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A Survey of Traditional and Cloud Specific Security Issues
The emerging technology popularly referred to as Cloud computing offers dynamically scalable computing resources on a pay per use basis over the Internet. Companies avail hardware and software resources as service from the cloud service provider as opposed to obtaining physical assets. Cloud computing has the potential for significant cost reduction and increased operating efficiency in computing. To achieve these benefits, however, there are still some challenges to be solved. Security is one of the prime concerns in adopting Cloud computing, since the user's data has to be released from the protection sphere of the data owner to the premises of cloud service provider. As more Cloud based applications keep evolving, the associated security threats are also growing. In this paper an attempt has been made to identify and categorize the security threats applicable to Cloud environment. Threats are classified into Cloud specific security issues and traditional security attacks on various service delivery models of Cloud. The work also briefly discusses the virtualization and authentication related issues in Cloud and tries to consolidate the various security threats in a classified manner. Springer-Verlag Berlin Heidelberg 2013. -
A Survey on 5G Standards, Specifications and Massive MIMO Testbed Including Transceiver Design Models Using QAM Modulation Schemes
Massive MIMO (Multiple Input Multiple Output)is the advanced technology in 5G architecture which improves mobile and data wireless system parameters in multiple folds. The basic idea of this technology is to include huge number of antennas in the base stations serving limited user equipment. This will enhance the parameters like spectral efficiency, data rate, wireless devices connectivity, energy or power efficiency and also, significant reduction in interference and error rates. The Third Generation Partnership Project (3GPP)consortium, International Mobile Telecommunication (IMT)and various partner telecom companies are on the way to develop unified architecture to meet the proposed 5G standards by the year 2020. Initial test beds and field-trials are already in process at various universities and telecom companies considering Long Term Evolution (LTE)releases features in the 5G architecture framework. However, the research is still an open issue on improving the parameters. This research paper provides a detailed overview on 5G standards, specifications and Field trials and test beds implemented by various universities and telecom industry utilizing Massive MIMO technology. This literature survey paper aims to enlighten the researchers working in the area of Massive MIMO to understand the test bed and field trials designs existing till date. This paper also motivates to complete experiments on Bit error rate (BER)estimation in various modulation schemes for single transmitter-receiver as well as in MIMO configuration. The reduction in BER is observed when MIMO models are used for transceiver design. The hardware utilization and simulation work of the field trials and testbed provide different existing techniques to develop a transceiver system which meets 5G standard. 2019 IEEE. -
A Survey on Adaptive Authentication Using Machine Learning Techniques
Adaptive authentication is a reliable technique to dynamically select the best mechanisms among multiple modalities to authenticate a user based on the users risk profile generated using behavior and context-based information. Websites or enterprise applications enabled with adaptive authentication will have a more robust security system as analyzing the large volume of the user, device, and browser data in real time generates a risk score that decides the appropriate level of security. Though a significant amount of research is being carried out on adaptive authentication, no single model is suitable for a global attack. This paper provides a structured (extensive) survey of current adaptive authentication techniques available in the literature to identify the challenges which demand future research. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Survey on Arrhythmia Disease Detection Using Deep Learning Methods
The Cardiovascular conditions are now one of the foremost common impacts on human health. Report from WHO, says that in India 45% of deaths are caused due to heart diseases. So, heart disease detection has more importance. Manual auscultation was used to diagnose cardiovascular problems just a few years ago. Nowadays computer-assisted technologies are used to identify diseases. Accurate detection of the disease can make recovery simpler, more effective, and less expensive. In this proposed work, 11years of research works on arrhythmia detection using deep learning are integrated. Moreover, here presents a comprehensive evaluation of recent deep learning-based approaches for detecting heart disease. There are a number of review papers accessible that focus on traditional methods for detecting cardiac disease. This article addresses some essential approaches for categorizing ECG signal images into desired classes, such as pre-processing, feature extraction, feature selection, and classification. However, the reviewed literatures consolidated details have been summarized. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A survey on artificial intelligence for reducing the climate footprint in healthcare
The primary mission of the healthcare sector is to protect from various ailments with improved healthcare services and to use advanced diagnostic solutions to promote reliable treatments for complex diseases. However, healthcare is among the significant contributors to the current climate crisis. Therefore, research is underway to identify various measures to reduce the emissions from advanced healthcare systems. Modern healthcare facilities invest significantly in renewable energy, efficient energy solutions, and intelligent climate cooling and control technologies. Furthermore, innovative technologies like artificial intelligence (AI) are proposed to enable automation for patient health monitoring. With the advances in AI, there are green AI goals for potentially reducing emissions through data-driven and well-optimized models for healthcare. Furthermore, novel machine learning and deep learning techniques are continually proposed for improved efficiency to reduce emissions. Therefore, the scope of the research is to review the potential of AI in healthcare for lowering emission rates and its methodologies, current approaches, metrics, challenges, and future trends to attain a straightforward pathway. 2022 -
A Survey on Domain-Specific Summarization Techniques
Automatic text summarization using different natural language processing techniques (NLP) has gained much momentum in recent years. Text summarization is an intensive process of extracting representative gist of the contents present in a document. Manual summarization of structured and unstructured text is a tedious task that involves immense human effort and time. There are quite a number of successful text summarization algorithms for generic documents. But when it comes specialized for a particular domain, the generic training of algorithms does not suffice the purpose. Hence, context-aware summarization of unstructured and structured text using various algorithms needs specific scoring techniques to supplement the base algorithms. This paper is an attempt to give an overview of methods and algorithms that are used for context-aware summarization of generic texts. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Survey on Enhancing System Performance of Wireless Sensor Network by Secure Assemblage Based Data Delivery
To provide secure data transmission in Cluster Wireless Sensor Networks (CWSNs), the challenging task is to provide an efficient key management technique. To enhance the performance of sensor networks, clustering approach is used. Wireless Sensor Network (WSN) comprises of large collection of sensors having different hardware configurations and functionalities. Due to limited storage space and battery life, complex security algorithms cannot be used in sensor networks. To solve the orphan node problem and to enhance the performance of the WSN, authors introduced many secure protocols such as LEACH, Sec-LEACH, GS-LEACH and R-LEACH, which were not secure for data transmission. The energy consumption in existing approach is more due to overhead incurred in computation and communication in order to achieve security. This paper studies about different schemes used for secure data transmission. We are proposing new methodology called IBDS and EIBDS that will increase the performance of WSN by reducing computational overhead and also increases resilience against the adversaries. 2017 IEEE. -
A Survey on Feature Selection, Classification, and Optimization Techniques for EEG-Based BrainComputer Interface
In braincomputer interface (BCI) systems, the electroencephalography (EEG) signal is extensively utilized, as the recording of EEG brain signals is having relatively low cost, the potentiality for user mobility, high time resolution, and non-invasive nature. The EEG features are extracted by the BCI to execute commands. In the feature set obtained, the computational complexity increases, and poor classifier generalization can be caused by the utilization of a lot of overlapping features. The irrelevant features accumulation could be avoided with the feature selection procedures application. The feature selection algorithms are utilized to select diverse features for each classifier. Classifiers are the algorithms that are run to attain the classification. The researchers have examined diverse classifier implementation techniques to identify the feature vectors class. A review of EEG-BCI techniques available in the literature for feature selection, classifiers, and optimization algorithms is presented in this work. The research challenges, gaps, and limitations are identified in this paper. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A survey on next-generation mixed line rate (MLR) and energy-driven wavelength-division multiplexed (WDM) optical networks
With the ever-increasing traffic demands, infrastructure of the current 10 Gbps optical network needs to be enhanced. Further, since the energy crisis is gaining increasing concerns, new research topics need to be devised and technological solutions for energy conservation need to be investigated. In all-optical mixed line rate (MLR) network, feasibility of a lightpath is determined by the physical layer impairment (PLI) accumulation. Contrary to PLI-aware routing and wavelength assignment (PLIA-RWA) algorithm applicable for a 10 Gbps wavelength-division multiplexed (WDM) network, a new Routing, Wavelength, Modulation format assignment (RWMFA) algorithm is required for the MLR optical network. With the rapid growth of energy consumption in Information and Communication Technologies (ICT), recently, lot of attention is being devoted toward "green" ICT solutions. This article presents a review of different RWMFA (PLIA-RWA) algorithms for MLR networks, and surveys the most relevant research activities aimed at minimizing energy consumption in optical networks. In essence, this article presents a comprehensive and timely survey on a growing field of research, as it covers most aspects of MLR and energy-driven optical networks. Hence, the author aims at providing a comprehensive reference for the growing base of researchers who will work on MLR and energy-driven optical networks in the upcoming years. Finally, the article also identifies several open problems for future research. 2015 by De Gruyter. -
A survey on next-generation Mixed Line Rate (MLR) and energy-driven Wavelength-Division Multiplexed (WDM) optical networks /
Journal of Optical Communications, Vol.36, Issue 2, pp.516-532, ISSN No: 2191-6322. -
A Survey on P4 Challenges in Software Defined Networks: P4 Programming
Software Defined Networking (SDN) has been a prominent technology in the last decade that increases networking programmability. The SDN philosophy decouples the application, control, and data plane to increase the network programmability. The data plane is an essential but unsolved component that receives less attention than control and application planes. Traditionally, the data plane uses fixed functions that forward packets using a limited number of protocols. The P4 (Programming Protocol-independent Packet Processors) language makes it possible to program SDN data plane, which push the SDN to the next level. In the research community and industry, programming the data plane has garnered significant attention. Surprisingly, there has been no comprehensive reviews of programmable data-plane switches, which have many advantages in today's networks. The authors reviewed the evolution of networks from legacy to programmable data planes, explained the fundamentals of programmable switches, and summarized the network generation from traditional to programmable networks. In this paper, SDN is described from a P4-centric standpoint and discusses over 75 related research papers. Several taxonomies for the field are provided, outline potential research areas, and provide greater details regarding the patterns that have led to the development of this technology. 2013 IEEE. -
A Survey on Solution of Imbalanced Data Classification Problem Using SMOTE and Extreme Learning Machine
Imbalanced data are a common classification problem. Since it occurs in most real fields, this trend is increasingly important. It is of particular concern for highly imbalanced datasets (when the class ratio is high). Different techniques have been developed to deal with supervised learning sets. SMOTE is a well-known method for over-sampling that discusses imbalances at the level of the data. In the area, unequal data are widely distributed, and ensemble learning algorithms are a more efficient classifier in classifying imbalances. SMOTE synthetically contrasts two closely connected vectors. The learning algorithm itself, however, is not designed for imbalanced results. The simple ensemble idea, as well as the SMOTE algorithm, works with imbalanced data. There are detailed studies about imbalanced data problems and resolving this problem through several approaches. There are various approaches to overcome this problem, but we mainly focused on SMOTE and extreme learning machine algorithms. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A survey on the intersection graphs of ideals of rings
Let L(R) denote the set of all non-trivial left ideals of a ring R. The intersection graph of ideals of a ring R is an undirected simple graph denoted by G(R) whose vertices are in a one-to-one correspondence with L(R) and two distinct vertices are joined by an edge if and only if the corresponding left ideals of R have a non-zero intersection. The ideal structure of a ring reects many ring theoretical properties. There is so much research that has been conducted during the last decade to explore the properties of G(R). This is a survey of the developments in the study on the intersection graphs of ideals of rings since its introduction in 2009. 2022 by the authors. -
A survey on various applications of internet of things on blockchain platform
[No abstract available] -
A Survey on Various Handoff Methods in Mobile Ad Hoc Network Environment
Communication has never been the same since the advent of cellular phones and numerous applications with different functionalities seem to crop up on a daily basis. Various applications seem to crop up on a daily basis. Ad hoc networks were developed with the intent of creating networks made up of interconnected nodes, on-the-go. Ad hoc networks have numerous applications, the most popular being vehicular ad hoc networks (VANETs). In VANETs, moving vehicles are considered to be the mobile nodes and mobile vehicular nodes move at high speeds. Mobility of the nodes makes it difficult to maintain stable communication links between the nodes and the access points. A process known as handoff is used to bridge this gap and is considered to be one of the solutions for unstable communication links over larger distances. Handoff can usually be seen when the nodes are mobile and start to move away from the access points. This paper discusses and compares various handoff methods that were proposed by various researchers with an intent to increase positive attributes while negating the rest of the components that do not support in increasing the efficiency of the handoff process. 2020, Springer Nature Singapore Pte Ltd. -
A Sustainability Approach to Geopolymer Brick Manufacture Using Mine Wastes
India has tons of by-products of industries like fly ash, ground granulated blast furnace slag (GGBS), and mine tailings from different ores. By incorporating these wastes in bricks, the carbon footprint can be minimized. This research pivots around the use of iron ore tailings (IOT) and slag sand as a substitute for clay or shale in the manufacture of stabilized geopolymer blocks. Iron ore tailings and slag sand were used for substitution in the range of 20-40% and 15-40% with increments of 5%. Fly ash, ground granulated blast furnace slag, and sodium silicates (Na2SiO3) were used with a constant value of 15%. The bricks were cast and cured at ambient temperature. The study includes testing of mechanical properties of geopolymer bricks as per IS recommendations. To study the macroanalysis, SEM and XRD analyses were also carried out on raw materials and developed composites. The outcomes of this investigation show that the inclusion of 25% of IOT and 30% of slag sand is acceptable as brick material. Springer Nature Singapore Pte Ltd. 2022. -
A sustainable approach for fish waste valorization through polyhydroxyalkanoate production by Bacillus megaterium NCDC0679 and its optimization studies
Polyhydroxyalkanoates (PHAs) are considered as the only class of truly biodegradable and biocompatible polymers. Although extensive research has been carried out in producing them from a wide variety of organisms, their commercialization still faces hurdles majorly associated with the cost of production media. This research work exploits the use of discarded fish scale waste as a major media component for biopolymer production. The major novelty of the research work is the utilization of a Bacillus megaterium NCDC0679 for PHA production using fish scale waste that is not reported previously. Furthermore, a sequential and systematic statistical optimization strategy employing response surface methodology was used to trace out the level of the most significant variables and their interaction effects on PHA production add to the significant novelty of this work. The significance of the model developed was determined from the p values of ANOVA. Under optimized levels of glucose (50g/L), NaCl (0.125g/L), and fish scale hydrolysate concentration (62.5% v/v), maximum PHA yield of 6.33g/L was achieved in the shake flask culture system. This was found to be 5.50-fold higher than the unoptimized medium. The ANOVA results established the significance of the model (p < 0.05). The extracted polymer was characterized through Fourier-transform infrared (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Thus, the present investigation suggests an innovative method for valorization of fish scale waste for commercial production of PHA. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
A sustainable approach for fish waste valorization through polyhydroxyalkanoate production by Bacillus megaterium NCDC0679 and its optimization studies
Polyhydroxyalkanoates (PHAs) are considered as the only class of truly biodegradable and biocompatible polymers. Although extensive research has been carried out in producing them from a wide variety of organisms, their commercialization still faces hurdles majorly associated with the cost of production media. This research work exploits the use of discarded fish scale waste as a major media component for biopolymer production. The major novelty of the research work is the utilization of a Bacillus megaterium NCDC0679 for PHA production using fish scale waste that is not reported previously. Furthermore, a sequential and systematic statistical optimization strategy employing response surface methodology was used to trace out the level of the most significant variables and their interaction effects on PHA production add to the significant novelty of this work. The significance of the model developed was determined from the p values of ANOVA. Under optimized levels of glucose (50g/L), NaCl (0.125g/L), and fish scale hydrolysate concentration (62.5% v/v), maximum PHA yield of 6.33g/L was achieved in the shake flask culture system. This was found to be 5.50-fold higher than the unoptimized medium. The ANOVA results established the significance of the model (p < 0.05). The extracted polymer was characterized through Fourier-transform infrared (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Thus, the present investigation suggests an innovative method for valorization of fish scale waste for commercial production of PHA. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. -
A sustainable approach to cloud computing: A comprehensive analysis of load balancing techniques in cognitive environments
Cloud computing is one of the rising eras in big-scale computing, where information is processed in big information centers. One of the demanding situations with that is to accomplish load balancing of all the nodes. In addition, it's essential for proper utilization of assets and division of the work. This indicates that effective allocation and usage of the computing resources among clients in sharing mode leads to satisfactory users as well as good utilization of resources. Balancing the load in huge data-centric systems and networks is required to achieve the stated goal. The load balancing problem is considered as an optimization problem, and the rules for a load provide the number of compensations (scalability enabling, bottleneck avoidance) and resource consumption. A number of proposed algorithms exist for the load balancing problem in the cloud environment. Efforts have been made in this chapter to examine and review a few of the weight balancing algorithms in cloud computing. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors. -
A Sustainable Business Model for Converting Construction and Demolition Waste to Wealth
India's rapid urbanisation necessitates a planning approach that ensures the sustainability of its cities through efficient waste management. This swift urban growth has significantly accelerated modern construction and demolition of older infrastructure or structures within Indian cities. C&D (Construction and Demolition) waste is accountable for approximately 30 percent of urban municipal waste within metropolitan areas. Managing C&D waste and transforming it into valuable resources presents considerable challenges for all urban local bodies (ULBs). Recycling C&D waste offers dual benefits: it reduces pressure on the extraction of virgin construction materials and helps mitigate environmental pollution. Recycled C&D waste can produce various valuable products, including aggregates of different sizes, manufactured sand, paver blocks, concrete bricks, double-tee precast panels for boundary walls, manhole covers, water tanks, and more. These products are durable and eco-friendly building materials that contribute to the conservation of natural resources. However, a sustainable business model is essential for understanding the volume of C&D waste produced and for addressing current challenges and opportunities at the city, regional, and state levels. The current research aims to gather information about the overall scenario of C&D waste management procedures in India, relying on secondary resources. It proposes a sustainable business model for C&D waste handling that transforms this specific waste into a valuable resource, identifying possible advantages and the resource efficiency of recycled items. permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.