1292 IEEE COMMUNICATIONS LETTERS, VOL. 17, NO. 6, JUNE 2013

Adaptive Retransmission Scheme forVideo Streaming over Content-Centric Wireless Networks

Longzhe Han, Seung-Seok Kang, Hyogon Kim, Member, IEEE, and Hoh Peter In, Member, IEEE

Abstract—This paper presents an adaptive retransmissionscheme to overcome video packet losses in content-centric wire-less networks. Because of in-network caching, the round-triptime (RTT) may fluctuate significantly. A new timeout estimationalgorithm is proposed to quickly adjust the timeout value. Thesequential hypothesis testing methodology is suggested to providetheoretical bounds on the probabilities of false-positive andfalse-negative detection rates. By considering the reasons forpacket losses, the scheme adaptively controls its retransmissionwindow size. Experimental results demonstrate that the proposedscheme efficiently recovers packet losses under various networkconditions.

Index Terms—Content-centric networking, loss recovery, videostreaming, wireless networks.

I. INTRODUCTION

V IDEO streaming applications can benefit substantiallyfrom content-centric networking (CCN). CCN is a novel

communication paradigm proposed by Jacobson et al. [1]to facilitate information sharing and distribution in the fu-ture Internet. The features of CCN, such as its named-datascheme, in-network caching, and intrinsic support of multicast,considerably improve the performance of video streamingapplications [2].

With continued advances in wireless technologies, multi-media services over wireless networks, such as mobile TV,video conferencing, video-on-demand, and video games, areexpected to become more prevalent in the future Internet.However, due to the nature of wireless channels, unavoidablepacket losses can seriously degrade video quality and userexperience [3]. Therefore, a packet loss recovery mechanismis vital to the success of multimedia services in the futurewireless Internet [3] [4].

Many studies have been conducted regarding video stream-ing in wired and wireless TCP/IP networks [3]–[6]. Howeverthe CCN shifts the traditional end-to-end perspective to acontent-oriented mode and the architecture of CCN is es-sentially different from TCP/IP networks [1]. Named data isthe unifying and essential element of CCN’s architecture. Todecouple data from their storage locations, data are identified,retrieved, and routed solely on the basis of their assigned

Manuscript received February 17, 2013. The associate editor coordinatingthe review of this letter and approving it for publication was A. Vinel.

This work was supported in part by Seoul R&BD Program (WR080951),and by a special research grant from Seoul Women’s University (2013), and byNext-Generation Information Computing Development Program through theNational Research Foundation of Korea funded by the Ministry of Education,Science and Technology (2012M3C4A7033345).

L. Han, H. Kim, and H. P. In (corresponding author) are with the Depart-ment of Computer Science and Engineering, Korea University, Republic ofKorea (e-mail: {lzhan, hyogon, hoh in}@korea.ac.kr).

S.-S. Kang is with the Department of Computer Science, Seoul Women’sUniversity, Republic of Korea (e-mail: msukang@swu.ac.kr).

Digital Object Identifier 10.1109/LCOMM.2013.043013.130326

names. Since CCN provides in-network caching, CCN nodescan cache data to satisfy future data requests. The receiverinitiates data transmission by broadcasting a data requestpacket, called an interest packet. Any node that receives theinterest packet and holds the matching data will transmitthe corresponding data packet to the receiver. Because thereceiver might receive data packets from different nodes, thetransmission delay can vary significantly.

In TCP/IP networks, the packet losses are recovered by theretransmission mechanism. The retransmission is based on theretransmission timeouts (RTO) algorithm [7]. Because data isalways delivered to the receiver from the source node, theRTO algorithm does not consider the RTT variation causedby in-network caching. In addition, the RTO algorithm recog-nizes a timeout as an indication of network congestion, andexponentially increases the timeout value when the RTO timerexpires. However, packet losses in content-centric wirelessnetworks can be caused by not only network congestion butalso wireless channel error. Consequently, the RTO algorithmis unsuitable for CCN.

Current CCN protocol does not provide a specific algorithmfor lifetime calculation [8]. To overcome video packet losses incontent-centric wireless networks, we propose a novel and effi-cient retransmission scheme that incorporates two algorithms:lifetime estimation and retransmission control. The lifetimeestimation algorithm utilizes probe interest packets to observethe RTT variation caused by in-network caching. In order toaccurately detect RTT variation, the lifetime estimation algo-rithm applies the sequential hypothesis testing methodology[9]. Thus, the algorithm provides theoretical bounds on theprobabilities of false-positive and false-negative detection ratesbased on the observed transmission outcomes. The lifetimeof interest packets is tuned for timely retransmission of lostpackets. CCN can work with any underlying protocols suchas TCP, UDP, IP and P2P. By introducing explicit conges-tion notification (ECN) into the CCN data packet header,the network congestion will be uniformly detected at theCCN protocol layer. According to ECN, the proposed schemedifferentiates wireless error loss from congestion loss. Basedon the reasons for packet losses, the retransmission controlalgorithm adaptively adjusts the retransmission window size.

The rest of this paper is organized as follows. Section IIdiscusses the structure of CCN nodes. Section III presentsour proposed adaptive retransmission scheme. Section IVdescribes the simulation settings used in our experimentsand analyzes our experimental results. Finally, Section Vsummarizes our work and concludes this paper.

II. CONTENT-CENTRIC NETWORKING

The CCN node has three main components: Content Store(CS), Pending Interest Table (PIT), and Forwarding Informa-

1089-7798/13$31.00 c© 2013 IEEE

HAN et al.: ADAPTIVE RETRANSMISSION SCHEME FOR VIDEO STREAMING OVER CONTENT-CENTRIC WIRELESS NETWORKS 1293

Interest Packet

Data Packet

RequestEngine

VideoDecoding

Video Streaming Client

PendingInterest Table Content Store

Life TimeEstimation

RetransmissionPolicy

Content-Centric Networks

Fig. 1. Adaptive retransmission scheme.

tion Base (FIB). Data packets are cached in the CS. TheLeast Recently Used (LRU) or Least Frequently Used (LFU)replacement algorithm is usually adopted to maintain the CS.The FIB contains the route information for forwarding interestpackets, and the PIT traces forwarded interest packets. To sendback a relevant data packet to the requester, the incoming faceof the interest packet is registered in the PIT. In addition, thePIT also works as a filter. After one node forwards a datapacket to the requester, the node will delete the correspondingentry in the PIT. If the node receives any duplicated datapackets, and find out no corresponding entry in the PIT, theduplicated data packets are dropped.

The design of CCN takes into account that underlyingnetworks might provide unreliable data delivery services. TheCCN protocol adopts the retransmission approach to recoverinterest or data packet losses. Each PIT entry is assigned atimer. The duration of the timer is indicated by the lifetimefield of the interest packet header. The application layer proto-cols should choose the value of the lifetime. If the value is notspecified by the application, a default value of four secondsis used [8]. When the timeout occurs at a forwarding node,the corresponding entry is removed from the PIT. Otherwise,if the timeout occurs at the data request node, the interestpacket will be retransmitted. The value of lifetime should beset large enough to allow for the return of the data packet.

III. ADAPTIVE RETRANSMISSION SCHEME

A. Transmission Outcome Model for CCN

The proposed scheme is deployed at the video client sidebecause the CCN adopts a receiver-driven approach, as pre-sented in Fig. 1. The request engine periodically transmitsthe interest packets corresponding to the video frame rateand packetization. The PIT temporarily stores the unresolvedinterest packets. Meanwhile, the CS buffers the received datapackets. When the playback point is reached, the data packetsare transmitted to the video decoder. The lifetime estimationalgorithm selects a small portion of the interest packets as

probe packets to capture the RTT variation caused by the in-network caching. The probe interest packet has the longestlifetime value, which is the play-out deadline of the packet.For ordinary interest packets, the lifetime value is calculatedby using the well-known RTO algorithm [7]. On the basisof Chebyshev’s inequality [10] and RTO algorithm [7], thelifetime value is calculated as

P (|X − μ̂| ≥ kσ̂) ≤ 1/k2 ⇒ threshold = μ̂+ kσ̂ (1)

where μ̂ and σ̂ are the smoothed RTT sample mean andsmoothed RTT sample variance respectively, and threshold isthe lifetime value [7]. The value k = 4 is used to guaranteethat at least 93.75% of the RTT samples fall below thethreshold [7].

All the nodes can reply to the interest packets, if they holdthe requested data, owing to the in-network caching capability.Thus, the data serving node is regarded as a temporal server.The in-network caching variation can be considered as thevariation of the temporal server location. The change in thetemporal server location affects the required transmissiondelay from the temporal server to the video client. There aretwo mutually exclusive cases: (1) the required transmissiondelay is less than or equal to the threshold and (2) therequired transmission delay is greater than the threshold. Inthe first case, the threshold effectively works. In the secondcase, however, the interest packets that use the threshold astheir lifetime would time out. The reason is that the lifetimeis not sufficient enough for the return of the data packets.Furthermore, the video clients use a pipelining approach totransmit the interest packets. If the second case occurs, theconsecutive interest packets also suffer from the successivetimeouts.

The video client has to detect the change only by thetransmission outcome of the interest packets because the CCNprotocols do not have the signaling information on the changein the temporal server location. Let Wi,j be a random variablethat denotes the outcome of the jth interest packet. Theordinary interest packet is denoted as i = 0, and i = 1 for theprobe interest packet. We define Wi,j , corresponding to thedifferent transmission outcomes, as

Wi=0,j =

{0 if RTT ≤ threshold1 if timeout occurs

(2)

Wi=1,j =

⎧⎨⎩

0 if RTT ≤ threshold1 if RTT > threshold2 if timeout occurs

(3)

The video client is required to quickly detect the variationat a high detection rate, as the video streaming is a real-time application. For meeting these requirements, a sequentialhypothesis testing is introduced to our proposed algorithm.

B. Lifetime Estimation Algorithm

There are two mutually exclusive cases, as mentioned inthe previous section. Let H0 denote the first case wherethe required transmission delay is less than or equal to thethreshold. Let H1 denote the second case where the requiredtransmission delay is greater than the threshold. We assumethat the conditional probabilities of the random variable on

1294 IEEE COMMUNICATIONS LETTERS, VOL. 17, NO. 6, JUNE 2013

the hypothesis Hm, Wi,j |Hm are independent and identicallydistributed. The average packet loss rate y is measured by thevideo client from the observations. Further, we can expressthe probability distribution of the random variable Wi,j as

Pr[Wi=0,j = 0|H0] = b(1− y),

P r[Wi=0,j = 1|H0] = 1− Pr[Wi=0,j = 0|H0].

P r[Wi=0,j = 0|H1] = (1− d)(1 − y),

P r[Wi=0,j = 1|H1] = 1− Pr[Wi=0,j = 0|H1].

P r[Wi=1,j = 0|H0] = b(1− y),

P r[Wi=1,j = 1|H0] = (1− b)(1− y),

P r[Wi=1,j = 2|H0] = 1−Pr[Wi=1,j = 0|H0]− Pr[Wi=1,j = 1|H0].

P r[Wi=1,j = 0|H1] = (1− d)(1 − y),

P r[Wi=1,j = 1|H1] = d(1− y),

P r[Wi=1,j = 2|H1] = 1−Pr[Wi=1,j = 0|H1]− Pr[Wi=1,j = 1|H1].

(4)

where b is the probability that the RTT samples are less than orequal to the threshold when H0 is true and without consideringthe packet losses. d is the probability that the RTT samplesare larger than the threshold when H1 is true and withoutconsidering the packet losses. On the basis of Chebyshev’sinequality [10] and the RTO algorithm [7], we obtain b = d =0.9375. Let Sn denote the observed outcomes of n interestpackets, and we define the likelihood ratio as

Λ(Sn) =Pr[Sn|H1]

Pr[Sn|H0]=

n∏t=1

Pr[Wi,t|H1]

Pr[Wi,t|H0](5)

where i is the indicator of the probe or an ordinary interestpacket. The detection process is developed, corresponding tothe likelihood ratio, as [9]:

result =

⎧⎨⎩

H0 if Λ(Sn) ≤ θ0H1 if Λ(Sn) ≥ θ1continue if θ0 < Λ(Sn) < θ1

(6)

where θ0 and θ1 are the thresholds, which are defined corre-sponding to the false positive probability α (accept H1 whenH0 is true) and detection probability β (accept H1 when H1

is true) as

θ0 ← 1− β

1− α, θ1 ← β

α. (7)

The values of α and β are typically selected as 0.01 and 0.99respectively. With reference to [9], the actual detection rate isbounded by β

α , and the false positive rate is bounded by 1−β1−α .

When the outcome of the detection process is H1, the lifetimeestimation algorithm resets the threshold value as

threshold =

{RTT p + kσ̂ if probe packet is receivedDplayout if probe packet is not received

(8)where RTT p is the RTT value of the probe packet, andDplayout is the play-out deadline of the packet. When H1

is actually true, the consecutive timeouts occur. The proposed

estimation algorithm requires only four or five observations togenerate the decision.

C. Adaptive Retransmission Control

Either network congestion or wireless transmission errorcan result in packet losses. If the network is congested,aggressive retransmission worsens the congestion. For efficientdetermination of the reason for the packet losses, the proposedscheme introduces an ECN into the CCN data packet. On thebasis of the CCN protocols [8], the data packet header includesan optional field, ExtOpt, for additional meta-information.The ECN is encoded into the ExtOpt field. Our proposedscheme does not assume any underlying protocols to supportthe ECN function because the CCN protocols can use any ofthe transport protocols, such as the TCP and UDP. When theCCN node experiences congestion, the incoming packets couldbe dropped by the queue management algorithms. However,the node would set the congestion encountered (CE) bit in theoutgoing data packets. By monitoring the CE bit, the receiverdetects the uplink congestion.

In the proposed scheme, the video client manages a retrans-mission window, which is the number of allowed pendingretransmission packets. By following the additive-increaseand multiplicative-decrease algorithm for the TCP congestioncontrol [11], the retransmission window is halved when the CEbits are set in the received data packets. If the CE bits are notset, the retransmission window is increased by one. However,the window size cannot exceed half of the total number ofpending packets. The advantage of the proposed approach isthat if the loss is only due to the wireless channel error, thepacket is retransmitted without increasing the threshold.

IV. SIMULATION AND RESULTS

A. Experimental Environment

We have developed CCN modules with the NS-2 simulator.UDP is used as the transport protocol. The proposed scheme iscompared with the default CCN approach and the RTO-basedapproach. The “Bridge (Close)” CIF (352×288) sequences areused as the video traces and encoded using the H.264/AVCstandard. There are 2001 frames in total, and the framesare encapsulated into 12260 CCN data packets. The mainencoding parameters are 30 fps frame rate, 400 Kbps bitrate, and 38.68 dB average peak signal-to-noise ratio (PSNR).The encoding structure is IPPPPIPPPP. The simulated networkconsists of 30 router nodes and 100 client nodes. While therouter nodes are connected via wired links, the client nodesaccess the video contents through wireless links (WLANs).The bandwidth of the wired link is 50 Mb/s, and the bit rateof the wireless link is 11 Mb/s. The transmission between thevideo clients and the access points is the unicast delivery. Thebuffer size for the CS, FIB and PIT is 1000 entries.

B. Experiment Results

Experiments are conducted for the different packet loss ratesto compare the performances of the three approaches. The loss

HAN et al.: ADAPTIVE RETRANSMISSION SCHEME FOR VIDEO STREAMING OVER CONTENT-CENTRIC WIRELESS NETWORKS 1295

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

0.025 0.05 0.075 0.1 0.125 0.15

Loss

Rec

over

y R

ate

Packet Loss Rate

CCN DefaultRTO

Proposed Scheme

Fig. 2. Loss Recovery Rate.

15

20

25

30

35

40

0.025 0.05 0.075 0.1 0.125 0.15

Ave

rage

PS

NR

(dB

)

Packet Loss Rate

CCN DefaultRTO

Proposed Scheme

Fig. 3. Average PSNR.

recovery rate is used to measure the efficiency of the threeapproaches. It is calculated as

RecoveryRate =Lnetwork − Lapplication

Lnetwork(9)

where Lnetwork is the number of lost packets that the receiverhas detected at the network layer, and Lapplication is thenumber of lost packets experienced by the application layer.As shown in (8), if probe packets are not received during thedetection period, the play-out deadline is used for the thresholdvalue. In order to accurately measure the required transmissiondelay, m probe packets are selected from a group of interestpackets, The probability of receiving at least one probe packetis

Ps(m) = 1− ym (10)

where y is the average packet loss rate measured by the videoclient. Assuming packet loss rate is not greater than 0.3, thenwe use m = 4, which guarantees that Ps is larger than orequal to 0.9919.

Fig. 2 shows the loss recovery rates for the CCN defaultapproach, RTO-based approach, and our proposed scheme.The CCN default approach assigns a static lifetime to eachof the interest packets. Considering the fact that the staticlifetime must be sufficient enough for the return of the data

packets from the different CCN nodes, this approach is themost conservative one. Therefore, it is unsuitable for delay-sensitive video streaming applications. The RTO algorithmcannot efficiently detect the RTT variation caused by the in-network caching and cannot distinguish the congestion loss

from the wireless error loss. Whenever a timeout occurs,the threshold value is doubled. The loss recovery rates arelower than those for our scheme, as the wireless error lossrate increases. For the evaluation of the video quality at theapplication layer, we have used the average PSNR as themeasurement criterion. Fig. 3 shows that a better video qualityhas been obtained with our proposed scheme when comparedwith the other approaches.

V. CONCLUSION

We have proposed an adaptive retransmission scheme torecover the video packet losses in content-centric wirelessnetworks. By applying the sequential hypothesis testing, theproposed scheme efficiently detects the RTT variation andtunes the timeout value. With taking into account the reasonsfor packet losses, our proposed scheme adaptively adjusts theretransmission window. The simulation results indicate thatour proposed scheme has achieved a better loss recovery rateand a better video quality when compared with the otherapproaches under various network conditions. As our futurework, we will perform a sensitivity analysis for differentnetwork bandwidths, video bit rates, and packet loss rates.

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