7,737 research outputs found
TimeTrader: Exploiting Latency Tail to Save Datacenter Energy for On-line Data-Intensive Applications
Datacenters running on-line, data-intensive applications (OLDIs) consume
significant amounts of energy. However, reducing their energy is challenging
due to their tight response time requirements. A key aspect of OLDIs is that
each user query goes to all or many of the nodes in the cluster, so that the
overall time budget is dictated by the tail of the replies' latency
distribution; replies see latency variations both in the network and compute.
Previous work proposes to achieve load-proportional energy by slowing down the
computation at lower datacenter loads based directly on response times (i.e.,
at lower loads, the proposal exploits the average slack in the time budget
provisioned for the peak load). In contrast, we propose TimeTrader to reduce
energy by exploiting the latency slack in the sub- critical replies which
arrive before the deadline (e.g., 80% of replies are 3-4x faster than the
tail). This slack is present at all loads and subsumes the previous work's
load-related slack. While the previous work shifts the leaves' response time
distribution to consume the slack at lower loads, TimeTrader reshapes the
distribution at all loads by slowing down individual sub-critical nodes without
increasing missed deadlines. TimeTrader exploits slack in both the network and
compute budgets. Further, TimeTrader leverages Earliest Deadline First
scheduling to largely decouple critical requests from the queuing delays of
sub- critical requests which can then be slowed down without hurting critical
requests. A combination of real-system measurements and at-scale simulations
shows that without adding to missed deadlines, TimeTrader saves 15-19% and
41-49% energy at 90% and 30% loading, respectively, in a datacenter with 512
nodes, whereas previous work saves 0% and 31-37%.Comment: 13 page
Raising awareness for water polution based on game activities using internet of things
Awareness among young people regarding the environment and its resources and comprehension of the various factors that interplay, is key to changing human behaviour towards achieving a sustainable planet. In this paper IoT equipment, utilizing sensors for measuring various parameters of water quality, is used in an educational context targeting at a deeper understanding of the use of natural resources towards the adoption of environmentally friendly behaviours. We here note that the use of water sensors in STEM gameful learning is an area which has not received a lot of attention in the previous years. The IoT water sensing and related scenaria and practices, addressing children via discovery, gamification, and educational activities, are discussed in detail
Neuro-linguistic programming techniques to improve the self-efficacy of undergraduate dissertation students
This paper aims to address the gap in the extant literature examining the support offered to, and required by, students in light of the changing nature of the undergraduate dissertation and the changing nature of the student undertaking it. For many, it will be the first time they will have undertaken a self-directed, major research project. The focus of this paper is to present the neuro-linguistic programming (NLP) framework for setting well-formed outcomes that was offered to students in the initial session of a pilot dissertation workshop support programme, initially targeting students completing dissertation projects on marketing topics within the Business School. Unlike modules on Research Methods the focus of this programme was not on methodology, but on soft skills such as goal setting, time management and motivation, along with practical skills such as those required to take advantage of developments in data processing technology. The paper also presents the findings of qualitative data gathered from responses of students in focus groups and in-depth interviews designed to explore students’ on-going motivation throughout the dissertation process. The paper concludes with a comparison of the results of those students who took part in the workshop sessions with those that did not
User-centered development of a Virtual Research Environment to support collaborative research events
This paper discusses the user-centred development process within the Collaborative Research Events on the Web (CREW) project, funded under the JISC Virtual Research Environments (VRE) programme. After presenting the project, its aims and the functionality
of the CREW VRE, we focus on the user engagement approach, grounded in the method of co-realisation. We describe the different research settings and requirements of our three embedded user groups and the respective activities conducted so far. Finally we elaborate on
the main challenges of our user engagement approach and end with the project’s next steps
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