5,708 research outputs found

    Δομή λεξικού για ασύρματα δίκτυα

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    Η κατανάλωση ενέργειας και η αποδοτηκότητα πρόσβασης είναι δύο βασικοί στόχοι και ανταγωνιστικοί στην ασύρματη εκπομπή δεδομένων. Για να αντιμετωπιστεί το ενεργειακό πρόβλημα στην ακολουθιακή αναζήτηση μαζί με τα δεδομένα έχουν προστεθεί δείκτες ( index ). Στην εργασία αυτή προτείνουμε ένα παραμετροποιήσημο αλγόριθμο εκπομπής δεδομένων τον Interpolation Index. Ο αλγόριθμος έχει δυνατότητα να βελτιστοποιήσει το χρόνο αναζήτησης κρατώντας σταθερό τον χρόνο συντονισμού (tuning time ) και αντίστροφα

    Pervasive Data Access in Wireless and Mobile Computing Environments

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    The rapid advance of wireless and portable computing technology has brought a lot of research interests and momentum to the area of mobile computing. One of the research focus is on pervasive data access. with wireless connections, users can access information at any place at any time. However, various constraints such as limited client capability, limited bandwidth, weak connectivity, and client mobility impose many challenging technical issues. In the past years, tremendous research efforts have been put forth to address the issues related to pervasive data access. A number of interesting research results were reported in the literature. This survey paper reviews important works in two important dimensions of pervasive data access: data broadcast and client caching. In addition, data access techniques aiming at various application requirements (such as time, location, semantics and reliability) are covered

    Data analytics 2016: proceedings of the fifth international conference on data analytics

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    The WiMAX PHY Layer

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    Pinwheel Scheduling for Fault-tolerant Broadcast Disks in Real-time Database Systems

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    The design of programs for broadcast disks which incorporate real-time and fault-tolerance requirements is considered. A generalized model for real-time fault-tolerant broadcast disks is defined. It is shown that designing programs for broadcast disks specified in this model is closely related to the scheduling of pinwheel task systems. Some new results in pinwheel scheduling theory are derived, which facilitate the efficient generation of real-time fault-tolerant broadcast disk programs.National Science Foundation (CCR-9308344, CCR-9596282

    DSI: A Fully Distributed Spatial Index for Wireless Data Broadcast

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    Advanced Protocols for Peer-to-Peer Data Transmission in Wireless Gigabit Networks

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    This thesis tackles problems on IEEE 802.11 MAC layer, network layer and application layer, to further push the performance of wireless P2P applications in a holistic way. It contributes to the better understanding and utilization of two major IEEE 802.11 MAC features, frame aggregation and block acknowledgement, to the design and implementation of opportunistic networks on off-the-shelf hardware and proposes a document exchange protocol, including document recommendation. First, this thesis contributes a measurement study of the A-MPDU frame aggregation behavior of IEEE 802.11n in a real-world, multi-hop, indoor mesh testbed. Furthermore, this thesis presents MPDU payload adaptation (MPA) to utilize A-MPDU subframes to increase the overall throughput under bad channel conditions. MPA adapts the size of MAC protocol data units to channel conditions, to increase the throughput and lower the delay in error-prone channels. The results suggest that under erroneous conditions throughput can be maximized by limiting the MPDU size. As second major contribution, this thesis introduces Neighborhood-aware OPPortunistic networking on Smartphones (NOPPoS). NOPPoS creates an opportunistic, pocket-switched network using current generation, off-the-shelf mobile devices. As main novel feature, NOPPoS is highly responsive to node mobility due to periodic, low-energy scans of its environment, using Bluetooth Low Energy advertisements. The last major contribution is the Neighborhood Document Sharing (NDS) protocol. NDS enables users to discover and retrieve arbitrary documents shared by other users in their proximity, i.e. in the communication range of their IEEE 802.11 interface. However, IEEE 802.11 connections are only used on-demand during file transfers and indexing of files in the proximity of the user. Simulations show that NDS interconnects over 90 \% of all devices in communication range. Finally, NDS is extended by the content recommendation system User Preference-based Probability Spreading (UPPS), a graph-based approach. It integrates user-item scoring into a graph-based tag-aware item recommender system. UPPS utilizes novel formulas for affinity and similarity scoring, taking into account user-item preference in the mass diffusion of the recommender system. The presented results show that UPPS is a significant improvement to previous approaches

    Automated Podcasting System for Universities

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    This paper presents the results achieved at Graz University of Technology (TU Graz) in the field of automating the process of recording and publishing university lectures in a very new way. It outlines cornerstones of the development and integration of an automated recording system such as the lecture hall setup, the recording hardware and software architecture as well as the development of a text-based search for the final product by method of indexing video podcasts. Furthermore, the paper takes a look at didactical aspects, evaluations done in this context and future outlook

    Learning to Transmit with Provable Guarantees in Wireless Federated Learning

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    We propose a novel data-driven approach to allocate transmit power for federated learning (FL) over interference-limited wireless networks. The proposed method is useful in challenging scenarios where the wireless channel is changing during the FL training process and when the training data are not independent and identically distributed (non-i.i.d.) on the local devices. Intuitively, the power policy is designed to optimize the information received at the server end during the FL process under communication constraints. Ultimately, our goal is to improve the accuracy and efficiency of the global FL model being trained. The proposed power allocation policy is parameterized using a graph convolutional network and the associated constrained optimization problem is solved through a primal-dual (PD) algorithm. Theoretically, we show that the formulated problem has zero duality gap and, once the power policy is parameterized, optimality depends on how expressive this parameterization is. Numerically, we demonstrate that the proposed method outperforms existing baselines under different wireless channel settings and varying degrees of data heterogeneity
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