An efficient route planning model for mobile agents on the internet of things using Markov decision process

• Published in: Ad hoc networks 2020-03, Vol.98, p.102053, Article 102053
• Main Authors: Yousefi, Shamim, Derakhshan, Farnaz, Karimipour, Hadis, Aghdasi, Hadi S.
• Format: Article
• Language: English
• Subjects: Data aggregation; Internet of Things (IoT); Markov Decision Process (MDP); Mobile agents; Route planning
• ISSN: 1570-8705; 1570-8713
• DOI: 10.1016/j.adhoc.2019.102053

•Development of an energy-efficient data aggregation method on IoT using mobile agents.•Designing a reliable angle-based grouping technique to organize the cluster-heads.•Development of an efficient route planning model for mobile agents on IoT using MDP. Data aggregation on the Internet of Things (IoT) needs context-aware routing protocols to satisfy the Quality of Services (QoS) requirements. Developing energy-efficient, delay-aware, and reliable route planning, in particular, is one of the significant challenges in the scenarios of data aggregation for IoT applications. The established data aggregation approaches, which exploit the client-server-based methods, struggle with the short lifetime of the network, and high data transmission delay. It does not cover the variety of applications, which developed through IoT. To address these challenges, in this paper, the concept of mobile software agents for data aggregation on the IoT is used. The paper proposes a novel route planning mechanism for data aggregation on IoT using mobile agents. The proposed mechanism is composed of two main stages. The first stage clusters the IoT devices; then, organizes the cluster-heads into some groups by using an angle-based process for the assignment of mobile agents. The main purpose of the second stage is to provide route planning for each mobile agent in each group of the cluster-heads for efficient data aggregation through Markov Decision Process (MDP). The results show that the proposed mechanism improves energy consumption, data transmission delay, and the reliability of the IoT.