P2PTV Multi-Channel Peers Analysis

P2PTV Multi-channel Peers Analysis Marwan Ghanem∗1, Olivier Fourmaux1, Fabien Tarissan2, and Takumi Miyoshi3 1Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 75005 Paris, France 2Université Paris-Saclay, ISP, ENS Cachan, CNRS, 94235 Cachan, France 3College of Systems Eng. and Sc., Shibaura Institute of Technology, Saitama, 337-8570 Japan September 3, 2016 Abstract shed some light on the evolution of the infrastructure policy. After being the support of the data and voice con- vergence, the Internet has become one of the main video providers such as TV-stream. As an alterna- 1 Introduction tive to limited or expensive technologies, P2PTV has turned out to be a promising support for such ap- After being the support of the data and voice conver- plications. This infrastructure strongly relies on the gence, the Internet has become one of the main video overlay composed by the peers that consume and dif- providers (live TV or video on demand). Those multi- fuse video contents at the same time. Understand- media services were previously confined to the video ing the dynamical properties of this overlay, and in broadcasting infrastructures (terrestrial, satellite or particular how the users switch from one overlay to hybrid fibre/coax). The transmission of broadcasting another, appears to be a key aspect if one wants to quality TV streams in High Definition (or soon in Ul- improve the quality of P2PTV. tra High Definition 4K/8K) requires the use of huge In this paper, we investigate the question of relying amount of communications networks resources. The on non-invasive measurement techniques to track the development of dedicated technologies to distribute presence of users on several channels of P2PTV. Us- these contents is either local and limited to a resi- ing two datasets obtained by using network measure- dential operator (IPTV), or global but complex and ment on P2PTV infrastructure, we show that such an expensive (CDN). approach contains sufficient information to track the The alternative to these limited or expensive tech- presence of users on several channels. Besides, ex- nologies could be partly or completely based on P2P. ploiting the view provided by sliding time windows, In this context, peers communicate via virtual mesh we are able to refine the analysis and track users that networks (overlays) that connect them. The dynamic switch from one channel to another, leading to the topology of these overlays depends on many param- detection of super-peers and providing explanations eters: location of resources, network status, internal of the different roles they can play in the infrastruc- mechanisms of peers, as well as the distributed con- ture. In addition, by comparing the results obtained tent and the behaviour of the peers directly involved on the two datasets, we show how such analyses can as consumers of content. In the case of TV streams, specific constraints re- ∗[email protected] quire significant adaptation of P2P (specifically re- 1 lated to real-time aspects). A new application class P2PTV has evolved (Section 6). Finally we conclude realizes this kind of service: P2PTV. For these appli- the paper by presenting the perspectives opened by cations, the content consists of audio/video streams the present study (Section 7). to distribute in real-time to a large number of re- ceivers. The large number of streams and their in- trinsic real-time characteristics generate timing con- 2 Related Works straints which are difficult to guarantee in the considered dynamic environment. Strict compliance with Several studies and experiments have been done to these constraints impacts directly on the peer’s qual- analyse P2PTV applications [1, 2, 3, 4, 5, 6, 7]. Rossi ity of experience and thus on his behaviour, which in et al. proposed a framework for comparing P2P ap- turn impacts the overlay. plications [6] in which they define a set of observable P2PTV applications broadcast hundreds of chan- features related to the protocols used by the appli- nels, each carrying a live audio/video content to thou- cations. They highlighted the main similarities and sands of peers. Each channel corresponds to an over- differences between several P2P applications. In par- lay integrating peers wishing to receive its contents, ticular, they provided the key elements that open the and these peers can switch channels at any time (usu- way to passive analyses one can use when the ap- ally depending on the contents) adding an extra dy- plications are proprietary and no internal access is namic factor. provided. Spoto et al. presented an investigation It is this dynamical aspect we intend to address of PPLive using both active and passive measure- in the present paper. Although several works have ments [3]. Using a crawler, they were able to classify been proposed to measure and analyse the activity the traffic into three classes as well as to show that on P2PTV infrastructure, tracking the presence of only 15% of peers could be considered as active peers, peers active on different channels remains challeng- revealing the potentials and limits of PPLive active ing. Here we show that we can rely on non-invasive measurement strategies. measurement techniques such as Wireshark to track Other works have been done on a more quantita- peers switching from one channel to another. To do tive perspective [8, 9, 10, 11]. Hei et al. proposed for so, we rely on 2 datasets obtained by measurements instance a large scale measurement study of P2PTV, campaigns that coordinate several points of measure using a PPLive dedicated crawler [8]. By collecting a on a well known P2PTV infrastructure; we show that huge amount of data in different scenarios, they have although the views obtained by such a measurement shown that P2P-TV peers have the same behaviour approach are partial, they are sufficient to detect as IPTV users. They also demonstrated the existence multi-channel peers and highlight particularities in of a small set of super-peers that highly contribute their behaviour, thus leading the way to a more in- to the video uploading. Similarly, using a crawler, depth investigations on the subject. Jia et al. tried to characterize PPStream [9]. They The remainder of the paper is organised as fol- were able to find certain characteristics such as geo- low: we start by presenting existing works related to graphical clustering, arrival/departure patterns and the analysis of P2PTV applications (Section 2) be- playback quality. fore presenting the dataset used in the present paper Magharei et al. proposed a study on the struc- (Section 3). Then we turn to the study of the infor- ture of networks that most P2PTV applications used. mation contained in the dataset in order to analyse They examine key issues with such structures and the behaviour of multi-channel peers. We start by how bottlenecks can appear [12]. exploiting the dataset by aggregating all the infor- By passively studying the traffic in P2PTV infras- mation (Section 4) before refining our analysis us- tructures, Silverston et al. were able to compare dif- ing narrowed views provided by sliding time win- ferent applications pointing out their similarities and dows (Section 5). Then we show that comparing the differences [13]. Looking more deeply into the traffic, two datasets gives insight on how diffusion through they discovered that signalling traffic tends to have 2 For capturing and monitoring traffic, Wireshark [18], Table 1: Properties of the dataset a well-known packet sniffer, was running on every Property 2013 2015 measurement PC during the campaigns. Therefore Duration 14 hours 7 days we have the totality of the traffic that has been sent Number of channels 12 10 and received by our machines. Number of peers 100 809 289 710 The first dataset was extracted from a 14 hour long Maximum number of 21 518 96 258 traffic measured on December 2013 using 12 points of peers per channel measure, while the second was extracted from a 7 day Average payload size 504 B 408 B long traffic measured on July 2015 using 10 points of Total payload size 193 GB 601 GB measure. We shall refer to those datasets later on as 2013 and 2015 respectively. a large inter-packet time while video traffic tends Table 1 presents the global properties of both to have a smaller one. They also looked into peer datasets. We can particularly notice the huge amount behaviour, revealing that the vast majority of peers of data exchanged (193 GB and 601 GB for 2013 and tend to receive data more than they send, pointing 2015 respectively). It is also worth noticing that, al- out potential reciprocity issues. though 2015 dataset is way longer (12 times longer There are also few studies more specific to the peer than 2013 dataset), it exhibits a less dense traffic than behaviour and the multi-channel observations [14, 15, expected (the total payload size is for instance only 3 16, 17]. Wang et al. analysed the traffic that is char- times higher), which is partly due to the lower num- acteristic to peers switching from one channel to an- ber of channels. other [16]. Using the most popular P2PTV applications such as PPLive or SOPCast, they monitored a As mentioned in many previous works [19], traffic channel for a given period and then suddenly changed generated by such applications can be shared out into to another one. They revealed that switching has a two categories. Control (or signalling) traffic which huge impact on the network efficiency as it increases could be either a heart beat signal, a peer’s list ex- the overload and adds a significant overhead. Finally, change or buffer maps in form of a bit vector, repre- Mitzutani et al.

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