Space Wireless Sensor Networks for planetary exploration: Node and network architectures

Rodrigues, Pedro; Oliveira, André; Oddi, Guido; Liberati, Francesco; Álvarez, F.; Cabás, Ramiro; Vladimirova, Tanya; Zhai, Xiaojun; Jing, Hongyuan; Crosnier, Michael

doi:10.1109/ahs.2014.6880175

Cited by 12 publications

(8 citation statements)

References 16 publications

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“…Energy efficiency is an important goal that should be considered when designing the node architecture and data processing algorithms of WSNs [23] for planetary exploration. This is because such WSNs operate in unfriendly and unattended environments, where it is impossible to access or replace dead nodes.…”

Section: Wsn Data Processing: Overview and Objectivesmentioning

confidence: 99%

Efficient Data-Processing Algorithms for Wireless-Sensor-Networks-Based Planetary Exploration

Zhai

Vladimirova

2016

Journal of Aerospace Information Systems

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Abstract:The SWIPE project (Space Wireless Sensor Networks for Planetary Exploration) aims to design a wireless sensor network (WSN) , which consists of small wireless sensor nodes dropped onto the Moon surface to collect scientific measurements. Data gathered from the sensors will be processed and aggregated for uploading to a lunar orbiter and subsequent transmission to Earth. In this paper efficient data processing/fusion algorithms are proposed, the purpose of which is to integrate the scientific sensor data collected by the WSN, reducing the data volume without sacrificing the data quality to satisfy energy constraints of WSN nodes operating in the extreme Moon environment. The results of an extensive simulation experiment targeted at the SWIPE lunar exploration mission is reported, which quantifies the performance efficiency of the data processing scheme. It is shown that the proposed data processing algorithms can reduce the WSN node energy consumption significantly, decreasing the data transmission energy up to 91%. In addition, it is shown that up to 99% of the accuracy of the original data can be preserved in the final reconstructed data.

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Section: Wsn Data Processing: Overview and Objectivesmentioning

confidence: 99%

Efficient Data-Processing Algorithms for Wireless-Sensor-Networks-Based Planetary Exploration

Zhai

Vladimirova

2016

Journal of Aerospace Information Systems

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“…Having more than one data sink increases the tolerance to possible Figure 1. (a) Planetary exploration scenario [7] and (b) SWIPE node [22].…”

Section: Network System View and Componentsmentioning

confidence: 99%

An any‐sink energy‐efficient routing protocol in multi‐hop wireless sensor networks for planetary exploration

Oddi

Pietrabissa

Liberati

et al. 2015

Int J Communication

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SUMMARYWireless sensor networks (WSNs) are made of spatially distributed autonomous sensors, which cooperate to monitor physical or environmental parameters and to deliver such data to one or more data sinks. A promising field of application of WSNs is planetary exploration, characterized by a continuous monitoring of the surface to have clear notion of planet conditions and prepare for future manned missions. The potentially large size of the region to be monitored and the line-of-sight limitations (as, for instance, on the Moon, which is the case study discussed in the paper) hamper the possibility of having 1-hop sensorsink communications. Therefore, to allow sensed data to reach the sink(s), the sensors must be able to create and maintain a multi-hop ad hoc network. This paper proposes an ad hoc routing algorithm applicable to WSNs for planetary exploration, aiming at (i) assuring any-cast communications with multiple data sinks, (ii) minimizing the control overhead for routing maintenance, (iii) being light in terms of memory/computational requirements, to be installed into low-power and low-memory/processing devices, (iv) being rapid to reconfigure in the presence of node failures and (v) optimizing the choice of the paths, to achieve energy balancing and saving. Extensive simulations show the efficiency of the proposed approach.

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“…The single-sensor scheduling protocol defined above can be extended to the case of nodes hosting different types of sensors (for example, the SWIPE node prototype is equipped with thermal, radiation, illumination and dust deposition sensors [6]). Considered each sensor type (e.g.…”

Section: B Multi-sensor Scheduling Algorithmmentioning

confidence: 99%

“…[4]. This paper considers the reference scenario studied in the SWIPE research project [5], [6], focused on a WSN deployed on a planet's surface for monitoring and gathering relevant data in preparation of manned missions. Such a scenario entails challenges that are often encountered in other WSN applications [7]: the need for manufacturing low cost, low mass, low volume nodes, with consequent stringent limitations on the memory and processing resources available, low space/weight budget available for energy storage systems, with consequent low autonomy on nodes,…”

Section: Introductionmentioning

confidence: 99%

A lightweight sensor scheduling algorithm for clustered wireless sensor networks

Liberati

Oddi

Lanna

et al. 2015

2015 23rd Mediterranean Conference on Control and Automation (MED)

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This paper deals with the design of a lightweight sensor scheduling algorithm in clustered wireless sensor networks (WSNs) for environmental observation. The aim is that of achieving energy savings and a fair distribution of the sensing task among WSN nodes, while ensuring that critical network tasks, such as data fusion, are not impaired. The proposed scheduling policy takes into account feedback on nodes' health status and the quality of the information provided by the nodes to be scheduled. As a result, dynamically variable schedules are produced, adapted to the current status of the WSN. Simulation results are presented to highlight the relevant features of the algorithm.

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Space Wireless Sensor Networks for planetary exploration: Node and network architectures

Cited by 12 publications

References 16 publications

Efficient Data-Processing Algorithms for Wireless-Sensor-Networks-Based Planetary Exploration

Efficient Data-Processing Algorithms for Wireless-Sensor-Networks-Based Planetary Exploration

An any‐sink energy‐efficient routing protocol in multi‐hop wireless sensor networks for planetary exploration

A lightweight sensor scheduling algorithm for clustered wireless sensor networks

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