جستجوی مقالات مرتبط با کلیدواژه "wireless sensor network" در نشریات گروه "مدیریت"
تکرار جستجوی کلیدواژه «wireless sensor network» در نشریات گروه «علوم انسانی»-
In intrusion detection applications, wireless sensor networks are commonly used. Many research literature papers are aimed at generating and evaluating the information on intruder detection in terms of probability of detection and false alarm rates. In two modalities, the model for acoustic signal and the sensor probability model, and in this research paper, the problems of passive motive intrusion detections have been solved. The aim is to establish a three-stage hierarchy to determine if mobile intruders are present. The sensor nodes at the fundamental level have a k-mean clustering grouping. For binary hypothesis testing, the strengths or probabilities in the cluster head are employed. Cluster leaders send their judgments to the Fusion Centre (FC) after completing a Likelihood Ratio Test (LRT) to ensure invaders are correctly inferred. A numerical analysis of the signals received determines the optimal value for probability computation. The resulting fusion rule maximizes detection likelihood regarding the allowed falsifying rates. The number of absolute sensor nodes determines the exact fusion rule. Compared to earlier fusion rules, simulation results show that the new fusion rule has a better ability to follow mobile invaders and enhanced accuracy and detection speed.Keywords: False alarm rate, Binary hypothesis, Probability detection, Wireless Sensor Network, Mobile intruder detection
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هدف
هدف این پژوهش مدل سازی ریاضی زنجیره تامین هوشمند، تحت سیاست مدیریت موجودی توسط فروشنده با رویکرد اینترنت اشیا، برای بهینه سازی و رفع چالش های زنجیره تامین سنتی، از قبیل عدم اطمینان، هزینه و تغییر تقاضای مشتریان است.
روشبر اساس نیازها و اهداف، یک مدل ریاضی دوهدفه ارایه شد که هدف های اول و دوم آن، به ترتیب حداقل ساختن هزینه و حداقل ساختن زمان زنجیره تامین است. در این مدل، یک زنجیره تامین چهارسطحی در نظر گرفته شده است که ارتباط مستقیم از تامین کننده به تولیدکننده و از تولیدکننده به خرده فروش و از خرده فروش به مشتری را امکان پذیر می کند. ماهیت این زنجیره هوشمند است و سطوح زنجیره از فناوری های شبکه حسگر بی سیم (WSN)، شناسایی فرکانس رادیویی (RFID)، بلاکچین و فروش اینترنتی بهره می برد.
یافته ها:
در این پژوهش، پس از اعتبارسنجی مدل به کمک نرم افزار گمز، یک مسیله پایه ای با روش constraint- حل شد که نتایج حاصل از حل مدل و نمودار پارتو ارایه شده است. بهینگی پیاده سازی فناوری های مزبور و همچنین واکنش زمان و هزینه به این پیاده سازی، کارآمدی مدل را نشان می دهد.
نتیجه گیری:
در این پژوهش یک مسیله پایه ای با روش constraint- حل شده است. مقادیر توابع هدف و نمودار پارتو، نتایج مطلوبی را نشان می دهد. با حل مدل در ابعاد کوچک و متوسط در نرم افزار گمز، مقادیر توابع هدف و زمان حل ارایه شده است که نتایج گویای اعتبار مدل است و می توان آن را در ابعاد بزرگ تر حل کرد. به دلیل کمبود حافظه نرم افزار گمز، برای حل ابعاد بزرگ مدل، باید از نرم افزار متلب و الگوریتم های فراابتکاری استفاده شود.
کلید واژگان: اینترنت اشیا, زنجیره تامین هوشمند, شبکه حسگر بی سیم, مدل سازی ریاضیObjectiveThe purpose of this research was to provide a mathematical model for smart supply chains with Vendor Managed Inventory (VMI) through the Internet of Things (IoT) technology to overcome traditional supply chain challenges and solve problems such as uncertainty, high costs, and changes in customer demands. Creating an intelligent and agile supply chain is essential to tackle these challenges and problems. Generally, customers are still skeptical and doubtful of the smart supply chain, and this skepticism is more likely to arise in the financial context. To improve efficiency, all organizations and institutions need to adapt themselves to external and internal changes, maintain supply chain inventory, and be flexible with customer demands.
MethodsPrevious studies discussed intelligent supply chains, IoT, and their combination and described the advantages and disadvantages of using these technologies. Despite much research in this field, no mathematical modeling has been done for a smart supply chain that incorporates technology and automation. Based on such needs and objectives, this study sought to design a two-objective mathematical model, with a four-level supply chain. In this model, there is a direct relationship from suppliers to manufacturers, from producers to retailers, and from retailers to customers. The supply chain was intelligently designed, and the chain levels used Wireless Sensor Network (WSN) technologies, Radio Frequency Identification (RFID), blockchain, and Internet sales.
ResultsThe designed model in this research was validated by GAMS software. The researchers identified 10 problems of small and medium dimensions in the model. They presented the results in the form of objective function values and solution time. The basic problem was solved using the -constraint method. The results obtained from solving the model and the Pareto diagram were presented in detail. The optimal implementation of the mentioned technologies, as well as the time and cost response to this implementation, proved the efficiency of the model.
ConclusionThe present study put forward a two-objective mathematical planning model. The first and second objectives of this model were to minimize the cost and decrease the time of the supply chain, respectively. By solving the basic problem, using the -constraint method, the values of the objective functions and the Pareto diagram showed desired results. Solving the model in small and medium-sized dimensions using GAMS software, the values of the objective functions and the solution time were achieved. Also, the results proved the validity of the provided model suggesting that it can be used in larger dimensions. However, due to the lack of memory in GAMS software, for large dimensions, the suggested mathematical model for the smart supply chain needs to be checked using MATLAB software and meta-heuristic algorithms.
Keywords: Internet of Things, Smart supply chain, Wireless Sensor Network, Mathematical Modeling -
AI-WSN: Direction of Arrival Estimation Based on Bee Swarm Optimization for Wireless Sensor NetworksAn Artificial Intelligence (AI) technique plays the most crucial factor to consider in energy utilization in a wireless sensor network (WSN). AI transforms industrial operations by optimizing the energy consumption in sensor nodes. As a result, it is crucial for improving sensor node location accuracy, particularly in unbalanced or Adhoc environments. Because of this, the purpose of this research is to improve the accuracy of the localization process in locations where sensor nodes encounter barriers or obstacles on a regular basis. The Bees Swarm Optimization (BSO) algorithm is used to segment sensor nodes in order to increase the accuracy of the Direction of Arrival (DoA) estimate between the anchor and unknown node pairs. Even in the presence of unbalanced conditions, the proposed DoA- BSO involving three separate bee colonies can identify plausible anchor nodes as well as segment nodes arranged in clusters. In order to obtain the intended result, the objective function is designed to take into consideration the hops, energy, and transmission distance of the anchor and unknown node pairs, among other factors. The studies are carried out in a large-scale WSN using sensor node pairs in order to determine the precision with which the DoA-BSO can be located. When comparing DoA-BSO to conventional approaches, the findings of the meta-heuristic algorithm show that it improves the accuracy and segmentation of nodes significantlyKeywords: Wireless Sensor Network, Direction of arrival, Bees Swarm Optimization, Energy estimation
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Malware attack is growing day by day in cyberspace. And Wireless Sensor Network (WSN) is also facing a hazardous type of situation due to attack of malware (malicious code, virus, worm etc.). Malwares target sensor nodes easily because, nodes are equipped with limited resources. Hence, security of WSN against malware attack is one of the imperative requisite. Malware spreads in the entire network wirelessly, which initiates from single infectious node and spread in the whole WSN. In this way the complete network comes under the security threat. Therefore, it is mandatory to apply the security technique through which to secure WSN against malware attacks. To secure WSN due to malware attacks a quarantine based model has been proposed. The proposed model consists of various epidemic states namely: Susceptible Carrier - Infectious - Quarantine - Recovered - Susceptible (SCIQRS). The model explained the propagation dynamics of malware in WSN and proposed a technique to prevent its propagation. The technique of quarantine along with recovery is to much effective in prevailing of malware propagation in WSN. For the determination of WSN stability and equilibrium points the expression of basic reproduction number has been obtained. Malware propagation is affected by different network parameters, which has been also discussed. The comparative investigation of proposed model has been carried out with existing model. The proposed model has been substantiated by simulation outcomesKeywords: Basic Reproduction Number, Malware Security, Stability, Wireless Sensor Network
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In many significant characteristics of the modern world, including particular industry, agriculture, and military applications, Wireless Sensor Networks (WSNs) have begun to emerge. Even though energy consumption is the greatest challenge confronting WSNs, it is essential to analyse the feasibility of the use of mobile components for the data collection on WSN networks. To collect information from their sensing terrain, WSNs use significant numbers of wireless sensor nodes. The method of acquiring data from the sensor nodes and forwarding this data to the node or base station is Data Collection (DC). In such methods, data collection is effective and efficient in data transfer for an extended WSN lifetime. The scientific and investigational analysis demonstrated that Routing Path Selection-DC has the robustness and low energy, is required to reduce the mobile sink's energy demand, which provides better results, and is adaptable dynamically to multiple situations, including the variance between the ground robot and the cost of energy. The research paper developed an approach that creates a data collection schedule that is collision-free where appropriate power limits are allocated and verifies its overall performance of virtual environment network latency.Keywords: Wireless Sensor Network, Base station, Connection request, Data collection, Mobile elements, Collision-free, Latency
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