This article is an editorial note submitted to CCR. It has NOT been peer reviewed Authors take full responsibility for this article’s technical content. Comments can be posted through CCR Online In this paper we propose a radical solution to data hosting and delivery for the Internet of the future. The current data delivery architecture is “network centric”, with content stored in data centers connected directly to Internet backbones. This approach has multiple drawbacks among which complexity of deploying data centers, power consumption, and lack of scalability are the most critical ones. We propose a totally innovative and orthogonal approach to traditional data centers, through what we call “nano ” data centers, which are essentially boxes deployed at the edge of the network (e.g., in home gateways, set-top-boxes, etc.) that cooperate in a peer-to-peer manner. Unlike traditional peer-to-peer clients, however, our nano data centers operate under a common management authority, e.g., the ISP who installs and maintains the set-top-boxes, and can thus cooperate more effectively and achieve a higher aggregate performance. Nano data centers are, therefore, better suited for providing guaranteed quality to new emerging applications such as online gaming, interactive IPTV and VoD, and user generated content.

Motivated by increased concern over energy consumption in modern data centers, we propose a new, distributed computing platform called Nano Data Centers (NaDa). NaDa uses ISP-controlled home gateways to provide computing and storage services and adopts a managed peer-to-peer model to form a distributed data center infrastructure. To evaluate the potential for energy savings in NaDa platform we pick Video-on-Demand (VoD) services. We develop an energy consumption model for VoD in traditional and in NaDa data centers and evaluate this model using a large set of empirical VoD access data. We find that even under the most pessimistic scenarios, NaDa saves at least 20 % to 30 % of the energy compared to traditional data centers. These savings stem from energypreserving properties inherent to NaDa such as the reuse of already committed baseline power on underutilized gateways, the avoidance of cooling costs, and the reduction of network energy consumption as a result of demand and service co-localization in NaDa.

Abstract—In recent years, Telcos worldwide have deployed IPTV networks to offer cable TV-like services over the IP backbones. Such walled garden IPTV networks are provisioned to guarantee the quality of service, fast channel switching, and user experience expected by TV viewers. A common key design element of these networks is the use of IP multicast within a single network domain to broadcast several hundreds of TV channels to millions of receivers. However, as the amount of content and channels increase and users demand more interactive and asynchronous viewing, current IPTV architectures are showing clear limitations. In this paper, we study next-generation Telco-managed IPTV architectures, where P2P distributed systems are integrated in Telco’s TV set-top boxes or home gateways. We explore how P2P can complement existing Telco-managed IPTV architectures to support advanced rewind functionalities and whether P2P can substitute IP multicast solutions towards supporting a potentially unlimited number of live channels. To this extent, we analyze the TV viewing behavior of a quarter million users using real traces from one of the largest Telco-managed IPTV networks in the world and show the synergistic strengths and the potential for various P2P IPTV combined architectures. I.

Abstract- IP-enabled set-top boxes are becoming key devices in home entertainment networks. In addition to providing TV signals, STBs have been providing pay-per view service for a long time. But this service suffers from bandwidth requirements at the source server and has scaling problems. We propose a new design for providing a peer-assisted VoD service where peers co-operate in delivering the content to other peers. This design uses a Bittorrent like protocol for peer-to-peer topology management and DHT for data retrieval with low startup time, provision for VCR operation and admission control to guarantee QoS for subscribers. It utilizes the large storage of STBs for better viewing experience with reduced jitter and the underlying network architecture to do a location aware content fetching and reduce the expensive cross AS traffic over the Internet. 1.

Abstract—We present CPM, a unified approach that exploits server multicast, assisted by peer downloads, to provide efficient video-on-demand (VoD) in a service provider environment. We describe our architecture and show how CPM is designed to dynamically adapt to a wide range of situations including highly different peer-upload bandwidths, content popularity, user request arrival patterns (including flash-crowds), video library size, and subscriber population. We demonstrate the effectiveness of CPM using simulations (based on the an actual implementation codebase) across the range of situations described above and show that CPM does significantly better than traditional unicast, different forms of multicast, as well as peer-to-peer schemes. Along with synthetic parameters, we augment our experiments using data from a deployed VoD service to evaluate the performance of CPM. I.

Abstract—Peer-assisted Video-on-Demand (VoD) systems have not only received substantial recent research attention, but also been implemented and deployed with success in large-scale realworld streaming systems, such as PPLive [1]. Peer-assisted Videoon-Demand systems are designed to take full advantage of peer upload bandwidth contributions with a cache on each peer. Since the size of such a cache on each peer is limited, it is imperative that an appropriate cache replacement algorithm is designed. There exists a tremendous level of flexibility in the design space of such cache replacement algorithms, including the simplest alternatives such as Least Recently Used (LRU). Which algorithm is the best to minimize server bandwidth costs, so that when peers need a media segment, it is most likely available from caches of other peers? Such a question, however, is arguably non-trivial to answer, as both the demand and supply of media segments are stochastic in nature. In this paper, we seek to construct an analytical framework based on optimal control theory and dynamic programming, to help us form an in-depth understanding of optimal strategies to design cache replacement algorithms. With such analytical insights, we have shown with extensive simulations that, the performance margin enjoyed by optimal strategies over the simplest algorithms is not substantial, when it comes to reducing server bandwidth costs. In most cases, the simplest choices are good enough as cache replacement algorithms in peer-assisted VoD systems. I.

The growth of video content and diversification of content-sharing methods in the Internet lead to an exciting range of new problems in networking, communications, and signal processing. They range from fundamental theory and analytic models to practical design and industry deployment. This informal note briefly discusses some of the opportunities arising out of the “content-pipe” gap and presents some of the fundamental problems in distributing content over a network.

Abstract—Traditional Video-on-Demand (VoD) systems reply purely on servers to stream video content to clients, which does not scale. In recent years, Peer-to-peer assisted VoD (P2P VoD) has proven to be practical and effective [1]. In P2P VoD, each peer contributes some storage to store videos (or segments of videos) to help the video server. Assuming peers have sufficient bandwidth for the given video playback rate, a fundamental question is what is the relationship between the storage capacity (at each peer), the number of videos, the number of peers and the resultant off-loading of video server bandwidth. In this paper, we use a simple statistical model to derive this relationship. We propose and analyze a generic replication algorithm RLB which balances the service to all movies, for both deterministic and random demand models, and both homogeneous and heterogeneous peers (in upload bandwidth). We use simulation to validate our results, for sensitivity analysis and for comparisons with other popular replication algorithms. This study leads to several fundamental insights for design P2P VoD systems in practice. I.

We consider the fully distributed Video-on-Demand problem, where n nodes called boxes store a large set of videos and collaborate to serve simultaneously n videos or less between them. It is said to be scalable when Ω(n) videos can be distributively stored under the condition that any sequence of demands for these videos can always be satisfied. Our main result consists in establishing a threshold on the average upload bandwidth of a box, above which the system becomes scalable. We are thus interested in the upload bandwidth video bitrate normalized upload capacity u = of a box. The number m of distinct videos stored in the system is called its catalog size. We show an upload capacity threshold of 1 for scalability in a homogeneous system, where all boxes have the same upload capacity. More precisely, a system with u < 1 has constant catalog size m = O(1) (every box must store some data of every video). On the other hand, for u> 1, an homogeneous system where all boxes have same upload capacity at least u admits a static allocation of m = Ω(n) videos into the boxes such that any adversarial sequence of video demands can be satisfied. Moreover, such an allocation can be obtained randomly with high probability. This result is generalized to a system of boxes that have heterogeneous upload capacities under some balancing conditions. ∗ Research supported by CRC “MARDI II ” INRIA – Orange Labs and by ANR project “ALADDIN”.

This paper considers large scale distributed content service platforms, such as peer-to-peer video-on-demand systems. Such systems feature two basic resources, namely storage and bandwidth. Their efficiency critically depends on two factors: (i) content replication within servers, and (ii) how incoming service requests are matched to servers holding requestedcontent. Toinformthecorrespondingdesignchoices, we make the following contributions. Wefirstshowthat, for underloadedsystems, so-called proportional content placement with a simple greedy strategy formatchingrequeststoserversensuresfullsystemefficiency provided storage size grows logarithmically with the system size. However, for constant storage size, this strategy undergoes a phase transition with severe loss of efficiency as system load approaches criticality. To better understand the role of the matching strategy in this performance degradation, we characterize the asymptotic system efficiency under an optimal matching policy. Our analysis shows that –in contrast to greedy matching– optimal matching incurs an inefficiency that is exponentially small in the server storage size, even at critical system loads. It further allows a characterization of content replication policies that minimize the inefficiency. These optimal policies, which differ markedly from proportional placement, have a simple structure which makes them implementable in practice. On the methodological side, our analysis of matching performance uses the theory of local weak limits of random graphs, and highlights a novel characterization of matching numbers in bipartite graphs, which may both be of independent interest.