Current Issue : July-September Volume : 2023 Issue Number : 3 Articles : 5 Articles
Software-defined networking (SDN) is an evolving technology providing proper segregation between the control part and data-forwarding domain of network devices. The expansion of the Internet of Things (IoTs) and embedded mobile devices increases the volume of traffic at the network backbone and causes processing costs in the control plane. This directly affects the Ternary Content Addressable Memory (TCAM) of the switches because insufficient space makes it more challenging to manage the flow-entries. In this situation, providing services to specific users who newly authenticate after the successful handoff from the previous SDN domain is challenging. This paper proposes a method for implanting the users’ primary domain’s flow-rules in the serving SDN domain. As the TCAM is already suffering from a short space, it is hard to handle the flow-tables of multiple SDN domains in limited TCAM storage. The SDN-based Integration of the Interdomain Flow-rule in the SDN (IIF-SDN) scheme maximizes the proficiency of the switches by effectively storing flow-table and flow-entries. The effectiveness of the proposed scheme is benchmarked with proactive and reactive SDN approaches....
The defence-in-depth (DiD) methodology is a defensive approach usually performed by network administrators to implement secure networks by layering and segmenting them. Typically, segmentation is implemented in the second layer using the standard virtual local area networks (VLANs) or private virtual local area networks (PVLANs). Although defence in depth is usually manageable in small networks, it is not easily scalable to larger environments. Software-defined networks (SDNs) are emerging technologies that can be very helpful when performing network segmentation in such environments. In this work, a corporate networking scenario using PVLANs is emulated in order to carry out a comparative performance analysis on defensive strategies regarding CPU and memory usage, communications delay, packet loss, and power consumption. To do so, a well-known PVLAN attack is executed using simulated attackers located within the corporate network. Then, two mitigation strategies are analysed and compared using the traditional approach involving access control lists (ACLs) and SDNs. The results show the operation of the two mitigation strategies under different network scenarios and demonstrate the better performance of the SDN approach in oversubscribed network designs....
Wireless sensor networks (WSNs) are widely used in industrial applications. However, many of them have limited lifetimes, which has been a considerable constraint on their widespread use. As a typical application of WSNs, distributed measurement of the electric field under highvoltage direct-current (HVDC) transmission lines also suffers from this issue. This paper first introduces the composition of the electric-field measurement system (EFMS) and its working principle. Considering the actual power supply of the system, this paper mainly introduces the composition of the wireless sensor node (WSND) and analyzes the power consumption and potential working state transformation of the WSND, together with a comprehensive study on parameters affecting the power consumption of the wireless communication unit. Moreover, an energy-efficient scheduling approach is proposed after specially designing a working sequence and the study on system parameters. The proposed approach is verified by experiments on not only the experimental line of the national HVDC test base, but also a commercial operation HVDC transmission line with the challenge of long endurance, which is considered in this paper with a new strategy. The results show that the proposed method can greatly extend the lifetime of the WSND....
Monitoring and collecting medical data using embedded medical diagnostic devices with multiple sensors and sending these actual measured data to the corresponding health monitoring centers using multipurpose wireless networks to take necessary measures to coordinate with family medical service centers and regional medical service departments is a popular medical big data architecture. However, healthcare big data is characterized by large data volume, fast growth, multimodality, high value and privacy, etc. How to organize and manage it in a unified and efficient way is an important research direction at present. In response to the problems of low balance and poor security in the storage of data collected by distributed sensor networks in healthcare systems, we propose a distributed storage algorithm for big data in healthcare systems. The platform adopts Hadoop distributed file system and distributed file storage framework as the healthcare big data storage solution, and implements data integration, multidimensional data query and analysis mining components based on Spark-SQL data query tool, Spark machine learning algorithm library and its mining and analysis pipeline development, respectively. The distributed storage model of big data and three data storage levels are constructed using cloud storage architecture, and the data storage intensity as well as levels are calculated by high data access in the upper level, data connection in the middle level, and data archiving in the lower level according to the set known data granularity, odds, and elasticity to realize big data storage. It is experimentally verified that the above algorithm has high distribution balance and low load balance in the storage process....
Over the course of its long development, the modern educational technology curriculum has undergone several changes and amassed a lot of information. Theoretically speaking, the state places a strong priority on the use of IT in schools. Students majoring in education should take educational technology courses so that they can learn the characteristics and application techniques of core current information-based teaching media and incorporate them into their own lesson plans and classroom activities. This will help them meet the information needs of today’s classrooms as they evolve with the advent of educational modernization and availability of educational information. Thus, this research employs a wireless sensor network (WSN) to gather and send data on ed tech classes and then employs AI to assess those classes’ quality and guide real-time changes to how they are taught and complete the following tasks: (1) The development status of educational technology courses and WSN at home and abroad is introduced. (2) The application of WSN in teaching is introduced, the basic principle of GRU neural network and related optimization algorithms is expounded, and the quality evaluation system of educational technology courses is constructed. (3) The IPSO-Adam-GRU evaluation model improves the GRU neural network’s hyperparameters with the help of the improved PSO approach and Adam gradient descent. The model is fed test data for evaluation, and the findings are compared to those from an expert’s evaluation to determine how well the model performs. The results demonstrate that the model established for this article is superior to others since it provides a more accurate assessment....
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