119,094 research outputs found
Improving BitTorrent's Peer Selection For Multimedia Content On-Demand Delivery
The great efficiency achieved by the BitTorrent protocol for the distribution
of large amounts of data inspired its adoption to provide multimedia content
on-demand delivery over the Internet. As it is not designed for this purpose,
some adjustments have been proposed in order to meet the related QoS
requirements like low startup delay and smooth playback continuity.
Accordingly, this paper introduces a BitTorrent-like proposal named as
Quota-Based Peer Selection (QBPS). This proposal is mainly based on the
adaptation of the original peer-selection policy of the BitTorrent protocol.
Its validation is achieved by means of simulations and competitive analysis.
The final results show that QBPS outperforms other recent proposals of the
literature. For instance, it achieves a throughput optimization of up to 48.0%
in low-provision capacity scenarios where users are very interactive.Comment: International Journal of Computer Networks & Communications(IJCNC)
Vol.7, No.6, November 201
Regulating Innovative Medicine: Fitting Square Pegs in Round Holes
Increasingly, innovative medical products are creating a quandary for the Food and Drug Administration ( FDA ) because they often transcend the FDA\u27s traditional categorical approach to regulating medical products. In a recent attempt to simplify this process, the FDA has proposed a new rule for regulating combination products. This iBrief discusses the FDA\u27s current approach and analyzes the possible affects of the proposed regulation. Because of the many shortcomings of both systems, this iBrief concludes that the FDA should instead stop assigning center jurisdiction based on a product\u27s primary mode of action, and give the Office of Combination Products internal agency jurisdiction over combination products. This alternative approach would increase consistency and efficiency while maintaining the FDA\u27s high standards for medical product safety and efficacy
Flexibly Instructable Agents
This paper presents an approach to learning from situated, interactive
tutorial instruction within an ongoing agent. Tutorial instruction is a
flexible (and thus powerful) paradigm for teaching tasks because it allows an
instructor to communicate whatever types of knowledge an agent might need in
whatever situations might arise. To support this flexibility, however, the
agent must be able to learn multiple kinds of knowledge from a broad range of
instructional interactions. Our approach, called situated explanation, achieves
such learning through a combination of analytic and inductive techniques. It
combines a form of explanation-based learning that is situated for each
instruction with a full suite of contextually guided responses to incomplete
explanations. The approach is implemented in an agent called Instructo-Soar
that learns hierarchies of new tasks and other domain knowledge from
interactive natural language instructions. Instructo-Soar meets three key
requirements of flexible instructability that distinguish it from previous
systems: (1) it can take known or unknown commands at any instruction point;
(2) it can handle instructions that apply to either its current situation or to
a hypothetical situation specified in language (as in, for instance,
conditional instructions); and (3) it can learn, from instructions, each class
of knowledge it uses to perform tasks.Comment: See http://www.jair.org/ for any accompanying file
Open source environment to define constraints in route planning for GIS-T
Route planning for transportation systems is strongly related to shortest path algorithms, an optimization problem extensively studied in the literature. To find the shortest path in a network one usually assigns weights to each branch to represent the difficulty of taking such branch. The weights construct a linear preference function ordering the variety of alternatives from the most to the least attractive.Postprint (published version
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.Comment: 19 PAGE
An experimental comparative study for interactive evolutionary computation problems
Proceeding of: EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Budapest, Hungary, April 10-12, 2006This paper presents an objective experimental comparative study between four algorithms: the Genetic Algorithm, the Fitness Prediction Genetic Algorithm, the Population Based Incremental Learning algorithm and the purposed method based on the Chromosome Appearance Probability Matrix. The comparative is done with a non subjective evaluation function. The main objective is to validate the efficiency of several methods in Interactive Evolutionary Computation environments. The most important constraint of working within those environments is the user interaction, which affects the results adding time restrictions for the experimentation stage and subjectivity to the validation. The experiments done in this paper replace user interaction with several approaches avoiding user limitations. So far, the results show the efficiency of the purposed algorithm in terms of quality of solutions and convergence speed, two known keys to decrease the user fatigue.This article has been financed by the Spanish founded research MCyT project OPLINK, Ref: TIN2006-08818-C04-02
Teaching about Madrid: A Collaborative Agents-Based Distributed Learning Course
Interactive art courses require a huge amount of computational resources to be running on real time. These computational resources are even bigger if the course has been designed as a Virtual Environment with which students can interact. In this paper, we present an initiative that has been develop in a close collaboration between two Spanish Universities: Universidad Politécnica de Madrid and Universidad Rey Juan Carlos with the aim of join two previous research project: a Collaborative Awareness Model for Task-Balancing-Delivery (CAMT) in clusters and the “Teaching about Madrid” course, which provides a cultural interactive background of the capital of Spain
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