Capacity analysis of multi-hop wireless sensor networks using multiple transmission channels: A case study using IEEE 802.15.4 based networks

Namboothiri, P Gireesan; Krishna, Murali

doi:10.1109/lcn.2010.5735691

Cited by 9 publications

(3 citation statements)

References 5 publications

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“…Network nodes will never use more than 5 channels at a time, which is the integer part of 16 channels divided by 3 hops. For more than 3 hops, nodes can reuse channels without interfering each other . Only the root would theoretically need to have up to 16 channels.…”

Section: Simulation Environment and Sfx Scalability Studymentioning

confidence: 99%

A distributed density optimized scheduling function for IEEE 802.15.4e TSCH networks

Municio

Spaey

Latré

2018

Trans Emerging Tel Tech

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The Industrial Internet of Things is a challenge for wireless sensor networks, where ultrareliability, guaranteed performance, and ultralow‐power consumption are mandatory requirements to enable critical IoT applications. The time‐slotted channel hopping (TSCH) mode of the IEEE 802.15.4e standard is one of the most promising technologies to accomplish these requirements by yielding guaranteed performance and, simultaneously, efficiently combating external interference and multipath fading. One of the challenges in TSCH networks is to build an efficient schedule for managing the access of the nodes to the timeslots and channels. Several scheduling algorithms have been proposed. Currently, the Scheduling Function Zero SFx is one of the proposed scheduling algorithms for 6TiSCH, the ongoing standard for an IPv6‐enabled stack working over TSCH. SFx is based on random resource allocation according to the traffic demand, which makes it inadequate for large‐scale and dense deployments due to internal collisions. This paper has two main goals. First, we extensively investigate the performance of SFx for large‐scale and dense scenarios, analyze its scalability, and identify its scheduling limitations. Second, we present a new TSCH‐based scheduling function, ie, the distributed broadcast‐based scheduling (DeBraS) algorithm, a scheduling solution designed for dense deployments based on sharing scheduling information between nodes to reduce collisions proactively. We show, through extensive and large‐scale simulations, that DeBraS supports much larger densities than state‐of‐the‐art scheduling functions, outperforming the current distributed 6TiSCH algorithm SFx up to 1.61 times in terms of throughput for large network sizes, at the expense of an increase in power consumption.

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Section: Simulation Environment and Sfx Scalability Studymentioning

confidence: 99%

A distributed density optimized scheduling function for IEEE 802.15.4e TSCH networks

Municio

Spaey

Latré

2018

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…III-C. Instead, the width of the schedule, i.e., the number of available channel offsets, is at least W = 3, since frequencies can be reused every 3-hops, thus avoiding also collisions due to interference 1 [29], [30].…”

Section: Detas Algorithm Descriptionmentioning

confidence: 99%

Decentralized Traffic Aware Scheduling in 6TiSCH Networks: Design and Experimental Evaluation

Accettura

Vogli

Palattella

et al. 2015

IEEE Internet Things J.

102

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Abstract-This paper capitalizes on two emerging trends, i.e. the growing use of wireless at the edge of industrial control networks and the growing interest to integrate IP into said networks. This is facilitated by recent design contributions from the IEEE and the IETF, where the former developed a highly efficient deterministic time-frequency scheduled medium access control protocol in form of IEEE 802.15.4e TSCH and the latter IPv6 networking paradigms in form of 6LoWPAN/ROLL, and scheduling approaches in form of 6TiSCH. The focus of the present work is on advancing the state of the art of deterministic 6TiSCH schedules towards more flexible but equally reliable distributed approaches. In addition, this paper aims to introduce the first implementation of 6TiSCH networks for factory automation environments: it outlines the challenges faced to overcome the scalability issues inherent to multi-hop dense low-power networks; the experimental results confirm that the naturally unreliable radio medium can support time-critical and reliable applications. These developments pave the way for wireless industry-grade monitoring approaches.

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“…In this study, one of the most utilized WSN platforms, MicaZ motes from Crossbow Technology, Inc., has been used as the testbed [26]. This platform is equipped with an IEEE 802.15.4 compliant, Chipcon CC240 RF transceiver and Atmega 128L micro-controller.…”

Section: Hardware and Softwarementioning

confidence: 99%

Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System

et al. 2014

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This paper presents a wireless sensor node (WSN) system where an electromagnetic (EM) energy harvester is utilized for charging its rechargeable batteries while the system is operational. The capability and the performance of an in-house low-frequency EM energy harvester for charging rechargeable NiMH batteries were experimentally verified in comparison to a regular battery charger. Furthermore, the power consumption of MicaZ motes, used as the WSN, was evaluated in detail for different operation conditions. The battery voltage and current were experimentally monitored during the operation of the MicaZ sensor node equipped with the EM vibration energy harvester. A compact (24.5 cm 3 ) in-house EM energy harvester provides approximately 65 µA charging current to the batteries when excited by 0.4 g acceleration at 7.4 Hz. It has been shown that the current demand of the MicaZ mote can be compensated for by the energy harvester for a specific low-power operation scenario, with more than a 10-fold increase in the battery lifetime. The presented results demonstrate the autonomous operation of the WSN, with the utilization of a vibration-based energy harvester. OPEN ACCESSEnergies 2014, 7 6324

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Capacity analysis of multi-hop wireless sensor networks using multiple transmission channels: A case study using IEEE 802.15.4 based networks

Cited by 9 publications

References 5 publications

A distributed density optimized scheduling function for IEEE 802.15.4e TSCH networks

A distributed density optimized scheduling function for IEEE 802.15.4e TSCH networks

Decentralized Traffic Aware Scheduling in 6TiSCH Networks: Design and Experimental Evaluation

Powering-up Wireless Sensor Nodes Utilizing Rechargeable Batteries and an Electromagnetic Vibration Energy Harvesting System

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