745 research outputs found
EUROPEAN CONFERENCE ON QUEUEING THEORY 2016
International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"
Sea Container Terminals
Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations
System-of-Systems Considerations in the Notional Development of a Metropolitan Aerial Transportation System
There are substantial future challenges related to sustaining and improving efficient, cost-effective, and environmentally friendly transportation options for urban regions. Over the past several decades there has been a worldwide trend towards increasing urbanization of society. Accompanying this urbanization are increasing surface transportation infrastructure costs and, despite public infrastructure investments, increasing surface transportation "gridlock." In addition to this global urbanization trend, there has been a substantial increase in concern regarding energy sustainability, fossil fuel emissions, and the potential implications of global climate change. A recently completed study investigated the feasibility of an aviation solution for future urban transportation (refs. 1, 2). Such an aerial transportation system could ideally address some of the above noted concerns related to urbanization, transportation gridlock, and fossil fuel emissions (ref. 3). A metro/regional aerial transportation system could also provide enhanced transportation flexibility to accommodate extraordinary events such as surface (rail/road) transportation network disruptions and emergency/disaster relief responses
EdgeRIC: Empowering Realtime Intelligent Optimization and Control in NextG Networks
Radio Access Networks (RAN) are increasingly softwarized and accessible via
data-collection and control interfaces. RAN intelligent control (RIC) is an
approach to manage these interfaces at different timescales. In this paper, we
develop a RIC platform called RICworld, consisting of (i) EdgeRIC, which is
colocated, but decoupled from the RAN stack, and can access RAN and
application-level information to execute AI-optimized and other policies in
realtime (sub-millisecond) and (ii) DigitalTwin, a full-stack, trace-driven
emulator for training AI-based policies offline. We demonstrate that realtime
EdgeRIC operates as if embedded within the RAN stack and significantly
outperforms a cloud-based near-realtime RIC (> 15 ms latency) in terms of
attained throughput. We train AI-based polices on DigitalTwin, execute them on
EdgeRIC, and show that these policies are robust to channel dynamics, and
outperform queueing-model based policies by 5% to 25% on throughput and
application-level benchmarks in a variety of mobile environments.Comment: 16 pages, 15 figure
- …