| 1. |
- Bell, Taylor, et al.
(författare)
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Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b
- 2024
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Ingår i: Nature Astronomy. - 2397-3366. ; 8:7, s. 879-898
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Tidskriftsartikel (refereegranskat)abstract
- Hot Jupiters are among the best-studied exoplanets, but it is still poorly understood how their chemical composition and cloud properties vary with longitude. Theoretical models predict that clouds may condense on the nightside and that molecular abundances can be driven out of equilibrium by zonal winds. Here we report a phase-resolved emission spectrum of the hot Jupiter WASP-43b measured from 5 μm to 12 μm with the JWST’s Mid-Infrared Instrument. The spectra reveal a large day–night temperature contrast (with average brightness temperatures of 1,524 ± 35 K and 863 ± 23 K, respectively) and evidence for water absorption at all orbital phases. Comparisons with three-dimensional atmospheric models show that both the phase-curve shape and emission spectra strongly suggest the presence of nightside clouds that become optically thick to thermal emission at pressures greater than ~100 mbar. The dayside is consistent with a cloudless atmosphere above the mid-infrared photosphere. Contrary to expectations from equilibrium chemistry but consistent with disequilibrium kinetics models, methane is not detected on the nightside (2σ upper limit of 1–6 ppm, depending on model assumptions). Our results provide strong evidence that the atmosphere of WASP-43b is shaped by disequilibrium processes and provide new insights into the properties of the planet’s nightside clouds. However, the remaining discrepancies between our observations and our predictive atmospheric models emphasize the importance of further exploring the effects of clouds and disequilibrium chemistry in numerical models.
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| 2. |
- Corodescu, Andrei-Alin, et al.
(författare)
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Big Data Workflows : Locality-Aware Orchestration Using Software Containers
- 2021
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:24
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Tidskriftsartikel (refereegranskat)abstract
- The emergence of the edge computing paradigm has shifted data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructures. Therefore, data processing solutions must consider data locality to reduce the performance penalties from data transfers among remote data centres. Existing big data processing solutions provide limited support for handling data locality and are inefficient in processing small and frequent events specific to the edge environments. This article proposes a novel architecture and a proof-of-concept implementation for software container-centric big data workflow orchestration that puts data locality at the forefront. The proposed solution considers the available data locality information, leverages long-lived containers to execute workflow steps, and handles the interaction with different data sources through containers. We compare the proposed solution with Argo workflows and demonstrate a significant performance improvement in the execution speed for processing the same data units. Finally, we carry out experiments with the proposed solution under different configurations and analyze individual aspects affecting the performance of the overall solution.
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| 3. |
- Esparza-Borges, E., et al.
(författare)
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Detection of Carbon Monoxide in the Atmosphere of WASP-39b Applying Standard Cross-correlation Techniques to JWST NIRSpec G395H Data
- 2023
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Ingår i: Astrophysical Journal Letters. - 2041-8213 .- 2041-8205. ; 955:1
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Tidskriftsartikel (refereegranskat)abstract
- Carbon monoxide was recently reported in the atmosphere of the hot Jupiter WASP-39b using the NIRSpec PRISM transit observation of this planet, collected as part of the JWST Transiting Exoplanet Community Early Release Science Program. This detection, however, could not be confidently confirmed in the initial analysis of the higher-resolution observations with NIRSpec G395H disperser. Here we confirm the detection of CO in the atmosphere of WASP-39b using the NIRSpec G395H data and cross-correlation techniques. We do this by searching for the CO signal in the unbinned transmission spectrum of the planet between 4.6 and 5.0 μm, where the contribution of CO is expected to be higher than that of other anticipated molecules in the planet’s atmosphere. Our search results in a detection of CO with a cross-correlation function (CCF) significance of 6.6σ when using a template with only 12C16O lines. The CCF significance of the CO signal increases to 7.5σ when including in the template lines from additional CO isotopologues, with the largest contribution being from 13C16O. Our results highlight how cross-correlation techniques can be a powerful tool for unveiling the chemical composition of exoplanetary atmospheres from medium-resolution transmission spectra, including the detection of isotopologues.
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| 4. |
- Flagg, Laura, et al.
(författare)
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Debris Disks Can Contaminate Mid-infrared Exoplanet Spectra: Evidence for a Circumstellar Debris Disk around Exoplanet Host WASP-39
- 2024
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Ingår i: Astrophysical Journal Letters. - 2041-8213 .- 2041-8205. ; 969:1
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Tidskriftsartikel (refereegranskat)abstract
- The signal from a transiting planet can be diluted by astrophysical contamination. In the case of circumstellar debris disks, this contamination could start in the mid-infrared and vary as a function of wavelength, which would then change the observed transmission spectrum for any planet in the system. The MIRI/Low Resolution Spectrometer WASP-39b transmission spectrum shows an unexplained dip starting at ∼10 μm that could be caused by astrophysical contamination. The spectral energy distribution displays excess flux at similar levels to that which are needed to create the dip in the transmission spectrum. In this Letter, we show that this dip is consistent with the presence of a bright circumstellar debris disk, at a distance of >2 au. We discuss how a circumstellar debris disk like that could affect the atmosphere of WASP-39b. We also show that even faint debris disks can be a source of contamination in MIRI exoplanet spectra.
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| 5. |
- Khan, Akif Quddus, et al.
(författare)
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A Taxonomy for Cloud Storage Cost
- 2024
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Ingår i: Management of Digital EcoSystems - 15th International Conference, MEDES 2023, Revised Selected Papers. - : Springer Nature. ; , s. 317-330
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Konferensbidrag (refereegranskat)abstract
- The cost of using cloud storage services is complex and often an unclear structure, while it is one of the important factors for organisations adopting cloud storage. Furthermore, organisations take advantage of multi-cloud or hybrid solutions to combine multiple public and/or private cloud service providers to avoid vendor lock-in, achieve high availability and performance, optimise cost, etc. This complicated ecosystem makes it even harder to understand and manage cost. Therefore, in this paper, we provide a taxonomy of cloud storage cost in order to provide a better understanding and insights on this complex problem domain.
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| 6. |
- Khan, Akif Quddus, et al.
(författare)
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Smart Data Placement for Big Data Pipelines : An Approach based on the Storage-as-a-Service Model
- 2022
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Ingår i: 2022 IEEE/ACM 15TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING, UCC. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 317-320
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Konferensbidrag (refereegranskat)abstract
- The development of big data pipelines is a challenging task, especially when data storage is considered as part of the data pipelines. Local storage is expensive, hard to maintain, comes with several challenges (e.g., data availability, data security, and backup). The use of cloud storage, i.e., Storageas-a-Service (StaaS), instead of local storage has the potential of providing more flexibility in terms of such as scalability, fault tolerance, and availability. In this paper, we propose a generic approach to integrate StaaS with data pipelines, i.e., computation on an on-premise server or on a specific cloud, but integration with StaaS, and develop a ranking method for available storage options based on five key parameters: cost, proximity, network performance, the impact of server-side encryption, and user weights. The evaluation carried out demonstrates the effectiveness of the proposed approach in terms of data transfer performance and the feasibility of dynamic selection of a storage option based on four primary user scenarios.
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| 7. |
- Khan, Akif Quddus, et al.
(författare)
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Smart Data Placement Using Storage-as-a-Service Model for Big Data Pipelines
- 2023
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 23:2
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Tidskriftsartikel (refereegranskat)abstract
- Big data pipelines are developed to process data characterized by one or more of the three big data features, commonly known as the three Vs (volume, velocity, and variety), through a series of steps (e.g., extract, transform, and move), making the ground work for the use of advanced analytics and ML/AI techniques. Computing continuum (i.e., cloud/fog/edge) allows access to virtually infinite amount of resources, where data pipelines could be executed at scale; however, the implementation of data pipelines on the continuum is a complex task that needs to take computing resources, data transmission channels, triggers, data transfer methods, integration of message queues, etc., into account. The task becomes even more challenging when data storage is considered as part of the data pipelines. Local storage is expensive, hard to maintain, and comes with several challenges (e.g., data availability, data security, and backup). The use of cloud storage, i.e., storage-as-a-service (StaaS), instead of local storage has the potential of providing more flexibility in terms of scalability, fault tolerance, and availability. In this article, we propose a generic approach to integrate StaaS with data pipelines, i.e., computation on an on-premise server or on a specific cloud, but integration with StaaS, and develop a ranking method for available storage options based on five key parameters: cost, proximity, network performance, server-side encryption, and user weights/preferences. The evaluation carried out demonstrates the effectiveness of the proposed approach in terms of data transfer performance, utility of the individual parameters, and feasibility of dynamic selection of a storage option based on four primary user scenarios.
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| 8. |
- Khan, Akif Quddus, et al.
(författare)
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Towards Cloud Storage Tier Optimization with Rule-Based Classification
- 2023
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Ingår i: Service-Oriented and Cloud Computing. - : Springer Nature. ; , s. 205-216
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Konferensbidrag (refereegranskat)abstract
- Cloud storage adoption has increased over the years as more and more data has been produced with particularly high demand for fast processing and low latency. To meet the users’ demands and to provide a cost-effective solution, cloud service providers (CSPs) have offered tiered storage; however, keeping the data in one tier is not a cost-effective approach. Hence, several two-tiered approaches have been developed to classify storage objects into the most suitable tier. In this respect, this paper explores a rule-based classification approach to optimize cloud storage cost by migrating data between different storage tiers. Instead of two, four distinct storage tiers are considered, including premium, hot, cold, and archive. The viability and potential of the approach are demonstrated by comparing cost savings achieved when data was moved between tiers versus when it remained static. The results indicate that the proposed approach has the potential to significantly reduce cloud storage cost, thereby providing valuable insights for organizations seeking to optimize their cloud storage strategies. Finally, the limitations of the proposed approach are discussed along with the potential directions for future work, particularly the use of game theory to incorporate a feedback loop to extend and improve the proposed approach accordingly.
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| 9. |
- Khan, Akif Quddus, et al.
(författare)
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Towards Graph-based Cloud Cost Modelling and Optimisation
- 2023
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Ingår i: Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1337-1342
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Konferensbidrag (refereegranskat)abstract
- Cloud computing has become an increasingly popular choice for businesses and individuals due to its flexibility, scalability, and convenience; however, the rising cost of cloud resources has become a significant concern for many. The pay-per-use model used in cloud computing means that costs can accumulate quickly, and the lack of visibility and control can result in unexpected expenses. The cost structure becomes even more complicated when dealing with hybrid or multi-cloud environments. For businesses, the cost of cloud computing can be a significant portion of their IT budget, and any savings can lead to better financial stability and competitiveness. In this respect, it is essential to manage cloud costs effectively. This requires a deep understanding of current resource utilization, forecasting future needs, and optimising resource utilization to control costs. To address this challenge, new tools and techniques are being developed to provide more visibility and control over cloud computing costs. In this respect, this paper explores a graph-based solution for modelling cost elements and cloud resources and potential ways to solve the resulting constraint problem of cost optimisation. We primarily consider utilization, cost, performance, and availability in this context. Such an approach will eventually help organizations make informed decisions about cloud resource placement and manage the costs of software applications and data workflows deployed in single, hybrid, or multi-cloud environments.
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| 10. |
- Nikolov, Nikolay, et al.
(författare)
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Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers
- 2021
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Ingår i: INTERNET OF THINGS. - : Elsevier BV. - 2543-1536 .- 2542-6605. ; 16, s. 100440-
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Tidskriftsartikel (refereegranskat)abstract
- Big Data processing, especially with the increasing proliferation of Internet of Things (IoT) technologies and convergence of IoT, edge and cloud computing technologies, involves handling massive and complex data sets on heterogeneous resources and incorporating different tools, frameworks, and processes to help organizations make sense of their data collected from various sources. This set of operations, referred to as Big Data workflows, requires taking advantage of Cloud infrastructures' elasticity for scalability. In this article, we present the design and prototype implementation of a Big Data workflow approach based on the use of software container technologies, message-oriented middleware (MOM), and a domain-specific language (DSL) to enable highly scalable workflow execution and abstract workflow definition. We demonstrate our system in a use case and a set of experiments that show the practical applicability of the proposed approach for the specification and scalable execution of Big Data workflows. Furthermore, we compare our proposed approach's scalability with that of Argo Workflows - one of the most prominent tools in the area of Big Data workflows - and provide a qualitative evaluation of the proposed DSL and overall approach with respect to the existing literature.
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