Padmavathi Mundur

Keyframe-based video summarization using Delaunay clustering

Recent advances in technology have made tremendous amounts of multimedia information available to the general population. An efficient way of dealing with this new development is to develop browsing tools that distill multimedia data as information oriented summaries. Such an approach will not only suit resource poor environments such as wireless and mobile, but also enhance browsing on the wired side for applications like digital libraries and repositories. Automatic summarization and indexing techniques will give users an opportunity to browse and select multimedia document of their choice for complete viewing later. In this paper, we present a technique by which we can automatically gather the frames of interest in a video for purposes of summarization. Our proposed technique is based on using Delaunay Triangulation for clustering the frames in videos. We represent the frame contents as multi-dimensional point data and use Delaunay Triangulation for clustering them. We propose a novel video summarization technique by using Delaunay clusters that generates good quality summaries with fewer frames and less redundancy when compared to other schemes. In contrast to many of the other clustering techniques, the Delaunay clustering algorithm is fully automatic with no user specified parameters and is well suited for batch processing. We demonstrate these and other desirable properties of the proposed algorithm by testing it on a collection of videos from Open Video Project. We provide a meaningful comparison between results of the proposed summarization technique with Open Video storyboard and K-means clustering. We evaluate the results in terms of metrics that measure the content representational value of the proposed technique.

Class-based access control for distributed video-on-demand systems

The focus of this paper is the analysis of threshold-based admission control policies for distributed video-on-demand (VoD) systems. Traditionally, admission control methods control access to a resource based on the resource capacity. We have extended that concept to include the significance of an arriving request to the VoD system by enforcing additional threshold restrictions in the admission control process on request classes deemed less significant. We present an analytical model for computing blocking performance of the VoD system under threshold-based admission control. Extending the same methodology to a distributed VoD architecture we show through simulation that the threshold performance conforms to the analytical model. We also show that threshold-based analysis can work in conjunction with other request handling policies and are useful for manipulating the VoD performance since we are able to distinguish between different request classes based on their merit. Enforcing threshold restrictions with the option of downgrading blocked requests in a multirate service environment results in improved performance at the same time providing different levels of quality of service (QoS). In fact, we show that the downgrade option combined with threshold restrictions is a powerful tool for manipulating an incoming request mix over which we have no control into a workload that the VoD system can handle.

End-to-end analysis of distributed video-on-demand systems

The focus of the research presented in this paper is the end-to-end analysis of a distributed Video-on-Demand (VoD) system. We analyze the distributed architecture of a VoD system to design global request handling and admission control strategies and evaluate them using global metrics. The performance evaluation methodology developed in this paper helps in determining efficient ways of using all resources in the VoD architecture within the constraints of providing guaranteed high quality service to each request. For instance, our simulation results show that request handling policies based on limited redirection of blocked requests to other resources perform better than load sharing policies. We also show that request handling policies based on redirection have simpler connection establishment semantics than load sharing policies and, therefore, are easily incorporated into reservation or signaling protocols.

Integrated admission control in hierarchical video-on-demand systems

We develop a unified model of a hierarchical video-on-demand (VoD) system by integrating the storage and the network subsystems. Rather than restricting the analysis to an isolated subsystem the performance of the VoD system is analyzed as an end-to-end system. On a system-wide basis, request handling and admission control policies are designed to minimize global performance metrics. Through our simulation, we compare different request handling policies and show that a hierarchical VoD architecture with request handling that allows retrials at more than one resource will minimize overall blocking.

Optimal server allocations for streaming multimedia applications on the internet

In this paper, we address the server selection problem for streaming applications on the Internet. The architecture we consider is similar to the content distribution networks consisting of geographically dispersed servers and user populations over an interconnected set of metropolitan areas. Server selection issues for Web-based applications in such an environment have been widely addressed; the selection is mostly based on proximity measured using packet delay. Such a greedy or heuristic approach to server selection will not address the capacity planning problem evident in multimedia applications. For such applications, admission control becomes an essential part of their design to maintain Quality of Service (QoS). Our objective in providing a solution to the server selection problem is threefold: first, to direct clients to the nearest server; second, to provide multiple sources to diffuse network load; third, to match server capacity to user demand so that optimal blocking performance can be expected. We accomplish all three objectives by using a special type of Linear Programming (LP) formulation called the Transportation Problem (TP). The objective function in the TP is to minimize the cost of serving a video request from user population x using server y as measured by network distance. The optimal allocation between servers and user populations from TP results in server clusters, the aggregated capacity of each cluster designed to meet the demands of its designated user population. Within a server cluster, we propose streaming protocols for request handling that will result in a balanced load. We implement threshold-based admission control in individual servers within a cluster to enforce the fair share of the server resource to its designated user population. The blocking performance is used as a trigger to find new optimal allocations when blocking rates become unacceptable due to change in user demands. We substantiate the analytical model with an extensive simulation for analyzing the performance of the proposed clustered architecture and the protocols. The simulation results show significant difference in overall blocking performance between optimal and sub-optimal allocations in as much as 15% at moderate to high workloads. We also show that the proposed cluster protocols result in lower packet loss and latencies by forcing path diversity from multiple sources for request delivery.

Threshold-based admission control for multi-class video-on-demand systems

The next generation of distributed digital video-on-demand (VoD) systems will use admission control tests to ensure that users receive predictable and guaranteed service. If the system cannot support a new request then that request is blocked This paper presents an analytical model to evaluate unified admission control strategies for distributed VoD systems with multiple video classes. We prove that there exists a computationally efficient technique to determine the blocking probabilities for newly arriving requests. Through numerical analysis we show the effect of different admission control policies on overall system blocking rates.

Dynamic load balancing across mirrored multimedia servers

The purpose of this paper is to present protocols for efficient load balancing across replicated multimedia servers in a metropolitan area network. Current multimedia infrastructures, even when they use mirrored servers, do not have standardized load balancing schemes. Existing schemes frequently require participation from the clients in balancing the load across the servers efficiently. We propose two protocols in this paper for fair load balancing without any client-side processing being required. Neither protocol requires any change to the network-level infrastructure. Using network packet loss and packet transmission delay as the chief metrics, we show the effectiveness of the protocols through extensive simulations.

Adaptive Multimedia System Architecture for Improving QoS in Wireless Networks

In this paper, we present an adaptive end-system based architecture for improving QoS in wireless networks. The proposed system adapts to fluctuating network resources by transmitting lower fidelity streams, chosen based on user preferences. Adaptation based on user preference leads to selection of data that satisfies both the network (avoids congestion) and user (better perceptual value). The system does not have any dependency on the underlying network, making its implementation possible in any wireless network.

Network service selection for distributed multimedia applications

An important question in the development of system support for distributed multimedia is the type of network service offered to applications. This paper compares two network service disciplines: weighted fair queueing (WFQ) and non-preemptive earliest deadline first (NEDF). We show that, for a broad class of high-bandwidth distributed multimedia applications, WFQ outperforms NEDF in terms of network throughput while still providing an application-adequate end-to-end service. This result holds despite the fact that NEDF offers applications far greater flexibility in terms of control over end-to-end delivery delay.

The Analysis and Performance of Multi-Rate Service in Distributed Video-on-Demand Systems

In this paper, we develop an end-to-end analysis of a distributed Video-on-Demand (VoD) system that includes an integrated model of the server and the network subsystems with analysis of its impact on client operations. The VoD system provides service to a heterogeneous client base at multiple playback rates. A class-based service model is developed where an incoming video request can specify a playback rate at which the data is consumed on the client. Using an analytical model, admission control conditions at the server and the network are derived for multi-rate service. We also develop client buffer requirements in presence of network delay bounds and delay jitter bounds using the same integrated framework of server and network subsystems. Results from an extensive simulation show that request handling policies based on limited redirection of blocked requests to other resources perform better than load sharing policies. The results also show that downgrading the service for blocked requests to a lower bitrate improves VoD system performance considerably. Combining the downgrade option with restrictions on access to high bitrate request classes is a powerful tool for manipulating an incoming request mix into a workload that the VoD system can handle.