Cost-efficient, QoS and Security aware Placement of Smart Farming IoT Applications in Cloud-Fog Infrastructure

TL;DR

This paper presents an ILP-based model for cost-efficient placement of smart farming IoT applications in cloud-fog infrastructure, balancing QoS and security constraints.

Contribution

It introduces a novel optimization model for IoT application placement considering cost, QoS, and security in cloud-fog environments.

Findings

QoS and security significantly impact placement cost

Relaxing security constraints reduces overall cost

ILP model effectively balances resource use and constraints

Abstract

Smart farming is a recent innovation in the agriculture sector that can improve the agricultural yield by using smarter, automated, and data driven farm processes that interact with IoT devices deployed on farms. A cloud-fog infrastructure provides an effective platform to execute IoT applications. While fog computing satisfies the real-time processing need of delay-sensitive IoT services by bringing virtualized services closer to the IoT devices, cloud computing allows execution of applications with higher computational requirements. The deployment of IoT applications is a critical challenge as cloud and fog nodes vary in terms of their resource availability and use different cost models. Moreover, diversity in resource, quality of service (QoS) and security requirements of IoT applications make the problem even more complex. In this paper, we model IoT application placement as an optimization problem that aims at minimizing the cost while satisfying the QoS and security constraints. The problem is formulated using Integer Linear Programming (ILP). The ILP model is evaluated for a small-scale scenario. The evaluation shows the impact of QoS and security requirement on the cost. We also study the impact of relaxing security constraint on the placement decision.