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.
The objective of this paper is, first, study a new collection of sets such as field and we discuss the properties of this collection. Second, introduce a new concepts related to the field such as measure on field, outer measure on field and we obtain some important results deals with these concepts. Third, introduce the concept of null-additive on field as a generalization of the concept of measure on field. Furthermore, we establish new concept related to - field noted by weakly null-additive on field as a generalizations of the concepts of measure on and null-additive. Finally, we introduce the restriction of a set function on field and many of its properties and characterizations are given.
This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
... Show MoreEverybody is connected with social media like (Facebook, Twitter, LinkedIn, Instagram…etc.) that generate a large quantity of data and which traditional applications are inadequate to process. Social media are regarded as an important platform for sharing information, opinion, and knowledge of many subscribers. These basic media attribute Big data also to many issues, such as data collection, storage, moving, updating, reviewing, posting, scanning, visualization, Data protection, etc. To deal with all these problems, this is a need for an adequate system that not just prepares the details, but also provides meaningful analysis to take advantage of the difficult situations, relevant to business, proper decision, Health, social media, sc
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreThe deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m
... Show Morehe Orthogonal Frequency Division Multiplexing is a promising technology for the Next Generation Networks. This technique was selected because of the flexibility for the various parameters, high spectral efficiency, and immunity to ISI. The OFDM technique suffers from significant digital signal processing, especially inside the Inverse/ Fast Fourier Transform IFFT/FFT. This part is used to perform the orthogonality/De-orthogonality between the subcarriers which the important part of the OFDM system. Therefore, it is important to understand the parameter effects on the increase or to decrease the FPGA power consumption for the IFFT/FFT. This thesis is focusing on the FPGA power consumption of the IFFT/FFT uses in the OFDM system. This researc
... Show More