Throughput analysis of a slotted Aloha-based network with energy harvesting nodes

Moradian, Masoumeh; Ashtiani, Farid

doi:10.1109/pimrc.2012.6362809

Cited by 18 publications

(14 citation statements)

References 12 publications

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“…The majority of work related to MAC protocols with EH focuses on slotted ALOHA, carrier‐sense multiple access, and DFSA . In particular, the FSA and DFSA protocols have been proposed in the past for data collection scenarios with EH where each end device has just 1 data packet to transmit per request to the gateway.…”

Section: Related Workmentioning

confidence: 99%

Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications

Vázquez-Gallego

Tuset-Peiró

Alonso

et al. 2017

Trans Emerging Tel Tech

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This paper presents, models, and evaluates energy harvesting–aware distributed queuing (EH‐DQ), a novel medium access control protocol that combines distributed queuing with energy harvesting (EH) to address data collection applications in industrial scenarios using long‐range and low‐power wireless communication technologies. We model the medium access control protocol operation using a Markov chain and evaluate its ability to successfully transmit data without depleting the energy stored at the end devices. In particular, we compare the performance and energy consumption of EH‐DQ with that of time‐division multiple access (TDMA), which provides an upper limit in data delivery, and EH‐aware reservation dynamic frame slotted ALOHA, which is an improved variation of frame slotted ALOHA. To evaluate the performance of these protocols, we use 2 performance metrics: delivery ratio and time efficiency. Delivery ratio measures the ability to successfully transmit data without depleting the energy reserves, whereas time efficiency measures the amount of data that can be transmitted in a certain amount of time. Results show that EH‐DQ and TDMA perform close to the optimum in data delivery and outperform EH‐aware reservation dynamic frame slotted ALOHA in data delivery and time efficiency. Compared to TDMA, the time efficiency of EH‐DQ is insensitive to the amount of harvested energy, making it more suitable for energy‐constrained applications. Moreover, compared to TDMA, EH‐DQ does not require updated network information to maintain a collision‐free schedule, making it suitable for very dynamic networks.

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Section: Related Workmentioning

confidence: 99%

Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications

Vázquez-Gallego

Tuset-Peiró

Alonso

et al. 2017

Trans Emerging Tel Tech

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“…However, the performance analyses of random access protocols on networks with energy harvesting is a much more recent area of research. Existing works focus on the assessment of slotted-ALOHA [8], CSMA [9] [10], Frame Slotted-ALOHA (FSA) [11], and Dynamic Frame Slotted-ALOHA (DFSA) [12]- [14]. However, to the best of the authors' knowledge, the design and analysis of random access protocols based on tree-splitting for wireless networks comprised of energy-harvesting nodes has never received attention.…”

Section: Introductionmentioning

confidence: 99%

Contention Tree-Based Access for Wireless Machine-to-Machine Networks With Energy Harvesting

Vázquez-Gallego

Kalalas

Alonso

et al. 2017

IEEE Trans. on Green Commun. Netw.

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Abstract-In this paper, we consider a wireless Machine-toMachine network composed of end-devices with energy harvesters that periodically transmit data to a gateway. While energy harvesting allows for perpetual operation, the uncertain amount of harvested energy may not guarantee fully continuous operation due to temporary energy shortages. This fact needs to be addressed at the Medium Access Control (MAC) layer. We thus investigate the performance of an Energy Harvestingaware Contention Tree-based Access (EH-CTA) protocol, which uses a tree-splitting algorithm to resolve collisions and takes energy availability into account. We derive a theoretical model to compute the probability of delivery and the time efficiency. In addition, we conduct a performance comparison of EH-CTA using an EH-aware Dynamic Frame Slotted-ALOHA (EH-DFSA) as a benchmark. We determine the parameters that maximize performance and analyze how it is influenced by the amount of harvested energy and the number of end-devices. Results reveal the superior performance of EH-CTA over EH-DFSA. While EH-DFSA requires an estimate of the number of contending enddevices per frame to adapt the frame length, EH-CTA uses short and fixed frame lengths, which enables scalability and facilitates synchronization as the network density increases.

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“…Perhaps the closest work to ours is [7], [8]. In [7], the authors adapt a closed queuing network model to analyze the throughput of a slotted Aloha network under energy harvesting constraints.…”

Section: Introductionmentioning

confidence: 99%

“…In [7], the authors adapt a closed queuing network model to analyze the throughput of a slotted Aloha network under energy harvesting constraints. In [8], they investigate distributed policies that maximize the sum throughput in a random access network.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analytical Markov model for slotted ALOHA with opportunistic RF energy harvesting

Ibrahim

Erçetin

ElBatt

2015

2015 IEEE International Conference on Communication Workshop (ICCW)

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In this paper, we investigate the performance of an ALOHA random access wireless network consisting of nodes with and without RF energy harvesting capability. We develop and analyze a Markov model for the system when nodes with RF energy harvesting capability are infinitely backlogged. Our results indicate that the network throughput is improved when the conventional nodes are underloaded. On the contrary, when all types of nodes have finite backlogs, we numerically demonstrate that the network throughput and delay are improved when the overall system is overloaded. We show that there exists a trade-off between energy efficiency and delay, and we determine the optimal number of energy harvesting nodes in a network maximizing the energy efficiency while satisfying a given delay requirement.

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Throughput analysis of a slotted Aloha-based network with energy harvesting nodes

Cited by 18 publications

References 12 publications

Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications

Combining distributed queuing with energy harvesting to enable perpetual distributed data collection applications

Contention Tree-Based Access for Wireless Machine-to-Machine Networks With Energy Harvesting

Analytical Markov model for slotted ALOHA with opportunistic RF energy harvesting

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