1578205
Broadcast on demand: efficient and timely dissemination of data in mobile environments
The demand for efficient scalable and cost effective mobile information access systems is rapidly growing. Radiofrequency broadcast plays a major role in mobile computing, and there is a need to provide service models for broadcasting information according to mobile users' needs. The authors present a model called broadcast on demand (BoD), which provides timely broadcasts according to requests from users. Compared to static broadcast, this approach has a different emphasis: it is based on a demand driven framework, aimed at satisfying the temporal constraints of the requests, and uses scheduling techniques at the server side to utilize the limited bandwidth dynamically and efficiently. Several broadcast transmission scheduling policies for BoD are examined. The study indicates that EDF-based policies combined with batching of requests achieve good performance. The results show that BoD is successful in satisfying the temporal constraints of the requests and is a viable service model for wireless broadcast stations.
2225573
Integrated scheduling of multimedia and hard real-time tasks
An integrated platform which is capable of meeting the requirements of both traditional real-time control processing and multimedia processing has enormous potential for accommodating various kinds of new applications. However, except for the simplest of situations, few, if any, research or commercial systems successfully provide architectural and OS mechanisms which can efficiently support both hard real-time computation and multimedia soft real-time computation. The authors propose a multimedia server execution on multiprocessor real-time operating systems to provide different classes of guarantee to support both types of processing. The multimedia server supports multiple periodic multimedia streams with a capability for graceful QoS degradation during system overload. They (i) develop several multimedia server scheduling algorithms, (ii) evaluate the performance of these algorithms, and (iii) discuss realistic system implementation issues on the SGI IRIX/REACT/PRO operating system.
1681173
Optimal proxy cache allocation for efficient streaming media distribution
We address the problem of efficiently streaming a set of heterogeneous videos from a remote server through a proxy to multiple asynchronous clients so that they can experience playback with low startup delays. We determine the optimal proxy prefix cache allocation to the videos that minimizes the aggregate network bandwidth cost. We integrate proxy caching with traditional server-based reactive transmission schemes such as hatching, patching and stream merging to develop a set of proxy-assisted delivery schemes. We quantitatively explore the impact of the choice of transmission scheme, cache allocation policy, proxy cache size, and availability of unicast versus multicast capability, on the resulting transmission cost. Our evaluations show that even a relatively small prefix cache (10%-20% of the video repository) is sufficient to realize substantial savings in transmission cost. We find that carefully designed proxy-assisted reactive transmission schemes can produce significant cost savings even in a predominantly unicast environment such as the Internet.
2290480
Optimal multicast smoothing of streaming video over an internetwork
A number of applications such as internet video broadcasts, corporate telecasts, distance learning etc. require transmission of streaming video to multiple simultaneous users across an internetwork. The high bandwidth requirements coupled with the multi-timescale burstiness of compressed video make it a challenging problem to provision network resources for transmitting streaming multimedia. For such applications to become affordable and ubiquitous, it is necessary to develop scalable techniques which can efficiently deliver streaming video to multiple heterogeneous clients across a heterogeneous internetwork. We propose using multicasting of smoothed video and differential caching of the video at intermediate nodes in the distribution tree, as techniques for reducing the network bandwidth requirements of such dissemination. We formulate the multicast smoothing problem, and develop an algorithm for computing the set of optimally smoothed transmission schedules for the tree (such that the transmission schedule along each link in the tree has the lowest peak rate and rate variability for any feasible transmission schedule for that link) given a buffer allocation to the different nodes in the tree. We also develop an algorithm to compute the minimum total buffer allocation to the entire tree and the corresponding allocation to each node, such that feasible transmission is possible to all the clients, when the tree has heterogeneous rate constraints. MPEG-2 trace-driven performance evaluations indicate that there are substantial benefits from multicast smoothing and differential caching. For example, the optimal multicast smoothing can reduce the total transmission bandwidth requirements in the distribution tree by more than a factor of 3 as compared to multicasting the unsmoothed stream.
6084623
Proxy prefix caching for multimedia streams
High latency and loss rates in the Internet make it difficult to stream audio and video without introducing a large playback delay. To address these problems, we propose a prefix caching technique whereby a proxy stores the initial frames of popular clips. Upon receiving a request for the stream, the proxy initiates transmission to the client and simultaneously requests the remaining frames from the server. In addition to hiding the delay, throughput, and loss effects of a weaker service model between the server and the proxy, this novel yet simple prefix caching technique aids the proxy in performing workahead smoothing into the client playback buffer. By transmitting large frames in advance of each burst, workahead smoothing substantially reduces the peak and variability of the network resource requirements along the path from the proxy to the client. We describe how to construct a smooth transmission schedule, based on the size of the prefix, smoothing, and playback buffers, without increasing client playback delay. Experiments with MPEG traces show how a few megabytes of buffer space at the proxy can substantially reduce the bandwidth requirements of variable-bit-rate video. Drawing on these results, we present guidelines for allocating buffer space for each stream, and how to effectively share buffer and bandwidth resources among multiple clients and streams.
6303606
Class-of-service mapping for QoS: a statistical signature-based approach to IP traffic classification
The ability to provide different Quality of Service (QoS) guarantees to traffic from different applications is a highly desired feature for many IP network operators, particularly for enterprise networks. Although various mechanisms exist for providing QoS in the network, QoS is yet to be widely deployed. We believe that a key factor holding back widespread QoS adoption is the absence of suitable methodologies/processes for appropriately mapping the traffic from different applications to different QoS classes. This is a challenging task, because many enterprise network operators who are interested in QoS do not know all the applications running on their network, and furthermore, over recent years port-based application classification has become problematic. We argue that measurement based automated Class of Service (CoS) mapping is an important practical problem that needs to be studied.
 In this paper we describe the requirements and associated challenges, and outline a solution framework for measurement based classification of traffic for QoS based on statistical application signatures. In our approach the signatures are chosen in such as way as to make them insensitive to the particular application layer protocol, but rather to determine the way in which an application is used -- for instance is it used interactively, or for bulk-data transport. The resulting application signature can then be used to derive the network layer signatures required to determine the CoS class for individual IP datagrams. Our evaluations using traffic traces from a variety of network locations, demonstrate the feasibility and potential of the approach.
6559774
A Movie Recommendation System – An Application of Voting Theory in User Modeling
Our research agenda focuses on building software agents that can employ user modeling techniques to facilitate information access and management tasks. Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems, can be used to recommend items of interest to users. To be successful, such systems should be able to model and reason with user preferences for items in the application domain. Our primary concern is to develop a reasoning procedure that can meaningfully and systematically tradeoff between user preferences. We have adapted mechanisms from voting theory that have desirable guarantees regarding the recommendations generated from stored preferences. To demonstrate the applicability of our technique, we have developed a movie recommender system that caters to the interests of users. We present issues and initial results based on experimental data of our research that employs voting theory for user modeling, focusing on issues that are especially important in the context of user modeling. We provide multiple query modalities by which the user can pose unconstrained, constrained, or instance-based queries. Our interactive agent learns a user model by gaining feedback aboutits recommended movies from the user. We also provide pro-active information gathering to make user interaction more rewarding. In the paper, we outline the current status of our implementation with particular emphasis on the mechanisms used to provide robust and effective recommendations.
18363724
Distribution-Sensitive Algorithms
We investigate a new paradigm of algorithm design for geometric problems that can be termed distribution-sensitive. Our notion of distribution is more combinatorial in nature than spatial. We illustrate this on problems like planar-hulls and 2D-maxima where some of the previously known output-sensitive algorithms are recast in this setting. In a number of cases, the distribution-sensitive analysis yields superior results for the above problems. Moreover these bounds are shown to be tight in the linear decision tree model.Our approach owes its spirit to the results known for sorting multisets and we exploit this relationship further to derive fast and efficient parallel algorithms for sorting multisets along with the geometric problems.
1281859
Unsupervised Surrogate Agents and Search Bias Change in Flexible Distributed Scheduling
Computational infrastructures for cooperative work should contain embedded agents for handling many routine tasks (Galegher, Kraut, Egldo 1990), but as the number of agents increases and the agents become geographically and/or conceptually dispersed, supervision of the agents will become increasingly problematic. We argue that agents should be provided with deep domain knowledge that allows them to make justifiable decisions, rather than shallow models of users to mimic. In this paper, we use the application domain of distributed meeting scheduling to investigate how agents embodying deeper domain knowledge can choose among alternative strategies for searching their calendars in order to create flexible schedules within reasonable cost.
17321203
On a Simple, Practical, Optimal, Output-Sensitive Randomized Planar Convex Hull Algorithm
In this paper we present a truly practical and provably optimalO(nlogh) time output-sensitive algorithm for the planar convex hull problem. The basic algorithm is similar to the algorithm presented by2, where the median-finding step is replaced by an approximate median. We analyze two such schemes and show that for both methods, the algorithm runs in expectedO(nlogh) time. We further show that the probability of deviation from expected running time approaches 0 rapidly with increasing values ofnandhfor any input. Our experiments suggest that this algorithm is a practical alternative to the worst-caseO(nlogn) algorithms such as Graham's and is especially faster for small output-sizes. Our approach bears some resemblance to a recent algorithm of13, but our analysis is substantially different.
13052705
Learning to Coordinate without Sharing Information
Researchers in the field of Distributed Artificial Intelligence (DAI) have been developing efficient mechanisms to coordinate the activities of multiple autonomous agents. The need for coordination arises because agents have to share resources and expertise required to achieve their goals. Previous work in the area includes using sophisticated information exchange protocols, investigating heuristics for negotiation, and developing formal models of possibilities of conflict and cooperation among agent interests. In order to handle the changing requirements of continuous and dynamic environments, we propose learning as a means to provide additional possibilities for effective coordination. We use reinforcement learning techniques on a block pushing problem to show that agents can learn complimentary policies to follow a desired path without any knowledge about each other. We theoretically analyze and experimentally verify the effects of learning rate on system convergence, and demonstrate benefits of using learned coordination knowledge on similar problems. Reinforcement learning based coordination can be achieved in both cooperative and non-cooperative domains, and in domains with noisy communication channels and other stochastic characteristics that present a formidable challenge to using other coordination schemes.