Sharif Digital Repository

Introducing a new paradigm, cognitive radio, for spectrum utilization of unlicensed users, new research on spectrum utilization of licensed users was planned. The results show inefficiency of spectrum usage, so cognitive radio network was introduced. Cognitive radio network should not have any affect on primary users activity, so these networks face with some chalenges and the important ones is the supporting of the QoS.
In this thesis after analyzing of the proposed routing metrics for finding best end-to-end path, the important ones of them were selected for more precise analyzing. After analyzing we find some disadvantage, can be improved by multi-radio. Although all of these metrics... 

Cognitive radio is a tool for optimal use of radio spectrum, not used by the primary users all the time. Two main features of a cognitive radio are cognitive capability and reconfigurability. An intelligent cognitive radio uses its cognition ability to identify the environmental parameters and makes future decisions based on this information. Then the reconfigurability is used to set the sending parameters to the calculated values in the cognition phase. Cogition phase consists of major steps; spectrum sensing, decision, mobility and handoff. Throughout this thesis we first propose a cooperative sensing scheme using algorithmic techniques based on sensors’ spatial information through... 

In mobile ad hoc networks, having an efficient routing protocol to deal with dynamics in network topology, based on the user behavior learning, has a significant role in generating more accurate results. It is valuable to use a realistic mobility model in such networks so that the results from the simulation will reflect the actual reaction of mobile nodes in the real world. Using a realistic mobility model helps simulation to have more accurate results in comparison with other kinds of mobility models especially in a Vehicular Ad hoc Network (VANET). Before exchanging information between moving vehicles, the destination node should be located. However, the existing location service... 

Wireless sensor networks (WSNs) can be used in a variety of applications. The prime shortcoming of these networks is their energy constraint. The main energy consumer in a sensor node is its radio transmitter. Therefore data prediction is one of the most effective methods to reduce the data transmission rate. By data prediction, a large amount of energy is saved; which results in the longevity of the network life. Environmental variations almost have similar effects on different sensor sources in a sensor device. So, considering the correlation between different sources reduces the noise impact and increases data prediction accuracy. In this thesis, we use temporal and multisource... 

Wireless Multimedia Sensor Networks (WMSNs) have many applications in survilient systems. In this kind of applications, although we have limited energy and computational power, we should provide minimal security to transfer data in such networks. These constraints are more crucial when we use multimedia that has more data for processing and transmission. Because of this huge amount of data, we must use compression for using less energy in both processing and transmission.
In some algorithms, it has been proposed to integrate compression and encryption in order to decrease time and power consumption. The proposed algorithm is several times faster than AES (Advanced Encryption Standard) or... 

An RFID (Radio Frequency Identification) device consists of a small and inexpensive microchip attached to an antenna. The chip can be very small and some RFID tags are thin enough to be embedded in paper. RFID are heavily used to track items in production environments and to label items in supermarkets, Hospital, Factory, License plate, Cattle….They are usually thought of as an advanced barcode. However, in this project we argue about RFID license plate and using RFID tags for recognize vehicle from distance. Radio Frequency Identification (RFID) tags has many applications in modern automatic and intelligent identification systems. Vehicles outfitted by RFID tags as License Plates, can be... 

Indoor Positioning Systems (IPS) are commonly used in context-aware environments in order to determine the location of any desired object. In such environments location awareness is a key to adequate response. There are several positioning technologies available such as beacon-based positioning, camera-based positioning, Wi-Fi positioning, etc. Among these positioning systems Radio Frequency Identification (RFID) positioning has significant advantages over other technologies. Flexibility, ease of implementation, cost and accuracy are key advantages for RFID positioning technology. RFID positioning systems are classified in three categories: RF signal analysis-based, active RFID and passive... 

The Vehicular Ad hoc Network (VANET) have been presented to enhance the safety and comfort of driver and passengers. Thus, the functionality of VANET is related to the accuracy of disseminated messages about surrounding environment. Therefore, it is critical to detect the true reports among false reports which they have been reported by malicious nodes. However, in this research, the proposed scheme presents a centralized trust management assessment scheme named Detection of Best Report (DBR) in vehicular ad hoc environments. Each received message is evaluated individually according to its reporter interactions during event reporting. Based on this evaluation in RSU, the most reliable nodes... 

Wireless LANs are becoming widespread in enterprises due to extensive usage of mobile devices and appearance of bring-your-own-device policies. However, mechanisms common in home WLANs are not sufficient for managing lots of access point and clients in an enterprise WLAN and WLAN controllers which are used in enterprises nowadays are limited to a fixed set of commands operated from a CLI and the source code is not changeable. Also, their effectiveness can be harvested alongside access points from the same vendor. Thus, dynamic high level programming for whole network configuration is an absolute need in this changing business environment and Software-defined Networking (SDN) will empower us... 

Optimization of energy consumption is generally important in mobile networks and in particular in automotive networks. One of the challenges of installing roadside units in automotive case networks is to provide energy to the equipment assigned to these units. In some cases, power is easily available, but in many places, the cost of energy is very high and does not have economic justification. Therefore, optimization of energy consumption in roadside unit is of great importance. Typically, vehicles limitations in terms of energy consumption for communications are far lower than that of a roadside unit. In this dissertation, part of roadside communication to vehicles is shifted to the... 

Reducing energy consumption is one of the challenges facing wireless sensor networks with many solutions introduced for them with each having advantages and disadvantages. Some of the solutions introduced are based on using movable sinks. In this project, we attempt at proposing a place for the establishment of sinks using genetic algorithm that can reduce energy consumption in the net knots and increase the net life. This work should be done after reviewing the results of past researches and introduced methods. We will analyze the practicality of the proposed model using simulation and will show their advantages over the previous mentioned methods  

In 2008, a decentralized and distributed payment solution called Bitcoin was born. Since then, it has made the payment industry think about banks and companies on the one hand and government authorities on the other. By using mathematics and cryptography, Bitcoin was able to eliminate the need for trust and in this way it was able to eliminate intermediaries such as banks. In traditional financial affairs such as banks, the user must trust the bank and everything relies on the bank’s servers. While Bitcoin stores the history of transactions in a public and distributed ledger. This ledger is encrypted so that the state of the blockchain is always reliable. In Bitcoin’s decentralized and... 

Along with the emergence of the smart city concept and the increasing demand for a wide range of vehicles, the Internet of Vehicles (IoV) has attracted a lot of attention by providing numerous benefits including vehicle accident warning, reducing pollution levels and traffic congestion, as well as entertainment services. Furthermore, IoV offers various services combining Vehicular ad hoc networks (VANETs) and IoT in smart cities. However, these types of networks are exposed to a variety of security and privacy risks due to the wireless nature, because the sensitive message is transmitted through an insecure channel in the IoV-based smart city environment, therefore, it is necessary to... 

Focusing on developing the EEPS (Energy Electric and Power System) based on the SG (Smart Grid) infrastructure to achieve implementation of EI (Energy Internet) ultimately, in order to analyze and manage the energy/power consumption, requires a robust embedded EMS (Energy Management System) to implement real-time LF (Load Forecasting), prevent the power waste and realize consumption management which eventually leads toward the smart industries/buildings. STLF (Short Term Load Forecasting) is an essential component that an industrial plant requires to manage the power, regarding the load fluctuations during production, and compulsory requirement of cost mitigation. This thesis, in order to... 

The main idea of the upcoming research is to provide a way of benefiting from processing at the edge and processing in the fog for the open source platform openremote; In such a way that the central core of the platform can offload its processing tasks to the edge of the network. With this work, a large amount of the processes that used to be done by the core will be offloaded from the core. On the other hand, by applying processes at the edge of the network, it becomes possible to eliminate a large amount of overhead caused by raw data transmission, and as a result, the productivity of the network increases. In the current research, in addition to designing a model to add the mentioned... 

The stock market is vital to the economy as it serves as a key indicator of economic health. AI algorithms can process vast amounts of market data at high speeds, identifying patterns and trends that are often invisible to human analysts. Forecasting future stock trends poses significant challenges due to the complex inter-stock and intra-stock dynamics that influence stock prices. Recently, graph neural networks have shown promising results by modeling multiple stocks as graph-structured data. However, many of these approaches depend on manually defined factors to construct static stock graphs, which fail to capture the rapidly changing interdependencies between stocks. In this work,... 

Mobility is one of the most challenging issues in mobile Ad-Hoc networks which has a significant impact on performance of network protocols. To cope with this issue, the protocol designers should be able to analyze the movement of mobile nodes in a particular wireless network. In this thesis, a new framework called Mobility Analyzer has been proposed. At first, Mobility Analyzer categorizes mobility models based on their mobility characteristics; subsequently, it uses mobility metrics for evaluating mobility traces which are collected by GPS or generated by mobility simulators. Finally, Mobility Analyzer recognizes the mobility model of mobility traces based on mobility metrics and measures... 

Recent researches show inefficient use of frequency spectrum such that there is shortage of frequency in operation. In order to overcome this problem cognitive radio are introduced that opportunist usage of frequency band is their prominent characteristic. Problems and challenges caused by using these networks are wide and increasing. In this thesis we focus on improving resource management algorithms in cognitive radio. In this study in order to have a dynamic and efficient management in choosing reliable and quality channels, reinforcement learning algorithms are used based upon existing data and experiences. Since this tool has the learning capability and analysis in dynamic situation of...