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Design and analysis of a peer-assisted VOD provisioning system for managed networks
Abstract
With the rise of VOD (Video-on-Demand) services provisioning as a successful service on the Internet and managed networks, we are witnessing a drive towards cost-efficiency and economies of scale. Many broadband operators around the world are experimenting with P2P (Peer-to-Peer) systems centered on STBs (Set-Top-Boxes) to increase the competitiveness of their VOD services offering. By leveraging the storage and uplink bandwidth capacities available at a certain number of STBs operated by the broadband operator, the savings in terms of backend streaming capacities will represent sizable and decisive gains in cost. In these systems, video contents are usually fragmented into a number of complementary content fragments, called sub-streams, which are randomly injected in the network of STBs, and the VOD service is essentially provisioned through multisource streaming sessions from neighboring STBs to the requesting STB. One of the main challenges in such peer-assisted streaming systems remains the maximization of the utilization of STB resources utility for a given content popularity pattern. In this paper, we specifically focus on the content injection strategy and how the different content fragments should be dispatched in the network to achieve the highest performance in the VOD services provisioning epoch. We demonstrate that the random injection strategy is not appropriate for maximizing the number of simultaneous VOD streaming sessions in the network. Our objective is to first gain a better understanding of the factors driving P2P-based VOD streaming systems and provide guidelines to better operate such systems and ultimately give service operators the tools to achieve different performance objectives and/or fit specific network configurations. Further, we propose a new content dispatching strategy that maximizes the number of served VOD sessions by balancing the streaming load among the different STBs. Finally, we propose a complementary streaming resources reprovisioning mechanism that acts in real-time to reprovision the resources for serving VOD sessions to new STBs and to release trapped resources for new incoming VOD service requests.
... Although there exist many approaches today for P2P live streaming over IP networks, P2P-VoD services provisioning is essentially a different problem as it involves streaming of pre-encoded content and, as such, it adds the whole content availability dimension to the problem [8]. With limited uplink and storage capacities at the peers, it is important to design effective resource allocation strategies that maximize the number of VoD session delivered during peak demand hours. ...
... Each duplicate is split into 5 complementary parts before storage in the network. The way the parts are spread in the network is investigated here [8]; it will be fixed throughout the experimental evaluation in this paper to more closely evaluate the resource allocation strategies. ...
With the rise of Video-on-Demand (VoD) systems as a preferred way to distribute video content over IP networks, many research works and innovations have focused on improving the scalability of streaming systems by looking at distributed approaches such as peer-to-peer (P2P). One of the most critical aspects in P2P-assisted streaming system is the real-time resource allocation, which drives the performance of the system in terms of capacity utilization and VoD requests rejection rates. In this paper, we specifically focus on the problem of maximizing the P2P streaming system utilization by effectively alternating between different resource allocation strategies. Switching between different resource allocation strategies is guided by a run-time statistical analysis of performances against predicted content popularity pattern. A key contribution of this paper resides in effectively combining different, and potentially conflicting, performance objectives when deciding on which resource allocation strategy to use. Indeed, we use a Bayesian Fusion to select the most appropriate resource allocation strategy to deal with future content demand. With our P2P resource allocation framework, a VoD service operator can combine any number of resource allocation strategies and formulate different performance objectives that meet the requirements of its network and the content consumption behavior of its users.
... They started to be deployed in homes to share Internet access among different devices and got additional functions as services (VoIP, IPTV) were delivered over the Internet. It is now fairly common to have home gateways embedding a hard drive, acting as Network Attached Storage to provide storage services to other home devices and offering some other ones to the outside world [7,19,20,21]. ...
... Another example is the concept of Nano Data Centers [7], where gateways are used to form a P2P system to offload data centers. Similarly, some approaches were proposed to move tasks from computers to static devices as set-top boxes, for VoD [20,36] and IPTV [37]. Yet, those applications fully run on gateways while, in our approach, the gateway only acts as buffering stage. ...
The availability of end devices of peer-to-peer storage and backup systems has been shown to be critical for usability and for system reliability in practice. This has led to the adoption of hybrid architectures composed of both peers and servers. Such architectures mask the instability of peers thus approaching the performances of client-server systems while providing scalability at a low cost. In this paper, we advocate the replacement of such servers by a cloud of residential gateways, as they are already present in users’ homes, thus pushing the required stable components at the edge of the network. In our gateway-assisted system, gateways act as buffers between peers, compensating for their intrinsic instability. We model such a system, for quick dimensioning and estimation of gains. We then evaluate our proposal using statistical distributions based on real world traces, as well as a trace of residential gateways for availability (that we have collected and now make available). Results show that the time required to backup data in the network is substantially improved, as it drops from days to a few hours. As gateways are becoming increasingly powerful in order to enable new services, we expect such a proposal to be leveraged on a short term basis.
... A similar approach, together with an optimal distribution algorithm are proposed in [24]. Another work that uses the contents' popularity to determine the optimal number of replicas on the peers is the model for peer-assisted streaming in [25] where the authors also propose a dispatching strategy for optimal utilization of the available uplink capacity of the peers. ...
... The main reason for that is the limited uplink capacity of the STBs, which is several times smaller than the necessary playback rate. To overcome this issue, we use an already accepted practice of partitioning of the contents [5,25]. For immediate and uninterrupted playing, a content item has to be streamed in parallel by as many peers as it is necessary for reaching its playback rate. ...
One of the key contributions of this work is that the model can substitute the long lasting simulations or the tedious measurements of the real systems in order to estimate the changes that would affect the system due to modifications of the system environment. The model can be also easily extended for planing the network environment for offering VoD service for High Definition (HD) videos. Although the network technologies permit higher upload rates, most of the users still do not have the sufficient capacity to stream entire videos, especially when the operator offers HD quality content. Therefore, our model could serve as a flexible tool for planning privately managed environments for VoD streaming.
... However, although the peers participate in the streaming process, the servers still remain an inevitable part of the system that guarantees the required QoS. The peer-assisted streaming combined with various content distribution schemes prove to be efficient in reducing [7,3,12,14,37,20,16,10,11] and even eliminating the traffic requested from the streaming servers [18,17]. While some of these systems assume that the peers are perfectly reliable, the authors in [3], deal with the possibility that some of the peers may be failed at the moment of choosing peers to assist in the streaming. ...
The growing popularity of the Video on Demand service in the Internet Protocol Television environments and the demand for increased quality of the offered videos are becoming a serious threat for the service providers because the high amounts of video traffic are causing congestion in the delivery networks. One of the most acceptable approaches to solve this issue is the peer-assisted streaming, where the peers participate in the streaming
process in order to alleviate the load on the streaming servers and in the core of the network.
Although the reliability of the Peer-to-Peer service is considerably improved in the managed
networks because of the control that the operators have over the clients’ Set-Top Boxes, the failures of the peers still cannot be completely eliminated. The operator can take advantage of the streaming and storage resources of the clients and use them for peer-assisted streaming only while they are watching a video, but not after they finish the streaming session because they may turn off their receiving devices until the next session. In this chapter, we address the issue of the failures of the peers in such environments and their influence on the traffic requested from the servers for providing uninterrupted video experience. For that purpose, we propose a precise mathematical tool for modelling a peer-assisted system for Video on Demand streaming in managed networks with non-cooperative peers, which may decide not to share their resources while they are not active. This tool calculates the performance of the system taking into consideration large variety of system parameters, including the failure probability and the time the peers spend until they decide to turn on the STB and join the network. As the results from the simulations verify the correctness of the mathematical model, we use it to analyse how the failures of the peers are affecting the system’s performance for different system parameters.
... In fact, there is a higher probability of satisfying a VOD request targeting the title T if the replicas of title T are spread over a larger number of STBs. These constraints can be achieved using the Popularity-Weighted Content Dispatching (PWCD) algorithm published in [3]. ...
In this document we propose simple approaches and guidelines to model and study peer-assisted (P2P) Video-on-Demand (VoD) systems. Furthermore, this document reports some simple approximation algorithms that can be exploited as fundamentals to develop further complex models.
... The peers help to reduce the traffic in the network core, but the servers still remain an inevitable part of the system that guarantees the required QoS. These solutions together with various content distribution schemes prove to be efficient in reducing [4], [5], [6], [7], [8], [9] and even eliminating the traffic requested from the streaming servers [10], [11]. ...
Video on Demand is a leading TV service offered by the IPTV operators in the past decade that has been rapidly gaining on popularity because it offers great convenience to the customers to watch any video they want at any time. However, the drawback of this service it that it is very resource demanding and expensive for the operator. One of the solutions for reducing the high traffic demands from the video servers is the imple-mentation of peer-assisted streaming, i.e., including the peers in the streaming process by taking advantage of their unused streaming and storage capacity. In order to estimate the reduction of the traffic demand depending on the network configuration and the intensity of demands for videos, we developed a stochastic model that determines the system behavior in stationary state. We proved that the model is a precise tool for estimating the server demands. However, the model requires high computation power for obtaining the desired results. The size of the number of linear equations that have to be solved grows rapidly with the growth of the number of peers and their streaming capacity, which is serious issue for using the model as a tool for estimation of the system performance. Therefore, we propose a sampling method that significantly reduces the size of the system of linear equations, and thus, reduces the computation time and resources required for obtaining the results. Our analysis shows that although the size of the system is reduced, the relative error compared to the original unreduced system is negligible.
... Although today there exist many approaches for P2P live streaming over IP networks, P2P VoD service provisioning is essentially a different problem as it involves streaming of preencoded content and, as such, it adds the whole content availability dimension to the problem [7]. With limited uplink and storage capacities at the peers, it is important to design effective resource allocation strategies that maximize the number of VoD sessions delivered during peak demand hours. ...
Video-on-Demand (VoD) systems are rising as a new dominant way to distribute video content over IP networks, although VoD services provisioning comes with its own scalability challenges for service providers. P2P video streaming systems are among the most scalable ways to deliver VoD services. While there has been much research work in the broad area of P2P communications, very limited research has been directed to the issue of resource allocation in P2P streaming systems where the real-time aspect adds another dimension to the problem. Most research work on P2P resource allocation tends to approach the problem with static strategies that do not dynamically adjust to changing content demand (popularity) trends, and fail to outperform over a long time period. In this article we specifically focus on the problem of maximizing the P2P streaming system capacity by effectively alternating between different resource allocation strategies. Switching between different resource allocation strategies is guided by a run-time statistical analysis of performance against a predicted content popularity pattern. A key contribution of this article resides in effectively combining different, and potentially conflicting, performance objectives when deciding which resource allocation strategy to use for the current time period. With our P2P resource allocation framework, a VoD service operator can combine any number of resource allocation strategies and formulate different performance objectives (decision criteria) that meet its requirements.
Aggregation Loss Bandwidth (ALB) within the last mile internet accounts for significant unusable bandwidth under current Internet Service Provider (ISP) centric routing strategies. Using a Hierarchical Network Topographical Routing (HNTR) scheme we show that this ALB can be exposed to the network and applications. A video streaming system is used as a case study to show the potential efficiency and monetary gains that can be made from exploiting this resource with minimal changes to the existing network infrastructure. This paper demonstrates the massive unused potential of the last mile Internet for video streaming services if a distributed management and billing architecture is introduced to the traditional Internet model.
Peer-assisted streaming network plays an important role in people’s daily lives, for users can watch multimedia resources anywhere, anytime. In this kind of network, servers need pre-pushing certain resources to users for caching which can be further retrieved by other users, and then the network performance can be improved. A key design algorithm in pre-pushing scheme is that which user should be selected to be pushed and how to price to keep the effectiveness and fairness of this action. To address this issue, we turn to multi-leader multi-follower Stackelberg model which is a hierarchical game model dealing with the resource competing among leaders and followers. In our model, we set that users are leaders who own bandwidth and define the price of a unit amount of bandwidth. Servers are followers and each of them selects a best user for pushing according to leaders’ equilibrium results. We build utility functions for each server and user, respectively, and maximize them according to the built Stackelberg model. The numerical simulation demonstrates the effectiveness and fairness of our proposed pushing scheme. Further, the comparison between traditional pre-pushing scheme and our proposed one is simulated which also shows that our proposed one can make more payoffs.
In this article, we present the design, implementation, and analysis of a scalable VOD (Video On Demand) distribution architecture for IP networks. The focus of our work is on the underlying multisource streaming architecture upon which the P2P (Peer-to-Peer) -based VOD services provisioning system relies. While multipoint-to-point multisource streaming is the core building block for a distributed VOD services provisioning system, it also introduces new reliability challenges as the streaming failure probability increases with the number of sources in a session. A major contribution of our work is the design of a suite of distinct yet complementary reliability/failover mechanisms that can be leveraged to improve the dependability of multisource streaming, and the viability of P2P-based VOD systems in general. Our work shows that the reliability/failover mechanisms can be arranged, combined, and alternated in advanced adaptation policies in order to deal with different conditions exhibited by the network. Another contribution of our work consists of implementing and assessing the performance of the different reliability mechanisms and adaptation policies in a real prototype system. We evaluate both the accuracy of streaming problems diagnosis, and the efficiency of the reliability mechanisms, in two adaptation strategies: one responsive to loss variation, and the other responsive to delay variation.
P2P file downloading and streaming have already become very popular Internet applications. These systems dramatically reduce the server loading, and provide a platform for scalable content distribution, as long as there is interest for the content. P2P-based video-on-demand (P2P-VoD) is a new challenge for the P2P technology. Unlike streaming live content, P2P-VoD has less synchrony in the users sharing video content, therefore it is much more difficult to alleviate the server loading and at the same time maintaining the streaming performance. To compensate, a small storage is contributed by every peer, and new mechanisms for coordinating content replication, content discovery, and peer scheduling are carefully designed. In this paper, we describe and discuss the challenges and the architectural design issues of a large-scale P2P-VoD system based on the experiences of a real system deployed by PPLive. The system is also designed and instrumented with monitoring capability to measure both system and component specific performance metrics (for design improvements) as well as user satisfaction. After analyzing a large amount of collected data, we present a number of results on user behavior, various system performance metrics, including user satisfaction, and discuss what we observe based on the system design. The study of a real life system provides valuable insights for the future development of P2P-VoD technology.
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.
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.
This paper studies the conditions under which peer-to-peer (P2P) technology may be beneficial in providing IPTV services over typical network architectures. It has three major contributions. First, we contrast two network models used to study the performance of such a system: a commonly used logical "Internet as a cloud" model and a "physical" model that reflects the characteristics of the underlying network. Specifically, we show that the cloud model overlooks important architectural aspects of the network and may drastically overstate the benefits of P2P technology. Second, we propose an algorithm called Zebra that pre-stripes content across multiple peers during idle hours to speed up P2P content delivery in an IPTV environment with limited upload bandwidth. We also perform simulations to measure Zebra's effectiveness at reducing load on the content server during peak hours. Third, we provide a cost-benefit analysis of P2P video content delivery, focusing on the profit trade-offs for different pricing/incentive models rather than purely on capacity maximization. In particular, we find that under high volume of video demand, a P2P built-in incentive model performs better than any other model, while the conventional no-P2P model generates more profits when the request rate is low. The flat-reward model generally falls in between the usage-based model and the built-in model in terms of profitability except for low request rates. We also find that built-in and flat-reward models are more profitable than the usage-based model for a wide range of subscriber community sizes.
We consider a P2P-assisted Video-on-Demand (VoD) system where each peer can store a relatively small number of movies to offload the server when these movies are requested. User requests are stochastic based on some movie popularity distribution. The problem is how to replicate (or place) content at peer storage to minimize the server load. Several variation of this replication problem have been studied recently with somewhat different conclusions. In this paper, we first point out that the main difference between these studies is in how they model the scheduling of peers to serve user requests, and show that these different scheduling assumptions will lead to different "op-timal" replication strategies. We then propose a unifying request scheduling model, parameterized by the maximum number of peers that can be used to serve a single request. This scheduling is called Fair Sharing with Bounded Out-Degree (FSBD). Based on this unifying model, we can compare the different replication strategies for different out-degree bounds and see how and why different replication strategies are favored depending on the out-degree. We also propose a new simple, adaptive, and essentially distributed replication algorithm, and show that this algorithm is able to adapt itself to work well for different out-degree in scheduling.
VOD services distribution is gaining unprecedented interest from the consumer communication industry due to its growing success in both the Internet and residential broadband market. In this article we present a scalable VOD distribution architecture for broadband operators. The solution is based on a P2P streaming concept in which a VOD streaming session requested by a given STB is actually provisioned via a multisource streaming session. This solution has the advantage of scaling naturally with the number of STBs in the network. In this article we focus on efficiently translating the popularity distribution into content availability in the network. Different aspects related to this issue are analyzed and challenges highlighted.
The availability of end devices of peer-to-peer storage and backup systems has been shown critical for usability and for system reliability in practice. This has led to the adoption of hybrid architectures composed of both peers and servers. Such architectures mask the instability of peers thus approaching the performances of client-server systems while providing scalability at a low cost. In this paper, we advocate the replacement of such servers by a cloud of residential gateways, as they are already present in users' homes, thus pushing the required stable components at the edge of the network. In our gateway-assisted system, gateways act as buffers between peers, compensating for their intrinsic instability. This enables to offload backup tasks quickly from the user's machine to the gateway, while significantly lowering the retrieval time of backed up data. We evaluate our proposal using real world traces including existing traces from Skype and Jabber as well as a trace of residential gateways for availability, and a residential broadband trace for bandwidth. Results show that the time required to backup data in the network is comparable to a server-assisted approach, while substantially improving the time to restore data, which drops from a few days to a few hours. As gateways are becoming increasingly powerful in order to enable new services, we expect such a proposal to be leveraged on a short term basis.
In this paper, we present Novasky, a real-world Video-on-Demand (VoD) system capable of delivering cinematic-quality video streams to end users. The foundation of the Novasky design is a peer-to-peer (P2P) storage cloud, storing and refreshing media streams in a decentralized fashion using local storage spaces of end users. We present our design objectives in Novasky, and how these objectives are achieved using a collection of unique mechanisms, with respect to caching strategies, coding mechanisms, and the maintenance of the supply-demand relationship when it comes to media availability in the P2P storage cloud. The production Novasky system has been implemented with over 100,000 lines of code. It has been deployed in the Tsinghua University campus network, operational since September 2009, attracting 10,000 users to date, and providing over 1,000 cinematic-quality video streams with bit rates of 1 - 2 Mbps. Based on real-world traces collected over 6 months, we show that Novasky can achieve rapid startups within 4 - 9 seconds, and extremely short seek latencies within 3 seconds. Our empirical experiences with Novasky may bring valuable insights to future designs of production-quality P2P storage cloud systems.
Content providers of P2P-Video-on-Demand (P2P-VoD) services aim to provide a high quality, scalable service to users, and at the same time, operate the system with a manageable operating cost. Given the volume-based charging model by ISPs, it is to the best interest of the P2P-VoD content providers to reduce peers' access to the content server so as to reduce the operating cost. In this paper, we address an important open problem: what is the “optimal replication ratio” in a P2P-VoD system such that peers will receive service from each other and at the same time, reduce the traffic to the content server. We address two fundamental problems: (1) what is the optimal replication ratio of a movie given its popularity, and (2) how to achieve the optimal ratios in a distributed and dynamic fashion. We formally show how movie popularities can impact server's workload, and formulate the video replication as an optimization problem. We show that the conventional wisdom of using the proportional replication strategy is non-optimal, and expand the design space to both passive replacement policy and active push policy to achieve the optimal replication ratios. We consider practical implementation issues, evaluate the performance of P2P-VoD systems and show that our algorithms can greatly reduce server's workload and improve streaming quality.
In this paper, we address the problem of content placement in peer-to-peer systems, with the objective of maximizing the utilization of peers' uplink bandwidth resources. We consider system performance under a many-user asymptotic. We identify optimal content placement strategies in a particular scenario of limited content catalogue, casting the problem into the framework of loss networks. We then turn to an alternative "large catalogue" scaling where the catalogue size grows with the peer population. Relating the system performance to properties of a specific random graph model, we establish a content placement strategy which again maximizes system performance, provided storage space per peer grows unboundedly, although arbitrarily slowly, with system size.
Motivated by increased concern over energy consumption in mod- ern 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 in- frastructure. 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 empiri- cal VoD access data. We find that even under the most pessimistic scenarios, NaDa saves at least 20% to 30% of the energy com- pared to traditional data centers. These savings stem from energy- preserving properties inherent to NaDa such as the reuse of al- ready 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.
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. 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.
P2P file downloading and streaming have already become very popular Internet applications. These systems dramat- ically reduce the server loading, and provide a platform for scalable content distribution, as long as there is interest for the content. P2P-based video-on-demand (P2P-VoD) is a new challenge for the P2P technology. Unlike streaming live content, P2P-VoD has less synchrony in the users sharing video content, therefore it is much more difficult to allevi- ate the server loading and at the same time maintaining the streaming performance. To compensate, a small storage is contributed by every peer, and new mechanisms for co- ordinating content replication, content discovery, and peer scheduling are carefully designed. In this paper, we describe and discuss the challenges and the architectural design issues of a large-scale P2P-VoD system based on the experiences of a real system deployed by PPLive. The system is also designed and instrumented with monitoring capability to measure both system and component specific performance metrics (for design improvements) as well as user satisfac- tion. After analyzing a large amount of collected data, we present a number of results on user behavior, various system performance metrics, including user satisfaction, and discuss what we observe based on the system design. The study of a real life system provides valuable insights for the future development of P2P-VoD technology.
The success of broadband residential Internet access is changing the way home users consume digital content and services. Currently, each home service requires the installation of a separate physical box (for instance, the NetFlix box or IPTV set-top-boxes). Instead, we argue for deploying a single box in the home that is powerful and flexible enough to host a variety of home services. In addition, this box is managed by the Internet Service provider and is able to provide service guarantees. We call such a box a service-hosting gateway (SHG), as it combines the functionalities of the home gateway managed by the network service provider with the capability of hosting services. Isolation between such services is ensured by virtualization. We demonstrate a prototype of our (SHG). It is based on the hardware platform that will be used for future home gateways. We illustrate the features of the SHG with multiple use cases ranging from simple service deployment scenarios to complex media distribution services and home automation features.
Internet Service Providers (ISPs) are in a constant race to meet the bandwidth demands of their subscribers. Access link upgrades, however, are expensive and take years to deploy. Many ISPs are looking for alternative solutions to reduce the need for continuous and expensive infrastructure expansion. This paper shows that there are many forms of local connectivity and storage in residential environments, and that these resources can be used to relieve the access network load. Making effective use of this local connectivity, however, introduces several challenges that require careful application and protocol design.We present a new system for a neighborhood-assisted video-on-demand service that reduces access link traffic by carefully placing VoD data across the neighborhood. We demonstrate that this approach can reduce the access network traffic that ISPs must provision for by up to 45% while still providing high-quality service.
IPTV, unlike Internet TV, delivers digital TV and multimedia services over IP-based networks with the required level of quality
of service (QoS) and quality of experience (QoE). Linear programming channels in IPTV are delivered through multicast, which
is highly scalable with the number of subscribers. Video-on-demand (VoD) content, on the other hand, is typically delivered
using unicast, which places a heavy load on the VoD servers and all the network components leading to the end-user set-top
boxes (STBs) as the demand increases. With the rapid growth of IPTV subscribers and the shift in video viewing habits, the
need to efficiently disseminate large volumes of VoD content has prompted IPTV service providers to consider the use of STBs
to assist in video content delivery. This paper describes our current research work on Zebroid, a potential VoD solution for
fiber-to-the-node (FTTN) networks, which uses IPTV data on a recurring basis to determine how to select, stripe, and preposition
popular content in selected STBs during idle hours. A STB requesting VoD content during the peak hours can then receive necessary
stripes from participating STBs in the neighborhood. Recent VoD request access patterns, STB availability data, and capacity
data on network components are taken into consideration in determining the parameters used in the striping algorithm of Zebroid.
We show both by simulation and emulation on a realistic IPTV testbed that the VoD server load can be reduced by more than
70% during peak hours by allocating only 8 GB of storage on each STB. The savings achieved through Zebroid would also allow
IPTV service providers to add more linear programming channels without expensive infrastructure upgrades.
In this paper we propose a radical solution to data host- ing 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 back- bones. This approach has multiple drawbacks among which complexity of deploying data centers, power consumption, and lack of scalability are the most critical ones. We pro- pose a totally innovative and orthogonal approach to tra- ditional 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 coop- erate more effectively and achieve a higher aggregate perfor- mance. 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.
Using proxy servers to cache and shape network traffic can significantly improve the energy efficiency of the participating mobile clients. In this article, we analyze the implications of hosting a BitTorrent proxy on a broadband router, which pushes the content to a mobile phone over wireless radio (WLAN or 3G). The amount of memory in a router is limited; therefore, our interest is in how to efficiently use memory to download BitTorrent content as fast as possible and at the same time transfer it to the mobile phone in an energy-efficient way. We investigate these aspects via a series of measurements. The results show that the proxy-based solution outperforms the torrent client running on the phone in terms of energy and download time. We also simulate the BitTorrent operation to understand how these memory-limited devices would influence the operation of the whole community.
In this paper, we address the problem of content placement in peer-to-peer
systems, with the objective of maximizing the utilization of peers' uplink
bandwidth resources. We consider system performance under a many-user
asymptotic. We distinguish two scenarios, namely "Distributed Server Networks"
(DSN) for which requests are exogenous to the system, and "Pure P2P Networks"
(PP2PN) for which requests emanate from the peers themselves. For both
scenarios, we consider a loss network model of performance, and determine
asymptotically optimal content placement strategies in the case of a limited
content catalogue. We then turn to an alternative "large catalogue" scaling
where the catalogue size scales with the peer population. Under this scaling,
we establish that storage space per peer must necessarily grow unboundedly if
bandwidth utilization is to be maximized. Relating the system performance to
properties of a specific random graph model, we then identify a content
placement strategy and a request acceptance policy which jointly maximize
bandwidth utilization, provided storage space per peer grows unboundedly,
although arbitrarily slowly, with system size.
We analyze a system where $n$ set-top boxes with same upload and storage capacities collaborate to serve $r$ videos simultaneously (a typical value is $r=n$). We give upper and lower bounds on the catalog size of the system, i.e. the maximal number of distinct videos that can be stored in such a system so that any demand of at most $r$ videos can be served. Besides $r/n$, the catalog size is constrained by the storage capacity, the upload capacity, and the maximum number of simultaneous connections a box can open. We show that the achievable catalog size drastically increases when the upload capacity of the boxes becomes strictly greater than the playback rate of videos.
We propose Push-to-Peer, a peer-to-peer system to cooperatively stream video. The main departure from previous work is that content is proactively pushed to peers, and persistently stored before the actual peer-to-peer transfers. The initial content placement increases content availability and improves the use of peer uplink bandwidth. Our specific contributions are: (i) content placement and associated pull policies that allow the optimal use of uplink bandwidth; (ii) performance analysis of such policies in controlled environments such as DSL networks under ISP control; (iii) a distributed load balancing strategy for selection of serving peers.
The compelling success of Internet Video-on-Demand (VoD) services imposes hard requirements on the current Internet in terms of servers and network capabilities (e.g. for load, bandwidth). Service scalability becomes then a crucial issue for which server replication acts as a commonly proposed solution. However, this technique brings new challenges in terms of server placement and selection. This paper presents an enhanced service oriented architecture permitting Service Providers (SP) to exploit a new virtual Home-Box (HB) layer for distributing efficient and scalable Future Internet VoD streaming services. Such proposed architecture enables strong collaboration between User and Service Environments for ensuring better Quality of Services to End-Users. The paper proposes an adaptive popularity-based video caching strategy among the introduced HB layer and compares it, through simulation, to existing CDNs' one. The obtained results highlight a very promising aspect for the introduction of HBs-assisted CDNs in the video delivery chain.
The compelling success of Internet Video-on-Demand (VoD) services imposes hard requirements on the current Internet in terms of servers and network capabilities (e.g. for load, bandwidth). Service scalability becomes then a crucial issue for which server replication acts as a commonly proposed solution. However, this technique brings new challenges in terms of server placement and selection. This paper presents an enhanced service oriented architecture permitting Service Providers (SP) to exploit a new virtual Home-Box (HB) layer for distributing efficient and scalable Future Internet VoD streaming services. Such proposed architecture enables strong collaboration between User and Service Environments for ensuring better Quality of Services to End-Users. The paper proposes an adaptive popularity-based video caching strategy among the introduced HB layer and compares it, through simulation, to existing CDNs' one. The obtained results highlight a very promising aspect for the introduction of HBs-assisted CDNs in the video delivery chain.
Nowadays, there has been significant deployment of peer-assisted on-demand streaming services over the Internet. Two of the most unique and salient features in a peer-ass
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isted on-demand streaming system are the differentiation in the demand (or request) and the prefetching capability with caching. In this paper, we develop a theoretical framework based on queuing models, in order to 1) justify the superiority of service prioritization based on a taxonomy of requests, and 2) understand the fundamental principles behind optimal prefetching and caching designs in peer-assisted on-demand streaming systems. The focus is to instruct how limited uploading bandwidth resources and peer caching capacities can be utilized most efficiently to achieve better system performance. To achieve these objectives, we first use priority queuing analysis to prove how service quality and user experience can be statistically guaranteed, by prioritizing requests in the order of significance, including urgent playback (e.g., random seeks or initial startup), normal playback, and prefetching. We then proceed to construct a fine-grained stochastic supply-demand model to investigate peer caching and prefetching as a global optimization problem. This not only provides insights in understanding the fundamental characterization of demand, but also offers guidelines toward optimal prefetching and caching strategies in peer-assisted on-demand streaming systems.
P2P-based video-on-demand (P2P-VoD) streaming service has recently emerged as a new paradigm of Internet application. Unlike streaming live content, P2P-VoD system require each user to contribute a small amount of storage since it has less synchrony in the users sharing video content. At the same time, new mechanisms for peer service scheduling are carefully designed. On briefly describing the architectural design based on the real system deployed by PPLive, we develop a stochastic model that seeks to expose the essential behavior of the PPLive P2P-VoD system. The performance evaluation followed shows that the system design of PPLive P2P-VoD system could guarantee good viewing quality, and sheds insight on the fundamental characteristics and limitations of the system quantitatively. Such theoretical analysis on P2P-VoD could help to improve the viewing quality and make such system more robust and scalable.
Using proxy servers to cache and shape network traffic can significantly improve the energy efficiency of the participating mobile clients. In this article, we analyze the implications of hosting a BitTorrent proxy on a broadband router, which pushes the content to a mobile phone over wireless radio (WLAN or 3G). The amount of memory in a router is limited; therefore, our interest is in how to efficiently use memory to download BitTorrent content as fast as possible and at the same time transfer it to the mobile phone in an energy-efficient way. We investigate these aspects via a series of measurements. The results show that the proxy-based solution outperforms the torrent client running on the phone in terms of energy and download time. We also simulate the BitTorrent operation to understand how these memory-limited devices would influence the operation of the whole community.
To improve the efficiency and the quality of a service, a network operator may consider deploying a peer-to-peer architecture among controlled peers, also called here nano data centers, which contrast with the churn and resource heterogeneity of peers in uncontrolled environments. In this paper, we consider a prevalent peer-to-peer application: live video streaming. We demonstrate how nano data centers can take advantage of the self-scaling property of a peer-to-peer architecture, while significantly improving the quality of a live video streaming service, allowing smaller delays and fast channel switching. We introduce the branching architecture for nano datacenters (BAND), where a user can “pull” content from a channel of interest, or content could be “pushed” to it for relaying to other interested users. We prove that there exists an optimal trade-off point between minimizing the number of push, or the number of relaying nodes, and maintaining a robust topology as the number of channels and users get large, which allows scalability. We analyze the performance of content dissemination as users switch between channels, creating migration of nodes in the tree, while flow control insures continuity of data transmission. We prove that this p2p architecture guarantees a throughput independently of the size of the group. Analysis and evaluation of the model demonstrate that pushing content to a small number of relay nodes can have significant performance gains in throughput, start-up time, playback lags and channel switching delays.
This paper explores requirements for efficient pre-seeding of video-on-demand (VoD) movie data onto numerous customer set-top boxes in a cable ISP environment. The pre-seeded content will then be distributed to other set-top boxes in the same cable community using a peer-to-peer (P2P) network protocol such as BitTorrent. The challenges and solutions required for P2P VoD provided by a fixed provider such as a cable company are fundamentally different from those seen in traditional P2P networks or client-server VoD solutions. Our work pre-positions data into set-top boxes using a mathematical programming algorithm. The objective of the algorithm is to minimize uplink traffic, given a popularity model for various pieces of content and information about storage and bandwidth capacity constraints at the customer nodes. Given the complex non-linear nature of P2P interactions, these mathematical programs are solved using non-linear optimization approaches. Using a BitTorrent-like peer-to-peer data delivery system, we show through extensive simulations that our mathematical model for pre-seeding data based on object popularity and node bandwidth availability leads to noticeably greater reductions in uplink traffic and VoD server load than a weighted-random pre-seeding scheme that only considers object popularity.
This paper presents and evaluates Toast, a scalable Video-on- Demand (VoD) streaming system that combines the popular Bit- Torrent peer-to-peer (P2P) file-transfer technology with a simple dedicated streaming server to decrease server load and increase client transfer speed. Toast includes a modified version of BitTor- rent that supports streaming data delivery and that communicates with a VoD server when the desired data cannot be delivered in real-time by other peers. The results show that the default BitTorrent download strategy is not well-suited to the VoD environment because it fetches pieces of the desired video from other peers without regard to when those pieces will actually be needed by the media viewer. Instead, strate- gies should favor downloading pieces of content that will be needed earlier, decreasing the chances that the clients will be forced to get the data directly from the VoD server. Such strategies allow Toast to operate much more efficiently than simple unicast distribution, reducing data transfer demands by up to 70-90% if clients remain in the system as seeds after viewing their content. Toast thus ex- tends the aggregate throughput capability of a VoD service, offload- ing work from the server onto the P2P network in a scalable and demand-driven fashion.
Video on Demand (VoD) service has become an increasingly popular service in recent years as a result of the rapid deployment of Fiber-to-the-Home networks. Due to its enormous bandwidth and stringent quality of service requirements, deploying an efficient and scalable VoD service still remains a challenge. In this paper, we propose a peer-to peer (P2P) VoD distribution scheme for PONs in which the P2P delivery is localized to within the same access network and in which a selected set of movies is pre-fetched into the customer premises equipment during off-peak hours. The proposed delivery scheme mitigates the load from the VoD server by exploiting the participation of the customer equipment in VoD distribution. In turn, this optimizes bandwidth consumption of the VoD service in both core and metro networks as the P2P video traffic is localized within the access network. We formulate movie pre-fetching as an optimization problem which determines the number of copies of each movie to be pre-fetched, and we propose a heuristic algorithm to solve it. Using simulations we show that our proposed replication algorithm performs much better than existing popularity based replication algorithm that has been proposed for similar purposes. Moreover, we show that our proposed delivery scheme effectively reduced the server load in busy hours while having high but random server load reduction in off-peak hours of service.
Energy consumption is responsible for a large fraction of costs in today's content distribution networks. In upcoming decentralized architectures based on set-top boxes (STB), acting as tiny servers, idle times can dominate distribution costs, since no cooling costs occurs and the Internet access is often paid in a flat-rate manner. The often assumed always-on property of STBs provides high availability but might also waste up to 93% of the baseline energy. In this paper we consider suitable standby policies that reduce energy consumption but still allow offloading content servers significantly. We devise optimal and heuristic standby policies and evaluate them in a realistic scenario to show that a near-optimal behavior can be reached by utilizing the specific features of STBs.
Observed on-demand usage patterns and its implications for large-scale VoD system design. Kasenna Whitepaper
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Kasenna (2006) Observed on-demand usage patterns and its implications for large-scale VoD
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RFC 3016: RTP payload format for MPEG-4 Audio/Visual streams (Proposed Standard)
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for MPEG-4 Audio/Visual streams (Proposed Standard). Internet Task Force
Achievable catalog size in peer-to-peer video-on-demand systems
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peer-to-peer video-on-demand systems. In: Proceedings of 2008 IEEE international conference
on peer-to-peer computing, P2P '08, pp 1-6
On next-generation telco-managed p2p tv architectures
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A unifying model and analysis of p2p vod replication and scheduling
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he started working as a research assistant at UPCT where he obtained his Ph.D. in 2011. Currently, he works as an assistant professor in the Department of Information Technologies and Communications at UPCT
- Juan Pedro Muñoz
Juan Pedro Muñoz-Gea received the Telematics Technical Engineering degree (cum laude) and
the Telecommunications Engineering degree (cum laude) in 2003 and 2005 respectively, both from
Universidad Politécnica de Cartagena (UPCT), Spain. In 2006, he started working as a research
assistant at UPCT where he obtained his Ph.D. in 2011. Currently, he works as an assistant professor
in the Department of Information Technologies and Communications at UPCT. His research
interests are focused on overlay networks and peer-to-peer systems.