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Vehicle-assisted framework for delay-sensitive applications in smart cities

Vehicle-assisted framework for delay-sensitive applications in smart cities

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With the advancement in technology, applications such as real-time object detection, route predictions, and infotainment required a significant amount of computing power. However, resource constraint onboard computing units installed in vehicles cannot provide the desired computing. Therefore, complex computation tasks are offloaded to nearby vehicles, connected roadside units (RSUs), or data centers. However, the main objective is to optimize the use of resources and to minimize the communication delay. Thus, various techniques have been proposed to support the computation of complex applications through near real-time resource sharing. In this chapter, we summarize the recent contributions proposed to support task distribution over vehicular networks. This work provides an overview of vehicular-assisted frameworks and their challenges. Further, explored a various resource selection methods proposed in the literature for efficient task offloading. To provide better understanding, the existing techniques are categorized as traditional, game-theory, fuzzy, and reward-based. This chapter serves as a guide for researchers to understand the challenges of vehicular-assisted networks and state-of-the-art contributions.

Chapter Contents:

  • 8.1 Introduction
  • 8.2 Vehicular networks
  • 8.3 Vehicle-assisted network and their challenges
  • 8.4 Traditional offloading decision models
  • 8.4.1 Emerging decision models for vehicular networks
  • 8.4.2 Data protection, security, and trust management
  • 8.5 Applications of vehicular networks
  • 8.6 Conclusion
  • 8.7 Future directions
  • References

Inspec keywords: fuzzy set theory; vehicular ad hoc networks; game theory; resource allocation

Other keywords: resource selection methods; delay-sensitive application; route prediction; vehicle-assisted framework; resource constraint onboard computing unit; data centers; smart cities; object detection; game-theory; roadside units

Subjects: Game theory; Combinatorial mathematics; Mobile radio systems

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