Manufacturing and logistics companies are forced to rethink their strategies due to increasing product variety, shorter product life cycles, and a shortage of skilled workers. Conventional system structures with central control instances are too inflexible to respond quickly and efficiently to dynamic influences such as short-term adjustments to process sequences or individual process conditions. To counteract these influences, increasingly intelligent and coordinated subsystems with specific areas of competence and functionalities are being integrated into production and logistics processes. Based on the analysis of challenges to intralogistics, this work presents a concept for controlling so-called coordination requirement points. In these locations, the interactions between system objects in internal material transport are coordinated, which is exemplarily implemented in a simulation environment. By varying complexity properties, the achievement of logistical targets at different degrees of autonomous control is analyzed, finding an increased “on time delivery” rate for increasing autonomy and the incorporation of order-relevant information.

Web performance has long proved to be one of the most sought after and difficult to achieve components for the web. Since the inception of the modern web infrastructure, the situation has been growing in complexity, adding remote hosts and objects, providing everything from computation infrastructure, content distribution capability, and targeted advertising. While many of these components provide improvements for some users, the complexity of the Internet often leaves other users suffering from poor performance. We propose Oak, a system which addresses client performance on the individual level, hence addressing challenges which may be unique to the user. Oak measures a user's performance for objects loading on a page, and determines which components are under-performing. Oak further provides an automated mechanism by which sites are able to replace resources with those provided by a better performing alternative service for a particular user. In this work, we demonstrate the prevalence of under-performing services on the web, finding that over 60% of the Alexa Top 500 have at least one under-preforming server. We further evaluate Oak on experimental and popular existing webpages, and demonstrate its effectiveness in making decisions in existing environments and with a distributed user base.

Enabling communication between routers and endpoints has long been sought after as an approach to congestion control in the Internet. However, the narrow-waist of TCP/IP has complicated the deployment of such communication. In this paper, we present Kick-Ass1, a congestion control mechanism that enables explicit rate congestion control protocols to be deployed within the TCP/IP stack. The key idea is to utilize packet lengths as a vehicle to communicate fine-grained explicit rate and other information from routers to endpoints and vice versa. Given that our approach (i) requires no explicit coordination among Kick-Ass routers, (ii) no explicit coordination among Kick-Ass routers and endpoints, and (iii) is effective on paths that include legacy routers, it provides a practical road towards a faster Internet, today. Using large-scale simulations, testbed experiments, and wide-area Internet evaluations, we demonstrate that (i) a basic explicit-rate protocol using the Kick-Ass mechanism improves flow completion times by up to an order of magnitude and outperforms endpoint-based approaches, including CUBIC and PCC. (ii) Kick-Ass is incrementally deployable on the Internet. (iii) Deploying Kick-Ass at end-hosts and edge routers can enable the above performance benefits, without waiting for universal adoption. (iv) Our packet-fragmentation mechanism is well behaved on the Internet.