On Link Estimation in Dense RPL Deployments

The Internet of Things vision foresees billions of devices to connect the physical world to the digital world. Sensing applications such as structural health monitoring, surveillance or smart buildings employ multi-hop wireless networks with high density to attain sufficient area coverage. Such applications need networking stacks and routing protocols that can scale with network size and density while remaining energy-efficient and lightweight. To this end, the IETF RoLL working group has designed the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). This paper discusses the problems of link quality estimation and neighbor management policies when it comes to handling high densities. We implement and evaluate different neighbor management policies and link probing techniques in Contiki’s RPL implementation. We report on our experience with a 100-node testbed with average 40-degree density. We show the sensitivity of high density routing with respect to cache sizes and routing metric initialization. Finally, we devise guidelines for design and implementation of density-scalable routing protocols

The future prospects of muon colliders and neutrino factories

The potential of muon beams for high energy physics applications is described along with the challenges of producing high quality muon beams. Two proposed approaches for delivering high intensity muon beams, a proton driver source and a positron driver source, are described and compared. The proton driver concepts are based on the studies from the Muon Accelerator Program (MAP). The MAP effort focused on a path to deliver muon-based facilities, ranging from neutrino factories to muon colliders, that could span research needs at both the intensity and energy frontiers. The Low EMittance Muon Accelerator (LEMMA) concept, which uses a positron-driven source, provides an attractive path to very high energy lepton colliders with improved particle backgrounds. The recent study of a 14 TeV muon collider in the LHC tunnel, which could leverage the existing CERN injectors and infrastructure and provide physics reach comparable to the 100 TeV FCC-hh, at lower cost and with cleaner physics conditions, is also discussed. The present status of the design and R&D efforts towards each of these sources is described. A summary of important R&D required to establish a facility path for each concept is also presented.Comment: 29 pages, 17 figure

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

The ContikiMAC Radio Duty Cycling Protocol

Low-power wireless devices must keep their radio transceivers off as much as possible to reach a low power consumption, but must wake up often enough to be able to receive communication from their neighbors. This report describes the ContikiMAC radio duty cycling mechanism, the default radio duty cycling mechanism in Contiki 2.5, which uses a power efficient wake-up mechanism with a set of timing constraints to allow device to keep their transceivers off. With ContikiMAC, nodes can participate in network communication yet keep their radios turned off for roughly 99% of the time. This report describes the ContikiMAC mechanism, measures the energy consumption of individual ContikiMAC operations, and evaluates the efficiency of the fast sleep and phase-lock optimizations

Thermal Stress Based Model Predictive Control of Power Electronic Converters in Electric Drives Applications

Power electronics is used increasingly in a wide range of application fields such as variable speed drives, electric vehicles and renewable energy systems. It has become a crucial component for the further development of emerging application fields such as lighting, more-electric aircrafts and medical systems. The reliable operation over the designed lifetime is essential for any power electronic system, particularly because the reliability of power electronics is becoming a prerequisite for the system safety in several key areas like energy, medicine and transportation. The thermal stress of power electronic components is one of the most important causes of their failure. Proper thermal management plays an important role for more reliable and cost effective energy conversion. As one of the most vulnerable and expensive components, power semiconductors, are the focus of this thesis. Active thermal control is a possibility to control the junction temperatures of power semiconductors in order to reduce the thermal stress. For this purpose the finite control-set model predictive control (FCS-MPC) is chosen. In FCS-MPC the switching vector is selected using a multi-parameter optimization that can include non-linear electric and thermal stress related models. This switching vector is directly applied to the physical system. This allows the direct control of the switching-state and the current through each semiconductor at each time instant. For cost-effective control of the thermal stress a measure for the degradation of the semiconductor's lifetime is necessary. Existing lifetime models in literature are based on the thermal cycling amplitudes and maximum values of recorded junction temperature profiles. For online estimation of the degradation, a method to detect the junction temperatures of the semiconductors during operation is designed and validated. An existing and proven lifetime model is adapted for online estimation of the thermal stress. An algorithm for the FCS-MPC is written that utilizes this model to drive the inverter with reduced stress and equalize the degradation of the semiconductors in a power module. The algorithm is demonstrated in simulation and validated in experiment. A technique to find the optimal trade-off between reduction of the thermal stress and allowing additional losses in the system is given. The effect of rotor flux variation of the machine on the junction temperatures of the driving inverter is investigated. It can be used as another parameter to control the junction temperature. This allows increasing the maximal thermal cycling amplitude that can be compensated by an active thermal controller. A suitable controller is proposed and validated in experiment. The integration of this technique into the FCS-MPC is presented

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated