Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they account for the vast bulk of traffic in data center networks. The incorrect use of network resources by EFs frequently disturbs the performance of MFs. To meet these issues, precise classification of network traffic has become crucial. This classification enables traffic-aware routing techniques. This paper offers a novel model for classifying SDN traffic into MF and EF using a spike neural network. Once identified, traffic is routed based on the classification results. For MF, the model uses the Dijkstra algorithm. For EF, the Widest Dijkstra algorithm is used. This model solves the difficulties of traffic heterogeneity in SDNs by integrating advanced classification techniques and strategic routing algorithms. It enables desirable resource allocation, eliminates congestion, and increases network performance and dependability. The models used have proven their efficiency by outperforming the traditional Software Defined Network and other algorithms in terms of: throughput by 60%, and 20%, bandwidth utilization by 5%, and 7%, packet loss by 50%, and latency by 60%, respectively.
ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreThe important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi
... Show MoreGoal of research is to investigate the impact of the use of effective learning model in the collection of the fourth grade students/Department of physics in the material educational methods and the development of critical thinking .to teach this goal has been formulated hypothesis cefereeten zero subsidiary of the second hypothesis .To investigate the research hypothesis were selected sample of fourth-grade students of the department of physics at the univers
... Show MoreThe research has been based on two main variables (information and communication technology) and the quality of blended education (physical and electronic), aiming to reveal the relationship between four dimensions (physical devices, software, databases, communication networks) and the elements of education represented by (the teacher, the student, the teaching process, curriculum). The methodology and post-analysis-based research were conducted at the Technical College of Management / Baghdad through polling the opinions of a random sample that included (80) teachers out of (86) and the number of students (276) representing a random sample from all departments of the college (for the morning study) out of (3500) stud
... Show MoreAnalyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col
... Show MoreSentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
... Show MoreAs a reservoir is depleted due to production, pore pressure decreases leading to increased effective stress which causes a reduction in permeability, porosity, and possible pore collapse or compaction. Permeability is a key factor in tight reservoir development; therefore, understanding the loss of permeability in these reservoirs due to depletion is vital for effective reservoir management. The paper presents a case history on a tight carbonate reservoir in Iraq which demonstrates the behavior of rock permeability and porosity as a function of increasing effective stress simulating a depleting mode over given production time. The experimental results show unique models for the decline of permeability and porosity as function effective str
... Show MoreThe problems of urban historic centers are considered some of the subjects which are widely dealt with in urban studies since the middle of the 20th century. literature of urban development have raised it , beside the fact that large number of urban development projects of the historical centers in many cities of the world ,and emerged from the application of these new problems projects added their original urban problems , because these projects have dealt with the physical structures with the neglect of the social and economic sides, which are the base in sustainable development nResearch problem was elaborated as : The unclearly of knowledge of the potentials of the sustainable development in solving the urban problems of historic cen
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