Performance Analysis of IEEE 802.15.4/Zigbee Standard Under Real Time Constraints

Fourati, Lamia Chaari; Kamoun, Lotfı

doi:10.5121/ijcnc.2011.3517

Cited by 27 publications

(25 citation statements)

References 18 publications

(12 reference statements)

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“…This also leads us to simplifying the calculation of Equation (8), allowing one to know the delay impact (Tm k,i ) of the unslotted CSMA/CA algorithm, taking into account their maximum values of parameters that produce the worst-case transmission message between task k,i and, therefore, Tm k,i = Tm wc , where Tm wc is the worst-case transit delay for all messages sent from task k to task i. Various researches have described how to calculate the effective and actual data rates of an IEEE 802.15.4 wireless network, permitting the calculation of the transmission time between neighbors, giving a very rough estimate for Tm wc [33][34][35], which is approximated to Tm wc = 385.308 ms between two neighboring nodes that employ the WiSe mote [38] for wireless microcontrollers, allowing us to reduce the calculation for each flow of the control loop to:…”

Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

“…The slotted CSMA/CA backoff algorithm is based on mainly two variables that correspond to: BE , which is the current backoff exponent, and NB , which is used to count the number of backoffs. The detailed algorithm can be seen in many works [31][32][33][34][35][36][37]. In our previous work, we performed an analysis of schedulability with strict real-time constraints and the synchronous mode of the 802.15.4 protocol [13,20].…”

Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

“…Nevertheless, one of our main goals in this work is to provide a strategy for addressing systems that are highly scalable and the network self-configuration, but fulfilling the real-time constraints imposed by the control system. In order to know the impact of the unslotted CSMA-CA algorithm, we compute the end-to-end delay in the worst case; doing that, the unslotted CSMA/CA parameters take their maximum values, which produce the worst-case transmission message between task k,i , which corresponds to the following maximum values: RetryLimit = 7, macMaxCSMABacko f f = 5 and aMaxBE = 5 [33,35]. This also leads us to simplifying the calculation of Equation (8), allowing one to know the delay impact (Tm k,i ) of the unslotted CSMA/CA algorithm, taking into account their maximum values of parameters that produce the worst-case transmission message between task k,i and, therefore, Tm k,i = Tm wc , where Tm wc is the worst-case transit delay for all messages sent from task k to task i.…”

Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

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Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

et al. 2016

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This paper describes the complete integration of a fuzzy control of multiple evaporator systems with the IEEE 802.15.4 standard, in which we study several important aspects for this kind of system, like a detailed analysis of the end-to-end real-time flows over wireless sensor and actuator networks (WSAN), a real-time kernel with an earliest deadline first (EDF) scheduler, periodic and aperiodic tasking models for the nodes, lightweight and flexible compensation-based control algorithms for WSAN that exhibit packet dropouts, an event-triggered sampling scheme and design methodologies. We address the control problem of the multi-evaporators with the presence of uncertainties, which was tackled through a wireless fuzzy control approach, showing the advantages of this concept where it can easily perform the optimization for a set of multiple evaporators controlled by the same smart controller, which should have an intelligent and flexible architecture based on multi-agent systems (MAS) that allows one to add or remove new evaporators online, without the need for reconfiguring, while maintaining temporal and functional restrictions in the system. We show clearly how we can get a greater scalability, the self-configuration of the network and the least overhead with a non-beacon or unslotted mode of the IEEE 802.15.4 protocol, as well as wireless communications and distributed architectures, which could be extremely helpful in the development process of networked control systems in large spatially-distributed plants, which involve many sensors and actuators. For this purpose, a fuzzy scheme is used to control a set of parallel evaporator air-conditioning systems, with temperature and relative humidity control as a multi-input and multi-output closed loop system; in addition, a general architecture is presented, which implements multiple control loops closed over a communication network, integrating the analysis and validation method for multi-loop control networks designed for multi-evaporator systems.

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Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

Section: Worst-case End-to-end Delay Flow Control Signals Analysismentioning

confidence: 99%

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Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

et al. 2016

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“…Beaconing is another feature implemented through this layer. Finally, the MAC sub-layer can be exploited by higher layers to achieve secure communication [12].…”

Section: Medium Access Control Sub-layermentioning

confidence: 99%

“…Its capabilities and structure are those typically associated to such network layers, including routing. The entity of data is created and processed by network layer data units from the payload of the application layer and performs routing according to the topology which is used [12].…”

Section: Network Layermentioning

confidence: 99%

Performance Evaluation of Zigbee Routing Protocol under Various Conditions using OPNET Modeler

Abdulrahman¹,

Yaseen²

2015

IJCA

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Zigbee, which has the standard IEEE 802.15.4. It is advisable method to build wireless personal area network (WPAN) which demands a low power consumption that can be produced by Zigbee technique. Our paper gives measuring efficiency of Zigbee involving the Physical Layer (PL) and Media Access Control (MAC) sub-layer , which allow a simple interaction between the sensors. We model and simulate two different scenarios, in the first one, we tested the topological characteristics and performance of the IEEE802.15.4 standard in terms of throughput, node to node delay and figure of routers for three network layouts (Star, Mesh and Cluster Tree) using OPNET simulator. The second scenario investigates the self-healing feature on a mesh topology from earlier design until it supports a large number of end points (>64,000) with dynamic routing. The self-healing is done by removing a router from the network during operation, and seeing the end devices find an alternate path to communicate with the coordinator.

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An Impact of Jamming Signal on the Energy Efficiency of ZigBee Network Elements

2019

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Performance Analysis of IEEE 802.15.4/Zigbee Standard Under Real Time Constraints

Abstract: ABSTRACT

Cited by 27 publications

References 18 publications

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

Performance Evaluation of Zigbee Routing Protocol under Various Conditions using OPNET Modeler

An Impact of Jamming Signal on the Energy Efficiency of ZigBee Network Elements

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