Resilience In Edge Computing
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Edge Computing Resilience
Edge computing has emerged as a powerful technology for efficiently executing tasks by pushing cloud computing capabilities to the edge of the network. This approach significantly improves the quality of services of IoT applications and greatly enhances the performance of resource-constraint edge devices. However, with the explosive growth in users and data generation, low-computing-capability devices often struggle to meet computation demands in time, posing a significant challenge to the success of edge computing. These challenges include latency requirements, low computational power, system heterogeneity, energy constraints and privacy issues. To address these challenges, it is critical to design robust edge computing systems. This book provides a systematic and comprehensive analysis of edge computing challenges and presents resilient designs and frameworks suitable for real-time edge computing applications. The discussion primarily focuses on overcoming resource constraints in unstable edge computing environments, which is achieved through various concepts and technologies, such as fault handling, optimization and computation offloading. The book is significant to researchers in the field of edge computing, especially in the context of the resource-constrained paradigm, IoT application execution in the edge and fog computing. The book features innovative models and frameworks for processing time-critical, energy-aware and privacy-aware applications. By reading this book, researchers and professionals will gain a deeper understanding of different technologies and frameworks for edge computing and develop an appreciation for edge computing resilience. This resilience makes the edge system robust against frequent system failures for real-time IoT applications. The book provides a foundation for future research in this field and is an essential read for those seeking to advance their knowledge and expertise in edge computing.
Resilience in Edge Computing
Computing paradigms have continuously evolved to address the growing demands of modern applications. Initially, cloud computing emerged as a transformative approach, enabling the offloading of computationally intensive tasks to centralized and virtualized infrastructures. These infrastructures provide resource scalability and flexibility, and thus can adapt to the diverse applications with varying requirements. However, the centralized nature of cloud computing resources induces additional communication delay and causes network overhead. This is especially problematic for time-sensitive and mission-critical applications. Eventually, edge computing was introduced as a complementary paradigm, bringing computational resources closer to end-users and devices. This proximity benefits time-critical applications by reducing delays and improving responsiveness. It also offers better privacy by processing sensitive data locally on devices or nearby servers, reducing the risk of exposure during transmission to centralized cloud systems. As a natural progression, multi-access edge computing (MEC) has emerged to address the unique requirements of highly dynamic environments. In many 6G-related projects, there is a clear trend toward virtualizing computing resources at the edge. Motivated by the cloud-edge-continuum that is the basis for next-generation metaverse applications and the need for low latency solutions, distributed computing is now receiving even more attention. A final hurdle for the wide use of edge computing for mission-critical applications is resilience. In this context, resilience is the ability of modern communication and computation systems to deal with unknown and unforeseen events, both from internal and external sources. Thus, making MEC resilient to outages, security incidents, and overall challenging conditions is of the highest importance. In this monograph, the current state-of-the-art of resilience in mobile edge computing is reviewed. MEC-specific challenges and resilience objectives are explored, and selected resilience measures are discussed. This monograph is an invaluable resource for beginners and experts in the field and provides a compound resource on resilience in MEC.
Software Architecture for Big Data and the Cloud
Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors.