From microalgae to bioenergy: Identifying optimally integrated biorefinery pathways and harvest scheduling under uncertainties in predicted climate

Lim, Juin Yau; Teng, Sin Yong; How, Bing Shen; Nam, KiJeon; Heo, SungKu; Máša, Vítězslav; Stehlı́k, Petr

doi:10.1016/j.rser.2022.112865

Cited by 20 publications

(2 citation statements)

References 97 publications

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“…These schemes commonly consider real‐time task requirements, 23 ESs' computing and storage resources, 24 network conditions, 25 and other relevant factors to ensure an optimal user experience and meet the QoS requirements. Current research on task scheduling solutions mainly focuses on resource management and optimization, 26 including load balancing, 27 service prediction, 28 and allocation optimization 24 . Flex‐MEC, a new task‐offloading architecture proposed in Reference 29, aims to accomplish efficient task assignment and scheduling among ESs in MEC.…”

Section: Related Workmentioning

confidence: 99%

SharpEdge: A QoS‐driven task scheduling scheme with blockchain in mobile edge computing

Gu,

Liu,

2024

Concurrency and Computation

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SummaryMobile edge computing (MEC) promotes the development and popularity of Internet of Things (IoT) devices with higher connectivity and ultra‐low latency through network topology optimization and real‐time data analysis. With the exponential growth of data traffic generated by IoT devices, it is essential to prevent edge servers (ESs) from overloading through efficient task scheduling to ensure the quality of service (QoS). However, the lack of trust and incentive mechanisms between ESs deployed and managed by different infrastructure providers makes it challenging to perform peer‐offloaded tasks. Moreover, to meet the low‐latency requirement of many IoT applications, the execution efficiency of the task scheduling scheme in MEC needs to be improved. To address the above challenges systematically, a QoS‐driven task scheduling scheme with blockchain in MEC named SharpEdge is proposed. In SharpEdge, ESs publish tasks with rewards and then select the most reliable executors through a historical performance‐based reputation mechanism to perform peer offloading. The performance of the executor will be recorded into the blockchain after the task is completed. In addition, a concurrent consensus mechanism using sharding technology is designed, improving task scheduling efficiency. We implement SharpEdge based on Hyperledger Fabric and verify its performance in a simulated MEC environment.

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Section: Related Workmentioning

confidence: 99%

SharpEdge: A QoS‐driven task scheduling scheme with blockchain in mobile edge computing

Gu,

Liu,

2024

Concurrency and Computation

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“…However, most microalgae biorefineries are not profitable due to the untapped new value-added products from microalgal biomass [193]. Furthermore, algae biomass-based biorefineries are a relatively new technology that requires substantial financial investments in research and development (R&D) and advocates for public and private policies, largescale demonstrations, deployment strategies, and assurance of continuous and sustainable production of algae biomass [197,198]. The economic feasibility and uncertain environmental performance of an algae biorefinery are the primary constraints to its deployment.…”

Section: Algae Biomassmentioning

confidence: 99%

An Overview of Algae for Biodiesel Production Using Bibliometric Indicators

Kombe

2023

International Journal of Energy Research

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Algae are a desirable biodiesel feedstock because they take up little space, have a high algal-cell biomass per unit area, and can sustainably meet a large portion of the world’s future energy needs. Using several bibliometric indicators, this study assesses the research productivity of algae for biodiesel production. The dataset was retrieved from the Scopus database using an appropriate keyword search. The VOSviewer v1.6.18 and Biblioshiny in R -studio were then utilised for bibliometric analysis and network visualisation. The study found that, with the first article being published in 1990 and an annual scientific growth rate of 14.76%, research on algae for the generation of biodiesel is still in its early phases. Although the possibility of utilising algae to produce biodiesel was originally mentioned in 1990, it was only until 2006 that several researchers started to show an interest in the subject. 101 articles were published in 2015, which is the most ever. The most prolific countries in terms of publications, ongoing collaborations and cooperation, best publishing institutions, and prestigious journals, as well as the most productive researchers and the most highly referenced works in the field, have all been recognised and presented. Finally, a keyword co-occurrence analysis of the subject was presented and discussed to provide research insights into the field. The bibliometric indicators of the study are intended to aid researchers in finding potential research topics, high-quality scientific literature, and suitable journals for publishing research on algae for biodiesel production.

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