14386113
P2P Recommendation Trust Model
Security trust model is an important research topic for the P2P application. This paper firstly analyzes the existing P2P network security trust models, and then puts forward a new P2P recommendation trust model based on the network of social relationships. The model provides different types of services to show the userpsilas interest in different areas, and gives recommendation based on the interested area. Feedback mechanism and punishment mechanism have been used to improve the model. The simulation shows that the model can truly evaluate entity behavior and effectively isolated from malicious nodes.
15162154
Trust Mechanism in Distributed Access Control Model of P2P Networks
Peer-to-peer network technologies have gained popularity without the need for centralized servers. With the consistent development of the network, the existing techniques about access control could not resolve the security issues in P2P networks perfectly. How to realize the trust mechanism in access control system is an important subject of P2P security research. In this paper, we analyze the lack of trust mechanism in the existing access control models, and present a recommendation trust model based on reputation. We introduce the related concepts in the trust model and explain the mechanism of trust. Then, a protocol of trust query is designed and calculations about trust are given. At last, we validate the availability of the trust model, and applied it in the existing access control model. The combining of trust mechanism and access control technologies makes the P2P networks securer.
14688887
Data Compression Algorithm Based on Hierarchical Cluster Model for Sensor Networks
A new distributed algorithm of data compression based on hierarchical cluster model for sensor networks is proposed, in which, the whole sensor network is mapped into a kind of hierarchical clusters model firstly, and then different wavelet transform models are used to commit data compression in inner and super clusters respectively. Theoretical analyses and simulation results show that, the above new methods have good performance of approximation, and can compress data and reduce the amount of data efficiently.
5460989
End-To-End Worst-Case Response Time Analysis for Hard Real-Time Distributed Systems
The verification of end-to-end response time for distributed hard real-time systems is quite necessary for safety-critical applications. Although current time analysis techniques can precisely analyze the response time, the performance is not quite satisfying, especially for large size distributed systems. This paper presents a novel end-to-end worst-case response time analysis approach for hard real-time distributed systems. This technique is based on the critical instant analysis and the canonical form transformation. It extends the traditional holistic analysis technique by exploiting the precedence relations between tasks on both different processors and the same processor. Simulation results have shown that this algorithm can achieve accurate results and offers good performance for systems with wide range of CPU utilizations and task set size, and therefore is applicable to schedulability analysis of complex distributed systems.
368510
A Performance Model for Domino Mail Server
Using performance model to analyze the Internet service is prevailing. However, the research of the performance model for mail server retrains in the immature status. In this paper, based on the queue theory, we propose a performance model for Domino mail server. The verification and analysis of the model are also presented. The experimental results show that this model characterizes the behavior of Domino mail server well and prove that it is useful for the qualitative performance measurement of Domino mail server.
5903999
Texture classification using multiresolution Markov random field models
Abstract Texture classification is an important topic in texture analysis. Texture classification has wide applications in remote sensing, computer vision, and image analysis. During the past years, several authors discussed to use multiresolution stochastic approaches to model textures. However, in these approaches, the highpass components which contain rich detailed information are lost. In this paper, we propose multiresolution MRF (MRMRF) modeling to describe textures. MRMRF modeling is a method trying to fuse filtering theory and MRF models. In the MRMRF modeling, highpass components are considered as well as lowpass components. “Brodatz texture database” is used in this paper for the experiments and Nearest Linear Combination (NLC) is used as measurement of distance to improve the recognition rate. The experimental results show that NLC has much better performance than Nearest Neighbor (NN) as the measurement in MRMRF modeling.
37162560
Fuzzy Control Strategy of Sub-mini Underwater Robots in Rectifying Control