End-to-end delay analysis in wireless sensor networks with service vacation

Alabdulmohsin, Ibrahim; Hyadi, Amal; Afify, Laila H.; Shihada, Basem

doi:10.1109/wcnc.2014.6952872

Cited by 8 publications

(3 citation statements)

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“…However, unlike [10], in our work we combine the contention phase (FSA protocol) with the contention-free phase (TDMA scheduling) and derive an exact expression for the E2E delay. In [11] the E2E analysis of a chain of K non-preemptive nodes from sensor to the sink is investigated. Poisson arrival rate and exponential service time are assumed for high (control) and low (data) priority traffic.…”

Section: Related Workmentioning

confidence: 99%

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End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

et al. 2019

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In this work it is considered a circular Wireless Sensor Networks (WSN) in a planar structure with uniform distribution of the sensors and with a two-level hierarchical topology. At the lower level, a cluster configuration is adopted in which the sensed information is transferred from sensor nodes to a cluster head (CH) using a random access protocol (RAP). At CH level, CHs transfer information, hop-by-hop, ring-by-ring, towards to the sink located at the center of the sensed area using TDMA as MAC protocol. A Markovian model to evaluate the end-to-end (E2E) transfer delay is formulated. In addition to other results such as the well know energy hole problem, the model reveals that for a given radial distance between the CH and the sink, the transfer delay depends on the angular orientation between them. For instance, when two rings of CHs are deployed in the WSN area, the E2E delay of data packets generated at ring 2 and at the “west” side of the sink, is 20% higher than the corresponding E2E delay of data packets generated at ring 2 and at the “east” side of the sink. This asymmetry can be alleviated by rotating from time to time the allocation of temporary slots to CHs in the TDMA communication. Also, the energy consumption is evaluated and the numerical results show that for a WSN with a small coverage area, say a radio of 100 m, the energy saving is more significant when a small number of rings are deployed, perhaps none (a single cluster in which the sink acts as a CH). Conversely, topologies with a large number of rings, say 4 or 5, offer a better energy performance when the service WSN covers a large area, say radial distances greater than 400 m.

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Section: Related Workmentioning

confidence: 99%

“…with c r max = 1; c k = 1 + #CH k+1 #CH k c k+1 , for k < r max . (11) being #CH k the number of CHs at ring k. Table 5 shows the values of c k for several sizes of the WSN (r max = 0, 1, 2, . .…”

Section: The Traffic Load and The Stability Conditionsmentioning

confidence: 99%

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

et al. 2019

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“…In many of the related work, such as [22] and [23], the delay characteristics of the system were inferred from analyzing the queue lengths and their first moments (or mean queue lengths and waiting times). Some of these related work, such as [24], were limited to only evaluating the average waiting times. While these results may provide a good estimate of the system's overall performance, they do not necessarily yield accurate results in terms of the SU's waiting-time behaviors.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of Multi-Modal Overlay/Underlay Switching Service Levels in Cognitive Radio Networks

2019

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Cognitive radio networks have become a popular platform for many systems and applications of the future, and especially for Smart City applications and the Internet of Things. The wireless transceivers used for communicating between the different devices in the cognitive radio networks can operate in either of the two modes, namely overlay and underlay, or a hybrid of these two modes. While operating in the underlay mode, secondary users are likely to experience varying transmission rates due to the fluctuating power levels from the primary users. This has the effect of the channel capacity being dynamic, which forces the secondary user to switch between different transmission rates, or ''service modes'', during a single networking session. In our previous work, we developed a discrete time queueing model for analyzing the performance of secondary users in such networks with multi-modal and hybrid overlay/underlay switching service levels. In this paper, we extend our previous work to present our novel result for computing the waiting-time distribution of the secondary users. Such results are essential for investigating the sensitivity of the secondary user's performance due to the queueing delays, and especially for real-time applications. INDEX TERMS Cognitive radio networks, hybrid overlay/underlay modes, discrete-time queues, waiting time distribution.

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ℋ₂ gain-scheduled design subject to inexact measurements: performance comparison of two models for additive uncertainty

Palma

Morais

Oliveira

2019

2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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End-to-end delay analysis in wireless sensor networks with service vacation

Cited by 8 publications

References 10 publications

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

Performance Analysis of Multi-Modal Overlay/Underlay Switching Service Levels in Cognitive Radio Networks

ℋ₂ gain-scheduled design subject to inexact measurements: performance comparison of two models for additive uncertainty

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End-to-end delay analysis in wireless sensor networks with service vacation

Cited by 8 publications

References 10 publications

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

Performance Analysis of Multi-Modal Overlay/Underlay Switching Service Levels in Cognitive Radio Networks

ℋ2 gain-scheduled design subject to inexact measurements: performance comparison of two models for additive uncertainty

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ℋ₂ gain-scheduled design subject to inexact measurements: performance comparison of two models for additive uncertainty