Future Directions to the Application of Distributed Fog Computing in Smart Grid Systems

2018 ◽  
pp. 162-195 ◽  
Author(s):  
Arash Anzalchi ◽  
Aditya Sundararajan ◽  
Longfei Wei ◽  
Amir Moghadasi ◽  
Arif Sarwat
Keyword(s):  
Smart Grid ◽  
Large Scale ◽  
New Technologies ◽  
Fog Computing ◽  
Data Communication ◽  
Grid Systems ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
Large Scale Integration ◽  
Integration Of Renewables

The rapid growth of new technologies in power systems requires real-time monitoring and control of bidirectional data communication and electric power flow. Cloud computing has centralized architecture and is not scalable towards the emerging internet of things (IoT) landscape of the grid. Further, under large-scale integration of renewables, this framework could be bogged down by congestion, latency, and subsequently poor quality of service (QoS). This calls for a distributed architecture called fog computing, which imbibes both clouds as well as the end-devices to collect, process, and act upon the data locally at the edge for low latency applications prior to forwarding them to the cloud for more complex operations. Fog computing offers high performance and interoperability, better scalability and visibility, and greater availability in comparison to a grid relying only on the cloud. In this chapter, a prospective research roadmap, future challenges, and opportunities to apply fog computing on smart grid systems is presented.

Future Directions to the Application of Distributed Fog Computing in Smart Grid Systems

2019 ◽  
pp. 2186-2212 ◽  
Author(s):  
Arash Anzalchi ◽  
Aditya Sundararajan ◽  
Longfei Wei ◽  
Amir Moghadasi ◽  
Arif Sarwat
Keyword(s):  
Smart Grid ◽  
Large Scale ◽  
New Technologies ◽  
Fog Computing ◽  
Data Communication ◽  
Grid Systems ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
Large Scale Integration ◽  
Integration Of Renewables

The rapid growth of new technologies in power systems requires real-time monitoring and control of bidirectional data communication and electric power flow. Cloud computing has centralized architecture and is not scalable towards the emerging internet of things (IoT) landscape of the grid. Further, under large-scale integration of renewables, this framework could be bogged down by congestion, latency, and subsequently poor quality of service (QoS). This calls for a distributed architecture called fog computing, which imbibes both clouds as well as the end-devices to collect, process, and act upon the data locally at the edge for low latency applications prior to forwarding them to the cloud for more complex operations. Fog computing offers high performance and interoperability, better scalability and visibility, and greater availability in comparison to a grid relying only on the cloud. In this chapter, a prospective research roadmap, future challenges, and opportunities to apply fog computing on smart grid systems is presented.

scholarly journals Caenorhabditis elegans, a Host to Investigate the Probiotic Properties of Beneficial Microorganisms

2020 ◽  
Vol 7 ◽  
Author(s):  
Cyril Poupet ◽  
Christophe Chassard ◽  
Adrien Nivoliez ◽  
Stéphanie Bornes
Keyword(s):  
Caenorhabditis Elegans ◽  
High Throughput Screening ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Probiotic Properties ◽  
C Elegans ◽  
Probiotic Potential ◽  
Challenges And Opportunities ◽  
Future Challenges

Caenorhabditis elegans, a non-parasitic nematode emerges as a relevant and powerful candidate as an in vivo model for microorganisms-microorganisms and microorganisms-host interactions studies. Experiments have demonstrated the probiotic potential of bacteria since they can provide to the worm a longer lifespan, an increased resistance to pathogens and to oxidative or heat stresses. Probiotics are used to prevent or treat microbiota dysbiosis and associated pathologies but the molecular mechanisms underlying their capacities are still unknown. Beyond safety and healthy aspects of probiotics, C. elegans represents a powerful way to design large-scale studies to explore transkingdom interactions and to solve questioning about the molecular aspect of these interactions. Future challenges and opportunities would be to validate C. elegans as an in vivo tool for high-throughput screening of microorganisms for their potential probiotic use on human health and to enlarge the panels of microorganisms studied as well as the human diseases investigated.

scholarly journals Challenges and Opportunities in Coastal Shoreline Prediction

2021 ◽  
Vol 8 ◽  
Author(s):  
Kristen D. Splinter ◽  
Giovanni Coco
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Shoreline Change ◽  
Sandy Beaches ◽  
Water Levels ◽  
Current State ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
Shoreline Prediction

Sandy beaches comprise approximately 31% of the world's ice-free coasts. Sandy coastlines around the world are continuously adjusting in response to changing waves and water levels at both short (storm) and long (climate-driven, from El-Nino Southern Oscillation to sea level rise) timescales. Managing this critical zone requires robust, advanced tools that represent our best understanding of how to abstract and integrate coastal processes. However, this has been hindered by (1) a lack of long-term, large-scale coastal monitoring of sandy beaches and (2) a robust understanding of the key physical processes that drive shoreline change over multiple timescales. This perspectives article aims to summarize the current state of shoreline modeling at the sub-century timescale and provides an outlook on future challenges and opportunities ahead.

Communication

2010 ◽  
pp. 47-74
Author(s):  
Valentin Cristea ◽  
Ciprian Dobre ◽  
Corina Stratan ◽  
Florin Pop
Keyword(s):  
Distributed Systems ◽  
Traffic Engineering ◽  
High Speed ◽  
High Performance ◽  
Large Scale ◽  
Data Communication ◽  
Path Diversity ◽  
Grid Systems ◽  
Distributed Communication ◽  
High Bandwidth

Communication in large scale distributed systems has a major impact on the overall performance and widely acceptance of such systems. In this chapter we analyze existing work in enabling high-performance communications in large scale distributed systems, presenting specific problems and existing solutions, as well as several future trends. Because applications running in Grids, P2Ps and other types of large scale distributed systems have specific communication requirements, we present different the problem of delivering efficient communication in case of P2P and Grid systems. We present existing work in enabling high-speed networks to support research worldwide, together with problems related to traffic engineering, QoS assurance, protocols designed to overcome current limitation with the TCP protocol in the context of high bandwidth traffic. We next analyze several group communication models, based on hybrid multicast delivery frameworks, path diversity, multicast trees, and distributed communication. Finally, we analyze data communication solutions specifically designed for P2P and Grid systems.

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