23 research outputs found

    Cooperative Interval Caching in Clustered Multimedia Servers

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    In this project, we design a cooperative interval caching (CIC) algorithm for clustered video servers, and evaluate its performance through simulation. The CIC algorithm describes how distributed caches in the cluster cooperate to serve a given request. With CIC, a clustered server can accommodate twice (95%) more number of cached streams than the clustered server without cache cooperation. There are two major processes of CIC to find available cache space for a given request in the cluster: to find the server containing the information about the preceding request of the given request; and to find another server which may have available cache space if the current server turns out not to have enough cache space. The performance study shows that it is better to direct the requests of the same movie to the same server so that a request can always find the information of its preceding request from the same server. The CIC algorithm uses scoreboard mechanism to achieve this goal. The performance results also show that when the current server fails to find cache space for a given request, randomly selecting a server works well to find the next server which may have available cache space. The combination of scoreboard and random selection to find the preceding request information and the next available server outperforms other combinations of different approaches by 86%. With CIC, the cooperative distributed caches can support as many cached streams as one integrated cache does. In some cases, the cooperative distributed caches accommodate more number of cached streams than one integrated cache would do. The CIC algorithm makes every server in the cluster perform identical tasks to eliminate any single point of failure, there by increasing availability of the server cluster. The CIC algorithm also specifies how to smoothly add or remove a server to or from the cluster to provide the server with scalability

    A demand adaptive and locality aware (dala) streaming media server cluster architecture

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    The wide availability of broadband networking technologies such as cable modems and DSL coupled with the growing popularity of the Internet has led to a dramatic increase in the availability and the use of online streaming media. With the “last mile ” network bandwidth no longer a constraint, the bottleneck for video streaming has been pushed closer to the server. Streaming high quality audio and video to a myriad of clients imposes significant resource demands on the server. In this work, we propose a demand adaptive and locality aware (DALA) clustered media server architecture that can dynamically allocate resources to adapt to changing demand and also maximize the number of clients serviced by the server cluster. Moreover, our design exploits temporal locality among requests by dispatching newly arriving requests to servers that are already servicing prior requests for those objects, thereby extracting the benefits of locality. We explore the efficacy of the DALA clustered architecture using simulations. Our simulation results show that DALA is highly adaptive, exhibits significant performance gains when compared to static schemes, and has a low system overhead. Our results demonstrate that DALA is a simple, yet effective approach for designing clustered media servers.

    Fifth NASA Goddard Conference on Mass Storage Systems and Technologies

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    This document contains copies of those technical papers received in time for publication prior to the Fifth Goddard Conference on Mass Storage Systems and Technologies held September 17 - 19, 1996, at the University of Maryland, University Conference Center in College Park, Maryland. As one of an ongoing series, this conference continues to serve as a unique medium for the exchange of information on topics relating to the ingestion and management of substantial amounts of data and the attendant problems involved. This year's discussion topics include storage architecture, database management, data distribution, file system performance and modeling, and optical recording technology. There will also be a paper on Application Programming Interfaces (API) for a Physical Volume Repository (PVR) defined in Version 5 of the Institute of Electrical and Electronics Engineers (IEEE) Reference Model (RM). In addition, there are papers on specific archives and storage products

    A Demand Adaptive and Locality Aware (DALA) Streaming

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    as cable modems and DSL coupled with the growing popularity of the Internet has led to a dramatic increase in the availability and the use of online streaming media. With the "last mile" network bandwidth no longer a constraint, the bottleneck for video streaming has been pushed closer to the server. Streaming high quality audio and video to a myriad of clients imposes significant resource demands on the server. In this work, we propose a demand adaptive and locality aware (DALA) clustered media server architecture that can dynamically allocate resources to adapt to changing demand and also maximize the number of clients serviced by the server cluster. Moreover, our design exploits temporal locality among requests by dispatching newly arriving requests to servers that are already servicing prior requests for those objects, thereby extracting the benefits of locality. We explore the efficacy of the DALA clustered architecture using simulations. Our simulation results show that DALA is highly adaptive, exhibits significant performance gains when compared to static schemes, and has a low system overhead. Our results demonstrate that DALA is a simple, yet effective approach for designing clustered media servers

    Effective interprocess communication (IPC) in a real-time transputer network

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    The thesis describes the design and implementation of an interprocess communication (IPC) mechanism within a real-time distributed operating system kernel (RT-DOS) which is designed for a transputer-based network. The requirements of real-time operating systems are examined and existing design and implementation strategies are described. Particular attention is paid to one of the object-oriented techniques although it is concluded that these techniques are not feasible for the chosen implementation platform. Studies of a number of existing operating systems are reported. The choices for various aspects of operating system design and their influence on the IPC mechanism to be used are elucidated. The actual design choices are related to the real-time requirements and the implementation that has been adopted is described. [Continues.

    A Demand Adaptive and Locality Aware (DALA) streaming media server cluster architecture

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    Text Similarity Between Concepts Extracted from Source Code and Documentation

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    Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p
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