Search results for "Network"
showing 10 items of 7718 documents
Improving Chord Lookup Protocol for P2PSIP-Based Communication Systems
2009
Chord has been suggested as mandatory overlay technology in the future P2PSIP-based communication systems. Chord allows for the available peer/resource lookup in no more than hops, where N is the total number of the peers in the overlay network. However, as a protocol originally designed for background downloading applications, Chord has a few drawbacks when supporting P2PSIP real-time communication systems. These drawbacks are related to ID assignment, the relation between ID and physical location, the routing styles and lack of cache, etc. In this paper, we investigate several approaches that can improve the efficiency of the peer/resource lookup algorithm. After that, we simulate two sys…
Joint routing and per-flow fairness in wireless multihop networks
2008
In wireless multihop networks communication between two end-nodes is carried out by hopping over multiple short wireless links. Traditional CSMA/CA based media access control does not work satisfactory in a multihop scenario, since an intended target of a communication may be subject to mutual interference imposed by concurrent transmissions from nodes which cannot directly sense each other, causing unfair throughput allocation. Although TDMA seems to be a more promising solution, careful transmission scheduling is needed in order to achieve error-free communication and fairness. In our previous work, a TDMA scheduling algorithm has been proposed that schedules the transmissions in a fair m…
Deep Learning for Resource-Limited Devices
2020
In recent years, deep neural networks have revolutionized the development of intelligent systems and applications in many areas. Despite their numerous advantages and potentials, these intelligent models still suffer from several issues. Among them, the fact that they became very complex with millions of parameters. That is, requiring more resources and time, and being unsuitable for small restricted devices. To contribute in this direction, this paper presents (1) some state-of-the-art lightweight architectures that were specifically designed for small-sized devices, and (2) some recent solutions that have been proposed to optimize/compress classical deep neural networks to allow their dep…
On Unstructured File Sharing Networks
2007
We study the interaction among users of unstructured file sharing applications, who compete for available network resources (link bandwidth or capacity) by opening multiple connections on multiple paths so as to accelerate data transfer. We model this interaction with an unstructured file sharing game. Users are players and their strategies are the numbers of sessions on available paths. We consider a general bandwidth sharing framework proposed by Kelly [1] and Mo and Walrand [2], with TCP as a special case. Furthermore, we incorporate the Tit-for-Tat strategy (adopted by BitTorrent [3] networks) into the unstructured file sharing game to model the competition in which a connection can be …
Technologies for green radio communication networks
2011
Since the introduction of cellular communications in the early '80s, the demand for two-way mobile communication services has increased tremendously. Today there are over 4 billion mobile users and 4.6 million radio base station sites worldwide. This rapid growth of the cellular mobile industry has been at the price of increased energy consumption and a sizable carbon footprint.
A Pattern Recognition Approach for Peak Prediction of Electrical Consumption
2014
Predicting and mitigating demand peaks in electrical networks has become a prevalent research topic. Demand peaks pose a particular challenge to energy companies because these are difficult to foresee and require the net to support abnormally high consumption levels. In smart energy grids, time-differentiated pricing policies that increase the energy cost for the consumers during peak periods, and load balancing are examples of simple techniques for peak regulation. In this paper, we tackle the task of predicting power peaks prior to their actual occurrence in the context of a pilot Norwegian smart grid network.
Full Reference Mesh Visual Quality Assessment Using Pre-Trained Deep Network and Quality Indices
2019
In this paper, we propose an objective quality metric to evaluate the perceived visual quality of 3D meshes. Our method relies on pre-trained convolutional neural network i.e VGG to extract features from the distorted mesh and its reference. Quality indices from well-known mesh visual quality metrics are concatenated with the extracted features resulting a global feature vector. this latter is used to learn the support vector regression (SVR) to predict the final quality score. Experimental results from two subjective databases (LIRIS masking database and LIRIS/EPFL general-purpose database) and comparisons with seven objective metrics cited in the state-of-the-art demonstrate the effective…
Target tracking with dynamically adaptive correlation
2016
Abstract A reliable algorithm for target tracking based on dynamically adaptive correlation filtering is presented. The algorithm is capable of tracking with high accuracy the location of a target in an input video sequence without using an offline training process. The target is selected at the beginning of the algorithm. Afterwards, a composite correlation filter optimized for distortion tolerant pattern recognition is designed to recognize the target in the next frame. The filter is dynamically adapted to each frame using information of current and past scene observations. Results obtained with the proposed algorithm in synthetic and real-life video sequences, are analyzed and compared w…
Ontology-based state representation for intention recognition in cooperative human-robot environments
2012
In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human-robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level states relationships that must be true for future actions to occur, a robot can use the detailed state information presented in this paper to infer the probability of subsequent actions occurring. This would enable the robot to better help th…
Multi-functional Protein Clustering in PPI Networks
2008
Protein-Protein Interaction (PPI) networks contain valuable information for the isolation of groups of proteins that participate in the same biological function. Many proteins play different roles in the cell by taking part in several processes, but isolating the different processes in which a protein is involved is often a difficult task. In this paper we present a method based on a greedy local search technique to detect functional modules in PPI graphs. The approach is conceived as a generalization of the algorithm PINCoC to generate overlapping clusters of the interaction graph in input. Due to this peculiarity, multi-facets proteins are allowed to belong to different groups correspondi…