MobiDesk: Mobile Virtual Desktop Computing

We present MobiDesk, a mobile virtual desktop computing hosting infrastructure that leverages continued improvements in network speed, cost, and ubiquity to address the complexity, cost, and mobility limitations of today's personal computing infrastructure. MobiDesk transparently virtualizes a user's computing session by abstracting underlying system resources in three key areas: display, operating system and network. MobiDesk provides a thin virtualization layer that decouples a user's computing session from any particular end user device and moves all application logic from end user devices to hosting providers. MobiDesk virtualization decouples a user's computing session from the underlying operating system and server instance, enabling high availability service by transparently migrating sessions from one server to another during server maintenance or upgrades. We have implemented a MobiDesk prototype in Linux that works with existing unmodified applications and operating system kernels. Our experimental results demonstrate that MobiDesk has very low virtualization overhead, can provide a full-featured desktop experience including full-motion video support, and is able to migrate users' sessions efficiently and reliably for high availability, while maintaining existing network connections

Weapon Release Scheduling from Multiple-Bay Aircraft using Multi-Objective Evolutionary Algorithms

The United States Air Force has put an increased emphasis on the timely delivery of precision weapons. Part of this effort has been to us multiple bay aircraft such the B-1B Lancer and B-52 Stratofortress to provide Close Air Support and responsive strikes using 1760 weapons. In order to provide greater flexibility, the aircraft carry heterogeneous payloads which can require deconfliction in order to drop multiple different types of weapons. Current methods of deconfliction and weapon selection are highly crew dependent and work intensive. This research effort investigates the optimization of an algorithm for weapon release which allows the aircraft to perform deconfliction automatically. This reduces crew load and response time in order to deal with time-sensitive targets. The overall problem maps to the Job-Shop Scheduling problem. Optimization of the algorithm is done through the General Multiobjective Parallel Genetic Algorithm (GENMOP). We examine the results from pedagogical experiments and real-world test scenarios in the light of improving decision making. The results are encouraging in that the program proves capable of finding acceptable release schedules, however the solution space is such that applying the program to real world situations is unnecessary. We present visualizations of the schedules which demonstrate these conclusions