To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management.
Streamlined peristaltic transport patterns, bifurcations of equilibrium points, and effects of an inclined magnetic field and channel are shown in this study. The incompressible fluid has been the subject of the model's investigation. The Reynolds values for evanescence and an infinite wavelength are used to constrain the flow while it is being studied in a slanted channel with a slanted magnetic field. The topologies over their domestic and cosmopolitan bifurcations are investigated for the outcomes, and notion of the dynamical system are employed. The Mathematica software is used to solve the nonlinear autonomous system. The flow is found to have three different flow distributions namely augmented, trapping and backward flow. Outc
... Show MoreThe human perception of science and knowledge is affected by the personal point of view, thus giving it its religious, mental and emotional dimensions to make that perception an effective tool for realizing the truth comprehensively in the delivery of knowledge to the depths of the human soul. The later is composed of multiple factors, which contributes to the human self-development with dimensions beyond the limits of mental logic and the perception of material and emotional situations. That knowledge in the perception of Islamic virtue, which must characterize each Muslim.
Human beings have been striving for knowledge and the understanding of the universe in which they live. For centuries, mankind has acquired knowledge directly an
The public budget is regarded a main tool for economic and social development. The preparation of the public budget constitute an important stream which enriches the developmental efforts and the definition of its priorities, therefore it is the focus point of many specializations. The public budget has numerous functions. It is a means to precise and to execute the political and economic goals of the executive authority, a mirror of the economic structure which reflects its strength and weakness points, specifies its revenues and others. Since the parliament is the voice of the society which expresses its interests, then, it must monitor the performance of the government so that the participation of the legislative authority in
... Show MoreIt is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological
... Show MoreSensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
... Show MoreLocalization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo
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