An Adaptive Backoff Mechanism for IEEE 802.15.4 Beacon‐Enabled Wireless Body Area Networks

Henna, Shagufta; Sarwar, Muhammad Awais

doi:10.1155/2018/9782605

Cited by 19 publications

(8 citation statements)

References 33 publications

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“…To conserve the energy of constrained devices, IEEE 802.15.4 standard adopts CSMA/CA to check the activity state of the propagation medium before engaging in possible data transactions [20,24] while bearing in mind how expensive it is to waste energy due to packet collision leading to retransmission. Before engaging in data transactions, in the slotted mechanism, nodes randomly select BP from the range of available periods computed by the BEB algorithm, and the countdown time is initiated.…”

Section: Related Workmentioning

confidence: 99%

“…Henna, S. et al [20] proposed the Traffic Adaptive Priority-Based MAC (TAP-MAC). In this work, data classes were categorized into three; class 1 -emergency, class 2 -on-demand, and class 3 -normal.…”

Section: Related Workmentioning

confidence: 99%

“…Contiki OS provides an efficient simulation environment for WSN with detailed statistical parameters. The Unit Disk Graph Medium (UDGM), with distance loss propagation model, was adopted with Constant Bit Rate (CBR) traffic model which is most suitable for resource-constrained devices generating data at a constant rate [20,29] with maximum frame size set to 127 bytes, which include 25 bytes of MAC Header and 102 bytes of payload [9,17] operating within the standard operational carrier frequency of 2.4 GHz and channel data rate of 250 kbps [4,9] (see Table 5).…”

Section: Performance Evaluationmentioning

confidence: 99%

“…In the literature, some existing data prioritization schemes have attempted to proffer solution to this issue [ 9 , 14 , 20 – 22 ]; however, higher and lower priority data uses the same backoff computation algorithm or expression to generate the range of backoff periods (BPs) for repeated transmission attempt by the nodes, which causes the nodes to select the same BP for every failed transmission attempt, leading to unnecessary power consumption. In this article, we proposed the Class of Service Traffic Priority MAC (CSTP-MAC) scheme.…”

Section: Introductionmentioning

confidence: 99%

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Optimized backoff scheme for prioritized data in wireless sensor networks: A class of service approach

et al. 2020

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Data prioritization of heterogeneous data in wireless sensor networks gives meaning to mission-critical data that are time-sensitive as this may be a matter of life and death. However, the standard IEEE 802.15.4 does not consider the prioritization of data. Prioritization schemes proffered in the literature have not adequately addressed this issue as proposed schemes either uses a single or complex backoff algorithm to estimate backoff time-slots for prioritized data. Subsequently, the carrier sense multiple access with collision avoidance scheme exhibits an exponentially increasing range of backoff times. These approaches are not only inefficient but result in high latency and increased power consumption. In this article, the concept of class of service (CS) was adopted to prioritize heterogeneous data (realtime and non-real-time), resulting in an optimized prioritized backoff MAC scheme called Class of Service Traffic Priority-based Medium Access Control (CSTP-MAC). This scheme classifies data into high priority data (HPD) and low priority data (LPD) by computing backoff times with expressions peculiar to the data priority class. The improved scheme grants nodes the opportunity to access the shared medium in a timely and power-efficient manner. Benchmarked against contemporary schemes, CSTP-MAC attained a 99% packet delivery ratio with improved power saving capability, which translates to a longer operational lifetime.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimized backoff scheme for prioritized data in wireless sensor networks: A class of service approach

et al. 2020

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“…In recent years, many efficient backoff algorithms have been developed to improve some of performance metrics of the IEEE 802.1.5.4 medium access control (MAC) protocol 9 . In addition, the IEEE 802.15.4 standard is suitable for wireless body area networks (WBANs) to improve the reliability of a network 10 . The current research focuses on improving some of the performance parameters of IEEE 802.15.4 based MAC protocol to achieve the different objectives, which can support many WSN applications.…”

Section: Introductionmentioning

confidence: 99%

An optimal clear channel assessment in IEEE 802.15.4 medium access control protocol for recurrent data transmission and long acknowledgement wait period

Asuti

Basarkod

2020

Trans Emerging Tel Tech

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The IEEE 802.15.4 standard medium access control (MAC) protocol is widely adopted for short‐range communication in current technologies such as Internet of Things, smart grids, and smart cities. The IEEE 802.15.4 standard adopts the carrier‐sense multiple access with collision avoidance channel access mechanism, which performs two consecutive clear channel assessment (CCA). However, performing two consecutive CCA may not be suitable for all types of network scenarios in a star topology‐enabled wireless sensor networks (WSN). In this article, we develop an optimal CCA channel access mechanism to address the recurrent data transmission and the long acknowledgement wait period which is encountered in two network scenarios considered in a star topology‐enabled WSN. To achieve these requirements, the proposed methodology performs five consecutive CCA for successful data transmission without going into the next backoff stage. Initially, an accurate Markov chain model is developed. Later, a set of mathematical expressions are developed for the proposed method. The model is validated using MATLAB 2017a programming tool. Simulation results show that the proposed methodology outperforms the existing CCA approaches in terms of channel collision time, delay, reliability, probability of collision, packet loss rate, and the probability of successful data transmission.

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Rakeness with block sparse Bayesian learning for efficient ZigBee‐based EEG telemonitoring

Hanafy

Ali

Shaalan

2019

Int J Communication

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SummaryFuture healthcare systems are shifted toward long‐term patient monitoring using embedded ultra‐low power devices. In this paper, the strengths of both rakeness‐based compressive sensing (CS) and block sparse Bayesian learning (BSBL) are exploited for efficient electroencephalogram (EEG) transmission/reception over wireless body area networks. A binary sensing matrix based on the rakeness concept is used to find the most energetic signal directions. A balance is achieved between collecting energy and enforcing restricted isometry property to capture the underlying signal structure. Correct presentation of the EEG oscillatory activity, EEG wave shape, and main signal characteristics is provided using the discrete cosine transform based BSBL, which models the intra‐block correlation. The IEEE 802.15.4 wireless communication technology (ZigBee) is employed, since it targets low data rate communications in an energy efficient manner. To alleviate noise and channel multipath effects, a recursive least square based equalizer is used, with an adaptation algorithm that continually updates the filter weights using successive input samples. For the same compression ratio (CR), results indicate that the proposed system permits a higher reconstruction quality compared with the standard CS algorithm. For higher CRs, lower dimensional projections are allowed, meanwhile guaranteeing a correct reconstruction. Thus, low computational high quality data compression/reconstruction are achieved with minimal energy expenditure at the sensors nodes.

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An Adaptive Backoff Mechanism for IEEE 802.15.4 Beacon‐Enabled Wireless Body Area Networks

Cited by 19 publications

References 33 publications

Optimized backoff scheme for prioritized data in wireless sensor networks: A class of service approach

Optimized backoff scheme for prioritized data in wireless sensor networks: A class of service approach

An optimal clear channel assessment in IEEE 802.15.4 medium access control protocol for recurrent data transmission and long acknowledgement wait period

Rakeness with block sparse Bayesian learning for efficient ZigBee‐based EEG telemonitoring

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