Vijey Thayananthan

Efficient techniques of key management and quantum cryptography in RFID networks

An efficient way of handling security keys using quantum cryptography QC for increasing security in radio frequency identification RFID networks is being investigated by network security industries. To establish secure RFID network, communication between any two nodes that hold RFID tags and/or readers merged with existing networks should be protected. In order to maximize the data security and secure transmission around RFID network, theoretical model of the quantum key management KM system based on RFID is introduced as a proposed research. This model not only manages the secure keys but also it defends passive eavesdropping attacks and other potential attacks. Novelties in this research are security keys of which QC is being utilized in RFID network with continuous key updates. To establish future security around RFID networks, efficient KM protocol and QC, which deal with quantum mathematical procedures and quantum physics, should be analyzed without affecting the legacy. Computational complexities in KM are increasing with the large key sizes, which are manageable through QC. To maximize the security and minimize the complexity in KM, QC with Grovers algorithm is introduced as a method in RFID network environments. So, we have proved that a number of operations with key sizes obtained in KM are reduced. In this proposal, QC will help to reduce the complexity of algorithms used in KM protocols and maximize the security. Copyright

Analysis of round-robin load-balancing algorithm with adaptive and predictive approaches

An enormous increase in the number of internet users which will tend to rise further, cluster-based web servers (CBWS) are experiencing a dramatic increase in web traffic. Round-robin load-balancing algorithm (RLBA), is one of the most widely used for distributing loads among the web servers due to its simplicity. However, in the case of non-uniform web traffic, RLBA load distribution is inefficient. In this paper, we have developed novel approaches to optimize the RLBA with the necessary procedures. We propose Adaptive RLBA (ARLBA) and Predictive RLBA (PRLBA). We validate the effectiveness of algorithms through simulation results. Server load correlation and load variance are used as the performance measuring parameters. ARLBA and PRLBA outperform RLBA in all the cases. ARLBA performs slightly better than Modified round robin (MRR) and vice versa in case of PRLBA.

Analysis of Cybersecurity Based on Li-Fi in Green Data Storage Environments

Industrial networking has many issues based on the type of industries, data storage, data centers, and cloud computing, etc. Green data storage improves the scientific, commercial and industrial profile of the networking. Future industries are looking for cybersecurity solution with the low-cost resources in which the energy serving is the main problem in the industrial networking. To improve these problems, green data storage will be the priority because data centers and cloud computing deals with the data storage. In this analysis, we have decided to use solar energy source and different light rays as methodologies include a prism and the Li-Fi techniques. In this approach, light rays sent through the prism which allows us to transmit the data with different frequencies. This approach provides green energy and maximum protection within the data center. As a result, we have illustrated that cloud services within the green data center in industrial networking will achieve better protection with the low-cost energy through this analysis. Finally, we have to conclude that Li-Fi enhances the use of green energy and protection which are advantages to current and future industrial networking.

Saudi License Plate Recognition System Using Artificial Neural Network Classifier

Many areas include public transportation, hospitals and shopping mall use the computer technologies for security reasons. The need for integrating the technology with human needs is increased dramatically. Car license plate recognition is one of those technologies that help people to secure themselves from different attacks either attacks that affect their lives or their properties. There is an increasing demand for a car plate recognition system that can recognize the character in the Saudi plate specifically. Many challenges found in the Saudi license plate which make this a difficult task. Unlike other countries, Saudi plate has Arabic letters and numbers, English letters and numbers, horizontal and vertical lines and finally the logo and the abbreviation of Kingdom of Saudi Arabia. The aim of this paper is to design a system that could recognize the plate number efficiently. The bi-linear interpolation algorithm was used to resize the license plate image to have a fixed size of all license plates. After resizing the image, different preprocessing techniques were applied to remove the unnecessary parts. Finally, an Optical Character Recognition (OCR) that is based on Artificial Neural Network (ANN) classifier is used to recognize the characters. Matlab tool was used for designing and testing. Several experiments conducted to calculate the accuracy and show the efficiency of our design. The results show that our system has 92% accuracy and can recognize both Arabic and English letters and numbers.

Analytical Model of Enhancing Traffic Performance Based on Weighted Nodes

Existing networks deemed as complex system merged with many wireless communication networks. Traditional routing algorithm may not be sufficient to meet such complex data transmission from the source nodes to the sink nodes. Therefore, serious studying and investigation for traffic performance and congestion over complex networks seem to be an urgent challenge. Data propagation over complex networks without adopting a finest routing techniques might lead to more network congestion or deterioration in the worst case. Shortest path (SP) routing method has been widely used for its simplicity and efficiency. In this paper network performance based on SP, has been studied, investigated and evaluated. Therefore, we have proposed the new routing algorithm based on weighted nodes and paths. Our novel proposed algorithm proved its capability to preserve high throughput and low latency compared to the SP technique. Also, we have introduced the framework of applying differential evolution which enhances the overall performance of the complex networks.

Analytical Model of Energy Saving Approach in Wireless Sensor Network

Applications for wireless networks are increasing because basic facilities in our daily life are depending on modern communication networks which include routing protocols and energy efficient algorithms. Future Multiple-input, multiple-output (MIMO) wireless applications and research challenges related to energy saving are also considered in this research. In this research, we propose an energy saving model for future wireless applications based on wireless sensor network (WSN). This model can also be utilized to maximize the total energy efficiency (EE) in existing WSN and other wireless network. In this model, Pn-manifold will be used as a method, which helps us to minimize the dimensions of the channel matrix that uses in the MIMO system. Dimensions related to rank of the matrix control the energy of the WSN involved with MIMO communication. Manifolds are applied in MIMO system, which enhances the efficiency of communication channel. Also, it provides less energy consumption, which reduces the overall cost in energy saving model. Feedback and computation of quantization considered with Pn-manifold provides better results in the analytical analysis.

Information and Communication Technology (ICT) Applications for Customer Relationship Management (CRM)

Information and communication technology (ICT) being developed for the next generation is growing in many dimensions for customer relationship management (CRM) that is looking to enhance modern facilities with minimum cost and maximum security in network communications. The application of e-Health over the next-generation wireless network is considered to be a Millennium Development Goal (MDG). Future wireless systems and ICT facilities based on next-generation networked radio frequency identification (NGN-RFID) systems are very useful for the health MDG, which is approached through CRM values. In this research, we consider customer facilities, relationship and management techniques between healthcare management committees of particular healthcare businesses in profitable healthcare industries or the health MDG in nonprofit projects through a NGN-RFID system that collects and handles all data from the CRM. The purpose of this research is to analyze possible ICT applications based on an NGN-RFID system for CRM, which focuses on the satisfaction of customers who are loyal to healthcare agencies authorized by the United Nations (UN). CRM limitations of selected CRM values and their strategic approaches considered for health MDGs are also briefly discussed.

Traffic Predicting Model for Dynamic Spectrum Sharing Over 5G Networks

Recently, wireless networks and traffic requirements have been rapidly aggregated in diverse applications in 5G environments. For this reason, researchers have investigated the influences of this growth based on a user’s requirements inside these networks. However, the stream of traffic has been considered a crucial role for the user’s needs over 5G network. In this paper, gigantic data traffic is considered for enabling dynamic spectrum sharing over 5G networks. Thus, various accessing plans are covered to manage the overall network traffic. Additionally, it proposes a traffic predicting model for a technique of managing traffic when multiple requests are received to decrease delays. It has considered different significances related to a large size of traffic practices. Additionally, this work will guide us to enhance traffic solutions within massive requests over outsized networks. Systematically, it has focused on the traffic flow, starting from the accessing steps until passing on requests to suitable spectrum carriers.

Analytical Techniques for Decision Making on Information Security for Big Data Breaches

In the big data processes, management and analytics are primary areas where we can introduce the decision making on information security to mitigate the big data breaches. According to the growing number of online systems and big data handling, mitigating the big data breaches is the serious problem during the processing period which needs to be monitored using appropriate technique. The goal of this research is to prevent the big data breaches using correct decision making based on information security concepts such as access control with authentication which depend on the management policies. The analytical approach of information security solution can also be useful for securing the big data infrastructure and key management that improve the big data breaches. As an analytical method, information security which focuses on detecting and securing the big data breaches is considered with access control. Here, we have introduced the multi-priority model influenced with the network calculus and access control which monitors the breaches during the big data processing. In the results and analysis, we can provide a graph which shows the monitoring improvement for decision making during the mitigation of big data breaches.

Relevance of Energy Efficiency Gain in Massive MIMO Wireless Network

The massive MIMO and energy efficiency (EE) analysis for the next generation technology are the hottest topics in wireless network research. This paper explains about massive MIMO wireless networks and EE for manifold channel which is an evolution massive MIMO. This research will help to design and implement a practical system of next generation network based on massive MIMO where efficient processing provides EE gain. In order to approach this research, different types of manifolds are considered with efficient techniques that depend on the rank of the channel matrix. Employing the specific manifold that helps to analyze the rate of the feedback increases not only the overall performance of the MIMO system but also the EE. We studied the convergence techniques used for optimizing quantization errors which have influences with manifold feedback. Here, we have focused on relevant areas which are very important to analyze EE gain in the future massive network. According to the selected results obtained in this research, many challenges will be possible to make useful proposals.