Joint Energy and QoS-Aware Memetic-Based Scheduling for M2M Communications in LTE-M

Dawaliby, Samir; Bradai, Abbas; Pousset, Yannis; Châtellier, Christian

doi:10.1109/tetci.2018.2883450

Cited by 25 publications

(18 citation statements)

References 36 publications

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“…LTE scheduling mechanism follows some constraints enforced by the LTE standard itself or by the limitation of the communicating UE. Some scheduling constraints and limitations are as following [80], [102], [109].…”

Section: Lte Resource Schedulingmentioning

confidence: 99%

“…The authors model the problem to the 0/1 knapsack problem. Dawaliby et al [109] proposed a technique that aims to minimize energy consumption while maintaining QoS requirements of M2M devices. The authors employ a cross-layer scheme using a Memetic-based algorithm the authors consider the QoS requirements while minimizing the energy consumption using discontinuous reception switching.…”

Section: Hybrid / Multi-objective Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks

et al. 2021

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The Machine-to-Machine (M2M) communication refers to an autonomous communication among devices that aims for a massive number of connected devices. M2M communication can support ubiquitous communication and full mechanical automation, and it will change everything from industry to ourselves. Recent developments in communication technology make Long Term Evolution (LTE)/Long Term Evolution-Advance (LTE-A) a promising technology for supporting M2M communication. LTE can support the diverse characteristic of M2M communication due to its IP connectivity, coverage area, and scalability. Therefore, the LTE schedulers should satisfy the need for M2M communication.Motivated from these facts, in this paper, we present a survey on classification of LTE / LTE-A scheduling methodologies from the perspective of M2M communication. We classify the schedulers based on their objectives, such as energy efficiency, spectrum efficiency, group-based, and Quality-of-Service (QoS) support for Machine Type Communication Devices (MTCDs). We also highlight the scope of future research direction for the scheduling work.

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Section: Lte Resource Schedulingmentioning

confidence: 99%

Section: Hybrid / Multi-objective Techniquesmentioning

confidence: 99%

A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Stressing the energy consumption of the M2M communication systems, the authors in [7], [8] develop energy-efficient resource allocation strategy for the MTCDs. Yang et al [7] study energy-efficient resource allocation schemes for an M2M-enabled cellular network with nonlinear energy harvesting.…”

Section: A Resource Allocation Schemes For M2m Communicationsmentioning

confidence: 99%

“…Aiming to minimize the total energy consumption of the network, the authors propose a joint power control and time allocation scheme for the MTCDs applying non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA) strategies. In [8], Dawaliby et al tackle the challenges of scheduling M2M traffic in long-term evolution (LTE) systems and propose a cross-layer resource allocation scheme that minimizes the energy consumption of the MTCDs.…”

Section: A Resource Allocation Schemes For M2m Communicationsmentioning

confidence: 99%

Energy Efficiency Optimization-Based Joint Resource Allocation and Clustering Algorithm for M2M Communication Systems

2019

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In recent years, machine-to-machine (M2M) communications have attracted great attentions from both academia and industry. In M2M communication systems, machine type communication devices (MTCDs) are capable of communicating with each other intelligently under highly reduced human interventions. Although diverse types of services are expected to be supported for MTCDs, various quality of service (QoS) requirements and network states pose difficulties and challenges to the resource allocation and clustering schemes of M2M communication systems. In this paper, we address the joint resource allocation and clustering problem in M2M communication systems. To achieve the efficient resource management of the MTCDs, we propose a joint resource management architecture, and design a joint resource allocation and clustering algorithm. More specifically, by defining system energy efficiency as the sum of the energy efficiency of the MTCDs, the joint resource allocation and clustering problem is formulated as an energy efficiency maximization problem. As the original optimization problem is a nonlinear fractional programming problem, which cannot be solved conveniently, we transform the optimization problem into power allocation subproblem and clustering subproblem. Applying iterative method-based energy efficiency maximization algorithm, we first obtain the optimal power allocation strategy based on which, we then propose a modified K-means algorithm to obtain the clustering strategy. Numerical results demonstrate the effectiveness of the proposed algorithm. INDEX TERMS Machine-to-machine (M2M) communications, resource allocation, clustering, energy efficiency.

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“…The convergence of emerging technologies, notably, artificial intelligence (AI) [21,22], internet of things (IoT) [28,29], and blockchain [13,16] is becoming more and more inevitable, constituting a normal advance in the fourth industrial revolution [64]. Because of the increased pervasiveness and importance of these three technologies in human life, they pose many risks related to health, security, safety, and other areas of life and thus will introduce significant ethical issues.…”

Section: Introductionmentioning

confidence: 99%

Converged AI, IoT, and blockchain technologies: a conceptual ethics framework

Nehme¹,

Sibai

Abdo

et al. 2021

AI Ethics

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The convergence of AI, IoT, and blockchain as the next disruptive technology is inevitable. Studying the ethics of these converged technologies is crucial for the steady development and adoption of the applications. Even though this topic is crucial, it is still not yet touched in the literature. This work is the first attempt to tackle this issue by developing a conceptual ethics framework for converged AI, IoT, and blockchain. The framework is based on a systematic literature review and categorizes the ethical issues into three layers namely micro (ethical issue involving the technology itself), meso (ethical issue involving the applications), and macro (ethical issue involving the society and institutions).

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Joint Energy and QoS-Aware Memetic-Based Scheduling for M2M Communications in LTE-M

Cited by 25 publications

References 36 publications

A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks

A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks

Energy Efficiency Optimization-Based Joint Resource Allocation and Clustering Algorithm for M2M Communication Systems

Converged AI, IoT, and blockchain technologies: a conceptual ethics framework

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