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FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing (1811.11978v1)

Published 29 Nov 2018 in cs.DC

Abstract: The requirement of supporting both latency sensitive and computing intensive Internet of Things (IoT) applications is consistently boosting the necessity for integrating Edge, Fog and Cloud infrastructure. Although there are a number of real-world frameworks attempt to support such integration, they have many limitations from various perspectives including platform independence, security, resource management and multi-application assistance. To address these limitations, we propose a simplified but effective framework, named FogBus for facilitating end-to-end IoT-Fog(Edge)-Cloud integration. FogBus offers a platform independent interface to IoT applications and computing instances for execution and interaction. It not only assists developers in building applications but also helps users in running multiple applications at a time and service providers to manage their resources. In addition, FogBus applies Blockchain, authentication and encryption techniques to secure operations on sensitive data. Because of its lightweight and cross platform software systems, it is easy to deploy, scalable and cost e_cient. We demonstrate the effectiveness of our framework by creating a computing environment with it that integrates finger pulse oximeter as IoT devices with Smartphone-based gateway and Raspberry Pi-based Fog nodes for Sleep Apnea analysis. We also run several experiments on this computing environment varying FogBus settings. The experimental results show that different FogBus settings can improve latency, energy, network and CPU usage of the computing infrastructure.

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Authors (4)
  1. Shreshth Tuli (37 papers)
  2. Redowan Mahmud (10 papers)
  3. Shikhar Tuli (15 papers)
  4. Rajkumar Buyya (192 papers)
Citations (306)

Summary

Overview of "FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing"

The paper presents FogBus, a framework designed to integrate IoT systems with Fog and Cloud infrastructures, addressing existing challenges in platform independence, security, and resource management. FogBus proposes a lightweight and efficient solution to enable the seamless operation of latency-sensitive and compute-intensive IoT applications by leveraging both local edge resources and remote cloud capabilities.

Key Contributions

The paper's principal contributions include:

  1. Framework Design and Implementation: FogBus facilitates IoT-Fog-Cloud integration, offering platform-independent execution environments and node-to-node interactions. It supports multiple applications simultaneously and provides APIs and programs compatible with a wide range of operating systems.
  2. Security Implementation: The paper introduces robust security mechanisms incorporating Blockchain, authentication, and encryption techniques to ensure the integrity and privacy of the data being processed and shared across the network.
  3. Decentralized Resource Management: With a focus on edge computing, FogBus can efficiently manage resources without relying on centralized control, thus improving response times and reducing latencies.
  4. Case Study and Prototype: The practical application of FogBus is validated with a prototype system for Sleep Apnea analysis, demonstrating improvements in various performance metrics, like latency and resource usage.
  5. Performance Evaluation: Comprehensive experiments reveal that adjusting FogBus settings significantly impacts task handling ability, service delivery latency, network usage, and energy consumption. Results indicate that a Fog-only configuration with disabled Blockchain functionality provides optimal performance in specific scenarios.

Implications and Future Directions

The FogBus framework signifies a flexible and efficient approach to IoT-enabled system management, largely due to its cross-platform capabilities and end-to-end security measures. By providing a PaaS model for application developers and service providers, FogBus enhances the deployment and management of applications across heterogeneous environments.

For future research, the authors identify several key areas for enhancement:

  • Advanced Resource Management: Developing dynamic provisioning policies could help balance load and Quality of Service more effectively.
  • Infrastructure Virtualization: Exploring Fog virtualization could provide additional layers of abstraction and efficiency.
  • Incorporation of AI: Integrating AI for operational control and prediction-based decision-making could elevate system resilience.
  • Application Placement and Migration: Improving the strategies for application placement and runtime migration can optimize latency and resource utilization.

FogBus stands to further reshape how IoT systems interface with computational infrastructures, particularly in fields requiring rapid data processing and stringent security measures, like healthcare and smart city development.