Bacterial Relay for Energy-Efficient Molecular Communications

Qiu, Song; Haselmayr, Werner; Li, Bin; Zhao, Chenglin; Guo, Weisi

doi:10.1109/tnb.2017.2741669

Cited by 32 publications

(12 citation statements)

References 48 publications

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“…Motivated by [27] and [28], the energy efficiency (EE) ρ total EE for the nano-communication networks is defined as the ratio of the long-term sum channel capacity to the corresponding long-term total related energy costs, given as,…”

Section: A Problem Formulationmentioning

confidence: 99%

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

Feng

Ali

Iqbal

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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In this paper, we investigate the wireless power transfer and energy-efficiency (EE) optimization problem for nano-centric vehicular networks operating over the terahertz band. The inbody nano-sensors harvest energy from a power station via radio-frequency signal and then use the harvested energy to transmit data to the sink node. By considering the properties of terahertz band (i.e., sensitivity to distance and frequency over the communication path), we adopt the Brownian motion model to develop a time-variant terahertz channel model and to describe the mobility of the nano-sensors. Thus, based on the channel model and energy resources, we further develop a long-term EE optimization problem. The EE optimization is further converted into a series of energy-efficient resource allocation problems over the time slots via equivalent transformation method. The resource allocation problem for each timeslot, which is formulated as a mixed integer nonlinear programming (MINLP), is solved based on the particle swarm optimization (PSO) method. In addition, a dynamic PSO-based EE optimization (DPEEO) algorithm is developed to obtain the sub-optimal solution for the EE optimization problem. By exploiting the special structure of the reformulated problem, an improved DPEEO algorithm, is presented which can handle the problem's constraints quite well, decreases the research space, and greatly reduces the length of the convergence time. Simulation results validate the theoretical analysis of our system.

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Section: A Problem Formulationmentioning

confidence: 99%

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

Feng

Ali

Iqbal

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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“…In [103], [104], a detailed mathematical model for the molecule synthesis cost in MC system with the absorbing receiver was provided to examine the energy efficiency of different relay schemes. In [105], the energy costs in the encoding and synthesizing plasmid, the plasmid transportation, the carrier bacterial transportation, the decapsulation and decoding were defined and examined within bacterial relay MC networks.…”

Section: B Mc-based Body-centric Nanonetwork 1) Achievable Informatmentioning

confidence: 99%

A Comprehensive Survey on Hybrid Communication in Context of Molecular Communication and Terahertz Communication for Body-Centric Nanonetworks

Yang

Deng

et al. 2020

IEEE Trans. Mol. Biol. Multi-Scale Commun.

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“…Bacterial Relay for Energy Efficient Molecular Communications (MCvB) [49] has been proposed to deliver information while considering energy efficiency using bacterial mobile relays for molecular communication in the Internet-of-Nano-Things. This technique first derives the probability of end-to-end delivery using a propagation model of information pickup and information delivery stages after introducing system parameters.…”

Section: Less Energy R E Q U E S T R E Q U E S T R E Q U E S T R E Q mentioning

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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Bacterial Relay for Energy-Efficient Molecular Communications

Cited by 32 publications

References 48 publications

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

Dynamic Wireless Information and Power Transfer Scheme for Nano-Empowered Vehicular Networks

A Comprehensive Survey on Hybrid Communication in Context of Molecular Communication and Terahertz Communication for Body-Centric Nanonetworks

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

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