Scalable, Data- intensive Network Computation

To enable groups of collaborating researchers at different locations to effectively share large datasets and investigate their spontaneous hypotheses on the fly, we are interested in de- veloping a distributed system that can be easily leveraged by a variety of data intensive applications. The system is composed of (i) a number of best effort logistical depots to en- able large-scale data sharing and in-network data processing, (ii) a set of end-to-end tools to effectively aggregate, manage and schedule a large number of network computations with attendant data movements, and (iii) a Distributed Hash Table (DHT) on top of the generic depot services for scalable data management. The logistical depot is extended by following the end-to-end principles and is modeled with a closed queuing network model. Its performance characteristics are studied by solving the steady state distributions of the model using local balance equations. The modeling results confirm that the wide area network is the performance bottleneck and running concurrent jobs can increase resource utilization and system throughput. As a novel contribution, techniques to effectively support resource demanding data- intensive applications using the ¯ne-grained depot services are developed. These techniques include instruction level scheduling of operations, dynamic co-scheduling of computation and replication, and adaptive workload control. Experiments in volume visualization have proved the effectiveness of these techniques. Due to the unique characteristic of data- intensive applications and our co-scheduling algorithm, a DHT is implemented on top of the basic storage and computation services. It demonstrates the potential of the Logistical Networking infrastructure to serve as a service creation platform

Analysis of the impact of advertising and the use of social media regarding product sales

A furniture has operated a new branch of the store in Hamilton. The existing one is currently running smoothly with stable sales day by day in Auckland. The company decided to process their product and service into new area which is Hamilton. As a truly fact, advertising and uses of social are two primary tools for the new store to increase marketing sales in a short period. The researcher decided to measure the impact of each method (advertising and uses of social media) on sales. This study aimed to discuss how the advertising and the uses of social media impact sales in Sue-E. In this study, a questionnaire with 18 questions was made by researcher, and it was used for further research. The target population was mainly focused in Sue-E furniture store where located in Hamilton city central, and there were 74 people have been participated in this survey. All data resulting from participators would only be used for this research and saved properly. Therefore, based on the results and the finding of this study, the variables of uses of social media had high impact on furniture sales in Sue-E, and the variables of advertising had a positive effect on furniture sales