent controls, they can be performed at the same time. The coordination effect of both controls needs to be investigated. Finally, other network topology than GEANT2012 needs to be studies. REFERENCES [1]

[2]

[3] [4] [5]

[6]

[7]

[8] [9]

[10] [11] [12]

[13] [14]

T. Koponen, et al. "A data-oriented (and beyond) network architecture."ACM SIGCOMM Computer Communication Review, Vol. 37, No. 4, pp.181-192, August.2007. Van Jacobson, et al. "Networking named content." Proceedings of the 5th international conference on Emerging networking experiments and technologies. ACM, pp.1-12, 2009. L.Zhang al. "Named data networking (ndn) project." Relatório Técnico NDN-0001, Xerox Palo Alto Research Center-PARC (2010).. “PURSUIT”, < http://www.fp7-pursuit.eu/PursuitWeb/> S. K. Fayazbakhsh, et al. "Less pain, most of the gain: Incrementally deployable icn." ACM SIGCOMM Computer Communication Review. Vol. 43. No. 4. pp.147-158, 2013. M. Rezazad, et al. "Ccndns: A strategy for spreading content and decoupling ndn caches." IFIP Networking,pp.20-22, Toulouse, France, May 2015 M. Badov, et al. "Congestion-aware caching and search in informationcentric networks.”, Information-centric networking. ACM, pp.37-46, 2014. Yi, Cheng, et al. "A case for stateful forwarding plane." Computer Communications 36.7,pp.779-791, 2013 D. Perino and M. Varvello. "A reality check for content centric networking." Proceedings of the ACM SIGCOMM workshop on Information-centric networking. ACM, pp.44-49, 2011. “ndnSIM documentation”, < http://ndnsim.net/2.1/ > L. Breslau, et al. "Web caching and Zipf-like distributions: Evidence and implications." In INFOCOM'99, pp. 126-134. IEEE, 1999.. P. Gill, et al. "Youtube traffic characterization: a view from the edge." Proceedings of the 7th ACM SIGCOMM conference on Internet measurement. ACM, pp.15-28, 2007. 
 “The Topology Zoo”, < http://www.topology-zoo.org/> “ns-3”,