Edge-Computing-Enabled Smart Cities: A Comprehensive Survey (1909.08747v2)

Abstract: Recent years have disclosed a remarkable proliferation of compute-intensive applications in smart cities. Such applications continuously generate enormous amounts of data which demand strict latency-aware computational processing capabilities. Although edge computing is an appealing technology to compensate for stringent latency related issues, its deployment engenders new challenges. In this survey, we highlight the role of edge computing in realizing the vision of smart cities. First, we analyze the evolution of edge computing paradigms. Subsequently, we critically review the state-of-the-art literature focusing on edge computing applications in smart cities. Later, we categorize and classify the literature by devising a comprehensive and meticulous taxonomy. Furthermore, we identify and discuss key requirements, and enumerate recently reported synergies of edge computing enabled smart cities. Finally, several indispensable open challenges along with their causes and guidelines are discussed, serving as future research directions.

• The paper presents a comprehensive taxonomy and analysis of edge computing in smart cities to guide future research.
• It highlights numerical forecasts, projecting a USD 717.2B market by 2023 and 500 billion IoT devices by 2030, which underscore scalability challenges.
• Practical case studies, including autonomous incident reporting and smart parking, demonstrate the benefits of localized data processing in urban environments.

Overview of "Edge-Computing-Enabled Smart Cities: A Comprehensive Survey"

The discussed survey comprehensively explores the significant role that edge computing plays in facilitating the functional infrastructure of smart cities. As compute-intensive applications grow within smart urban environments, latency reduction and local data processing become essential. Edge computing provides a localized solution by transferring computational processes closer to data sources, mitigating latency issues commonly associated with centralized cloud computing.

Core Contributions

The survey systematically dissects the evolution and state-of-the-art applications of edge computing in the context of smart cities. A noteworthy aspect is the paper's taxonomy, which classes literature based on capabilities and implementation strategies in edge computing. Additionally, it outlines essential requirements and challenges, providing a crucial framework for future research and development.

Key Findings and Implications

1. Numerical Predictions: The smart city market is projected to grow significantly, with estimates suggesting that market share could reach USD 717.2 billion by 2023, growing at a CAGR of 18.4%. The number of IoT devices is expected to reach 500 billion by 2030, underlining the exponential expansion of connected technologies that edge computing needs to support.
2. Technological Synergy: The paper identifies key technologies intersecting with edge computing, such as cloudlet, fog computing, and mobile edge computing. These enable the distinctive low-latency, geo-distributed characteristics of edge computing paradigms.
3. Real-World Applications: Motivational scenarios like autonomous cars accident reporting, smart forest fire detection, smart parking systems, and smart homes illustrate edge computing's applicability. These case studies emphasize real-time data processing capabilities required for immediate response and efficient application management.
4. Critical Parameters: The survey emphasizes context-awareness, scalability, security, and sustainability as critical evaluative criteria. These parameters serve as benchmarks in implementing edge computing architectures robustly.
5. Challenges and Guidelines: The paper identifies major open challenges like intelligent caching, collaborative edge computing, and cybersecurity. By outlining potential solutions such as AI-assisted caching and blockchain-based security, it draws a roadmap for advancements needed to harness the full potential of edge computing in smart cities.

Implications for Future Developments

As smart cities evolve, edge computing is poised to be an indispensable element of their infrastructure. The digital transformation towards more responsive urban environments requires sophisticated, comprehensive interplay between data sources, processing capabilities, and analytic procedures. The next steps in this line of research may involve deeper dives into the interoperability between diverse systems and advancing edge-based AI to handle the increasing data loads efficiently.

Continued exploration in resource management and economic incentives in the deployment of edge computing across urban landscapes will be necessary to address scalability and to ensure holistic growth of smart city frameworks. Furthermore, as integration with next-generation technologies like 5G progresses, adaptive methods to manage diverse service requirements become increasingly pertinent. These areas offer rich avenues for further research and practical development.

In conclusion, this survey not only maps the current terrain of edge computing in smart cities but also charts the course for future inquiry and application, thereby fostering an environment ripe for innovation and technological progress in urban settings.