On-demand Streaming Research Articles

From Torrent to Stream

Music production in the 21st century shifted from a largely commodified industrial model to a radically decentralized one, technologically facilitated by new efficiencies in search of functionality, delivery, and peer-to-peer connectivity. In the older music economy, the media of music (its tangible forms—vinyl, cassette, compact disc, etc.) were fused with its contents (its sounding forms—songs, pieces, etc.), thereby facilitating their efficient circulation as physical commodities (grounded in licensing agreements, copyright protections, and so on). In the newer economy, medium and content are increasingly delinked; the former is effectively dematerialized (or, more accurately, micro-materialized as virtualized format), thereby posing new challenges to law and policy governing musical creation, distribution, and consumption. In the context of music’s new technological prostheses (digital recording studios, on-demand streaming services, algorithmic aggregators, and the like) the question of equitable sources of revenue for musical labor has re-surfaced as a central debate in our times. The article assesses the promise of disintermediation in relation to new formations of labor, characterized by increased entrepreneurial reliance on flexible and globalized networks of production and distribution.

On-demand streaming services and music industry revenues — Insights from Spotify's market entry

On-demand streaming services that rely on subscription fees or advertising as a revenue source (e.g., Spotify) are a topic of ongoing controversial debate in the music industry because their addition to the distribution mix entails the risk of cannibalization of other distribution channels (e.g., purchases of downloads or CDs) and might reduce overall revenues. To date, no research has assessed the effect of streaming services on revenue, and whether cannibalization indeed takes place. Our research fills this void and assesses the impact of free and paid streaming services on music expenditures and on total music industry revenue. To this end, we constructed a research design in which we observed a panel of more than 2500 music consumers repeatedly over more than one year. This approach allows us to eliminate individual-specific unobserved effects that may otherwise confound the identification of a cannibalization effect. Our results show that the adoption of a free streaming service as well as the adoption of a paid streaming service cannibalizes consumers' music expenditures. The net effect of paid streaming services on revenue, however, is clearly net positive. In contrast, the net effect of free streaming services on revenue is only positive for consumers who were relatively inactive before the adoption. On the industry level, our findings suggest that the negative effect of free streaming on industry revenue is offset by the positive effect of paid streaming in the context that we analyze. Hence, in the market that we study and under the assumptions that we make, we estimate that the overall effect of streaming on industry revenue is positive.

Optimizing Caching in a Patch Streaming Multimedia-on-Demand System

In on-demand multimedia streaming systems, streaming techniques are usually combined with proxy caching to obtain better performance. The patch streaming technique has no start-up latency inherent to it, but requires extra bandwidth to deliver the media data in patch streams. This paper proposes a proxy caching technique which aims at reducing the bandwidth cost of the patch streaming technique. The proposed approach determines media prefixes with high patching cost and caches the appropriate media prefix at the proxy/local server. Herein the scheme is evaluated using a synthetically generated media access workload and its performance is compared with that of the popularity and prefix-aware interval caching scheme (the prefix part) and with that of patch streaming with no caching. The bandwidth saving, hit ratio and concurrent number of clients are used to compare the performance, and the proposed scheme is found to perform better for different caching capacities of the proxy server.

A First Design Approach to a Multimedia SDK Based on a Hybrid P2P Architecture

The Internet multimedia streaming increased proportional to the number of streaming users and from 2005 peer-to-peer media streaming received a substantial amount of research attention and was applied for both live and on-demand video streaming. This technique succeeded to provide a large number of multimedia streams while consuming less bandwidth than in the case of a client-server architecture. Multimedia streaming is a complex subject, it widens over various computer science fields as the networking area, multimedia compression area and the security area. Due to the increasing need of multimedia streaming applications and the need for continuous communication with harsh constraints such as real-time communication, low bandwidth and content security, the need for a flexible and extensible tool is justified, and the main purpose of such a tool is to facilitate the development of applications such as Goober (9), IConf (10), Ekiga (11) or Skype (12). The responsibilities of such SDK are to capture efficiently multimedia information from a web camera and/or a microphone and send them to its peer. The proposed SDK was built on the .NET Framework 4.5 based on a hybrid peer-to-peer architecture. The SDK can be integrated on multiple .NET platforms such .NET Framework 4.5, Silverlight, and Windows Phone 8, and due to its flexibility it can be used by desktop clients, web clients and mobile clients. From a communication perspective, the SDK starts several independent services which capture incoming data, and uses dynamic proxy objects to send data to its peers, services which assure the necessary degree of parallelism needed to have a responsive application with real-time communication.

Service availability of a peer with dynamic buffering for multiple description coded videos on multi-source streaming networks

In multi-source streaming systems, such as peer-to-peer (P2P), because the buffer space of each peer is limited, most systems employ the cache-and-relay schemes that require each peer to cache the most recent video blocks it receives. As long as a peer keeps the initial part of the video stream in the buffer, it can relay the cached blocks to new arriving peers in a pipelining fashion and then reduce the loading of a server. In our previous research work, we propose a novel caching scheme for peer-to-peer on-demand video streaming, called Dynamic Buffering, which relies on the feature of Multiple Description Coding to gradually reduce the number of cached descriptions in a peer once the buffer is full in order to prolong the service availability of a peer. In this paper we study the service availability of a peer with dynamic buffering for various numbers of different forwarded descriptions, and provide detailed analysis on how the number of different forwarded descriptions affects the average service availability of a peer. In addition, we derive the mathematical formulas of the reduction of the average service availability of a peer for various numbers of different forwarded descriptions, compared to the best case of the service availability of a peer, and the gain of the average service availability of a peer by releasing the overlapped buffer space with child peers. Our experimental results show that the reduction of the average service availability of a peer is only related to the number of different forwarded descriptions. Besides, regardless of arrival rates, most peers forwarding only one description would possess the highest average service availability for various numbers of different forwarding descriptions, which matches the criteria of the previous work Splitstream.

Delivery Consolidation and Service Competition Among Internet Service Providers

The infrastructure of the Internet, by and large, is maintained by Internet service providers (ISPs) that cater to regional customers and by Internet backbone providers (IBPs) that serve large organizations and ISPs. Some IBPs have recently branched into content delivery network (CDN) services; separately, other ISPs have started offering on-demand video streaming to compete with pure-play content providers. These developments have intensified the competition in both content delivery and media-streaming markets. For the content delivery market, we study the competition equilibriums by analyzing factors such as market share, cost structure, service pricing, and subscriber preference. Our approach helps identify conditions under which a content provider should choose an IBP over the incumbent CDN for content distribution. We also show how an IBP’s CDN venture affects its interconnection relationship with ISPs. For the streaming service market, we examine conditions under which a content provider would partner with an ISP to lower operating and marketing costs while providing a more streamlined subscriber experience. Analytically, our game-theoretical models can optimize key contracting and pricing strategies for multiple classes of service providers; empirically, insights derived from the proposed models have anticipated events that coincide with several recent developments in content delivery and streaming service markets.

Ant-Inspired Mini-Community-Based Solution for Video-On-Demand Services in Wireless Mobile Networks

Highly efficient distribution and management of media resources and fast content discovery are key determinants for mobile peer-to-peer video-on-demand solutions, especially in wireless mobile networks. Virtual communities making use of users' common characteristics such as interest and interaction to describe the boundary of sharing content and objects are a promising avenue for high-efficiency resource sharing. In this paper, we propose a novel ant-inspired mini-community-based video sharing solution for on-demand streaming services in wireless mobile networks (AMCV). AMCV relies on a newly designed two layer architecture and on an algorithm inspired from the indirect communication between ants via pheromone trails which enables them to discover and use shortest paths. The architecture is composed of a mini-community network layer and a community member layer. The ant-inspired algorithm enables finding the common interest of users in video content within large amounts of pseudo disorderly interactive behavior data. AMCV proposes an ant colony optimization-based community communication strategy that dynamically bridges communities to support fast search for resources. AMCV achieves high scalability by making use of a designed community maintenance mechanism to uniformly distribute the maintenance cost of members and resources in the community, according to various member roles. Simulation-based testing shows how AMCV outperforms another state-of- the-art solution in terms of a wide set of performance metrics.

Dissecting the protocol and network traffic of the OnLive cloud gaming platform

Cloud gaming is a new paradigm that is envisaged to play a pivotal role in the video game industry in forthcoming years. Cloud gaming, or gaming on demand, is a type of online gaming that allows on-demand streaming of game content onto non-specialised devices (e.g. PC, smart TV, etc.). This approach requires no downloads or game installation because the actual game is executed on the game company's server and is streamed directly to the client. Nonetheless, this revolutionary approach significantly affects the network load generated by online games. As cloud gaming presents new challenges for both network engineers and the research community, both groups need to be fully conversant with these new cloud gaming platforms. The purpose of this paper is to investigate OnLive, one of the most popular cloud gaming platforms. Our key contributions are: (a) a review of the state-of-the-art of cloud gaming; (b) reverse engineering of the OnLive protocol; and (c) a synthetic traffic model for OnLive.

Analyzing Peer Selection Policies for BitTorrent Multimedia On-Demand Streaming Systems in Internet

The adaptation of the BitTorrent protocol to multimedia on-demand streaming systems essentially lies on the modification of its two core algorithms, namely the piece and the peer selection policies, respectively. Much more attention has though been given to the piece selection policy. Within this context, this article proposes three novel peer selection policies for the design of BitTorrent-like protocols targeted at that type of systems: Select Balanced Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select Optimistic Neighbour Policy (SONP). These proposals are validated through a competitive analysis based on simulations which encompass a variety of multimedia scenarios, defined in function of important characterization parameters such as content type, content size, and client interactivity profile. Service time, number of clients served and efficiency retrieving coefficient are the performance metrics assessed in the analysis. The final results mainly show that the novel proposals constitute scalable solutions that may be considered for real project designs. Lastly, future work is included in the conclusion of this paper.

On Client’s Interactive Behaviour to Design Peer Selection Policies for Bittorrent-Like Protocols

Peer-to-peer swarming protocols have been proven to be very efficient for content replication over Internet. This fact has certainly motivated proposals to adapt these protocols to meet the requirements of on-demand streaming system. The vast majority of these proposals focus on modifying the piece and peer selection policies, respectively, of the original protocols. Nonetheless, it is true that more attention has often been given to the piece selection policy rather than to the peer selection policy. Within this context, this article proposes a simple algorithm to be used as basis for peer selection policies of BitTorrent-like protocols, considering interactive scenarios. To this end, we analyze the client interactive behaviour when accessing real multimedia systems. This analysis consists of looking into workloads of real content providers and assessing three important metrics, namely temporal dispersion, spatial dispersion and object position popularity. These metrics are then used as the main guidelines for writing the algorithm. To the best of our knowledge, this is the first time that the client interactive behaviour is specially considered to derive an algorithm for peer selection policies. Finally, the conclusion of this article is drawn with key challenges and possible future work in this research field.

Cinematic-Quality VoD in a P2P Storage Cloud: Design, Implementation and Measurements

In this paper, we explore the design space and practice of a new peer-to-peer (P2P) storage cloud, which is capable of replicating, refreshing and on-demand streaming of cinematic-quality video streams, in a decentralized fashion using local storage spaces of end users. We identify key design challenges and tradeoffs in such a P2P storage cloud, and how these are addressed by making informed design choices in a step-by-step fashion. Following our design choices, we have implemented a real-world Video-on-Demand (VoD) system with over 100,000 lines of code, called Novasky, which features new coding-aware peer storage replacement and server push-to-peer strategies, in order to maintain media availability and to balance the system-wide supply-demand relationship in the P2P storage cloud. Since September 2009, it has been deployed in the Tsinghua University campus network, attracting 10,000 users during our measurement studies from February to July 2010, 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, while maintaining reasonable operational overhead and server bandwidth costs. Our general understanding on the design tradeoffs of P2P storage cloud and practical experiences with Novasky may bring valuable guidelines to future designs of production-quality P2P storage cloud systems.

A scalable delivery solution and a pricing model for commercial video-on-demand systems with video advertisements

This paper presents a scalable delivery solution for commercial near on-demand video streaming systems with an associated pricing model. The proposed delivery solution combines the benefits of periodic broadcasting and stream merging, thereby enabling scalable video delivery. Video advertisements are delivered to the clients prior to viewing the requested videos. The revenues generated from the ads are used to subsidize the price of the requested videos. The pricing is determined based on the total ad viewing time. The proposed solution includes an efficient ad allocation scheme and a new constraint-based scheduling approach. In addition, the paper investigates how targeted advertisements can be efficiently supported. Furthermore, we investigate the effectiveness of the overall solutions and analyze and compare the effectiveness of various scheduling policies and ad allocation alternatives in terms of several metrics, including client defection probability, average number of viewed ads per client, price, channel utilization, revenue, and profit.

Mathematical Analysis of caching policies and cooperation in YouTube-like services

Abstract Currently, most video on-demand services offered over the Internet do not exploit the idle resources available from end-users. We discuss the benefits of user-assistance in video on-demand systems, where users are both clients and servers, helping with the task of video distribution. The mathematical machinery for the systematic analysis of video on-demand services is not mature yet. In this paper we develop a deterministic fluid model to determine the expected evolution of user-assisted on-demand video streaming services. We theoretically prove that cooperative systems always outperform non-cooperative solutions. A combinatorial optimization problem is proposed, where the goal is to distribute a set of video items into repositories trying to offer the minimum waiting times to end-users. This combinatorial problem is proved to be in the class of NP-Complete computational problem, and is heuristically solved with a GRASP methodology. Predictions inspired in YouTube scenarios suggest the introduction of cooperation is both robust and extremely attractive from an economical viewpoint as well.

Peer-Assisted On-Demand Streaming: Characterizing Demands and Optimizing Supplies

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-assisted 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.

VOD STREAMING WITH A NETWORK CODING EQUIVALENT CONTENT DISTRIBUTION SCHEME

Although random access operations are desirable for on-demand video streaming in peer-to-peer systems, they are difficult to efficiently achieve due to the asynchronous interactive behaviors of users and the dynamic nature of peers. In this paper, we propose a network coding equivalent content distribution (NCECD) scheme to efficiently handle interactive videoon- demand (VoD) operations in peer-to-peer systems. In NCECD, videos are divided into segments that are then further divided into blocks. These blocks are encoded into independent blocks that are distributed to different peers for local storage. With NCECD, a new client only needs to connect to a sufficient number of parent peers to be able to view the whole video and rarely needs to find new parents when performing random access operations. In most existing methods, a new client must search for parent peers containing specific segments; however, NCECD uses the properties of network coding to cache equivalent content in peers, so that one can pick any parent without additional searches. Experimental results show that the proposed scheme achieves low startup and jump searching delays and requires fewer server resources. In addition, we present the analysis of system parameters to achieve reasonable block loss rates for the proposed scheme.

Leading change through creative destruction: how Netflix's self-destruction strategy created its own market

By continuing to build the Netflix brand as a cutting-edge pioneer with a culture of innovation, Netflix has conquered the video rental-by-mail market under the transformational, charismatic leadership of CEO Reed Hastings. This paper offers the perspective that Netflix has survived a planned process of creatively designed destruction to renew its long-term strategy as it leads the video rental industry into the emerging world of on-demand streaming content. Drawing on the construct of ethical anarchy by Hurst (2002, 2012), as well as contributions from Morgan (2006, 2011), Jaworski (2011), and Argyris (2002), this research builds upon the concept of organisational renewal and sustainability through crisis and change, and argues that Netflix’s actions have been strategic and purposeful, leveraging innovation and customer loyalty.

Reshaping The Music Distribution Model: An Itunes Opportunity

Many experts believe that subscription services are the last great hope for the music recording industry; however, the underwhelming success of existing subscription services have deterred music rights holders from embracing the subscription model. While many understand why the subscription model should be implemented, few understand how it could be introduced. This study sought to create a conceptual framework to demonstrate how an on-demand subscription-based streaming service could be successfully implemented, in music, by studying a successful subscription model, Netflix, which operates in a parallel industry. By examining Netflix, and analyzing the differences and similarities between the video and music industries, this study created a conceptual framework which demonstrates how to successfully implement a similar service model in music, with the opportunity to create significant value.

Multisource Video On-Demand Streaming in Wireless Mesh Networks

We study the multisource video on-demand (VoD) application in multichannel multiradio wireless mesh networks. When a user initiates a new video request, the application can stream the video not only from the media servers, but also from the peers that have buffered the video. The multipath multisource video on-demand streaming has been applied in wired networks with great success. However, it remains a challenging task in wireless networks due to wireless interference. In this paper, we first focus on the problem of finding the maximum number of high-quality and independent paths from the user to the servers or peers for each VoD request by considering the effect of wireless interference. We formulate it as a constrained maximum independent paths problem and propose two efficient heuristic path discovery algorithms. Based on the multiple paths discovered, we further propose a joint routing and rate allocation algorithm, which minimizes the network congestion caused by the new VoD session. The algorithm is aware of the optimization for both existing and potential VoD sessions in the wireless mesh network. We evaluate our algorithms with real video traces. Simulation results demonstrate that our algorithm not only improves the average video streaming performance over all the coexisting VoD sessions in the network, but also increases the network's capacity of satisfying more subsequent VoD requests.

Oh Mercy: How On-Demand Interactive Streaming Services Navigate the Digital Music Rights Licensing Landscape

Many view the music industry’s transition to an online distribution based business model as having been inevitable since Napster first made consumers aware of the ease with which they could access vast amounts of music online. Others insist the average listener’s growing familiarity with online music download services combined with the recent integration of on-demand interactive streaming services into social networking platforms resulted in Billboard recognizing the need to amend its coronation process. Regardless of what caused this paradigm shift, two things are clear: online music distribution is here to stay and on-demand streaming audio is the “state of the art.” In recent years, a plethora of on-demand services began offering users the ability to stream an exhaustive catalog of songs. These services are all vying to become the “celestial jukebox” of choice for the rapidly growing segment of music consumers who prefer listening to unlimited music via on-demand interactive streams over paying for individual records or downloads. This article endeavors to explain how on-demand streaming services are able to navigate the modern music licensing landscape and deliver music to their ever-growing pools of subscribers. Section I describes the difference between on-demand streaming services and other types of streaming services, then briefly discusses the history of the law pertaining to streaming technology. Section II identifies the specific rights that an on-demand streaming service implicates each time it streams a song to a user’s computer or device. Section III uses a contemporary example to demonstrate exactly how an on-demand interactive service must go about securing the licenses necessary to stream a song without infringing the rights copyright holders have to their respective works. Finally, Section IV highlights some obstacles on-demand services face under the modern music licensing regime and suggests ways for simplifying the licensing process.

Query Adaptation Techniques in Temporal-DHT for P2P Media Streaming Applications

Peer-to-Peer (P2P)-based approach for on-demand video streaming systems (P2P-VoD) characterized by asynchronous user-interactivity has proven to be practical and effective in recent years with real-world Internet-scale deployment (Huang, Li, & Ross, 2007). Current state-of-art P2P-VoD systems employ tracker server for discovering content suppliers which poses scalability and bottleneck issues. Temporal-DHT is a structured P2P based approach which can efficiently accommodate the large number of update operations with the continuous change of user’s playing position and supporting asynchronous jumps (Bhattacharya, Yang, & Zhang, 2010). The authors propose different query adaptation strategies based upon content popularity distributions and shortage bandwidth ratios which are proved to be effective in improving the performance of P2P streaming system by deriving certain optimized solutions. They formulate valuable optimization problems in the context of a P2P-VoD system such as minimization of query search cost, server bandwidth consumption, and a joint cost-load framework. The authors provide optimized solutions that achieve the best result for the above mentioned optimization objectives. They show extensive simulation studies under various scenarios of search cost, streaming quality, and other associated factors in a dynamic network environment where users are free to asynchronously join/leave the system.