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QC 20230614

We present radio-frequency (RF) information harvesting, a chan-nel sensing technique that takes advantage of the energy in the wireless medium to detect channel activity at essentially no en-ergy cost. RF information harvesting is essential for event-driven wireless sensing applications using battery-less devices that har-vest tiny amounts of energy from impromptu events, such as op-erating a switch, and then transmit the event notification to a one-hop gateway. As multiple such devices may concurrently de-tect events, coordinating access to the channel is key. RF infor-mation harvesting allows devices to break the symmetry between concurrently-transmitting devices based on the harvested energy from the ongoing transmissions. To demonstrate the benefits of RF information harvesting, we integrate it in a tailor-made ultra low-power hardware MAC protocol we call Radio Frequency-Distance Packet Queuing (RF-DiPaQ). We build a hardware/software proto-type of RF-DiPaQ and use an established Markov framework to study its performance at scale. Comparing RF-DiPaQ against sta-ple contention-based MAC protocols, we show that it outperforms pure Aloha and 1-CSMA by factors of 3.55 and 1.21 respectively in throughput, while it saturates at more than double the offered load compared to 1-CSMA. As traffic increases, the energy saving of RF-DiPaQ against CSMA protocols increases, consuming 36% less energy than np-CSMA at typical offered loads., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Embedded Systems

We present the experimental evaluation of different security mechanisms applied to persistent state in intermittent computing. Whenever executions become intermittent because of energy scarcity, systems employ persistent state on non-volatile memories (NVMs) to ensure forward progress of applications. Persistent state spans operating system and network stack, as well as applications. While a device is off recharging energy buffers, persistent state on NVMs may be subject to security threats such as stealing sensitive information or tampering with configuration data, which may ultimately corrupt the device state and render the system unusable. Based on modern platforms of the Cortex M*series, we experimentally investigate the impact on typical intermittent computing workloads of different means to protect persistent state, including software and hardware implementations of staple encryption algorithms and the use of ARM TrustZone protection mechanisms. Our results indicate that i) software implementations bear a significant overhead in energy and time, sometimes harming forward progress, but also retaining the advantage of modularity and easier updates; ii) hardware implementations offer much lower overhead compared to their software counterparts, but require a deeper understanding of their internals to gauge their applicability in given application scenarios; and iii) TrustZone shows almost negligible overhead, yet it requires a different memory management and is only effective as long as attackers cannot directly access the NVMs., QC 20210907

Careful energy management is a prerequisite for long-term, unattended operation of solar-harvesting sensing systems. We observe that in many applications the utility of sensed data varies over time, but current energy-management algorithms do not exploit prior knowledge of these variations for making better decisions. This paper presents PreAct, the first energy-management algorithm that exploits time-varying utility to optimize application performance. PreAct's design combines strategic long-term planning of future energy utilization with feedback control to compensate for deviations from the expected conditions. We implement PreAct on a low-power microcontroller and compare it against the state of the art on multiple years of real-world data. Our results demonstrate that PreAct is up to 53 % more effective in utilizing harvested solar energy and significantly more robust to uncertainties and inefficiencies of practical systems. These gains translate into an improvement of 28% in the end-to-end performance of a real-world application we investigate when using PreAct.

Buildings are amongst the largest consumers of electrical energy in developed countries. Building efficiency can be improved by adapting building systems to a change in the environment or user context. Appropriate action, however, can only be taken if the building control system has access to reliable real-time data. Sensors providing this data need to be ubiquitous, accurate, have low maintenance cost, and should not violate privacy of building occupants. We conducted a 3 year study in a mid-size office space with 15 offices and 25 people. Specifically, we focused on sensing modalities that can help improve energy efficiency of buildings. We have deployed 25 indoor climate sensor nodes and 41 wireless power meters, submetered 12 electric loads in circuit breaker boxes, logged data from our building control system and tracked activity on 40 desktop computers. We summarize our experiences with the cost, data yields, and user privacy concerns of the different sensing modalities and evaluate their accuracy using ground-truth experiments.

Long-term tracking of small-size animals with wireless sensor networks remains a challenge as only limited energy harvesting and storage is possible due to stringent size and weight constraints for animal collars. We present first experiences towards a perpetual monitoring system for free-living flying foxes. The high mobility of flying foxes requires a delay tolerant wireless network for data gathering: GPS positions and sensor data have to be stored locally until a wireless gateway deployed in bat congregation areas, so called roosting camps, comes within radio range. In this chapter, we present the system architecture and discuss our design decisions towards sustainable and reliable monitoring of flying foxes with a limited energy budget for sensing, storage and communication. Using empirical data from three free-living flying foxes, we characterize the overall system performance in terms of energy consumption and latency.

Current computerised methods used at the large open pit truck and shovel iron ore operation in Quebec, show several limitations. The short range production planning (SRPP) process objective is to suggest an optimal mining sequence given an initial pit configuration and to improve grade control and equipment use. A new software package, developed by Ad Opt and Quebec Cartier Mining, and based on dynamic programming, provides a daily solution comprising a precise drilling and blasting sequence, shovel displacements and utilisation in time, as well as the type and quantity of material to be mined. It is being used at Mount Wright to obtain suggested planning strategies and in "what if" scenarios. Automated interfacing with the long range planning and truck dispatching systems is underway., Current computerised methods used at the large open pit truck and shovel iron ore operation in Quebec, show several limitations. The short range production planning (SRPP) process objective is to suggest an optimal mining sequence given an initial pit configuration and to improve grade control and equipment use. A new software package, developed by Ad Opt and Quebec Cartier Mining, and based on dynamic programming, provides a daily solution comprising a precise drilling and blasting sequence, shovel displacements and utilisation in time, as well as the type and quantity of material to be mined. It is being used at Mount Wright to obtain suggested planning strategies and in "what if" scenarios. Automated interfacing with the long range planning and truck dispatching systems is underway.

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