Ewa Kusmierek

Loopback: exploiting collaborative caches for large-scale streaming

In this paper, we propose a Loopback approach in a two-level streaming architecture to exploit collaborative client/proxy buffers for improving the quality and efficiency of large-scale streaming applications. At the upper level we use a content delivery network (CDN) to deliver video from a central server to proxy servers. At the lower level a proxy server delivers video with the help of collaborative client caches. In particular, a proxy server and its clients in a local domain cache different portions of a video and form delivery loops. In each loop, a single video stream originates at the proxy, passes through a number of clients, and finally is passed back to the proxy. As a result, with limited bandwidth and storage space contributed by collaborative clients, we are able to significantly reduce the required network bandwidth, I/O bandwidth, and cache space of a proxy. Furthermore, we develop a local repair scheme to address the client failure issue for enhancing service quality and eliminating most required repairing load at the central server. For popular videos, our local repair scheme is able to handle most of single-client failures without service disruption and retransmissions from the central server. Our analysis and simulations have shown the effectiveness of the proposed scheme.

A Network-Aware Approach for Video and Metadata Streaming

Providing quality of service (QoS) for Internet-based video streaming applications requires the server and/or client to be network-aware and adaptive. We present a dynamic rate and quality adaptation algorithm where the server varies its sending rate (without varying the quality level) to adapt to the network and client conditions and only as a last resort, does quality adaptation. We place the adaptation logic at the client since it has better knowledge about both the demand (buffer conditions, variable bit-rate requirements) and supply (network conditions). Our approach is unique because the servers sending rate is calculated based on the clients varying demand (consumption rate) and the network status. Also, we do not model the network as a black-box but instead augment endpoint observations with a feedback from the network to represent its status more precisely. To make an informed adaptation decision, the client requires sizes of all frames in the variable bit rate video. But the overhead involved in sending this metadata is significant. So we propose a lossy compression technique to reduce the amount of control information and consequently the overhead. We also present a scheduling algorithm, dynamic scheduling algorithm for reduced trace delivery (DART), to deliver the compressed control information to the client. This algorithm can be used to deliver any form of metadata (like subtitles, alerts, etc.), especially in applications like IP-TV. Simulations show that the proposed techniques can significantly improve user perceived QoS when compared to other popular adaptation methods.

Streaming video delivery over internet with adaptive end-to-end QoS

Many multimedia applications rely on video streaming techniques. However, video delivery over a Best Effort network such as todays Internet is a challenge. Traffic load in the network changes dynamically and in an unpredictable way causing the resource availability to vary. Providing an application level end-to-end quality of service in such an environment requires network-awareness and ability to adapt. We address the issue of mapping between application-level quality of service for streaming video and network-level quality of service. We show that continuous playback requires a limit on the delay jitter. We tackle the problem of providing end-to-end video quality given that the network does not guarantee limited delay variability. Our approach is unique in a way we do not model network as a black box but investigate what information about the network status is necessary for an application to make adaptation decisions. We rely on simple multi-level ECN-based mechanism to obtain a feedback from the network as well as on end-point observations to determine available bandwidth. Such an approach allows to obtain better user-perceived video quality by providing additional information to properly interpret the arrival rate observed at the end-point. We propose a 3-rate adaptation mechanism for video streaming to illustrate the philosophy of adaptivity based on network awareness, where the network awareness is not limited to observing network reaction to a set of stimuli.

An integrated network resource and QoS management framework

We present an integrated network resource and QoS management framework based on the idea of decoupling the network control plane from the data plane. Our framework is capable of providing per-flow QoS guarantees using a scalable core-stateless packet forwarding mechanism at the network core. A virtual time reference system provides the abstraction of the data plane. A bandwidth broker performs all control and resource management functions while router functionality is kept minimal to make the performance of its main function, packet forwarding, efficient We present the bandwidth broker architecture, its modules and their implementations as well as the implementation of the packet forwarding mechanism at the routers. We describe also the design of the interface between the bandwidth broker and the routers as well as the interface between the bandwidth broker and the users (applications).

iTVP: large-scale content distribution for live and on-demand video services

iTVP is a system built for IP-based delivery of live TV programming, video-on-demand and audio-on-demand with interactive access over IP networks. It has a country-wide range and is designed to provide service to a high number of concurrent users. iTVP prototype contains the backbone of a two-level hierarchical system designed for distribution of multimedia content from a content provider to end users. In this paper we present experience gained during a few months of the prototype operation. We analyze efficiency of iTVP content distribution system and resource usage at various levels of the hierarchy. We also characterize content access patterns and their influence on system performance, as well as quality experienced by users and user behavior. In our investigation, scalability is one of the most important aspects of the system performance evaluation. Although the range of the prototype operation is limited, as far as the number of users and the content repository is concerned, we believe that data collected from such a large scale operational system provides a valuable insight into efficiency of a CDN-type of solution to large scale streaming services. We find that the systems exhibits good performance and low resource usage.

Energy efficient organization of mobile sensor networks

One of main design issues for a sensor network is conservation of energy available at each sensor node. To increase lifetime of a sensor network, we can organize the sensors into disjoint sets so that only one set is active at a time. The lifetime of the network increases proportionally to the number of disjoint sets. In general, sensors are randomly scattered in the monitored area, thus the number of disjoint sets is significantly smaller than in the ideal case. In this paper, we propose a way to increase the number of disjoint set using mobile sensors. We organize sensors into disjoint sets using the heuristic proposed by Sljjepcevic et al.[8]. Then, we rearrange mobile sensors that are not included in any set. The rearrangement process consists of two phases. In the first phases, we identify the fields that are not covered by any of the remaining sensors. Then we identify the locations from which mobile sensors could cover the fields. In the second phase, our proposed heuristic selects sensors to be rearranged and locations where they will move to. This selection is made by considering the coverage before and after a mobile sensor is moved. Our experiments show that we can effectively increase the number of disjoint set with a small number of mobile sensors rearranged.

Proxy-Assisted Periodic Broadcast Architecture for Large-Scale Video Streaming

Many multimedia applications rely on video streaming techniques. However, large scale video delivery is still challenging since it requires a large amount of resources. In this paper we propose a proxy-assisted periodic broadcast architecture for video delivery to a large number of clients over the Internet. Our video delivery technique is based on a combination of periodic broadcast by central server and proxy server caching. A proxy server caches either part or the entire video based on the video popularity. A video stored in the central server is partitioned into two parts, a server prefix and a server suffix, based on the aggregated demand for the video from all communities. In principle, the server prefix is delivered by unicast and the server suffix is delivered by periodic broadcast. The combination of proxy prefix and server prefix defines a wide spectrum of different video delivery modes. The transmission of a video can be either partially unicast or partially period broadcast depending on the relationship between proxy prefix and server prefix. We further define and solve the optimization problems for proxy prefix selection and server prefix selection in order to minimize the total resource requirements. Performance of our system is evaluated through a number of tests.

Proxy-assisted periodic broadcast for video streaming with multiple servers

Large scale video streaming over the Internet requires a large amount of resources such as server I/O bandwidth and network bandwidth. A number of video delivery techniques can be used to lower these requirements. Periodic broadcast by a central server combined with proxy caching offers a significant reduction of the aggregate network and server I/O bandwidth usage. However, the resources available to a single server are still limited. In this paper we propose a system with multiple geographically distributed servers. The problem of multiple servers for periodic broadcast is quite different from the problem of object location for multiple web servers. Multiple servers offer increased amount of resources and service availability and may potentially allow a further reduction of network bandwidth usage. On the other hand, the benefit of periodic broadcast mostly comes from high demand videos. With multiple servers holding a video, the demand of the video at each server is reduced. Therefore, it is a challenge to use multiple servers efficiently. We first analyze the dependence of the resource requirements on the number and locations of the servers. Based on the character of the function describing such a dependence, we formulate and solve the problem of video location and delivery, in a way that minimizes resource usage. We explore a trade-off between network and I/O bandwidth requirements. We evaluate our proposed solutions through a number of tests.

Improved n 1-cover discovery using perimeter coverage information

Over-deploying sensors into a coverage region allows for coverage guarantees in the face of random deployments. Extending the lifetime of these deployments by only turning on a handful of sensors that cover the entire region is a viable means of conserving energy. In order to maximally extend the life of a sensor network, several problems must be solved. These are: the 1-cover, the k-cover and n 1-covers. The 1-cover and k-cover problems have been solved previously; however, the n 1-cover problem has proven more difficult to address. We present a perimeter-centric approach to the NP-complete n 1-covers problem, which chooses neighbours based on an optimal disk placement theory, but takes practical constraints into consideration. Simulation results have shown that our system outperforms both the critical field selection algorithm and an n 1-cover selection algorithm derived from Zhang and Hous OGDC algorithm.

Loopback: Exploiting collaborative caches for large-scale streaming

In this paper, we propose a novel loopback approach in a two-level streaming architecture to exploit collaborative client/proxy buffers for improving the quality and efficiency of large-scale streaming applications. At the upper level we use an overlay to deliver video from a central server to proxy servers, at the lower level a proxy server delivers video with the help of collaborative caches. In particular, a proxy server and its clients in a local domain cache different portions of a video and form delivery loops. In each loop, a single video stream originates at the proxy, passes through a number of clients, and is passed back to the proxy. As a result, with limited bandwidth and storage space contributed by collaborative clients, we are able to significantly reduce the requirements of network bandwidth, I/O bandwidth, and cache space at a proxy. Furthermore, we develop local repair schemes to address the client failure issues for enhancing server quality and eliminating most repairing load at servers. For popular videos, our local repair schemes are able to handle most of single-client failures without service disruption and retransmissions from a central server. Our analysis and simulations have shown the efficacy of loopback in various settings.