Journal of Internet Services and Applications

Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly important area.

Mentoring is a well-known way to help newcomers to Open Source Software (OSS) projects overcome initial contribution barriers. Through mentoring, newcomers learn to acquire essential technical, social, and organizational skills. Despite the importance of OSS mentors, they are understudied in the literature. Understanding who OSS project mentors are, the challenges they face, and the strategies they use can help OSS projects better support mentors’ work. In this paper, we employ a two-stage study to comprehensively investigate mentors in OSS. First, we identify the characteristics of mentors in the Apache Software Foundation, a large OSS community, using an online survey. We found that less experienced volunteer contributors are less likely to take on the mentorship role. Second, through interviews with OSS mentors (n=18), we identify the challenges that mentors face and how they mitigate them. In total, we identified 25 general mentorship challenges and 7 sub-categories of challenges regarding task recommendation. We also identified 13 strategies to overcome the challenges related to task recommendation. Our results provide insights for OSS communities, formal mentorship programs, and tool builders who design automated support for task assignment and internship.

With the growth, ready availability and affordability of wireless technologies, proactive context-aware recommendations are a potential solution to overcome the information overload and the common limitations of mobile devices (inconvenience of data input and Internet browsing). The automatic provision of just-in-time information or recommendations tailored to each user’s needs/preferences contextualised from the user’s activities, location, usage patterns, time, and connectivity may not only facilitate access to information but also remove barriers to the adoption of current and future services on mobile devices. This paper describes a hybrid P2P context-aware framework called JHPeer which supports a variety of context-aware applications in mobile environments. Any context-aware information services such as recommendation services could use the collected and shared contextual information in JHPeer network. An analytic hierarchy process based multi-criteria ranking (AHP-MCR) approach has been developed and used to rate recommendations in a variety of domains. The weights of the contexts criteria can be assigned by the user or automatically adjusted via individual-based and/or group-based assignment. Additionally, a Bayesian network algorithm is applied to solve the cold-start problem in recommendation systems. The paper also proposes a strategy for using Bayesian networks for recommendation services. A news recommendation application has been implemented on the developed JHPeer framework, which proactively pushes relevant news based on the users’ contextual information. Evaluation studies show that the system can push relevant recommendations to mobile users appropriately.