Energy Security as a Key Driving Factor for Socioeconomic Development: From Mitigation to Solution

This book looks at the increasing demand for energy of contemporary societies and economies from around the world. Energy is the driving force behind development. As such, the future challenge will be not only to meet the rising demand but also to implement less reliance on depleting fossil fuels, which cause damage to the environment. Moreover, the sustainability of supplied energy requires a reduction of emissions to control the absorption capacity vis-à-vis the environment. Globally, policymakers have largely recognized the significance of the relationship between energy and economic progress. Policymakers usually consider the social and economic aspects of energy security in terms of affordability and accessibility of service. The conditions of socioeconomic development depend on safe, secure, and sustainable energy at affordable prices. One of the prime concerns of policymakers should be to ensure energy security at the national level. These factors result in an increasing interest in undertaking activities in developing renewable resources. Energy efficiency is treated as the most cost-effective way to reduce energy demand while maintaining stable economic activity. Increasing energy efficiency is an important contributive aspect to solving issues in relation to climate change, energy security, and energy competitiveness. As a result, no country can afford to waste energy—giving rise to this Special Issue of “Energy Security as a Key Driving Factor for Socioeconomic Development: From Mitigation to Solution” in the journal Energies

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen