QoS-Aware Energy-Efficient Cooperative Scheme for Cluster-Based IoT Systems

Song, Liumeng; Chai, Kok Keong; Chen, Yue; Schormans, J.A.; Loo, Jonathan; Vinel, Alexey

doi:10.1109/jsyst.2015.2465292

Cited by 49 publications

(26 citation statements)

References 28 publications

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“…The energy-efficient RA problems have been well studied for various systems, eg, other works [14][15][16][17] have considered energy-efficient RA in OFDMA-based HetNets, while previous works [18][19][20][21][22][23][24][25][26][27][28] were based on SC-FDMA-based HetNets. Furthermore, other works [29][30][31][32][33][34][35][36][37][38][39] have considered the energy-efficient RA problems in OFDMA-based C-RAN, except the work of Tran et al, 36 which is based on nonorthogonal multiple-access-based H-CRAN, while the work of Ali et al 40 considered network sum rate maximization in multitier C-RAN.…”

Section: Contributionmentioning

confidence: 99%

Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs

Ali

Ahmad

Khan

2018

Trans Emerging Tel Tech

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The rapid growth of connected devices and multimedia applications intensify the needs of high data rate and energy‐efficient networks. Multitier heterogeneous cloud radio access networks have been presented as a capable candidate for fifth‐generation networks for much higher data rate and energy efficiency (EE) than fourth generation. Therefore, in this paper, we consider the EE maximization in the uplink of a single‐carrier frequency division multiple access–based multitier heterogeneous cloud radio access network. We formulate a joint subchannel assignment, power allocation, and remote radio head association problem for EE maximization. Single‐carrier frequency division multiple access introduces subchannel exclusivity and subchannel adjacency constraints. These constraints, respectively, ensure the allocation of a subchannel to a single user at a time and the allocation of multiple subchannels to a user only if they are adjacent. In addition, we put constraints on each user's minimum data rate and maximum transmit power. Due to the simultaneous consideration of these four constraints, the solution of the formulated problem becomes harder. Therefore, a three‐step algorithm is developed, which solves this problem in an iterative manner. Simulation results verify that our proposed algorithm significantly improve the EE of the network.

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Section: Contributionmentioning

confidence: 99%

Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs

Ali

Ahmad

Khan

2018

Trans Emerging Tel Tech

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“…QoS-Aware Energy-Efficient Cooperative Scheme for Cluster-Based IoT Systems (QEECS) [42] has been suggested to provide tradeoff between energy efficiency and QoS provisioning by formulating a multi objective optimization problem, while using network lifetime and outage probability as metric, respectively. This technique considers two phases for data transmission: setup phase and steady state phase.…”

Section: Energy Efficient Scheduling Techniquesmentioning

confidence: 99%

“…The limitations of energy consumption should be adapted through the association of artificial neural networks. Moreover the QoS constrained system may be controlled in an intelligent manner for every IoT application that may have a distinct energy profile [42]. According to the requirements of every application in an IoT network, novel techniques and research based on QoS constraints can contribute to providing potential solutions [3].…”

Section: Qos Constraints Approachesmentioning

confidence: 99%

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Kumar

Kaiwartya

et al. 2017

Energies

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Abstract:Energy efficiency is a significant characteristic of battery-run devices such as sensors, RFID and mobile phones. In the present scenario, this is the most prominent requirement that must be served while introducing a communication protocol for an IoT environment. IoT network success and performance enhancement depend heavily on optimization of energy consumption that enhance the lifetime of IoT nodes and the network. In this context, this paper presents a comprehensive review on energy efficiency techniques used in IoT environments. The techniques proposed by researchers have been categorized based on five different layers of the energy architecture of IoT. These five layers are named as sensing, local processing and storage, network/communication, cloud processing and storage, and application. Specifically, the significance of energy efficiency in IoT environments is highlighted. A taxonomy is presented for the classification of related literature on energy efficient techniques in IoT environments. Following the taxonomy, a critical review of literature is performed focusing on major functional models, strengths and weaknesses. Open research challenges related to energy efficiency in IoT are identified as future research directions in the area. The survey should benefit IoT industry practitioners and researchers, in terms of augmenting the understanding of energy efficiency and its IoT-related trends and issues.

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“…3 Most of these IoT devices are powered by batteries, which limits the lifetime of these devices. Although a lot of works have been conducted to address this issue, for example, sleeping and wake-up schemes, 4 energy-efficient routing, 5 and collaborative transmission, [6][7][8] they can only alleviate the issue by enlarging the lifetime of IoT devices in IoT networks. It is impossible to recharge or replace IoT devices' batteries in some cases because of environment restrictions or high costs, which impairs the sustainability of IoT networks.…”

Section: Introductionmentioning

confidence: 99%

Energy consumption optimization for self‐powered IoT networks with non‐orthogonal multiple access

Luo

et al. 2019

Int J Communication

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Energy harvesting (EH) has been considered as one of the promising technologies to power Internet of Things (IoT) devices in self-powered IoT networks. By adopting a typical harvest-then-transmit mode, IoT devices with the EH technology first harvest energy by using wireless power transfer (WPT) and then carry out wireless information transmission (WIT), which leads to the coordination between WPT and WIT. In this paper, we consider optimizing energy consumption of periodical data collection in a self-powered IoT network with non-orthogonal multiple access (NOMA). Particularly, we take into account time allocation for the WPT and WIT stages, node deployment, and constraints for data transmission. Moreover, to thoroughly explore the impact of different multiple access methods, we theoretically analyse and compare the performance achieved by employing NOMA, frequency division multiple access (FDMA), and time division multiple access (TDMA) in the considered IoT network. To validate the performance of the proposed method, we conduct extensive simulations and show that the NOMA outperforms the FDMA and TDMA in terms of energy consumption and transmission power. KEYWORDSInternet of Things (IoT), non-orthogonal multiple access, wireless information transmission, wireless power transfer Int J Commun Syst. 2020;33:e4174.wileyonlinelibrary.com/journal/dac

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QoS-Aware Energy-Efficient Cooperative Scheme for Cluster-Based IoT Systems

Cited by 49 publications

References 28 publications

Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs

Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs

Cross-Layer Energy Optimization for IoT Environments: Technical Advances and Opportunities

Energy consumption optimization for self‐powered IoT networks with non‐orthogonal multiple access

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