Peer-assisted video-on-demand: cost reduction and performance enhancement for users, overlay providers, and network operators

Peer-assisted content delivery is an attractive way to distribute video content through the Internet at low costs. This approach combines the scalability of the peer-to-peer paradigm, in which users contribute their resources, and the service level guarantees of server-based systems. Thus, peer-assistance enables a content provider to reduce its server hosting costs, which is crucial in a commercial scenario. However, to be successful, such systems must take into account the interests of all three stakeholders involved: (1) users that demand high streaming quality with low fees and limited resource contribution, (2) content providers that aim to decrease server hosting costs, and (3) network operators that aim to avoid inefficient use of their infrastructure due to the network-oblivious behavior of peer-assisted overlays. In this thesis, we address these requirements and develop adaptive mechanisms to achieve a benefit for all three stakeholders, resulting in the so-called triple-win situation. Our main scenario is video-on-demand streaming, in which users can request pre-stored video content at any time and watch the video while downloading it. Thereby, video-on-demand streaming imposes stricter requirements compared to other systems that utilize peer resources, such as BitTorrent-like file sharing. Ideally, the video playback should start within few seconds and there should be no playback stalling. First, we focus on dedicated servers or caches that are essential resources in peerassisted streaming systems. Their provision is necessary to guarantee a satisfying quality of experience to consumers, yet they cause significant and largely avoidable costs for the content provider, which can be minimized. The high dynamics of uncontrolled peers, however, result in unpredictable changes of the resource demand. Since peers additionally offer services to other peers, the supply of resources is also dynamic. This behavior makes the management of peer-assisted systems and the proper allocation of resources challenging. This thesis proposes adaptive allocation policies, a new approach to address this issue. The policies estimate the capacity situation and service demand of the system to adaptively optimize allocated resources. Extensive simulations, verified by testbed measurements, prove the efficiency of our approach, which achieves a more competitive performance than well-dimensioned static systems. In the next step, we examine content delivery overlays from the network operators’ perspective, since such overlays are responsible for a large amount of consumer traffic, including the costly inter-domain traffic. The existing approaches often fail to satisfy the requirements of all involved stakeholders.We propose a novel incentive-based traffic management mechanism where a network operator offers additional free resources to selected users. The mechanism assigns resources to users that behave compliant with the network and overlay policies. Our evaluation shows that this approach satisfies the requirements of network operators and overlay participants (provider and users). To this end, the proposed mechanism is able to reduce the inter-domain traffic while improving the overlay performance.We also show that even a single network operator can successfully apply the proposed mechanism. Finally, we consider the availability of peer resources in peer-assisted content distribution. Besides contributing upload bandwidth, it is important that peers stay online after finishing their downloads to serve new download requests. The longer a peer stays online the more it can help to offload the servers. However, too extensive online time often results in high energy consumption paid by users without an adequate benefit to the system. In upcoming decentralized architectures based on set-top boxes that act as tiny servers, their energy consumption can even dominate distribution costs. Therefore, we propose advanced standby policies that reduce the energy consumption of set-top boxes while still offloading servers significantly. We evaluate the standby polices in a lifelike scenario. The results show that a near-optimal behavior can be realized by utilizing common features of set-top boxes such as the wake-up timer. We further extend a standby policy with network awareness to address the needs of network operators. In this regard, the resulting policy takes into account the interests of all three stakeholders: users, content providers, and network operators.