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Abstract-A rapidly emerging trend in the IT landscape is the uptake of large-scale datacenters moving storage and data processing to providers located far away from the end-users or locally deployed servers. For these large-scale datacenters power efficiency is a key metric, with the PUE (Power Usage Effectiveness) and DCiE (Data Centre infrastructure Efficiency) being important examples. This paper proposes a belief rule based expert system to predict datacenter PUE under uncertainty. The system has been evaluated using real-world data from a data center in the UK. The results would help planning construction of new datacenters and the redesign of existing datacenters making them more power efficient leading to a more sustainable computing environment. In addition, an optimal learning model for the BRBES demonstrated which has been compared with ANN and Genetic Algorithm; and the results are promising.

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Purpose -This paper aims to present part of the work of an ongoing research project that is looking at socio-cultural and technological developments from a mobile technology convergence view; in order to show how culturally aware convergence developments in mobile technology can be adopted and employed for the betterment of society. Design/methodology/approach -The paper presents a scenario for a mobile technology enabled learning environment in support of the conventional learning approach with a focus on enabling parental involvement and contribution to the daily learning objectives of their children and hence enhancing a quality learning experience. It further critically discusses issues of interface design -at both the device and application levels -that will have an impact on the quality of e-learning, with a focus on mobile technology. Findings -The paper shows how interface design can positively enhance the quality defining characteristics of learning in an e-learning environment. Ways of achieving these characteristics of learning through effective e-learning are reported. This is done by addressing requirements for quality-learning through effective interface-design considerations, towards meeting the overall quality requirements of learning that should be intrinsic to a holistic e-learning environment. The value of human computer interaction and the critical factors of promoting productive interaction are addressed. Research limitations/implications -There are several factors affecting quality of e-learning as a tool and approach to flexible and independent learning. The advent and use of mobile technology has been investigated in this work from a socio-cultural and technological perspectives in two continents. The limitations lie in the depth of investigations and how far the findings can be applied to the diversity of learners. Practical implications -As the effects of cultures and the rapid technological advancements take toll on teaching and learning the findings reported in this paper have far reaching implications for learners from different cultures and also for attempts at bridging existing digital divide. Originality/value -The approach adopted in the research is unique by virtue of new findings and ideas presented. The paper highlights the opportunities for mobile devices and technology to play a role in the development of communities through technology aided learning (e-learning), with a focus on e-learning systems and technology requirements for delivering a quality learning experience. IntroductionIn today's global world, the role of technology in delivering learning objectives in the formal and informal learning environment continues to grow. This to a large extent can be attributed to developments in internet-and web-related technology paralleled with developments in the information and communication technology domain. Such developments have made it possible for rich e-learning applications and content resources to be developed and delivered to learners across the globe. A learning trend ...

Abstract-The main goal of this proposed project is to harness the emerging IoT technology to empower elderly population to selfmanage their own health, stay active, healthy, and independent as long as possible within a smart and secured living environment. An integrated open-sourced IoT ecosystem will be developed. It will encompass the entire data lifecycle which involves the following processes: data acquisition, data transportation; data integration, processing, manipulation and computation; visualisation; data intelligence and exploitation; data sharing; data storage. This innovative cloud-based IoT ecosystem will provide a one-stop shop for integrated smart IoTenabled services to support older people (greater or equal to 65 years old) who live alone at home (or care homes). Another innovation of this system is the design and implementation of an integrated IoT gateway for wellebing wearable and home automation system sensors with varying communication protocols. The SMART-ITEM system and services will appropriately address the following (i) smart health and care; (ii) smart quality of life; (iii) SMART-ITEM social community. The development of the system will be based on the User Centred Design methodology so as to ensure active user engagement throughout the entire project lifecycle and necessary standards as well as compliances will be adhered to (e.g. security, trust and privacy) in order to enhance user acceptance.

The long-standing dominance of the Simple Network Management Protocol (SNMP), in its various flavours (though particularly the original SNMPv1) is being challenged by the development of agent-based (and more specifically mobile-agent based) network management support. One of the criticisms of SNMP is that it suffers from a common failing of such client-server based paradigms, namely the performance problems caused by all traffic being directed to and from a single location (the network management platform). The behaviour of such client-server applications has been explored through the use of the OPNET simulation system, populating the model using data collected from a study of the way a network management platform is used both to monitor a properly-functioning network and to collect information in response to fault situations. Initial results are presented for version 1 of SNMP showing the behaviour of the resultant system over a network configuration which includes both local and wide area network links.

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