Salimah Binti Mokhtar

Big data

We use structuralism and functionalism paradigms to analyze the origins of big data applications.Current trends and sources of big data.Processing technologies, methods and analysis techniques for big data are compared in detail.We analyze major challenges with big data and also discussed several opportunities.Case studies and emerging technologies for big data problems are discussed. Big data is a potential research area receiving considerable attention from academia and IT communities. In the digital world, the amounts of data generated and stored have expanded within a short period of time. Consequently, this fast growing rate of data has created many challenges. In this paper, we use structuralism and functionalism paradigms to analyze the origins of big data applications and its current trends. This paper presents a comprehensive discussion on state-of-the-art big data technologies based on batch and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also discusses big data analytics techniques, processing methods, some reported case studies from different vendors, several open research challenges, and the opportunities brought about by big data. The similarities and differences of these techniques and technologies based on important parameters are also investigated. Emerging technologies are recommended as a solution for big data problems.

Enabling Communication Technologies for Smart Cities

Tremendous advancements in heterogeneous communication technologies have enabled smart cities objects to interact with each other while ensuring network connectivity. However, these communication technologies cannot provide flawless connectivity in smart cities due to the coexistence of thousands of devices, which brings about several problems. In this article, we discuss the enabling communication and networking technologies used in smart cities. The similarities and differences among different communication technologies based on the important parameters are also analyzed. Moreover, a taxonomy is devised by classifying the literature based on future and emerging technologies, modern communication technologies, IEEE wireless technology standards, objectives, network classes, and mode of operations. Furthermore, some reported case studies of different cities (Barcelona, Stratford, Singapore, and Porto) are also presented. Lastly, several research challenges, such as interference management, scalable wireless solutions, interoperability support among heterogeneous wireless networks, mobility management, and high energy consumption that remain to be addressed for enabling unimpaired connectivity in smart cities are discussed as future research directions.

Mobile ad hoc cloud: A survey

The unabated flurry of research activities to augment various mobile devices in terms of compute-intensive task execution by leveraging heterogeneous resources of available devices in the local vicinity has created a new research domain called mobile ad hoc cloud MAC or mobile cloud. It is a new type of mobile cloud computing MCC. MAC is deemed to be a candidate blueprint for future compute-intensive applications with the aim of delivering high functionalities and rich impressive experience to mobile users. However, MAC is yet in its infancy, and a comprehensive survey of the domain is still lacking. In this paper, we survey the state-of-the-art research efforts carried out in the MAC domain. We analyze several problems inhibiting the adoption of MAC and review corresponding solutions by devising a taxonomy. Moreover, MAC roots are analyzed and taxonomized as architectural components, applications, objectives, characteristics, execution model, scheduling type, formation technologies, and node types. The similarities and differences among existing proposed solutions by highlighting the advantages and disadvantages are also investigated. We also compare the literature based on objectives. Furthermore, our study advocates that the problems stem from the intrinsic characteristics of MAC by identifying several new principles. Lastly, several open research challenges such as incentives, heterogeneity-ware task allocation, mobility, minimal data exchange, and security and privacy are presented as future research directions. Copyright

Online Document Management System for Academic Institutes

Nowadays, electronic systems enable the rapid creation and distribution of documents. Therefore, people replace paper documents with electronic documents, in academic area electronic documents as information sources have increased in number and retrieving the information among huge number of documents become a problem. A recent study shows positive feedback from students towards establishing a document management system in local universities new innovative tools are necessary to access relevant information, in faculty of university student are very interested to have a system to manage, retrieve and sharing documents. Document management system in faculty can improve efficiency and effectiveness of research and also can improve knowledge sharing among students and get new idea from other researches. students need a well-organized knowledge repository in order to reuse information throughout the research, is creating new opportunities for collaboration, coordination, and information exchange among students that work on a construction project. and consequently reduce costs and response times. The entire service is delivered through INTERNET browse so in any location can access documents.

Heterogeneity-Aware Task Allocation in Mobile Ad Hoc Cloud

Mobile Ad Hoc Cloud (MAC) enables the use of a multitude of proximate resource-rich mobile devices to provide computational services in the vicinity. However, inattention to mobile device resources and operational heterogeneity-measuring parameters, such as CPU speed, number of cores, and workload, when allocating task in MAC, causes inefficient resource utilization that prolongs task execution time and consumes large amounts of energy. Task execution is remarkably degraded, because the longer execution time and high energy consumption impede the optimum use of MAC. This paper aims to minimize execution time and energy consumption by proposing heterogeneity-aware task allocation solutions for MAC-based compute-intensive tasks. Results of the proposed solutions reveal that incorporation of the heterogeneity-measuring parameters guarantees a shorter execution time and reduces the energy consumption of the compute-intensive tasks in MAC. A system model is developed to validate the proposed solutions’ empirical results. In comparison with random-based task allocation, the proposed five solutions based on CPU speed, number of core, workload, CPU speed and workload, and CPU speed, core, and workload reduce execution time up to 56.72%, 53.12%, 56.97%, 61.23%, and 71.55%, respectively. In addition, these heterogeneity-aware task allocation solutions save energy up to 69.78%, 69.06%, 68.25%, 67.26%, and 57.33%, respectively. For this reason, the proposed solutions significantly improve tasks’ execution performance, which can increase the optimum use of MAC.

National IT initiatives and development — the Malaysian experience

This paper reviews the Malaysian approach in developing and implementing IT initiatives in the creation of information-rich society in the country. It also addresses various issues that have to be faced by a developing country in positioning itself towards achieving a fully-developed status nation by the year 2020.