基于UDP的网络视频传输与同步的研究

视频在网络传输过程中常常由于UDP本身不可靠的性质造成数据包丢失的问题。为了解决这一问题,本文针对基于UDP的网络视频传输与同步展开了研究。首先本文介绍了传输层UDP协议的基本原理;其次,针对网络视频传输对于实时性和连续性等方面的要求本文提出了一种网络视频数据的传输模型;然后,为了解决在互联网中由于传输的延迟随机性所导致的数据同步问题,本文提出了一种时间戳来解决视频同步问题的方法,在视频数据的发送端,通过为数据传输设定一个参考时钟,在实际生成数据流时根据参考时钟上的时间将数据块与时间戳绑定;在视频数据的接收端,通过读取数据块中的时间戳值,并参考当前参考时钟上的时间来进行视频数据帧重组从而解决了视频数据传输不同步的问题．．     

WSN中虚拟时戳与父亲责任链时钟同步算法

通过对无线传感器网络时钟同步算法的研究,提出了适用于单跳网的虚拟时戳时钟同步算法与适用于多跳网的父亲责任链时钟同步算法。为确保整个时钟同步的健壮性与同步过程低的能量消耗,进而提出了携子寻父算法,当利用邻居表构造的层次链路树发生断链时,其以较小的代价快速恢复父亲责任链。实验结果显示其具有较高的精度,适合于大规模无线传感器网络的数据采集与监测等应用。     

一种抗重放攻击的Web服务认证协议

用户调用Web服务时需要双向认证。为此,提出一种抗重放攻击的Web服务认证协议。基于时间戳/消息ID缓存的抗重放攻击方法,利用简单对象访问协议的请求/响应消息和WS-Security规范设计双向认证协议,使用Axis2的Module机制加以实现。实验结果表明,该协议能避免单纯采用时间戳所带来的时钟同步问题,具有较好的抗重放攻击能力。     

An efficient and secure multi-server authentication scheme with key agreement

Remote user authentication is used to validate the legitimacy of a remote log-in user. Due to the rapid growth of computer networks, many network environments have been becoming multi-server based. Recently, much research has been focused on proposing remote password authentication schemes based on smart cards for securing multi-server environments. Each of these schemes used either a nonce or a timestamp technique to prevent the replay attack. However, using the nonce technique to withstand the replay attack is potentially susceptible to the man-in-the-middle attack. Alternatively, when employing the timestamp method to secure remote password authentication, it will require the cost of implementing clock synchronization. In order to solve the above two issues, this paper proposes a self-verified timestamp technique to help the smart-card-based authentication scheme not only effectively achieve password-authenticated key agreement but also avoid the difficulty of implementing clock synchronization in multi-server environments. A secure authenticated key agreement should accomplish both mutual authentication and session key establishment. Therefore, in this paper we further give the formal proof on the execution of the proposed authenticated key agreement scheme.     

Normalized Efficient Routing Protocol for WSN

WSNs （wireless sensor networks） consist of thousands of tiny nodes having the capability of sensing, computation, and wireless communications. Unfortunately these devices are limited energy devices, that is means we must save energy as much as possible, to increase network life time as long as possible. In this paper we introduce NEER--normalized energy efficient routing protocol that increases network life time through switching between AODV protocol that depends on request-reply routing, and MRPC that depends on residual battery in routing.     

Solve the Humanware Problem： Take the Full Advantage of Telemedicine

Telemedicine＇s greatest problem is not found in software and hardware. Many can make software and hardware work. It has for long been clear that telemedicine has diffusion problems. Focus should be shifted over to the humanware. Telemedicine means work is done by virtual organizations. For the future of telemedicine, organizational issues will represent a challenge. Organizations consist of humans in interaction. In Norwegian telemedicine projects, organizational problems were identified and solutions to the problems were designed. More than 40 publications show numerous organizational consequences and numerous types of organizational consequences. When it comes to the solving telemedicine＇s organizational problems, learning from the experience others have is important. It is not necessary for all to invent what the organizational problems are. Organizing health care around the physical telecommunication networks is associated with the concept of network organization. The electronic networks become an infrastructure around which single health care providers are distributed. Such network organization means a formation of alliances between organizations. Centralization and decentralization are important terms for all organizing. Telemedicine makes the question of centralization or decentralization relevant. Telemedicine requires collaboration between participating parties. Obtaining the benefits of telemedicine is dependent on implementing the right measures for good collaboration. We know there are problems with telemedicine virtual organizations, but solutions to these problems exist. For the future of telemedicine, doing work with organization is important. Skilled managers have an important role to play.     

Controllability of time-variant Boolean control networks and its application to Boolean control networks with finite memories

This paper investigates the controllability of time-variant Boolean control networks(BCNs).For the time-variant BCNs,a necessary and sufcient condition for the controllability is given,and a control design algorithm is presented.For a BCN with fnite memories,an equivalent transformation to a time-variant BCN is constructed.Then a necessary and sufcient condition for the controllability and a control design algorithm are obtained.     

Performance Evaluation of Lateration,KNN and Artificial Neural Networks Techniques Applied to Real Indoor and Outdoor Location in WSN

WSN （wireless sensors networks） is a promising research area which has been in center of attention in many applications on telecommunications. Despite of many existing applications, a bunch of algorithms have been created or applied to solve different issues surrounding WSN. An attractive subtopic on research area is Localization Algorithms. Due to the countless applications, it is almost impossible to list all the algorithms applicable to solve sensor＇s location problem in WSN over distinguished parameters associated to diverse environments. This paper evaluates a geometrical algorithm, an instance based algorithm and a function approximator algorithm, having the RSS/ （received signal strength indicator） as metric to estimate planar coordinates in an indoor and outdoor environment using a WSN based on IRIS mote. The analysis of the WSN is constructed over statistical data obtained from empirical experiments and the observed characteristics of the algorithms. We also estimate the performance for different parameters configurations applied to the algorithms for both indoor and outdoor environment. Also, some comments about the tradeoff between the accuracy and the performance of the algorithms are made objecting to. Also, some objections about the tradeoff between the accuracy and the performance of the algorithms are made when relevant.     

High-Accuracy and High-Speed Calculation Method for Large-Scale Multi-layer Network Designs by Integrated Decomposition Method

A multi-layer network design, which excuses light-path design and IP routing design at the same time, has attracted great attention for IP over WDM network designs. The multi-layer network design problem can be solved by using a MILP （mixed integer linear programming） problem. However, the MILP problem for a large-scale network cannot be calculated due to the huge amount of variables used in the computation. In order to cope with this problem, a calculation method, which decomposes the original MILP problem into smaller sub-problems and obtains an approximate solution by solving these smaller MILP problems, has been proposed. However, this method has a defect that the calculation accuracy is degraded. In order to cope with this problem, we propose a novel method that solves the original MILP problem using the results of the sub-problems. We evaluate our proposed method by the computational experiments and show the effectiveness of our method.     

A Modular Simulation Tool of an Orchestrator for Allocating Virtual Resources in SDN

SDN （Software-Defined Networking） and NFV （Network Functions Virtualization） are technologies for enabling innovative network architectures. Nevertheless, a fundamental problem in instantiation of VNs （Virtual Networks）, performed by NFV, is an optimal allocation of resources offered by one or more SDN domain networks. The process of instantiation of VNs is performed in several phases, including splitting and mapping algorithms. For each one of these phases, researchers have developed algorithms, being possible to obtain different results combining them. This paper introduces a modular and flexible graphical discrete event simulation tool for solving the complete virtual resource allocation in SDN domain networks problem. A Java-based tool has been developed to integrate existing and future algorithms related researchers can select the appropriate algorithm in each phase performance evaluation of the selected and proposed algorithms. to each phase of the process. The simulator is a test-bed in which and display the results in a graphical form, while obtaining a     

A Privacy Taxonomy for the Management of Ubiquitous Environments

Pervasive and ubiquitous environments must handle the detection and management of users, devices and services, while guaranteeing the privacy of both the users and the environment itself. Current techniques for handling privacy found in the literature treating the subject in various ways, while concentrating on the device management, communication protocols, user profiles and environmental access. This paper examines a control model for privacy in pervasive environments from the perspective of the environment. A prototype was devised and tested to validate the generic model of privacy which was also used to compare taxonomic concepts in the literature. Moreover, the prototype was devised and tested to validate the generic model of privacy for control and manage various users, devices and environments and so on. The prototype was based on Percontrol （a system for pervasive user management）, which was only intended to identify users using Wi-Fi, and now it is capable of managing temperature, luminosity and other preferences, measured by a WSN （wireless sensor network） embedded to Percontrol, and the data treatment is done by an ANN （artificial neural network）. Results confirmed the viability of device detection with Wi-Fi, Bluetooth and RFID （radio frequency identification） for an increases slight of the latency in registering new devices on the system.     

Sequence memory based on an oscillatory neural network

In the brain,the discrete elements in a temporal order is encoded as a sequence memory.At the neural level,the reproducible sequence order of neural activity is very crucial for many cases.In this paper,a mechanism for oscillation in the network has been proposed to realize the sequence memory.The mechanism for oscillation in the network that cooperates with hetero-association can help the network oscillate between the stored patterns,leading to the sequence memory.Due to the oscillatory mechanism,the firing history will not be sampled,the stability of the sequence is increased,and the evolvement of neurons’states only depends on the current states.The simulation results show that neural network can effectively achieve sequence memory with our proposed model.     

Communication and monitor of breast cancer signal in the pulse-output genetic circuit network

Pulse-output genetic circuit networks have the advantages in stability and accuracy.In this paper,we analyze some important parameters in a typical inverter,and then design a pulse-output genetic circuit of breast cancer signal communication and monitor of breast cancer signal.We first design a single-index monitor circuit.When a certain tumor marker’s concentration exceeds the positive criterion,the circuit will output a pulse as a warning.Since the diagnose results derived from one single tumor marker are sometimes indeterminate,an integrated circuit is proposed to construct a multi-index monitor circuit network.The multi-index detection can strongly increase the correct recognition rate in terms of accuracy and safety.This circuit network may also be used in other fields of gene diagnosis with some modifications,and some experiments designed to validate them had been done.     

Associative categorization of frequent patterns based on the probabilistic graphical model

Discovering the hierarchical structures of differ- ent classes of object behaviors can satisfy the requirements of various degrees of abstraction in association analysis, be- havior modeling, data preprocessing, pattern recognition and decision making, etc. In this paper, we call this process as associative categorization, which is different from classical clustering, associative classification and associative cluster- ing. Focusing on representing the associations of behaviors and the corresponding uncertainties, we propose the method for constructing a Markov network （MN） from the results of frequent pattern mining, called item-associative Markov net- work （IAMN）, where nodes and edges represent the frequent patterns and their associations respectively. We further dis- cuss the properties of a probabilistic graphical model to guar- antee the IAMN＇s correctness theoretically. Then, we adopt the concept of chordal to reflect the closeness of nodes in the IAMN. Adopting the algorithm for constructing join trees from an MN, we give the algorithm for IAMN-based associa- tive categorization by hierarchical bottom-up aggregations of nodes. Experimental results show the effectiveness, efficiency and correctness of our methods.     

Towards energy-efficient storage placement in large scale sensor networks

Data storage has become an important issue for energy efficient data management in sensor networks. In this paper, we investigate the optimized storage placement problem in large scale sensor networks, aiming to achieve minimized energy cost. In order to efficiently deal with large scale deployment areas with irregular shape, we propose to utilize the hop as the computation unit instead of the node, such that computation complexity can be greatly reduced. We propose methodologies to solve the optimization problem both in situations for limited and unlimited numbers of storage units. The ultimate goal of this paper is to give fundamental guidance for optimized storage placement in large scale sensor networks. Simulation results show that our methodologies can greatly reduce the overall energy consumption compared to other strategies.     

Network selection policy based on effective capacity in heterogeneous wireless communication systems

A great deal of previous research was based on the concept of Shannon theory without considering the delay characteristic. However, in reality, different services have different delay constraints. In this paper, two new network selection policies are proposed for heterogeneous wireless communication systems using effective capacity, which incorporate delay in the transmission rate. Users can access the proper network after considering the delay demands of different services. Our proposed policies aim to maximize the entire throughput with different delay constraints. Both the mathematicM analysis and simulations show that the proposed network selection policies can improve network throughput while providing quality-of-service guarantees.     

Channel Aware Opportunistic Routing in Multi-Radio Multi-Channel Wireless Mesh Networks

Opportunistic routing （OR） involves multiple candidate forwarders to relay packets by taking advantage of the broadcast nature and multi-user diversity of the wireless medium. Compared with traditional routing （TR）, OR is more suitable for the unreliable wireless link, and can evidently improve the end to end throughput. At present, there are many achievements concerning OR in the single radio wireless network. However, the study of OR in multi-radio wireless network stays the beginning stage. To demonstrate the benefit of OR in multi-radio multi-channel network, we propose a new route metric -- multi-channel expected anypath transmission time （MEATT）, which exploits the channel diversity and resource of multiple candidate forwarders for OR. Based on the new metric, a distributed Mgorithm named Channel Aware Opportunistic Routing （CAOR） is proposed. The simulation results demonstrate that MEATT improves 1.14 and 1.53 times of the average throughput than existing expected anypath transmission time （EATT）and metric of interference and channel switching cost （MIC） respectively. The average delay of MEATT is 17% and 40% lower than those of EATT, MIC, respectively.     

The Impact of Extra Traffic on the Control Channel over the Performance of CCA Applications

This paper presents an analysis of the impact of competing traffic on the control channel on the performance of applications like CCA （chain collision avoidance）. These vehicular network＇s applications are addressed to traffic safety aiming chain collision avoidance. This work shows the impact of signaling messages of other applications （in the control channel） in the CCA application＇s performance. The results were carried out considering since an ideal scenario （without concurrent traffic） until a scenario with high utilization level of control channel. Besides, the impact of the transmission power in the CCA applications is also evaluated.     

Graph-Theoretic Approach to Network Analysis

Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than the elements themselves. These constraints follow generalized Kirchhoff＇s laws derived from physical constraints. Once we have a graph; then the working environment becomes the graph-theory. An algorithm derived from graph theory is developed within the paper in order to analyze general networks. The algorithm is based on computing all the spanning trees in the graph G with an associated weight. This weight is the product ofadmittance＇s of the edges forming the spanning tree. In the first phase this algorithm computes a depth first spanning tree together with its cotree. Both are used as parents for controlled generation of off-springs. The control is represented in selecting the off-springs that were not generated previously. While the generation of off-springs, is based on replacement of one or more tree edges by cycle edges corresponding to cotree edges. The algorithm can generate a frequency domain analysis of the network.     

Using Genetic Algorithm to Support Artificial Neural Network for Intrusion Detection System

The following methods detect the attacks intrusion detection system： ANN （artificial neural network） for recognition and GA （genetic algorithm） for optimization of ANN results. We use KDD-CUP dataset to obtain the results, which shows around 0.9998 accuracy of applied methods in detecting the threads. ANN with GA requires 18 features.