Browsing by Author "Fernando, V"

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    item: Thesis-Full-text
    Auto-tuning multi-tiered application for performance
    Fernando, V; Jayasena, S
    Auto-Tuning Multi Tiered Applications for Performance With the widespread use of cluster-based environments, getting the maximum possible performance from multi-tiered web applications becomes an important task. The large numbers of configurable parameters in such environments and applications, however, makes manual performance tuning (i.e., searching for and identifying key parameters that affect performance and optimal values for those parameters) extremely difficult, if not virtually impossible. The problem becomes further complicated because the key parameters and/or their optimal values will vary across environments, applications and workloads. In this work, we explore the autotuning approach, which is generally used to automatically tune the performance of programs in traditional HPC settings, to tune multi-tiered web applications. Our approach is based on OpenTuner, a framework used to build auto-tuners to search through a configuration space for an optimal configuration. Even for this autotuning approach, the wide variations and the dynamic nature in the runtime environment, such as network congestion, variations in demand, possible node failures and changes in workloads pose a significant challenge. In this work, we explore offline and online tuning techniques to overcome the challenges of autotuning multi-tiered applications. We present results of offline autotuning experiments that tuned benchmark applications for multiple performance goals. We show that 20% - 25% improvements in response time and throughput can be achieved through our offline autotuning approach. We present a way of reducing the tuning time by pruning the configuration space. We identify the parameters in web servers that contribute most to performance. We also show that different performance goals can lead to differences in configurations and discuss the shortcomings of offline autotuning methods. We also take a look at online tuning methods and show that online tuning of multi-tiered applications is feasible.
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    item: Conference-Abstract
    The Impact of green attributes on customer loyalty of supermarket outlets in Sri Lanka
    (2017) Fernando, V; Abeysekara, N; Samarasinghe, GD; Kuruppu, GN
    Despite environmental concern and positive attitude of customers towards sustainability and green products, market share of green products remains confined which is considered as green purchase inconsistency’ of ‘green attitude behavior gap’. Therefore, the objectives of this research study are: to identify whether the supermarket outlets in Sri Lanka possess green attributes, to what extent, to describe the present level of customer loyalty towards super market outlets and finally, to explain the relationship between green attributes of supermarket outlets in Sri Lanka and customer loyalty of the outlets. Data was collected through a structured questionnaire from 198 customers who came to selected supermarkets in Colombo district. The data was analyzed through the descriptive statistics and inferential analysis. The findings of the study revealed that Green Attributes of the supermarkets are not at a satisfactory level to achieve the customer loyalty and hence very low customer loyalty towards Sri Lankan supermarket. Further, attributes such as green products, eco branding and green price of the product have positive relationship with customer Loyalty. These attributes that it needs to improve further in order to develop the green concept among Sri Lankan customers.