11794423
An adaptive consistency maintenance approach for replicated continuous applications
Consistency maintenance is a key problem to replicated continuous applications and dead reckoning (DR) algorithm is widely used in this area. In order to eliminate short-term inconsistency caused by DR algorithm, local-lag approach was proposed. For the purpose of simplicity, fixed lag value is used by local-lag approach and the performance of the approach is greatly deteriorated. In this paper, an adaptive consistency maintenance approach, which is based on local-lag approach, is proposed. The new approach can adjust lag value according to the estimated typical network latency. In order to ensure the criterion of consistency correctness, a lag value adjustment method is also proposed. Through two experiments, the performance of the new approach is evaluated and the results indicate that it is feasible and can greatly improve the performance of the application.
30915392
An HCI method to improve the human performance reduced by local-lag mechanism
Local-lag mechanism can maintain consistency for replicated continuous applications, but with a tradeoff of adding delay to local operations. To relieve the negative effects of the delay, this paper proposes an HCI method named echo. With the help of the echo method users can immediately perceive the results of their operations and how large the lag is. In order to evaluate the proposed method, a desktop collaborative virtual environment (CVE) system and a virtual object control task were employed to study the effects of the echo method on human performance (including task completion time, error count, and interaction quality). Experimental results indicate that when the lag exceeds 100ms the echo method can improve human performance with the effects becoming more evident when a larger lag is used.
63481154
MobiMessenger: An Instant Messenger System Based on Mobile Ad-Hoc Network
Mobile ad-hoc network offers many new ways for CSCW resolution. So we develop an ad-hoc instant messenger, MobiMessenger, which will be used as a platform for our future research work on ad-hoc collaboration. In this paper, we present the design and implement of MobiMessenger, which is based on AODV algorithm, including the system architecture and implementation. Also present our future work on ad-hoc collaboration.
24161285
Effects of Local-Lag Mechanism on Task Performance in a Desktop CVE System
Consistency maintenance is a kernel problem in Collaborative Virtual Environment (CVE) research. The approaches used in Networked Virtual Environments (e.g., DR algorithm) could not be used in CVEs, for they could not prevent short-term inconsistency. Therefore, local-lag mechanism has been proposed to eliminate short-term inconsistency in CVEs. Choosing a proper lag value is a key problem in local-lag mechanism. This paper studied the effects of lag value (0ms–900ms) on task performance in a desktop CVE system. Experimental results indicate that the effect of lag value on task performance is not linear. The effect could be separated into four segments by three dividing points: 150ms, 300ms and 600ms. Lag has no effect on task performance while ranging from 0ms to 150ms. From 150ms to 300ms, lag slightly affects task performance. Lag deteriorates task performance seriously while ranging from 300ms to 600ms. When lag is longer than 600ms, the task cannot be accomplished sometimes.
11658624
Statistical Feature Selection for Mandarin Speech Emotion Recognition
Performance of speech emotion recognition largely depends on the acoustic features used in a classifier. This paper studies the statistical feature selection problem in Mandarin speech emotion recognition. This study was based on a speaker dependent emotional mandarin database. Pitch, energy, duration, formant related features and some velocity information were selected as base features. Some statistics of them consisted of original feature set and full stepwise discriminant analysis (SDA) was employed to select extracted features. The results of feature selection were evaluated through a LDA based classifier. Experiment results indicate that pitch, log energy, speed and 1st formant are the most important factors and the accuracy rate increases from 63.1 % to 76.5 % after feature selection. Meanwhile, the features selected by SDA are better than the results of other feature selection methods in a LDA based classifier and SVM. The best performance is achieved when the feature number is in the range of 9 to 12.
46218447
Parallelizing Progressive Computation for Skyline Queries in Multi-disk Environment
Given a set of d-dimensional points, skyline query returns the points that are not dominated by any other point on all dimensions. In this paper, we study an interesting scenario of skyline retrieval, where multi-dimensional points are distributed among multiple disks. Efficient algorithms for parallelizing progressive skyline computation are developed, using the parallel R-trees. The core of our scheme is to visit more entries from some disks simultaneously and enable effective pruning strategies with dominance checking to prune away the non-qualifying entries. Extensive experiments with synthetic data confirm that our proposed algorithms are both efficient and scalable.
2039675
On Detection of Bounded Global Predicates
Distributed programs often follow some bounded global predicates, for example, the total number of certain tokens is always the same or bounded in a range. In order to detect bounded global predicates, we can first derive the minimum and maximum global snapshots and then check if the minimum and maximum are out of the range. Recently, Chase and Garg proposed an efficient method to derive the minimum global snapshot by reducing this problem to a maximum network flow problem. A restriction of this method is that all message values (e.g., the token number in messages) must be zero and all process state values (e.g., the token number in processes) must be non-negative. In this paper, we propose an elegant technique, called normalization. By using this technique, we can remove the above restriction and also derive the minimum and maximum global snapshots at the same time.
206929170
Optimizing the Fast Fourier Transform on a Multi-core Architecture
The rapid revolution in microprocessor chip architecture due to multicore technology is presenting unprecedented challenges to the application developers as well as system software designers: how to best exploit the parallelism potential due to such multi-core architectures? In this paper, we report an in-depth study on such challenges based on our experience of optimizing the fast Fourier transform (FFT) on the IBM Cyclops-64 chip architecture - a large-scale multi-core chip architecture consisting 160 thread units, associated memory banks and an interconnection network that connect them together in a shared memory organization. We demonstrate how multi-core architectures like the C64 could be used to achieve a high performance implementation of FFT both in 1D and 2D cases. We analyze the optimization challenges and opportunities including problem decomposition, load balancing, work distribution, and data-reuse, together with the exploiting of the C64 architecture features such as the multi-level of memory hierarchy and large register files. Furthermore, the experience learned during the hand-tuned optimization process have provided valuable guidance in our compiler optimization design and implementation. The main contributions of this paper include: 1) our study demonstrates that successful optimization for C64-like large-scale multi-core architectures requires a careful analysis that can identify certain domain-specific features of a target application (e.g. FFT) and match them well with some key multi-core architecture features; 2) our optimization, assisted with hand-tuned process, provided quantitative evidence on the importance of each optimization identified in 1); 3) automatic optimization by our compiler, the design and implementation of which is guided by the feedbacks from 1) and 2), shows excellent results that are often comparable to the results derived from our time-consuming hand-tuned code.
12012725
An intelligent control system with a multi-objective self-exploration process
Abstract This paper proposes a novel approach based on artificial intelligence technologies (multi-objective Self-Exploration process based Intelligent Control System—mSEICS) for intelligent control systems. Not only can this system adapt to various environments, but it can also continually improve its performance. The mSEICS consists of four basic functions, controller, receptor, m-adaptor and advancer. A five-layer fuzzy neural network is applied to implement the controller. The receptor is used to evaluate the performance of system. The m-adaptor (multi-objective based adaptor) that comprises two elements, action explorer and rule generator, can generate a variety of new action sets in order to adapt to various environments. The Pareto optimality based multi-objective genetic algorithm is proposed to implement the action explorer to discover multiple action sets, and the rule generator is employed to transform the action set to fuzzy rules. In addition, the advancer consisting of action discoverer and rule generator is constructed to produce the novel action set to enhance the system efficiency. The parallel-simulated annealing approach is presented to realize the action discoverer. An application of the robotic path planning is applied to demonstrate the proposed model. The simulation results show that the mobile robot can reach the target successfully in various environments, and the proposed model is more efficient than the similar model.
6035916
Ranking web objects from multiple communities
Vertical search is a promising direction as it leverages domain-specific knowledge and can provide more precise information for users. In this paper, we study the Web object-ranking problem, one of the key issues in building a vertical search engine. More specifically, we focus on this problem in cases when objects lack relationships between different Web communities, and take high-quality photo search as the test bed for this investigation. We proposed two score fusion methods that can automatically integrate as many Web communities (Web forums) with rating information as possible. The proposed fusion methods leverage the hidden links discovered by a duplicate photo detection algorithm, and aims at minimizing score differences of duplicate photos in different forums. Both intermediate results and user studies show the proposed fusion methods are practical and efficient solutions to Web object ranking in cases we have described. Though the experiments were conducted on high-quality photo ranking, the proposed algorithms are also applicable to other ranking problems, such as movie ranking and music ranking.
26961598
A Distributed Power-Efficient Data Gathering and Aggregation Protocol for Wireless Sensor Networks
In this paper, we propose a distributed power-efficient data gathering and aggregation algorithm (DPEG), in which a node, according to its residual energy and the strength of signal received from its neighboring nodes, independently makes its decision to compete for becoming a cluster head. In addition, assume that the inter-cluster communication data is, in a multi-hop manner, sent to the designated node, which then sends the data gathered by the whole network to the base station. DPEG also proposes a simple approach to solve the cluster coverage problem. With the increase in node density, this approach lets sensor network lifetime be linear in the number of nodes. Our experimental results have proved that DPEG algorithm, in the best case, lets sensor network lifetime be respectively increased by 1800% and 300% as compared with another two data gathering and aggregation protocols— LEACH and PEGASIS.