جستجوی مقالات مرتبط با کلیدواژه "wireless sensor network" در نشریات گروه "ریاضی"

One of the main challenges already faced by communication networks is the efficient management of increasing complexity. Cognitive networks are put forwarded in the framework of evolution of network architectures as novel paradigms to provide autonomous in network reasoning to support end to end goals. This paper aims at proposing a new method for modifying spectral efficiency of topology control using new vertex coloring algorithm in Thomas cognitive networks.

Message and node authentication is one among the foremost effective ways to prevent nodes from being propagated, forwarded, and corrupted, unauthorized messages over wireless sensor networks (WSNs). In order to alleviate those challenges, several message authentication schemes based on symmetric or public key cryptosystems have been developed. Despite various benefits, many challenges still exist in the attack mitigating in the wireless sensor network such as considering the reputation of a source and updating it dynamically by considering node transmission characteristics on packet data with the source and intermediate node acts neighbour. In addition, most of them have the constants of communication overhead, high computations, resilience and scalability. To address these issues, a novel polynomial-based scheme has been developed and it has been named Spatial Temporal based Distributed Message and Source Security Authentication Protocol. However, this scheme address all the weakness of built-in threshold-based schemes employed for message authentication in determining the degree of the polynomial. The puzzle-based node authentication has been enabled for intermediate nodes; the proposed scheme allows unlimited message transmission by any node without the struggling problem of the threshold.

Wireless Sensor Networks (WSNs) have many potential applications and unique challenges. They usually consist of hundreds or thousands small sensor nodes such as MICA2 which operate autonomously conditions such as cost invisible deployment and many application domains, lead to small size and limited resources sensors. WSNs are susceptible to many types of link layer attacks and most of traditional networks security techniques are unusable on WSNs  due to wireless and shared nature of communication channel, untrusted transmissions, deployment in open environments, unattended nature and limited resources. So, security is a vital requirement for these networks; but we have to design a proper security mechanism that attends to WSN's constraints and requirements. In this paper, we focus on security of WSNs, divide it (the WSNs security) into four categories and will consider them, include: an overview of WSNs, security in WSNs, the threat model on WSNs, a wide variety of WSNs' link layer attacks and a comparison of them. This work enables us to identify the purpose and capabilities of the attackers; also, the goal and effects of the link layer attacks on WSNs are introduced. Also, this paper discusses known approaches of security detection and defensive mechanisms against the link layer attacks; this would enable it security managers to manage the link layer attacks of WSNs more effectively.

Humanity is currently experiencing one of the short periods of transition thanks to novel sensing solutions for smart cities that bring the future to today. Overpopulation of cities demands the development of solid strategic planning that uses infrastructure, innovation, and technology to adapt to rapid changes. To improve mobility in cities with a larger and larger vehicle fleet, a novel sensing solution that is the cornerstone of a smart parking system, the smart vehicular presence sensor (SPIN-V, in its Spanish abbreviation), is presented. The SPIN-V is composed of a small single-board computer, distance sensor, camera, LED indicator, buzzer, and battery and devoted to obtain the status of a parking space. This smart mobility project involves three main elements, namely the SPIN-V, a mobile application, and a monitoring center, working together to monitor, control, process, and display the parking space information in real-time to the drivers. In addition, the design and implementation of the three elements of the complete architecture are presented.

In Agricultural Fields there are different climate conditions, greenhouses parameters are important to monitored regulate the crop production, and we would like to make a automation system to trace down climate conditions at different locations. The Wireless Sensor Network (WSN) do the job to automate and analyze the comparable parameters. We would like to develop a smartphone application and sensors used are electrochemical sensors, location sensors BeagleBone Controller and Various Sensors are Used.

In dense traffic Wireless Sensor Network (WSN), traffic congestion can increase routing overhead and packet loss, which restricts the entire network performance, therefore a traffic-aware and congestion-control data delivery is required to control the traffic. The proposed Energy-efficient Q-learning and Kullback Sparse Encoder (EQ-KSE) method is used for traffic-aware routing and congestion-control data delivery method for WSN. The method enforces a traffic balancing strategy using the energy-efficient reward function and estimates the wireless link quality by the Energy-efficient and Q-Learning Routing algorithm. On the basis of the estimation of each wireless link, the Energy-efficient Q-Learning based Traffic-aware Routing model makes routing decisions through energy and queue length to reduce routing overhead and time significantly. With the obtained optimal routes data aggregation are performed at the sink node, causing a proportionate amount of congestion. To handle this issue, a Kullback Leibler Sparse Auto Encoder (KL-SAE) Congestion-control Data Delivery method is proposed. This KL-SAE model with the aid of the reconstruction loss function, through divergence reduces the congestion, therefore contributing to packet loss, and packet delivery ratio. Simulation results show that EQ-KSE method performs traffic-aware routing by minimizing both the route selection time and overhead. In high node density scenarios, it also betters the state-of-the-art methods in packet delivery ratio and packet loss rate.

One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the proposed method of this paper can take into account both types of uncertainty with a new and different approach. In this method, we avoid fuzzy transformations to probabilities and vice versa, and fuzzy uncertainties and probabilities are considered jointly. For this purpose, in the original graphical model, first, the type of uncertainty of each node is identified, and accordingly two separate fuzzy and probabilistic networks are constructed. In these networks, relations between nodes are expressed in terms of a set of rules. In each network, fuzzy and probabilistic inference is individually constructed and ultimately the values obtained from each network are combined. This method has been tested on a real problem of localization in wireless sensor networks. In this case, a sensor with uncertain location should be able to predict its location from the received power of its adjacent sensors. In the given scenario, 60 sensors with uncertain locations and 121 sensors with a specific location are considered. Meanwhile, the average location error of sensors has been used to evaluate the methods. The simulation results show the efficiency of the proposed method well.

Network throughput and energy conservation are two conflicting important performance metrics for wireless sensor networks. Since these two objectives are in conflict with each other, it is difficult to achieve them simultaneously. In this paper, a joint duty cycle scheduling and energy aware routing approach is proposed based on evolutionary game theory which is called DREG. Making a trade-off between energy conservation and network throughput, the proposed approach prolongs the network lifetime. The paper is divided into the following sections: Initially, the discussion is presented on how the sensor nodes can be scheduled to sleep or wake up in order to reduce energy consumption in idle listening. The sensor wakeup/sleep scheduling problem with multiple objectives is formulated as an evolutionary game theory. Then, the evolutionary game theory is applied to find an optimal wakeup/sleep scheduling policy, based on a trade-off between network throughput and energy efficiency for each sensor. The evolutionary equilibrium is proposed as a solution for this game. In addition, a routing approach is adopted to propose an energy aware fuzzy logic in order to prolong the network lifetime. The results show that the proposed routing approach balances energy consumption among the sensor nodes in the network, avoiding rapid energy depletion of sensors that have less energy. The proposed simulation study shows the more efficient performance of the proposed system than other methods in term of network lifetime and throughput.