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A Cloud-based Middleware for Self-Adaptive IoT-Collaboration Services.

Soojin Park1, Sungyong Park2

  • 1Graduate School of Management of Technology, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 04107, Korea. psjdream@sogang.ac.kr.

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Summary
This summary is machine-generated.

This study introduces a cloud-based middleware framework for adaptable Internet of Things (IoT) collaboration services, addressing context awareness and domain dependency challenges. The framework enables efficient component sharing and self-adaptation across multiple IoT domains.

Keywords:
cloud serviceinternet of thingsmiddleware platformself-adaptation

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Area of Science:

  • Computer Science
  • Software Engineering
  • Distributed Systems

Background:

  • Existing middleware frameworks for IoT collaboration services struggle with context awareness and uncertainty across multiple domains.
  • Current solutions are often single-system limited, domain-specific, and require significant developer effort for self-adaptive services.
  • Lack of reusability hinders the efficient development and deployment of IoT collaboration services in diverse environments.

Purpose of the Study:

  • To propose a novel cloud-based middleware framework for developing generic, self-adaptive IoT collaboration services.
  • To address limitations of existing frameworks by enabling efficient context awareness, uncertainty management, and cross-domain component reuse.
  • To provide a platform for developers to manage domain-specific components and facilitate the creation of adaptable IoT services.

Main Methods:

  • Development of a cloud-based middleware framework with distinct layers for domain-dependent and independent components.
  • Implementation of cloud services for uploading, searching, and launching components within a MAPE (Monitoring, Analysis, Planning, Execution) cycle.
  • Utilizing a web-based interface for convenient management of components and Virtual Machines (VMs).

Main Results:

  • The proposed framework demonstrates feasibility through a simulation of an IoT service for criminal suspect tracing.
  • Performance evaluation indicates a low overhead (6%) compared to pure Java-based middleware.
  • The framework exhibits scalability, supporting an increase in the number of VMs up to 16.

Conclusions:

  • The proposed cloud-based middleware framework effectively supports self-adaptive IoT collaboration services.
  • It enhances generic applicability by separating domain-specific logic and promoting component reuse across different domains.
  • The framework offers an efficient and scalable solution for developing and deploying complex IoT collaboration services.