Improved Harris Hawks Optimization Algorithm Based Data Placement Strategy for Integrated Cloud and Edge Computing

Cloud computing is considered to facilitate a more cost-effective way to deploy scientific workflows.The individual tasks of a scientific work-flow necessitate a diversified number of large states that are spatially located in different datacenters,thereby resulting in huge delays during data transmis-sion.Edge computing minimizes the delays in data transmission and supports the fixed storage strategy for scientific workflow private datasets.Therefore,this fixed storage strategy creates huge amount of bottleneck in its storage capacity.At this juncture,integrating the merits of cloud computing and edge computing during the process of rationalizing the data placement of scientific workflows and optimizing the energy and time incurred in data transmission across different datacentres remains a challenge.In this paper,Adaptive Cooperative Foraging and Dispersed Foraging Strategies-Improved Harris Hawks Optimization Algorithm(ACF-DFS-HHOA)is proposed for optimizing the energy and data transmission time in the event of placing data for a specific scientific workflow.This ACF-DFS-HHOA considered the factors influencing transmission delay and energy consumption of data centers into account during the process of rationalizing the data placement of scientific workflows.The adaptive cooperative and dispersed foraging strategy is included in HHOA to guide the position updates that improve population diversity and effectively prevent the algorithm from being trapped into local optimality points.The experimental results of ACF-DFS-HHOA confirmed its predominance in minimizing energy and data transmission time incurred during workflow execution.

A Workflow Demonstrator for Processing Catalysis Research Data

The UK Catalysis Hub(UKCH)is designing a virtual research environment to support data processing and analysis,the Catalysis Research Workbench(CRW).The development of this platform requires identifying the processing and analysis needs of the UKCH members and mapping them to potential solutions.This paper presents a proposal for a demonstrator to analyse the use of scientific workflows for large scale data processing.The demonstrator provides a concrete target to promote further discussion of the processing and analysis needs of the UKCH community.In this paper,we will discuss the main requirements for data processing elicited and the proposed adaptations that will be incorporated in the design of the CRW and how to integrate the proposed solutions with existing practices of the UKCH.The demonstrator has been used in discussion with researchers and in presentations to the UKCH community,generating increased interest and motivating furtherdevelopment.

Making Canonical Workflow Building Blocks Interoperable across Workflow Languages

We introduce the concept of Canonical Workflow Building Blocks(CWBB),a methodology of describing and wrapping computational tools,in order for them to be utilised in a reproducible manner from multiple workflow languages and execution platforms.The concept is implemented and demonstrated with the BioExcel Building Blocks library(BioBB),a collection of tool wrappers in the field of computational biomolecular simulation.Interoperability across different workflow languages is showcased through a protein Molecular Dynamics setup transversal workflow,built using this library and run with 5 different Workflow Manager Systems(WfMS).We argue such practice is a necessary requirement for FAIR Computational Workflows and an element of Canonical Workflow Frameworks for Research(CWFR)in order to improve widespread adoption and reuse of computational methods across workflow language barriers.

F4ESS-a framework for interdisciplinary data-driven earth system science

Earth system science is an interdisciplinary effort to understand the fundamentals and interactions of environmental processes.Interdisciplinary research is challenging since it demands the integration of scientific schemes and practices from different research fields into a collaborative work environment.This paper introduces the framework F4ESS that supports this integration.F4ESS provides methods and technologies that facilitate the development of integrative work environments for Earth system science.F4ESS enables scientists a)to outline structured and summarized descriptions of scientific procedures to facilitate communication and synthesis,b)to combine a large variety of distributed data analysis software into seamless data analysis chains and workflows,c)to visually combine and interactively explore the manifold spatiotemporal data and results to support understanding and knowledge creation.The F4ESS methods and technologies are generic and can be applied in various scientific fields.We discuss F4EsS in the context of the interdisciplinary investigation of flood events.