A Recommender System (RS) is the most significant technologies that handle the information overload problem of Retrieval Information by suggesting users with correct and related items. Today, abundant recommender systems have been developed for different fields and we put an effort on collaborative filtering (CF) recommender system. There are several problems in the recommender system such as Cold Start, Synonymy, Shilling Attacks, Privacy, Limited Content Analysis and Overspecialization, Grey Sheep, Sparsity, Scalability and Latency Problem. The current research explored the privacy in CF recommender system and defined the perspective privacy attributes (user's identity, password, address, and postcode/location) which are required to be addressed. Using the base models as Homomorphic and Hash Encryption scheme, we have proposed a hybrid model Homomorphic Hash Encryption (H2E) model that addressed the privacy issues according to defined objectives in the current study. Furthermore, in order to evaluate the privacy level, H2E was implementing in medicine recommender system and compared the consequences with existing state-of-the-art privacy protection mechanisms. It was observed that H2E outperform to other models with respect to determined privacy objectives. Leading to user's privacy, H2E can be considered a promising model for CF recommender systems.

Since the last decade, many new trends have been introduced to access network technologies and services through internet. Cloud computing is one of those significant technologies that reduce the cost and increase the productivity by providing a variety of services. Recently, cloud computing based system is primarily used for multimedia applications. Over the cloud computing, multimedia applications has some significant quality of service (QoS) requirements such as bandwidth, jitter, latency etc. But due to some limitations in services providing, it is constantly complex to make selection for an appropriate service. Keeping in view the provision of multimedia services through cloud computing, many different concepts and approaches that provide better cloud services under the constraints of QoS attributes have been described in the literature. The goal of this paper is to assess the applicability and provision of multimedia applications over cloud computing through enhanced quality of service. We have identified the primary quality of service msetrics evaluation of multimedia services over cloud computing.  Furthermore, under these metrics we evaluated the existing approaches that provide multimedia related services with their strengths and limitations. This evaluation approach could provide the service that can provide better QoS in multimedia applications over cloud computing.

In the modern era, the ideas related to software developments are totally replaced the old traditional software development to CBSD. CBSD is the approach that can provide reusability of components to develop new software under minimum chances of risks. Beyond the CBSD features, there are still some significant risks overall the development phase. Generally, the quality of a developed software is depending upon the component integration phase. Nevertheless, component integration phase plays a tremendous role in the success of CBSD that leads to develop new risk free software. The objective of this research was to identify all the risks in CBSD and applied risk reduction activities to mitigate these risks. On the basis of the literature survey, categorized the risks into different categories. For this, an online questionnaire was performed to identify the risks and the risk reduction activities. 85% results point out that CBSD approach is the best approach as compared to the traditional approach. 80% results show that it performs the risk reduction activities, then the quality of the product improves. However, it is a step towards the mitigation of the vulnerabilities and reducing the cost of maintenance.

System Architecture evaluation and formal specification are the significant processes and practical endeavors in all domains. Many methods and formal descriptive techniques have been proposed to make a comprehensive analysis and formal representation of a system architecture. This paper consists of two main parts, in first we evaluated system performance, quality attribute in Remote Temperature Sensor clients-Server architecture by implementing an ATAM model, which provides a comprehensive support for evaluation of architecture designs by considering design quality attributes and how they can be represented in the architecture. In the second part, we computed the selected system architecture in ISO standards formal description technique LOTOS with which a system can be specified by the temporal relation between interactions and behavior of the system. Our proposed approach improves on factors such as ambiguity, inconsistency and incompleteness in current system architecture.

During the last decade, Heterogeneous systems are emerging for high performance computing [1]. In order to achieve high performance computing (HPC), existing technologies and programming models aims to see rapid growth toward intra-node parallelism [2]. The current high computational system and applications demand for a massive level of computation power. In last few years, Graphical processing unit (GPU) has been introduced an alternative of conventional CPU for highly parallel computing applications both for general purpose and graphic processing. Rather than using the traditional way of coding algorithms in serial by single CPU, many multithreading programming models has been introduced such as CUDA, OpenMP, and MPI to make parallel processing by using multicores. These parallel programming models are supportive to data driven multithreading (DDM) principle [3]. In this paper, we have presented performance based preliminary evaluation of these programming models and compared with the conventional single CPU serial processing system. We have implemented a massive computational operation for performance evaluation such as complex matrix multiplication operation. We used data driven multithreaded HPC system for performance evaluation and presented the results with a comprehensive analysis of these parallel programming models for HPC parallelism.