Cloud Infrastructure Design Model for Green Smart City: Case Study of Electricity Generating Authority of Thailand

Thirasupa, Ririnda; Saivichit, Chaiyachet; Aswakul, Chaodit

doi:10.1007/978-981-15-1465-4_15

Cited by 4 publications

(6 citation statements)

References 10 publications

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“…The authors claim their model is generalized and can be applied to most buildings in Europe. [39] 2020 Datacenters A controller is created to control the cloud.…”

Section: B Cloud Computing For Energy Management In Buildings/homesmentioning

confidence: 99%

“…The power usage is uploaded to a cloud platform, which is then used by the utility companies to shed the electrical load when most houses are operating on the local energy storage. Likewise, the method proposed in [39] takes the load from the power grid using a smart city cloud controller (SCCC) and encourages the use of renewable energy, respectively.…”

Section: B Cloud Computing For Energy Management In Buildings/homesmentioning

confidence: 99%

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Energy Management in Smart Buildings and Homes: Current Approaches, a Hypothetical Solution, and Open Issues and Challenges

et al. 2021

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Energy plays a pivotal role for economic development of a country. A reliable energy source is needed to improve the living standards of people. To achieve such a goal, governments and industries are trying to install a new energy infrastructure called the "Smart Grid". This helps to manage the electricity generation and distribution in an efficient manner. Buildings and other structures are the biggest consumers of electricity. There is a need to reduce the energy consumption so that the resources can be utilized efficiently. Therefore, in this paper, we give a comprehensive state-of-the-art on various recent techniques and solutions which provide energy savings in smart homes and buildings. This includes statistical models, cloud computing based solutions, fog computing and smart metering based architectures, and several other IoT (internet of things) inspired solutions. We also present a hypothetical model that treats energy supply and usage in buildings as a self-managing energy system (SES). This paper is concluded by highlighting several open issues and challenges related to energy management in buildings.INDEX TERMS Energy Management, Smart Buildings and Homes.

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“…The authors claim their model is generalized and can be applied to most buildings in Europe. [39] 2020 Datacenters A controller is created to control the cloud.…”

Section: B Cloud Computing For Energy Management In Buildings/homesmentioning

confidence: 99%

Section: B Cloud Computing For Energy Management In Buildings/homesmentioning

confidence: 99%

Energy Management in Smart Buildings and Homes: Current Approaches, a Hypothetical Solution, and Open Issues and Challenges

et al. 2021

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“…Furthermore, three case studies are reported for each scenario to evaluate the ILP model's performance by considering the effect of task storage requirement, task computation requirement, and task granularity. Only one task parameter is varied to study its effect in each case study, as shown in Table 3, while the other task requirements are kept constants by assigning a value for each parameter based on [8]. The proportion of task x i,j , the task completion time t i and the payoff from private cloud computing…”

Section: Experimental Peer-to-peer Federated Cluster and Edge-core Cluster Scenariosmentioning

confidence: 99%

“…In the past, researchers have put efforts into finding the best solution for allocating tasks and optimizing power consumption depending on different assumptions. The linear programming has been formulated in [8] to manage cloud resources from green energy and in [9] to solve optimal processes deployment on hierarchical cloud resources. Both works in [8] and [9], however, lack the demand's granularity concern.…”

Section: Introductionmentioning

confidence: 99%

“…The linear programming has been formulated in [8] to manage cloud resources from green energy and in [9] to solve optimal processes deployment on hierarchical cloud resources. Both works in [8] and [9], however, lack the demand's granularity concern. In [10], the authors concentrate on predicting the cost of utilization on private cloud networks and finding a linear programming solution to minimize the cost within an interval time.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Cloud Orchestration Model of Containerized Task Scheduling Strategy Using Integer Linear Programming: Case Studies of IoTcloudServe@TEIN Project

Swatthong

Aswakul

2021

Energies

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As a playground for cloud computing and IoT networking environment, IoTcloudServe@TEIN has been established in the Trans-Eurasia Information Network (TEIN). In the IoTcloudServe@TEIN platform, a cloud orchestration for conducting the flow of IoT task demands is imperative for effectively improving performance. In this paper, we propose the model of optimal containerized task scheduling in cloud orchestration that maximizes the average payoff from completing tasks within the whole cloud system with different levels of cloud hierarchies. Based on integer linear programming, the model can take into account demand requirement and resource availability in terms of storage, computation, network, and splittable task granularity. To show the insights obtainable from the proposed model, the edge-core cluster of IoTcloudServe@TEIN and its peer-to-peer federated cloud scenario with OF@TEIN+ are numerically experimented and herein reported. To evaluate the model’s performance, payoff level and task completion time are considered by comparing with a well-known round-robin scheduling algorithm. The proposed ILP model can be a guideline for the cloud orchestration in IoTcloudserve@TEIN because of the lower task completion time and the higher payoff level especially upon the large demand growth, which is the major operation range of concerns in practice. Moreover, the proposed model illustrates mathematically the significance of implementing cloud architecture with refined splittable task granularity via the light-weighted container technology that has been used as the basis for IoTcloudServe@TEIN clustering design.

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IoT-based Office Buildings Energy Management with Distributed Edge Computing Capability

Moghadam

Abapour

2023

2023 8th International Conference on Technology and Energy Management (ICTEM)

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Cloud Infrastructure Design Model for Green Smart City: Case Study of Electricity Generating Authority of Thailand

Cited by 4 publications

References 10 publications

Energy Management in Smart Buildings and Homes: Current Approaches, a Hypothetical Solution, and Open Issues and Challenges

Energy Management in Smart Buildings and Homes: Current Approaches, a Hypothetical Solution, and Open Issues and Challenges

Optimal Cloud Orchestration Model of Containerized Task Scheduling Strategy Using Integer Linear Programming: Case Studies of IoTcloudServe@TEIN Project

IoT-based Office Buildings Energy Management with Distributed Edge Computing Capability

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