أثبتت الشبكات المحددة بالبرمجيات (SDN) تفوقها في معالجة مشاكل الشبكة العادية مثل قابلية التوسع وخفة الحركة والأمن. تأتي هذه الميزة من SDN بسبب فصل مستوى التحكم عن مستوى البيانات. على الرغم من وجود العديد من الأوراق والدراسات التي تركز على إدارة SDN، والرصد، والتحكم، وتحسين QoS، إلا أن القليل منها يركز على تقديم ما يستخدمونه لتوليد حركة المرور وقياس أداء الشبكة. كما أن المؤلفات تفتقر إلى مقارنات بين الأدوات والأساليب المستخدمة في هذا السياق. تقدم هذه الورقة كيفية محاكاة إحصاءات المرور وتوليدها والحصول عليها من بيئة SDN. وبالإضافة إلى ذلك، تعالج المقارنة بين الأساليب المستخدمة في جمع بيانات شبكة المعرفة برمجياً لاستكشاف قدرة كل طريقة، وبالتالي تحديد البيئة المناسبة لكل طريقة. تمت محاكاة اختبار SDN باستخدام برنامج Mininet مع طوبولوجيا الأشجار ومفاتيح OpenFlow. تم توصيل وحدة تحكم RYU بإرسال التحكم. تُستخدم الأدوات الشهيرة iperf3 و ping و python scripts لجمع مجموعات بيانات الشبكة من عدة أجهزة في الشبكة. تم استخدام Wireshark وتطبيقات RYU وأمر ovs-ofctl لمراقبة مجموعة البيانات المجمعة. تظهر النتائج نجاحًا في إنشاء عدة أنواع من مقاييس الشبكة لاستخدامها في المستقبل لتدريب الآلة أو خوارزميات التعلم العميق. وخلصت إلى أنه عند توليد البيانات لغرض التحكم في الازدحام، فإن iperf3 هو أفضل أداة، في حين أن ping مفيد عند توليد البيانات لغرض الكشف عن هجمات DDoS. تعد تطبيقات RYU أكثر ملاءمة للاستفسار عن جميع تفاصيل طوبولوجيا الشبكة نظرًا لقدرتها على عرض الطوبولوجيا وخصائص التبديل وإحصائيات التبديل. كما تم استكشاف العديد من العقبات والأخطاء وإدراجها ليتم منعها عندما يحاول الباحثون إنشاء مجموعات البيانات هذه في جهودهم العلمية التالية.
There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn
In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
Reliable data transfer and energy efficiency are the essential considerations for network performance in resource-constrained underwater environments. One of the efficient approaches for data routing in underwater wireless sensor networks (UWSNs) is clustering, in which the data packets are transferred from sensor nodes to the cluster head (CH). Data packets are then forwarded to a sink node in a single or multiple hops manners, which can possibly increase energy depletion of the CH as compared to other nodes. While several mechanisms have been proposed for cluster formation and CH selection to ensure efficient delivery of data packets, less attention has been given to massive data co
Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b
... Show MoreToday, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int
... Show MoreA true random TTL pulse generator was implemented and investigated for quantum key distribution systems. The random TTL signals are generated by low cost components available in the local markets. The TTL signals are obtained by using true random binary sequences based on registering photon arrival time difference registered in coincidence windows between two single – photon detectors. The true random TTL pulse generator performance was tested by using time to digital converters which gives accurate readings for photon arrival time. The proposed true random pulse TTL generator can be used in any quantum -key distribution system for random operation of the transmitters for these systems
An experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of yield and its components in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1 = cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses) by using RCBD with three repl
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