Design and Analysis of Hybrid Software Defined Network System for Stability Enhancement

Software-defined networks (SDNs) facilitate more efficient routing when traffic flows using centralized network view. On the other hand, traditional distributed routing still has the advantage of better scalability, robustness, and swift reaction to events such as failure. Therefore significant potential benefits to adopt a hybrid operation where both distributed and centralized routing mechanisms co-exist. This hybrid operation however imposes a new challenge to network stability since a poor and inconsistent design can lead to repeated route switching when the two control mechanisms take turns to adjust the routes. In this paper, we discuss the ways of solving the stability problem. To develop the stable networking environment three tire routing architecture is proposed. The router stability is enhanced and speed of data transfer is high in this proposed system. The router will analyze the network traffic that occurs during the data transfer and redirect to the other router. The algorithms used in this proposed systems are Support vector machine algorithm and Multilayer perception algorithm. The stability of a hybrid-software defined network involves the consistency between the centralized routing performed by the centralized controller and the distributed routing performed by the individual local routers. If these two control units are not consistent with each other, the routing decision may be overturned repeatedly as they take turns to modify the routes. &nbsp

The Future of Artificial Intelligence with Respect to Society: A Comprehensive Review

Artificial Intelligence (AI) is still in its infancy but continues to bring tremendous benefits to human life and may well prove to be the most powerful technology ever invented. It has played a vital role in our society and has transformed lifestyle of humans to a massive extent. It has the potential to transform health sector, increase productivity, can play a major role in saving environment and enhance both freedom and democracy. In recent past the AI has penetrated into human’s life to a greater extent. Although this penetration has impacted into positive and negative ways on society but, this current era of Digitization can’t survive without adopting AI tools and technologies in solving highly complex and diverse societal problems. Presently, the dependency of humans on AI system has increase manifold and in near future the society may leads to explainable AI, where there are chances for every human activity to be controlled by machines. In this paper, we begin with a general introduction to the field of artificial intelligence, then progress to exploring the subsets of AI and examine their practical applicability with respect to different domains of society followed by Impactful Evaluation where the positive influence of AI in different fields has been explored. Lastly, the focus has been paid to Critical Evaluation in which the negative consequences and various challenges associated with AI has been paid attention. In conclusion, several recommendations for AI systems and their associated applications have been made to enhance its applicability in the society. &nbsp

Application of Shell Model Calculations with Modified Surface Delta Interaction For the Two Nuclei

By applying Shell model with Modified Surface Delta Interaction on Tellurium nucleus and Tin nucleus , that have two valence nucleons outside the closed core , we obtained the values of the energy levels and excitation energies of the two nuclei, after determining the value of the two constants and for Modified Surface Delta Interaction by least square fitting method. When we comparing the value of standard deviation of our calculated excitation energies with some previous studies calculated in different ways, we found that nucleus shows good agreement with experimental values compared to these studies, while nucleus does not show a good agreement. Therefore the application of the Shell model with Modified Surface Delta Interaction, in its present form, on nuclei whose valence nucleons are located after the magic number N = 82, needs to be modified, such as taking into account the excitation closed core and configuration mixing. &nbsp

A Comparative Study Between RIPEMD160 and SHA256 Hash Functions On Digital Holy Quran Integrity Verification

In Data Security and Cryptography areas, hash functions play a fundamental and important role in the field of Integrity, This paper presents a performance evaluation of two cryptographic hash functions SHA256 and RIPEMD160 which used to verify the integrity of digital holy Quran and determine which one is better. SHA256 and RIPEMD160 hash functions have been selected in this comparison because their characteristics speed and space characteristics, both hash functions have their own advantages and disadvantages what distinguishes them from others, which will be discuss in detail in Background section. This study focuses on security and performance analysis. Security analysis where many experiments be applied to find out the strength and effectiveness of each two hash functions and hash collisions be analysed. The performance analysis will be applied by measuring the speed of the proposed methods in this study. The results show that the RIPEMD160 hash function is faster than SHA256 hash function for the integrity verification on a digital copy of the Holy Quran. &nbsp

HARQ Scheme for different MCS users over LTE and LTE-Advanced Networks

In Long Term Evolution (LTE) and LTE-Advanced networks, due to multifold data traffic growth and unpredictable variation in the received signal strength, there is no guarantee for successful reception of data packets without any error. This becomes a challenging task for Mobile Network Operators (MNOs) to support more reliable data transmissions over the network. The LTE and LTE-Advanced networks uses Hybrid Automatic Repeat reQuest (HARQ) scheme to recovery of error data packets, however the received signal strength may vary from QPSK to 64QAM regions. Therefore the performance evaluation of different Modulation and Coding Scheme (MCS) users such as QPSK, 16QAM and 64QAM for different HARQ retransmissions under different data traffic condition is vital for MNOs to predict the per user throughput and recovery of error data packets of different MCS users for different HARQ retransmissions. Hence in this paper using QualNet 8.2 network simulator, the attempt has been made to study the performance of different MCS users for different HARQ retransmissions under different data traffic scenarios. Simulation results show that the data packets received with error are less as the cell load is within its capacity and less HARQ retransmissions are sufficient to recovery of error data packets, whereas in higher data traffic scenarios, for data intensive services maximum HARQ retransmissions are vital to fulfil QoS requirements. &nbsp

Implementation of Intrusion Detection and Prevention System Based on Software Approachs

The detection of security vulnerabilities is ever more difficult as cyber-attacks get more complicated. The faith in security services like data confidentiality and integrity is eroded by a failure to prevent security breaches. The literature has suggested a number of intrusion detection techniques to counter computer security risks. This effort aims to create an intrusion detection and prevention system, or "IDPS,” An integrated system that maximizes each factor`s advantages while reducing its disadvantages is the proposed solution for intrusion prevention. By demonstrating how attackers can elude detection. The outcome of this research is a security system that can recognize attack attempts, block the IP address of the attacker, and carry out network forensic investigations. According to the findings of our study, Snort the IPS mode in PfSense, can identify assaults aimed at your system, and PfSense, having visualization capability, immediately implements preventive actions by blocking the attacker`s IP address. Network forensics can use this method to conduct an investigation into an attack and determine whether the attack is having a negative impact based on the alarms produced by the snort. It also sheds light on potential future research challenges to stop these attacks and strengthen computer systems` security. &nbsp

Application of Adaptive Neuro-Fuzzy Inference Systems in Mobile’s Spam

The function of science is to explain reality logically. With the increased usage of the internet, spamming is the most typical problem that we faced every day. Service of mailing and web applications are much spammed, nowadays this expansion in the number of spam messages has turned into a significant issue. Accessibility of messaging services for a minimal price has come about in the expansion of spam messages. Spam location is attempting a direct result of the necessity for semantic analysis of the compact spam messages, which overall will for the most part have overlapping polarities. In this work, a portable spam order strategy is created in light of an Adaptive Neuro Inference System(ANFIS) containing Gini record fuzzy and Back-Propagation in machine learning. The methodology includes Gini’s index models for information indexes and a back-propagation-based neural network as the AI classifier. This paper presents the assessment of the introduced system based on the error, accuracy of classification, and the number of iterations. &nbsp

Optimizing Resource Utilization in Cloud Networks: An Analysis of VM Selection and Placement Policies

Cloud computing enables on-demand computing, providing users with elastic resources on a pay-as-you-go basis. The proliferation of data-driven applications and services has led to increased demand for computational resources, prompting the deployment of large data centers that consume significant amounts of energy and emit CO2 into the environment. As VM placement and selection significantly impact energy consumption, this paper explores various benchmark algorithms for VM selection and placement policies, evaluating their performance based on SLA violations, energy consumption, and the number of migrations. The study utilizes the cloudsim toolkit and analyzes real workloads from the CoMon project. &nbsp

Optimizing and Enhancing Performance Classification Algorithm on Heart Disease through Feature Selection

The ever-increasing size of datasets in the Big Data era requires effective methods for extracting meaningful information. Data Mining provides a means to analyze large datasets and uncover valuable patterns that can inform future decisions. In this study, we analyze a healthcare dataset of heart diseases to predict the likelihood of a patient having a heart disease based on specific parameters. To accomplish this, we implement decision tree classification algorithms such as ADTree, J48, and RandomForest. Additionally, a feature selection algorithm is applied to remove the least significant three attributes from the dataset, resulting in improved classification performance. Comparing the previous and current results reveals the effectiveness of this approach in enhancing the classification accuracy. &nbsp

Design of an IoT-based management and monitoring system for intelligent irrigation

Agriculture plays a major role in the world economy and most people depend on it for their livelihood. This makes water an important resource that must be conserved using the latest available technologies. Today, the Internet of Things has expanded its capabilities to smart agriculture. In this research, an automated and low-cost system for intelligent irrigation based on a fuzzy-based energy-aware routing approach is presented. In addition, a neural network is trained to determine the best irrigation program, based on information received from sensors (such as temperature, soil moisture, etc.). The user in the system can monitor the data collection process with mobile phones, mobile computers, etc. and manage the irrigation of agricultural products. The proposed system proves its intelligence, low cost and portability, its suitability for greenhouses, farms, etc. The simulation results show that the proposed method offers better results compared to the LEACH protocol as well as the WSN-IoT algorithm in various criteria such as grid life and power consumption &nbsp