Continuous Sensing on Intermittent Power

Majid, Amjad Yousef; Schilder, Patrick; Langendoen, Koen

doi:10.1109/ipsn48710.2020.00-36

Cited by 14 publications

(5 citation statements)

References 33 publications

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“…Why not compare with Coalesced Intermittent Sensor (CIS)? CIS [41] only works for scenarios where the target energy is variable but equal for every node. Here, each node keeps track of the energy at the other nodes and then calculates the number of active nodes to randomly chooses whether to sleep or wake up.…”

Section: Discussionmentioning

confidence: 99%

“…This is a more straightforward case than the previous one because, unlike the previous case, each node can easily calculate the energy status of the other nodes. Previous works [41] have focused on the second scenario, and thus we focus on the more explored scenario where the available energy at each node varies.…”

Section: Energy Characteristicsmentioning

confidence: 99%

“…For a swarm of identical nodes to synchronize, multiple-node support is necessary, which involves the recovery of conflicting packets. Our closest related work, CIS [41], enables continuous sensing with distributed battery-free devices. Unlike AICS, CIS only considers the scenario where the energy available to every node is the same.…”

Section: Related Workmentioning

confidence: 99%

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Amalgamated Intermittent Computing Systems

Islam

Luo

Nirjon

2023

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation

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source type, it sends a notification. A battery-powered system is always on and thus can capture data and identify when the bell rang at time unit 2 (Figure 1a). However, an intermittent system that activates once every three seconds misses capturing the event (Figure 1b). Even if a battery-free node captures the sample, it may fail to finish processing it in time, resulting in an undetected event. Multiple identical nodes are also redundant because they will all be active simultaneously (Figure 1c).The opportunity lies in that only one of the many intermittent systems must capture and process the event successfully to identify if the bell rang. Thus, scheduling the wake-up and sleep cycle can amalgamate three identical intermittent systems with only one active node at any time. As a result, an amalgamated intermittent system captures and processes all the samples and can identify the bell ring at time unit 2 in Figure 1d. In summary, with sufficient intermittent systems working as an amalgamated system, we can emulate a battery-powered node when the power-off period does not exceed the energy buffer self-discharging time.Though scheduling a swarm of nodes to work collaboratively is not a new problem [54,55], these algorithms rely on active communication among the nodes. Frequent communication among multiple nodes is infeasible in intermittent computing systems, as communication is often the most power-hungry operation [23]. Though zero-power passive communication [20,50] is promising, these methods can communicate with only one node at a time, increasing communication time among all the nodes in a swarm. Moreover, while passive backscatter communication depends on an active receiver [50] or transceivers [20], they require precise (milliseconds or even nanoseconds) time synchronization to allow the sender and receiver to turn on the radio simultaneously. Bonito [21] proposes a learned wake-up schedule for effective communication, and Flync [20] provides an effective solution for neighbor discovery despite intermittency.However, these works only support one device and often require prior knowledge about the energy pattern. Moreover, required packet conflict recovery makes them insufficient for frequent communication across a swarm of systems.We propose AICS, a framework that amalgamates a swarm of intermittent nodes for prolonging the collective power-on period without inter-node communication. AICS allows each intermittent system to decide whether to wake up or go to sleep by predicting other nodes' behavior without communication. To increase successful capture and computing and maximize energy utilization, AICS reduces the number of simultaneously active nodes when the power-off period is less than the self-discharging time.Coalesced Intermittent Sensor (CIS) [41] is our closest related work which randomly wakes up each intermittent system to avoid concurrent active systems. However, it only considers the scenario where the same energy is available to every node of the swarm. Despite being an important scenario...

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Section: Discussionmentioning

confidence: 99%

Section: Energy Characteristicsmentioning

confidence: 99%

See 1 more Smart Citation

Amalgamated Intermittent Computing Systems

Islam

Luo

Nirjon

2023

Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation

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“…Their advantages hence reside at the level of transmission semantics: One-Take transmits data that with high probability induces better classifier performance, irrespective of how those transmissions are scheduled. The protocol thus complements systems that orchestrate specific in-network interactions [50], partially process data prior to transmission [50], or adjust wake-up schedules [33].…”

Section: In-network Aggregation and Inferencementioning

confidence: 99%

One-Take: Gathering Distributed Sensor Data Through Dominant Symbols for Fast Classification

Oostvogels

Michiels

Hughes

2022

2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)

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Sensor networks gather data at one or more gateway devices by sequentially receiving data frames from individual sensor nodes. In cases where applications rely on data that is distributed across several nodes, the latency of such node-by-node data collection scales with the number of nodes and the frame sizes involved, impeding fast decision-making. This paper seeks to overcome that limitation for latency-sensitive classification problems by introducing One-Take, a cross-layer aggregation protocol that aims to decouple the process of data gathering from network size and frame length. The protocol leverages dominance properties between concurrently transmitted symbols to convey so-called collages, messages that describe relationships between data held by several nodes, rather than local information from any single node. Collages thus transmit a hash of distributed data that is computed within the physical layer, thereby communicating more informative features than regular frames of the same length. Experiments on a recent wireless mesh network platform, called Zero-Wire, demonstrate that two-byte collages are delivered correctly 99% of the time and, using public sensor network data sets, show that One-Take achieves a latency reduction of circa 42% relative to node-by-node transmissions.

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“…WSNs consist of a number of stationary or portable sensor nodes that communicate wirelessly to convey detected, processed and stored signals to their receivers, requiring uninterrupted power supply [3]. For this purpose, alkaline batteries have dominantly been used but they come with several drawbacks including their size, maintenance costs, hazardous components and limited lifecycle [4]. Duan et al [5] highlights the current limitations in WSNs and emphasizes that limited power available for sensors cause weak network communication life cycle and difficulties are faced with battery replacement for remote widespread sensors.…”

Section: Introductionmentioning

confidence: 99%

A bistable rotary-translational energy harvester from ultra-low-frequency motions for self-powered wireless sensing

Masabi

Theodossiades

2022

J. Phys. D: Appl. Phys.

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This paper presents the design, theoretical modelling and experimental study of a bi-stable energy harvester using rotary-translational motion for ultra-low frequency and low excitation amplitude energy sources. A spherical magnet is adopted to produce the rotary-translational motion to convert ultralow-frequency kinetic energy into electricity over a wide frequency range. The bi-stable mechanism is realized by introducing two tethering magnets underneath the sphere magnet’s oscillating path, significantly enhancing the operating range of the harvester. A theoretical model including the impact dynamics, magnetic interaction and electromagnetic conversion has been established to explore the electromechanical behaviours of the harvester under different operating conditions. The results illustrate that the energy harvester operates in intra-well or inter-well motion depending on whether the input excitation is adequate to conquer the potential barrier depth. A prototype is developed to illustrate the design and to validate the theoretical model. The prototype generates sufficient power (mW) at frequencies lower than 2 Hz with excitation amplitudes as low as 0.1g. A peak output power of 9 mW (1.53 mW RMS) is obtained at 2 Hz and 0.7g with 750 Ω external load. The developed energy harvester is integrated with an off-the-shelf power management solution to power a wireless sensing system to successfully record real-time temperature variation in the environment.

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Continuous Sensing on Intermittent Power

Cited by 14 publications

References 33 publications

Amalgamated Intermittent Computing Systems

Amalgamated Intermittent Computing Systems

One-Take: Gathering Distributed Sensor Data Through Dominant Symbols for Fast Classification

A bistable rotary-translational energy harvester from ultra-low-frequency motions for self-powered wireless sensing

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