Energy-efficient computing for wildlife tracking

Juang, Philo; Oki, Hidekazu; Wang, Yong; Martonosi, Margaret; Peh, Li Shiuan; Rubenstein, Daniel I.

doi:10.1145/605397.605408

Cited by 1,075 publications

(23 citation statements)

References 20 publications

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“…Eon [Sorber et al 2007] is one of the earliest efforts to target harvested-energy computation, scheduling prioritized tasks based on energy availability. ZebraNet [Juang et al 2002] dealt with the challenges of solar energy in an adversarial environment.…”

Section: Energy-harvesting and Intermittent Computingmentioning

confidence: 99%

Alpaca: intermittent execution without checkpoints

Maeng

Colin

Lucia

2017

Proc. ACM Program. Lang.

192

261

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The emergence of energy harvesting devices creates the potential for batteryless sensing and computing devices. Such devices operate only intermittently, as energy is available, presenting a number of challenges for software developers. Programmers face a complex design space requiring reasoning about energy, memory consistency, and forward progress. This paper introduces Alpaca, a low-overhead programming model for intermittent computing on energy-harvesting devices. Alpaca programs are composed of a sequence of userdefined tasks. The Alpaca runtime preserves execution progress at the granularity of a task. The key insight in Alpaca is the privatization of data shared between tasks. Updates of shared values in a task are privatized and only committed to main memory on successful execution of the task, ensuring that data remain consistent despite power failures. Alpaca provides a familiar programming interface and a highly efficient runtime model. We also present an alternate version of Alpaca, Alpaca-undo, that uses undo-logging and rollback instead of privatization and commit. We implemented a prototype of both versions of Alpaca as an extension to C with an LLVM compiler pass. We evaluated Alpaca, and directly compared to three systems from prior work. Alpaca consistently improves performance compared to the previous systems, by up to 23.8x, while also improving memory footprint in many cases, by up to 17.6x. C1:A program must preserve progress despite losing volatile state on power failures. C2: A program must have a consistent view of its state across volatile and non-volatile memory. C3: A program must respect atomicity constraints (e.g., sampling related sensors together).G1: Applications should place as few restrictions on the hardware as possible.G2: Applications should be tunable at design time to use the energy storage capacity efficiently. G3: Applications should minimize runtime overhead and memory footprint. Recent work made progress toward several of these goals, but necessarily compromised on others. This paper develops Alpaca 1 , a programming and execution model that allows software to execute intermittently. Like state-of-the-art systems, Alpaca preserves progress despite power failures (C1) and ensures memory consistency (C2). Alpaca uses a static task model that can adhere to programmer-provided atomicity constraints and energy availability (G2, C3). Memory updates made by an Alpaca task only commits atomically when the task completes. By discarding memory updates on power failure, Alpaca can restart a task with negligible cost, without checkpointing the volatile state as in prior work [Lucia and Ransford 2015;; Van Der Woude and Hicks 2016] (G3). Unlike prior work that requires the entire memory to be non-volatile [Van Der Woude and Hicks 2016], Alpaca can leverage both volatile and non-volatile memory (G1). We present two different versions of Alpaca with different design choices. Alpaca's design differences, relative to state-of-the-art systems, translate into performance gains of 4-5.2x o...

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Section: Energy-harvesting and Intermittent Computingmentioning

confidence: 99%

Alpaca: intermittent execution without checkpoints

Maeng

Colin

Lucia

2017

Proc. ACM Program. Lang.

192

261

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“…preying, running, etc.). Thus, we imported a second movement model from the ZebraNet GPS data to model the behavior of real animal mobility [6]. We evaluated the performance of the proposed opportunistic network in ONE simulator with the imported movement models [16].…”

Section: A Simulation Set-upmentioning

confidence: 99%

Towards a New Opportunistic IoT Network Architecture for Wildlife Monitoring System

Ayele

Meratnia

Havinga

2018

2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)

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Abstract-In this paper we introduce an opportunistic dual radio IoT network architecture for wildlife monitoring systems (WMS). Since data processing consumes less energy than transmitting the raw data, the proposed architecture leverages opportunistic mobile networks in a fixed LPWAN IoT network infrastructure. This solution will facilitate an IoT devices to be deployed for ultra-low power and sustainable wildlife monitoring applications. As part of the IoT infrastructure, a LoRa based network is presented with coverage characterization and preliminary test bed deployment for wildlife tracking purpose. In addition, through simulation, the utilization of existing BLE based opportunistic data collection protocols for the proposed architecture is investigated.

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“…In the context of our case study, two wildlife monitoring projects are of interest: ZebraNet [25] and SWIM [36]. In the first case, zebra are fitted with collars and the data is collected by a mobile node on a vehicle that moves around the area.…”

Section: Opportunistic Networkmentioning

confidence: 99%

Hybrid performance modelling of opportunistic networks

Bortolussi

Galpin

Hillston

2012

Electron. Proc. Theor. Comput. Sci.

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We demonstrate the modelling of opportunistic networks using the process algebra stochastic HYPE. Network traffic is modelled as continuous flows, contact between nodes in the network is modelled stochastically, and instantaneous decisions are modelled as discrete events. Our model describes a network of stationary video sensors with a mobile ferry which collects data from the sensors and delivers it to the base station. We consider different mobility models and different buffer sizes for the ferries. This case study illustrates the flexibility and expressive power of stochastic HYPE. We also discuss the software that enables us to describe stochastic HYPE models and simulate them

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Energy-efficient computing for wildlife tracking

Cited by 1,075 publications

References 20 publications

Alpaca: intermittent execution without checkpoints

Alpaca: intermittent execution without checkpoints

Towards a New Opportunistic IoT Network Architecture for Wildlife Monitoring System

Hybrid performance modelling of opportunistic networks

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