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Full-Text Articles in Physical Sciences and Mathematics
Webarc: Website Archival Using A Structured Approach, Ee Peng Lim, Maria Marissa
Webarc: Website Archival Using A Structured Approach, Ee Peng Lim, Maria Marissa
Research Collection School Of Computing and Information Systems
Website archival refers to the task of monitoring and storing snapshots of website(s) for future retrieval and analysis. This task is particularly important for websites that have content changing over time with older information constantly overwritten by newer one. In this paper, we propose WEBARC as a set of software tools to allow users to construct a logical structure for a website to be archived. Classifiers are trained to. determine relevant web pages and their categories, and subsequently used in website downloading. The archival schedule can be specified and executed by a scheduler. A website viewer is also developed to …
Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee
Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee
Research Collection School Of Computing and Information Systems
Wireless broadcast is very suitable for delivering information to a large user population. In this paper, we concentrate on data allocation methods for multiple broadcast channels. To the best of our knowledge, this is the first allocation model that takes into the consideration of items' access frequencies, items' lengths. and bandwidth of different channels. We first derive the optimal average expected delay for multiple channels for the general case where data access frequencies, data sizes, and channel bandwidths can all be non-uniform. Second, we develop TOSA, a multi-channel allocation method that does not assume a uniform broadcast schedule for data …
Optimal Scheduling In A Queue With Differentiated Impatient Users, Amy Csizmar Dalal, Scott Jordan
Optimal Scheduling In A Queue With Differentiated Impatient Users, Amy Csizmar Dalal, Scott Jordan
Faculty Work
We consider a M/M/1 queue in which the average reward for servicing a job is an exponentially decaying function of the job’s sojourn time. The maximum reward and mean service times of a job are i.i.d. and chosen from arbitrary distributions. The scheduler is assumed to know the maximum reward, service rate, and age of each job. We prove that the scheduling policy that maximizes average reward serves the customer with the highest product of potential reward and service rate.