“Improving Caching for Web Applications” by Daniel Byrne
Abstract: Web applications employ caches to store the data that is most commonly accessed. The cache improves the application’s performance by reducing the time it takes to fetch a piece of data from the application’s database. Since the cache typically resides in a limited amount system memory, maximizing the memory utilization is key to delivering the best performance possible. In addition, application data access patterns change over time, so the system should be adaptive in its memory allocation policy as opposed to current static allocations.In this work, we address both multi-tennancy (where a single cache is used for multiple applications) and dynamic workloads (changing access patterns) using a sharing model that relates the cache size to the application miss-rate, know as a miss-ratio curve. Intuitively, the larger the cache, the less likely the system will need to fetch the data from the database. Our efficient, online construction of the miss-ratio curve allows for us to determine the optimal memory allocation given the available system memory, while adapting to changing data access patterns. We show that our model outperforms the existing state-of-the-art sharing model in terms of overall cache hit-rate and does so at a lower time cost.
“Maximizing Coverage in VANETs” by Ali Jalooli
The success of vehicular networks is highly dependent on the coverage of message, which refers to the Euclidean spatial distance that a message once initiated by a given mobile node (i.e., source vehicle) can reach within time t. We studied the crucial problem of optimal utilization of roadside units (RSUs) in 2-D environments, and proposed a greedy algorithm, which by taking the V2V communication into consideration, finds the optimal locations for RSUs deployment to achieve the maximum message coverage.