The challenges of cloud computing technology adoption in e-government

 The endless transformation of technological innovation requires greater collaboration of Information Communication and Technology (ICT) in various areas especially in public sectors. Many attempts have been made in improving the quality of E-Government services; one of it is adopting the cloud computing technology. Successful implementation of cloud computing technology can benefit the public sector in many ways one of it is cost reduction. Most government organizations especially in the developing countries are committed in adopting the cloud technology based on the increased demands in cloud adoption in E Government services. Unfortunately, despite all the benefits, the cloud computing technology raises some major risks. The success of implementation of cloud computing technology is determined by how well the government tackles the challenges. Therefore, this paper specifically surveyed the associated challenges of adopting Cloud Technology for E-Government by choosing Malaysia as the case study.

Trust enhanced security in SaaS cloud computing

Trust problem in Software as a Service Cloud Computing is a broad range of a Data Owner’s concerns about the data in the Cloud. The Data Owner’s concerns about the data arise from the way the data is handled in locations and machines that are unknown to the Data Owner.

Service and cloud computing supporting genomic analysis of the mammalian species

 This research focused on building Software as a Service clouds to support mammalian genomic applications such as personalized medicine. Outcomes of this research included a Software as a Service cloud framework, the Uncinus research cloud and novel genomic analysis software. Results have been published in high ranking peer-reviewed international journals.

Cloud computing : principles and paradigms

The primary purpose of this book is to capture the state-of-the-art in Cloud Computing technologies and applications. The book will also aim to identify potential research directions and technologies that will facilitate creation a global market-place of cloud computing services supporting scientific, industrial, business, and consumer applications. We expect the book to serve as a reference for larger audience such as systems architects, practitioners, developers, new researchers and graduate level students. This area of research is relatively recent, and as such has no existing reference book that addresses it. This book will be a timely contribution to a field that is gaining considerable research interest, momentum, and is expected to be of increasing interest to commercial developers. The book is targeted for professional computer science developers and graduate students especially at Masters level. As Cloud Computing is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years, its knowledge will help position our readers at the forefront of the field. © 2011 John Wiley & Sons, Inc.

A clusterized firewall framework for cloud computing

Cloud computing is becoming popular as the next infrastructure of computing platform. However, with data and business applications outsourced to a third party, how to protect cloud data centers from numerous attacks has become a critical concern. In this paper, we propose a clusterized framework of cloud firewall, which characters performance and cost evaluation. To provide quantitative performance analysis of the cloud firewall, a novel M/Geo/1 analytical model is established. The model allows cloud defenders to extract key system measures such as request response time, and determine how many resources are needed to guarantee quality of service (QoS). Moreover, we give an insight into financial cost of the proposed cloud firewall. Finally, our analytical results are verified by simulation experiments.

Energy efficiency on location based applications in mobile cloud computing: a survey

The constrained battery power of mobile devices poses a serious impact on user experience. As an increasingly prevalent type of applications in mobile cloud environments, location-based applications (LBAs) present some inherent limitations concerning energy. For example, the Global Positioning System based positioning mechanism is well-known for its extremely power-hungry attribute. Due to the severity of the issue, considerable researches have focused on energy-efficient locating sensing mechanism in the last a few years. In this paper, we provide a comprehensive survey of recent work on low-power design of LBAs. An overview of LBAs and different locating sensing technologies used today are introduced. Methods for energy saving with existing locating technologies are investigated. Reductions of location updating queries and simplifications of trajectory data are also mentioned. Moreover, we discuss cloud-based schemes in detail which try to develop new energy-efficient locating technologies by leveraging the cloud capabilities of storage, computation and sharing. Finally, we conclude the survey and discuss the future research directions. © 2013 Springer-Verlag Wien.

FEACS: a flexible and efficient access control scheme for cloud computing

In the past few years, cloud computing has emerged as one of the most influential paradigms in the IT industry. As promising as it is, this paradigm brings forth many new challenges for data security because users have to outsource sensitive data on untrusted cloud servers for sharing. In this paper, to guarantee the confidentiality and security of data sharing in cloud environment, we propose a Flexible and Efficient Access Control Scheme (FEACS) based on Attribute-Based Encryption, which is suitable for fine-grained access control. Compared with existing state-of-the-art schemes, FEACS is more practical by following functions. First of all, considering the factor that the user membership may change frequently in cloud environment, FEACS has the capability of coping with dynamic membership efficiently. Secondly, full logic expression is supported to make the access policy described accurately and efficiently. Besides, we prove in the standard model that FEACS is secure based on the Decisional Bilinear Diffie-Hellman assumption. To evaluate the practicality of FEACS, we provide a detailed theoretical performance analysis and a simulation comparison with existing schemes. Both the theoretical analysis and the experimental results prove that our scheme is efficient and effective for cloud environment.

Enabling cloud computing in emergency management systems

Emergencies, including both natural and man - made disasters, increasingly pose an immediate threat to life, health, property, and environment. For example, Hurricane Katrina, the deadliest and most destructive Atlantic tropical cyclone of the 2005 Atlantic hurricane season, led to at least 1,883 people's death and an estimated loss of - 108 billion property. To reduce the damage by emergencies, a wide range of cutting-edge technologies on medicine and information are used in all phases of emergency management. This article proposes a cloud-based emergency management system for environmental and structural monitoring that utilizes the powerful computing and storage capability of datacenters to analyze the mass data collected by the wireless intelligent sensor network deployed in civil environment. The system also benefits from smartphone and social network platform to setup the spatial and population models, which enables faster evacuation and better resource allocation.

Dynamic cloud service selection using an adaptive learning mechanism in multi-cloud computing

Cloud service selection in a multi-cloud computing environment is receiving more and more attentions. There is an abundance of emerging cloud service resources that makes it hard for users to select the better services for their applications in a changing multi-cloud environment, especially for online real time applications. To assist users to efficiently select their preferred cloud services, a cloud service selection model adopting the cloud service brokers is given, and based on this model, a dynamic cloud service selection strategy named DCS is put forward. In the process of selecting services, each cloud service broker manages some clustered cloud services, and performs the DCS strategy whose core is an adaptive learning mechanism that comprises the incentive, forgetting and degenerate functions. The mechanism is devised to dynamically optimize the cloud service selection and to return the best service result to the user. Correspondingly, a set of dynamic cloud service selection algorithms are presented in this paper to implement our mechanism. The results of the simulation experiments show that our strategy has better overall performance and efficiency in acquiring high quality service solutions at a lower computing cost than existing relevant approaches.