Article detail · 2021
A QoS-Aware Service Composition Mechanism in the Internet of Things Using a Hidden-Markov-Model-Based Optimization Algorithm
- Year
- 2021
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue IEEE Internet of Things Journal
- Catalog match (ISSN) IEEE Internet of Things Journal
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Recently, a new technology topic has been known as the Internet of Things (IoT), where all devices like smartphones, smart TVs, medical and healthcare ones, and home appliances have been applied for data generating. Due to the variety of services, the numerous service composition problems, mostly related to the Quality-of-Service (QoS) parameters, are recognized in the IoT domain. Since this issue is an NP-hard obstacle, different metaheuristic approaches have been utilized up until now to solve it. Many varieties of services can be brought into the IoT, depending on users’ demands. In this research, we have proposed an effective way based on a hidden Markov model (HMM) and an ant colony optimization (ACO) to answer the service composition issue by enhancing the QoS. The HMM has been trained to predict QoS. The emission and transition matrices have been improved using the Viterbi algorithm. We have executed the QoS estimation using the ACO algorithm and found a suitable path. The outcomes have illustrated the efficacy of the introduced method regarding availability, response time, cost, reliability, and energy consumption compared to the previous methods.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
110 citations
OpenAlex cited_by_count (cache / database)
14 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review 2024
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- An Efficient Design of Multiplier for Using in Nano-Scale IoT Systems Using Atomic Silicon 2023
- An energy-aware clustering method in the IoT using a swarm-based algorithm 2021
- A Quality-of-Service-Aware Service Composition Method in the Internet of Things Using a Multi-Objective Fuzzy-Based Hybrid Algorithm 2023
- A deep analysis of nature-inspired and meta-heuristic algorithms for designing intrusion detection systems in cloud/edge and IoT: state-of-the-art techniques, challenges, and future directions 2024
- An Energy-Aware IoT Routing Approach Based on a Swarm Optimization Algorithm and a Clustering Technique 2022
- A Probabilistic Approach to Load Balancing in Multi-Cloud Environments via Machine Learning and Optimization Algorithms 2025
- QoS-based routing protocol and load balancing in wireless sensor networks using the markov model and the artificial bee colony algorithm 2023
- Meet User’s Service Requirements in Smart Cities Using Recurrent Neural Networks and Optimization Algorithm 2023