Performance analysis of unslotted CSMA/CA in wireless networks

Lauwens, Ben; Scheers, Bart; Capelle, Antoine Van de

doi:10.1007/s11235-009-9220-7

Cited by 43 publications

(27 citation statements)

References 25 publications

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“…In [18], the authors proposed a novel analytical model of the unslotted CSMA saturation throughput using a semi-Markov process that retrieves the interaction between MAC and PHY layers to derive the CCA output. Performance evaluation showed that the probability that CCA succeeds (respectively fails) clearly depends on the actual backoff stage.…”

Section: Analysis Of the Beaconless Ieee 802154 Schemementioning

confidence: 99%

Performance Evaluation of Unslotted CSMA/CA for Wireless Sensor Networks: Energy Consumption Analysis and Cross Layer Routing

Korbi¹,

Saı̈dane²

2017

IJCNIS

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Abstract-The IEEE 802.15.4 standard is considered as the most notorious MAC layer for wireless sensor networks (WSNs) in both centralized and distributed context. For instance, in multi hop environment, the beaconless IEEE 802.15.4 is used. Several works evaluated the performance of the beaconless IEEE 802.15.4 in terms of average delay, average energy consumption, throughput etc. But, none of the existing studies derived accurate energy consumption bounds of this MAC layer. In this paper, our contribution is twofold. We first propose a comprehensive energy consumption analysis of the unslotted CSMA/CA algorithm. The results are validated through simulation. Then, we exploit our analysis to propose a cross layer routing scheme that enhances the native PEGASIS protocol. Our scheme called Average Energy Enhanced PEGASIS (AE2-PEGASIS) considers the average energy consumption at the MAC layer when constructing the routes to the sink.

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Section: Analysis Of the Beaconless Ieee 802154 Schemementioning

confidence: 99%

Performance Evaluation of Unslotted CSMA/CA for Wireless Sensor Networks: Energy Consumption Analysis and Cross Layer Routing

Korbi¹,

Saı̈dane²

2017

IJCNIS

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“…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%

“…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%

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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“…Therefore, if the packet generation time were lower than that taken for the CSMA-CA plus the propagation time, then the client would fill its buffer faster than it can empty it. According to [48] this time is estimated to 6.09 ms. This is comparable to the packet generation time relative to a client rate of 150 requests per second.…”

Section: Workloadmentioning

confidence: 99%

TinyCoAP: A Novel Constrained Application Protocol (CoAP) Implementation for Embedding RESTful Web Services in Wireless Sensor Networks Based on TinyOS

Ludovici

Moreno

Calveras

2013

JSAN

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Abstract:In this paper we present the design and implementation of the Constrained Application Protocol (CoAP) for TinyOS, which we refer to as TinyCoAP. CoAP seeks to apply the same application transfer paradigm and basic features of HTTP to constrained networks, while maintaining a simple design and low overhead. The design constraints of Wireless Sensor Networks (WSNs) require special attention in the design process of the CoAP implementation. We argue that better performance and minimal resource consumption can be achieved developing a native library for the operating system embedded in the network. TinyOS already includes in its distribution an implementation of CoAP called CoapBlip. However, this is based on a library not originally designed to meet the requirements of TinyOS. We demonstrate the effectiveness of our approach by a comprehensive performance evaluation. In particular, we test and evaluate TinyCoAP and CoapBlip in a real scenario, as well as solutions based on HTTP. The evaluation is performed in terms of latency, memory occupation, and energy consumption. Furthermore, we evaluate the reliability of each solution by measuring the goodput obtained in a channel affected by Rayleigh fading. We also include a study on the effects that high workloads have on a server.

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Performance analysis of unslotted CSMA/CA in wireless networks

Cited by 43 publications

References 25 publications

Performance Evaluation of Unslotted CSMA/CA for Wireless Sensor Networks: Energy Consumption Analysis and Cross Layer Routing

Performance Evaluation of Unslotted CSMA/CA for Wireless Sensor Networks: Energy Consumption Analysis and Cross Layer Routing

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

TinyCoAP: A Novel Constrained Application Protocol (CoAP) Implementation for Embedding RESTful Web Services in Wireless Sensor Networks Based on TinyOS

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