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A Survey on Mobile Edge Computing: The Communication Perspective

Yuyi Mao(Hong Kong University of Science and Technology), Changsheng You(University of Hong Kong), Jun Zhang(Hong Kong University of Science and Technology), Kaibin Huang(University of Hong Kong), Khaled B. Letaief(Hong Kong University of Science and Technology)
January 1, 2017IEEE Communications Surveys & Tutorials5,592 citations
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5.6k

Citations

229

Influential Citations

IEEE Communications Surveys & Tutorials

Venue

2017

Year

Abstract

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

Analysis

Why This Paper Matters

Mobile edge computing (MEC) represents a fundamental shift in how we think about mobile computing, moving from centralized cloud architectures to distributed edge nodes. This survey, published in IEEE Communications Surveys & Tutorials and cited over 5,500 times, has become a foundational reference for researchers and practitioners working on 5G and IoT systems. Its importance lies in bridging two traditionally separate disciplines: wireless communications and mobile computing.

By focusing on joint radio-and-computational resource management, the paper provides a holistic framework for understanding how to optimize latency and energy consumption in MEC systems. This is critical for enabling emerging applications such as augmented reality, autonomous vehicles, and industrial IoT, which demand ultra-low latency and high reliability.

The paper also identifies key open challenges and future research directions, including cache-enabled MEC, mobility management, green MEC, and privacy-aware MEC. These directions have since become active research areas, demonstrating the survey's forward-looking perspective.

Technical Contributions

  • Comprehensive Survey: The paper systematically reviews state-of-the-art MEC research, organizing it around joint radio-and-computational resource management.
  • Paradigm Shift: It articulates the transition from mobile cloud computing to MEC, highlighting the benefits of pushing computation, control, and storage to network edges.
  • Resource Management Focus: It emphasizes the need to jointly optimize wireless communication and computational resources, covering techniques for computation offloading and network architecture design.
  • Open Challenges: It identifies and discusses critical issues such as MEC system deployment, cache-enabled MEC, mobility management, green MEC, and privacy-aware MEC.
  • Standardization and Applications: It introduces recent standardization efforts and typical MEC application scenarios, bridging research and practice.

Results

As a survey paper, it does not present new experimental results. However, it synthesizes findings from the literature to highlight the promised gains of MEC, including dramatic reductions in latency and mobile energy consumption. These gains are essential for meeting the stringent requirements of 5G and IoT applications. The paper also notes that advancements in the identified research directions will facilitate the transformation of MEC from theory to practice.

Significance

The paper's significance is evidenced by its high citation count and its role in shaping MEC research. It has provided a common vocabulary and framework for researchers across communications, networking, and mobile computing. By outlining future directions, it has catalyzed research in areas like cache-enabled MEC and privacy-aware MEC. Moreover, its discussion of standardization efforts helps align academic research with industry needs, accelerating the adoption of MEC in 5G networks. Overall, this survey has been instrumental in advancing the field of mobile edge computing and continues to be a key reference for both newcomers and experts.

mobile-edge-computing5gresource-managementcomputation-offloadingwireless-communicationssurveylatency-optimizationenergy-efficiency
Computer Vision

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