OSERENA: a Coloring Algorithm Optimized for Dense Wireless Networks

Amdouni, Ichrak; Minet, Pascale; Adjih, Cédric

doi:10.2991/ijndc.2013.1.1.3

Cited by 5 publications

(3 citation statements)

References 19 publications

(21 reference statements)

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“…Subsequently, during the neighbourhood detection phase, each node determines its neighbour nodes by periodically emitting “Hello” messages to its adjacent nodes at the 1-hop. Readers interested in more details on OSERENA can consult References [34,35,36] (Table A1). The second OCARI feature guarantees a low consumption rate.…”

Section: Figure A1mentioning

confidence: 99%

An OCARI-Based Wireless Sensor Network for Heat Measurements during Outdoor Fire Experiments

Carlotti

Silvani

Innocenti

et al. 2019

Sensors

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This study presents a new wireless measurement system for outdoor fire experiments based on an OCARI wireless sensor network (WSN). The open-source radio communication OCARI stack (‘Open Communication Protocol for Ad Hoc Reliable Industrial Instrumentation’) allows to overcome the limitations of the previous wireless solutions for fire measurements, especially those based on proprietary systems, such as Zigbee, wherein users cannot control energy consumption and timestamping. This paper presents the design of an Atmel/ARM-based platform compatible with the wireless OCARI stack, adapted to record and communicate data from heat transducers—namely, a K-type thermocouple and heat fluxmeter. A 5-node WSN using heat sensors faces a 10 m2 natural fire of excelsior (pine wood) in outdoor conditions. Measurements from the OCARI-WSN were compared with the same measurements simultaneously recorded on a datalogger, a standard wired solution in fire science. Thus, six fire experiments were performed for different fuel loads, and the incident heat radiation varies with the fire size under variable wind conditions. The technological breakdown of timestamping identified in previous low-energy consumption and low-cost wireless systems is overcome by the present solution.

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Section: Figure A1mentioning

confidence: 99%

An OCARI-Based Wireless Sensor Network for Heat Measurements during Outdoor Fire Experiments

Carlotti

Silvani

Innocenti

et al. 2019

Sensors

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“…The distributed coloring method has been proposed in [8,[19][20][21][22]. When nodes are assigned colors with the distributed coloring method, each node assigns itself with the minimum color number so that the whole network can minimize the number of colors.…”

Section: Related Workmentioning

confidence: 99%

A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

Zeng

Yang

Liu

2014

International Journal of Distributed Sensor Networks

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TDMA protocols are recognized to save energy consumption by avoiding unnecessary idle listening and communication collision. As sensor nodes are usually equipped with limited resource supply, they are thus desirable to improve network capacity and energy efficiency by adopting TDMA scheduling for wireless sensor networks (WSNs). This paper proposes a TDMA scheduling approach, which reuses time slots among sensor nodes, for WSNs. Specifically, with the idea of consecutive slots assignment, our approach can reduce both the time and energy cost of establishing nodes' schedule. Furthermore, the energy of node's switching is also reduced. To avoid the transmission of a node's result interference to all irrelevant receivers within its interference range, we develop a slot negotiation mechanism for slot assignment. We perform extensive simulations in NS-2 to evaluate our proposed approach. The results show that our approach outperforms existing TDMA scheduling in terms of time and energy overhead.

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“…Evolutionary algorithms (EA) are wildly used in wireless networks 1 , milling operations 2 and other different area. As an important branch of EA, swarm intelligence algorithms attracted many scholars by the virtue easy applying and high performance.…”

Section: Introductionmentioning

confidence: 99%

A Pair-wise Bare Bones Particle Swarm Optimization Algorithm for Nonlinear Functions

Guo¹,

Sato²

2017

IJNDC

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Bare bones particle swarm optimization is a parameter-free swarm intelligence algorithm which is famous for easy applying. It has aroused wide concern of academic circle on its principles and applications in recent years. However, losing the diversity quickly still causes the premature convergence in the iteration process. Hence, a pair-wise bare bones particle swarm optimization algorithm is proposed in this paper to balance the exploration and exploitation. Moreover, a separate iteration strategy is used in pair-wise operator to enhance the diversity of the swarm. A pair of particles will be placed in different groups and will be applied with different evolutionary strategies. Also, to verify the performance of the proposed algorithm, a set of well-known nonlinear benchmark functions are used in the experiment. Furthermore, several evolutionary algorithms are also evaluated on the same functions as the control group. Finally, the experiment results and statistical analysis confirm the performance of PBBPSO with nonlinear functions.

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OSERENA: a Coloring Algorithm Optimized for Dense Wireless Networks

Cited by 5 publications

References 19 publications

An OCARI-Based Wireless Sensor Network for Heat Measurements during Outdoor Fire Experiments

An OCARI-Based Wireless Sensor Network for Heat Measurements during Outdoor Fire Experiments

A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

A Pair-wise Bare Bones Particle Swarm Optimization Algorithm for Nonlinear Functions

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