A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a self-configuring network without using any existing infrastructure. Network nodes in a mobile Ad-hoc network move in some motion patterns called mobility models. The mobility models play a very important role in determining the protocol performance in MANET. Thus, it is essential to study and analyze various mobility models and their effect on MANET protocols. If we can recognize the mobility pattern of motion of mobile nodes in our environment we can customize our network protocols to deal with that existing mobility model. In this paper we introduce a new method for classification and pattern recognition of mobility traces into mobility models in mobile Ad-hoc networks. This method uses a simple learning based classification method to recognize the existing mobility model in raw mobility traces which was collected from real motion of mobile Ad-hoc nodes or mobility traces generated by mobility simulators. Our simulation results prove ability of our proposed method to accurately classify given unknown mobility traces into various mobility models.

Mobility Prediction in mobile ad-hoc networks is used in location aided routing and mobility aware topology control protocols. These protocols assume that each node knows its current position, speed and movement direction angle. Using this information the protocols can predict the future position of each node. Also they can predict some parameters like future distance between 2 neighboring nodes. Future distance between 2 neighboring nodes is used in some applications like mobility aware topology control protocols. The major problem with these protocols is the inaccuracy of future distance predictor which uses mobility prediction to estimate the future distance of neighboring nodes. The efficiency of this estimator varies in presence of different mobility models, sampling rates and different speed ranges. In this paper, we introduce an adaptive mobility prediction method that uses learning automaton to estimate the coefficients of a simple adaptive filter in order to predict the future distance of 2 neighboring nodes. We evaluated this estimator in different mobility models and sampling rate. Simulation results show significant improvement in accuracy of the future distance prediction mechanism which causes more accurate prediction especially in low sampling rates.

Topology control in mobile ad-hoc networks allows better spatial reuse of the wireless channel and control over network resources. Topology control algorithms tend to optimize network power usage by keeping the topology connected. However, few efforts have focused on the issue of topology control with mobility. One of the most efficient mobility aware topology control protocols is the "mobility aware distributed topology control protocol". The major problem with this protocol is the future distance predictor which uses mobility prediction to estimate the future distance of neighboring nodes. The efficiency of this estimator varies in presence of different mobility models, sampling rates and different speed ranges. In this paper, we introduce an adaptive mobility prediction method that uses learning automaton to estimate the coefficients of a simple adaptive filter in order to predict the future distance of two neighboring nodes. We evaluated this estimator in the mobility aware distributed topology control protocol. Simulation results show significant improvement in accuracy of the future distance prediction and reduction in power consumption of each node.

A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a self-configuring network without using any existing infrastructure. Since MANETs are not currently deployed on a large scale, research in this area is mostly simulation based. Among other simulation parameters, the mobility model plays a very important role in determining the protocol performance in MANET. Thus, it is essential to study and analyze various mobility models and their effect on MANET protocols. In this paper we introduce a new framework for simulation of mobility models in mobile Ad-Hoc networks. This simulator can generate mobility traces in various mobility models. The mobility traces can be customized for different network simulators using XML and text output formats. User friendly graphical interface and batch processing ability makes our simulator one of the most efficient and useful mobility simulators in this field of research. We also propose some new features and parameters in mobility models to make the behavior of our simulator supported mobility models more similar to real world mobile node motions and fix some problems in last proposed methods to generate mobility models.

In the modern era, the advancement of information technology requires improvement in other fields such as communication technologies, management of human resources, business environments, legal backgrounds, and so on. Indicators that measure the growth of ICTs in different societies have also pointed out this importance. National legislators are always seeking means to improve ICTs and use them as an enabler of industry in their countries. a number of developing countries have devoted a considerable effort but have not achieved the results they were expecting. In recent years, Iran, like many other of the developing countries, has made a desperate attempt to get engaged in similar activities, but nothing in particular has been achieved. In this paper, we will take a system dynamics approach to model changes in the progress of information technology in Iran. Sources of many of the problems showed up After the simulation of the model. We have also outlined the policies required for reaching a steady growth in the future.

The accessibility of broadband Internet to home users has pushed video broadcasting applications up in the list of the most favorite IP-based applications. A Peer-to-Peer overlay network is an attractive foundation for video streaming as it can shift the burden of content distribution from the network routers and servers to the clients. However, live Peer-to-Peer media streaming systems face many challenges such as bandwidth heterogeneity, node churn, and selfish nodes. Although many tree based and mesh based streaming protocols have been proposed, each has its own drawbacks such as unreliability and unfairness in the tree based and long startup delay and complex scheduling in mesh based protocols.
In this project, we propose a new layered video streaming protocol called LayeredCast that compensates the mentioned drawbacks of the previous approaches by using a hybrid of mesh and tree structures. It provides an adaptive scheme to enhance the video quality by using a layered video codec for heterogeneous clients. Since all clients need to download the base layer, a tree network pushes the base layer to all peers with low delay while the enhancement layers are pulled over a mesh network based on the user need. We have evaluated the performance of the LayeredCast based on the play-back quality in the clients in the presence of ungraceful leave and heterogeneous bandwidth on an innovative simulation framework.

Peer-to-peer networks have attracted considerable attention from researchers both in academia and in industry as an infrastructure for distributed computing and multimedia broadcasting. In recent years, many protocols have been proposed which use P2P networks in order to implement a video multicast application. In this paper, we present a problem-based viewpoint to survey the challenges in designing P2P live video streaming applications through a comprehensive analysis of negative and positive points of their solutions. We categorized these points in an innovative hierarchical structure based on four categories: topology, send/receive data mechanisms, incentive, and group management.

Nowadays, technology pursues to make our environment more intelligent. This means that technology will serve us in every part of our environment in an embedded manner. This services could not be implemented without close communication among different entities, combining their services, and recognizing the context. To realize ubiquitous computing systems needs many challenges including discovering and integrating entities, interaction between two entities, and context recognition to be solved. Ontology is the key to enable different entities to communicate with each other and the environment. There have been proposed many frameworks in order to concretize the usage of ontologies in this field. This report surveys the challenges ubiquitous computing systems which ontology could solve and introduces different frameworks for implementing the solutions in the real world.

Refactoring patterns help us to change our code to be more object-oriented and more maintainable. In this report, I tried to investigate the characteristics of these patterns in order to propose a classification for them. Then, their association with GRASP patterns has been analyzed to know the goal of each pattern better. At last, a sequence for applying these patterns has been proposed based on the investigated characteristics and associations

Nowadays, intra-organization and inter-organization interaction between online applications is increasing. Therefore, it is necessary to establish a flexible, extendible, and open-source standard for this communication. Web-Service is a de facto standard for machine-to-machine interaction over a network. It is based on three technologies, SOAP, WSDL, and UDDI, which use an XML document as their basis. As in some services, it is consequential to secure the service. Web Service Security, as a framework, proposed to preserve the security of a service using other technologies such as XML cryptography and XML digital signature. This is necessary to note that this technology does not define any algorithm to secure a document, but only defines a consistent way to use the predefined security algorithms. In this report, I studied XML, Web Service, Web Service Security, and its related protocols and languages such as SAML, XKMS, and XACML. Moreover, I have gathered the code samples for using these protocols in this document and implemented a working sample using AXIS framework in Java.

By continuance of the trend of miniaturizing the computing features, increasing their density on chips and approaching the nanoscale dimensions, quantum effects become a rule rather than the exception and results in various problems. Although some nanodevices created in limited scales, but despite the high defect ratio of these devices, providing an effective architecture for nanocomputers is a big difficult step. One of the most promising solutions is using fault and defect tolerance techniques in these architectures. Teramac is the world's first truly defect tolerant computer. It uses processes to locate and route around defects, and using a software interface, shield the user from the additional complexity that arises due to defect tolerance.
In this technical report we first study current technology limitations, and next propose a list of nanocomputer architecture candidates. As a promising alternative we discussed on reconfigurable and defect tolerant systems and their best classical example, The Teramac.

A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a self-configuring network without using any existing infrastructure. Since MANETs are not currently deployed on a large scale, research in this area is mostly simulation based. Among other simulation parameters, the mobility model plays a very important role in determining the protocol performance in MANET. Thus, it is essential to study and analyze various mobility models and their effect on MANET protocols. In this project we introduce a new framework for simulation of mobility models in mobile Ad-Hoc networks. This simulator can generate mobility traces in various mobility models. The mobility traces can be customized for different network simulators using XML and text output formats. User friendly graphical interface and batch processing ability makes our simulator one of the most efficient and useful mobility simulators in this field of research. We also propose some new features and parameters in mobility models to make the behavior of our simulator supported mobility models more similar to real world mobile node motions and fix some problems in last proposed methods to generate mobility models.
On the other hand, if we can recognize the mobility pattern of motion of mobile nodes in our environment we can customize our network protocols to deal with that existing mobility model. We introduce a new method for classification and pattern recognition of mobility traces into mobility models in mobile Ad-hoc networks. This method uses a simple learning based classification method to recognize the existing mobility model in raw mobility traces which was collected from real motion of mobile Ad-hoc nodes or mobility traces generated by mobility simulators. Our simulation results prove ability of our proposed method to accurately classify given unknown mobility traces into various mobility models.

Cooperation among nodes is vital in Mobil Ac Hoc Networks (MANETs) since in such networks nodes depend on each other for forwarding and routing packets. However, cooperation in such operations consumes nodes’ recourses such as battery and bandwidth. Therefore it is necessary to design mechanisms to enforce nodes to forward packets when the source and destination of the packet are other nodes. A centralized solution is inapplicable in this situation since nodes in MANETs communicate on a peer-to-peer basis without any central authority. In this paper, we present a distributed fair solution to judge, punish and re-admit a selfish node, forcing nodes to cooperate with each other.
Our scheme is different from previous ones in that it combines two characteristics that have been separately handled in previous works. The first characteristic is fairness of reputation system regarding position of nodes in the network and the second one is the ability to cope with false reputation information distributed by malicious nodes. Unlike previous fair solutions, this scheme can cope with false disseminated information. We also propose a new scheme to manage movement of nodes, considering the fact that it is to be designed for a fair reputation system. The experimental results suggest that the proposed scheme can successfully identify selfish and malicious nodes and react accordingly