When Scavengers Meet Industrial Wireless

Martínez, Borja; Vilajosana, Xavier; Chraim, Fabien; Vilajosana, Ignasi; Pister, Kristofer S. J.

doi:10.1109/tie.2014.2362891

Cited by 30 publications

(23 citation statements)

References 20 publications

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“…Some realistic models for power consumption in wireless sensor network devices are presented in [36,37]. These works focus on obtaining realistic models that split the overall consumption into different sources.…”

Section: Energy Model Validation and Discussionmentioning

confidence: 99%

Building IoT Applications with Raspberry Pi and Low Power IQRF Communication Modules

et al. 2016

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Typical Internet of Things (IoT) applications involve collecting information automatically from diverse geographically-distributed smart sensors and concentrating the information into more powerful computers. The Raspberry Pi platform has become a very interesting choice for IoT applications for several reasons: (1) good computing power/cost ratio; (2) high availability; it has become a de facto hardware standard; and (3) ease of use; it is based on operating systems with a big community of users. In IoT applications, data are frequently carried by means of wireless sensor networks in which energy consumption is a key issue. Energy consumption is especially relevant for smart sensors that are scattered over wide geographical areas and may need to work unattended on batteries for long intervals of time. In this scenario, it is convenient to ease the construction of IoT applications while keeping energy consumption to a minimum at the sensors. This work proposes a possible gateway implementation with specific technologies. It solves the following research question: how to build gateways for IoT applications with Raspberry Pi and low power IQRF communication modules. The following contributions are presented: (1) one architecture for IoT gateways that integrates data from sensor nodes into a higher level application based on low-cost/low-energy technologies; (2) bindings in Java and C that ease the construction of IoT applications; (3) an empirical model that describes the consumption of the communications at the nodes (smart sensors) and allows scaling their batteries; and (4) validation of the proposed energy model at the battery-operated nodes.

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Section: Energy Model Validation and Discussionmentioning

confidence: 99%

Building IoT Applications with Raspberry Pi and Low Power IQRF Communication Modules

et al. 2016

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“…The transmissions are added to graph G one by one (lines 5-17). For each link in φ k , if the type of the link is L1, there are two transmissions (the initial transmission and the first retransmissions) on that link, and two corresponding vertices {v a , v a+1 } are added into vertex set V (lines [7][8]. If the type of the link is L2, there is one transmission (the second retransmission) passing through the link, and only one vertex {v a } is added (lines 14-15).…”

Section: B Establishing the Releasing Sequence Graphmentioning

confidence: 99%

“…Otherwise, the deadline will be missed. Therefore, its prime priority is set to the highest value (lines [6][7][8]. V is the set of vertices that have been released but not scheduled.…”

Section: Our Heuristic Algorithm: Extended Rate-monotonic (E-rm)mentioning

confidence: 99%

“…IRELESSHART [1]- [3] is a wireless networking technology that has been widely used in industrial applications, e.g., industrial process control [4], collaborative location and tracking systems [5], and monitoring systems [6], [7]. These applications usually have stringent requirements regarding the reliability and real-time performance of WirelessHART networks.…”

Section: Introduction Wmentioning

confidence: 99%

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Reliability and Temporality Optimization for Multiple Coexisting WirelessHART Networks in Industrial Environments

Jin

Kong

et al. 2017

IEEE Trans. Ind. Electron.

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Abstract-WirelessHART is a networking technology that is widely used in industrial wireless sensor networks. Its reliability and real-time performance are essential to industrial production. Many works have studied these two aspects, primarily focusing on a single WirelessHART network. However, multiple WirelessHART networks usually coexist in a real industrial environment. Applying existing approaches to such coexisting networks would cause performance degradation due to communication interference among these networks. In this paper, we propose a holistic framework that optimizes both reliability and temporality for multiple coexisting networks. The framework consists of two levels. The upper level targets communication channel management, and the lower level addresses data flow scheduling. For the upper level, we propose a network isolation algorithm that improves the data transmission reliability through dynamically adjusting channel assignments to different WirelessHART networks. For the lower level, we propose data flow scheduling algorithms that guarantee the temporality of data flows within each isolated network. These algorithms minimize the number of channels reserved by each isolated network and further enhance the transmission reliability through alleviating channel resource contention. We conduct trace-driven simulations of the channel management algorithm, and the results demonstrate that our algorithm exhibits stable performance and reduces packet loss by 36%. For the scheduling algorithms, the simulations demonstrate that in contrast with existing algorithms, the greater the number of coexisting networks, the fewer resources our algorithms use. When eight networks coexist, our algorithms outperform existing ones by consuming up to 63% fewer channel resources.

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“…In order to obtain the deterministic services for industrial automations [12], TSCH protocol is introduced as part of IEEE802.15.4e standard [10]. It uses frequency hopping method, in which different transmission frequencies are chosen at different times by the nodes of WSN.…”

Section: Introductionmentioning

confidence: 99%

Simulation Study of Topological Structures and Node Coordinations for Deterministic WSN with TSCH

Perumalla

Ramanjaneyulu

Kolli

2017

JOIV : Int. J. Inform. Visualization

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Abstract-Time-Slotted Channel hopping (TSCH) that was introduced in IEEE802.15.4e is a promising technique to offer deterministic data deliveries in Wireless Sensor Networks (WSN). Its main strength lies in using multiple channels for the transmissions, using frequency hopping method. However, it takes more time for initializing the network, as beacons have to be released on multiple frequencies and scanning needs to be carried out by the devices in all those frequencies for joining the network. In this work, a simulation study is carried out to investigate the effect of these delays for different types of multihop networks. The benefit of introducing multiple coordinators in reducing these time delays is also studied. It is found that the delays are increasing linearly with the number of hops in the network and adding an additional coordinator can bring down the initialization time by half.

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When Scavengers Meet Industrial Wireless

Cited by 30 publications

References 20 publications

Building IoT Applications with Raspberry Pi and Low Power IQRF Communication Modules

Building IoT Applications with Raspberry Pi and Low Power IQRF Communication Modules

Reliability and Temporality Optimization for Multiple Coexisting WirelessHART Networks in Industrial Environments

Simulation Study of Topological Structures and Node Coordinations for Deterministic WSN with TSCH

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