3648509
A Dynamic Quota-Based Peer Selection Strategy in BitTorrent
BitTorrent employs a static quota-based peer selection strategy to fixedly allocate upload quotas for the tit-for-tat (TFT) choke algorithm and optimistic unchoke (OU) algorithm, which would incur a paradox of supply and demand between upload peers and request peers, where many request peers stay in the starvation state while many upload quotas stay in the idleness state. We propose a dynamic quota-based peer selection strategy, where request peers are classified by the principle of investment return and according to dynamic changed numbers of different request peers an upload peer adaptively allocates upload quotas for the TFT and OU algorithms. Simulation experiment shows that our dynamic quota allocation scheme can eliminate the paradox of supply and demand, increase the resource utility ratio of upload peers, and decrease the file download time, at the cost of uploading more a few file blocks for each upload peer.
38710648
A Resource Allocating Neural Network Based Approach for Detecting End-to-End Network Performance Anomaly
Automatic detection of end-to-end network performance anomalies is important to efficient network management and optimization. We present an end-to-end network performance anomalies detection method, based on characterizing of the dynamic statistical properties of RTT normality. The experiment on real Internet end-to-end path RTT data shows that, the proposed method is accurate in detecting performance anomalies, it can successfully detect about 96.25% anomalies in the experiment.
15759515
An Effective Evidence Theory Based K-Nearest Neighbor (KNN) Classification
In this paper, we study various K nearest neighbor (KNN) algorithms and present a new KNN algorithm based on evidence theory. We introduce global frequency estimation of prior probability (GE) and local frequency estimation of prior probability (LE). A GE for a class is the prior probability of the class across the whole training data space based on frequency estimation; on the other hand, a LE for a class in a particular neighborhood is the prior probability of the class in this neighborhood space based on frequency estimation. By considering the difference between the GE and the LE of each class, we present a solution to the imbalanced data problem in some degree without doing re-sampling. We compare our algorithm with other KNN algorithms using two benchmark datasets. Results show that our KNN algorithm outperforms other KNN algorithms, including basic evidence based KNN.
18692029
A CCI-Feedback-Aided Scheduling Technique for MU-MIMO
Imperfect channel state information (CSI) at the transmitter is one of the major challenges that the downlink multiuser multiple-input-multiple-output (MU-MIMO) technology faces in real applications. It will lead to increased co- channel interference (CCI) among users and deteriorate the capacity of MU-MIMO seriously, especially at high signal-to- noise-ratios (SNRs). In this paper, we propose an advanced MU-MIMO scheduling technique to improve the capacity of MU-MIMO in the case of imperfect CSI at the transmitter (CSIT). The rational behind the proposed scheme is the observation that the CCI level increases with the number of users simultaneously supported in MU-MIMO transmission. Thus, decreasing the number of simultaneous users can reduce CCI and sometimes even increase the sum capacity. Motivated by this observation, we design a CCI-feedback-aided scheduling technique, which adaptively adjusts the number of simultaneous users based on the CCI measurement at the user side. Simulation results have shown that considerable capacity gain can be achieved by the proposed scheduling technique at the cost of only one bit additional feedback per user and marginal complexity increase at both the transmitter and user side.
15406626
A Lightweight Sensor Network Management System Design
In this paper, we propose a lightweight and transparent management framework for TinyOS sensor networks, called L-SNMS, which minimizes the overhead of management functions, including memory usage overhead, network traffic overhead, and integration overhead. We accomplish this by making L-SNMS virtually transparent to other applications hence requiring minimal integration. The proposed L-SNMS framework has been successfully tested on various sensor node platforms, including TelosB, MICAz and IMote2.
30143163
A Fast and Accurate Progressive Algorithm for Training Transductive SVMs
This paper develops a fast and accurate algorithm for training transductive SVMs classifiers, which utilizes the classification information of unlabeled data in a progressive way. For improving the generalization accuracy further, we employ three important criteria to enhance the algorithm, i.e. confidence evaluation, suppression of labeled data, stopping with stabilization. Experimental results on several real world datasets confirm the effectiveness of these criteria and show that the new algorithm can reach to comparable accuracy as several state-of-the-art approaches for training transductive SVMs in much less training time.
7977463
LiveBT: Providing Video-on-Demand Streaming Service over BitTorrent Systems
BitTorrent (BT) is one of the most popular Peer-to- Peer (P2P) protocols for delivering media files in the Internet today. Although BT is quite efficient for sharing and downloading files by using P2P swarming technique, the users have to download almost the whole media file before playing it. This is determined by the Rarest-Block-Download-First strategy of standard BT implementations, which is designed for fast delivery of files in the systems but not for streaming application. In this paper, we present LiveBT, a new protocol which supports video-on- demand streaming service and is totally compatible to the current BitTorrent protocol. LiveBT enables users to play hot movies shared in the BT systems smoothly just after 2-3 minutes of buffering time. We also develop the prototype of LiveBT and test the performance through the real BT download tasks of media files. By comparing our prototype with some popular BT clients claiming to support view-as- download service such as Bitcomet, we find that LiveBT spends a much shorter buffering time to play and achieves quite smooth playback performance.