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Emergence of cloud computing as the inevitable IT computing paradigm, the perception of the compute reference model and building of services has evolved into new dimensions. Serverless computing is an execution model in which the cloud service provider dynamically manages the allocation of compute resources of the server. The consumer is billed for the actual volume of resources consumed by them, instead paying for the pre-purchased units of compute capacity. This model evolved as a way to achieve optimum cost, minimum configuration overheads, and increases the application's ability to scale in the cloud. The prospective of the serverless compute model is well conceived by the major cloud service providers and reflected in the adoption of serverless computing paradigm. This review paper presents a comprehensive study on serverless computing architecture and also extends an experimentation of the working principle of serverless computing reference model adapted by AWS Lambda. The various research avenues in serverless computing are identified and presented.

<span lang="EN-US">The objective of evaluating User Experience (UX) in this era of technology is to enhance the user satisfaction. Earlier applications were built with the aim of reducing the work of users. But with the evolution of the technology, the emergence of new gadgets and new trends in the information technology, the applications had to be more user-centric. The primary objective of this research is to evaluate the user experience of web applications based on different UX parameters using different techniques and given a rating. Each of these ratings are combined to determine the overall rating of UX for the web application. Also, the secondary objective of this research is to provide suggestions or recommendations based on the ratings to improve the UX of the web applications. An experimental study was conducted and the results show a significant improvement. Areas of further enhancements have also been identified and presented.</span>

Service request scheduling has a major impact on the performance of the service processing design in a large-scale distributed computing environment like cloud systems. It is desirable to have a service request scheduling principle that evenly distributes the workload among the servers, according to their capacities. The capacities of the servers are termed high or low relative to one another. Therefore, there is a need to quantify the server capacity to overcome this subjective assessment. Subsequently, a method to split and distribute the service requests based on this quantified server capacity is also needed. The novelty of this research paper is to address these requirements by devising a service request scheduling principle for a heterogeneous distributed system using appropriate statistical methods, namely Conjoint analysis and Z-score. Suitable experiments were conducted and the experimental results show considerable improvement in the performance of the designed service request scheduling principle compared to a few other existing principles. Areas of further improvement have also been identified and presented.

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Detecting the image and identifying the face has become important in the field of computer vision in recognizing and analyzing, reconstructing into 3D, and labelling the image. Feature extraction is usually the first stage in detection and recognition of the image processing and computer vision. It supports the conversion of the image into a quantitative data. Later, this converted data can be used for labelling, classifying and recognizing a model. In this paper, performance of such feature extraction techniques viz. Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG) and Convolutional Neural Network (CNN) technique are applied to detect and recognize the face. The experiments conducted with a data set addressing the issues like pose variation, facial expression and intensity of light. The efficiency of the algorithms was evaluated based on the computational time and accuracy rate.

Mobile Ad-hoc Network (MANET) is a mobile network which has a large scale of self-directed nodes which is powerful to form a shortterm means of communication network, without any use of prior communications. Due to its uniqueness like partial resources, varying loops and shortfall of controlling the networks, these networks are exposed to diverse network layer issues. The "Ad hoc on demand distance vector" is a self-starting directing procedure whose security is compromised with the distinct form of attack named as "BlackHole" and "Grey Hole" attacks. This "malicious node" publicize as such, it contains the supreme track to the target during the route discovery process and thus interrupt the real communication and corrupt network performance. This paper introduces a new method in which a base node is introduced in the network that increases the probability of detecting multiple malicious nodes in the network and further separate them from taking part in any communication. It detects the corrupted nodes and prevent it by causing an effect for the communication. The proposed method has been experimented using NS2 and the results found to be efficient.