Articles
| Open Access | A Comprehensive Analysis of Communication Protocols, Security Vulnerabilities, and Energy-Aware Architectures in Large-Scale Internet of Things Ecosystems
Dr. Jonathan M. Keller , Department of Computer and Information Systems Rheinland Technical University, GermanyAbstract
The Internet of Things has emerged as a dominant technological paradigm, enabling pervasive interconnection among heterogeneous devices across consumer, industrial, and critical infrastructure domains. The rapid growth in IoT deployments has intensified challenges related to communication efficiency, protocol interoperability, security resilience, and long-term energy sustainability. These challenges are exacerbated by the constrained nature of IoT devices, which operate under strict limitations in power, processing capability, and memory while remaining continuously exposed to dynamic and often hostile network environments. This article presents a comprehensive and integrative analysis of IoT ecosystems, focusing on communication protocol architectures, documented security vulnerabilities, and energy-aware operational strategies. Drawing strictly from the provided references, the study synthesizes industry reports, academic surveys, and protocol-level analyses to examine how protocol choices influence attack surfaces, system reliability, and energy consumption patterns. Particular attention is given to constrained protocol stacks, machine-to-machine communication models, routing and aggregation mechanisms, and embedded communication reliability in distributed energy systems. A descriptive and theory-driven methodology is employed to analyze interactions across system layers without reliance on mathematical modeling or visual artifacts. The findings reveal persistent trade-offs between scalability and security, as well as between energy efficiency and communication robustness. The discussion highlights structural limitations in current IoT designs and argues for vertically integrated, cross-layer approaches that align embedded communication reliability, network-level efficiency, and security enforcement. The article concludes by outlining future research directions aimed at developing resilient, secure, and energy-balanced IoT architectures capable of sustaining large-scale deployment.
Keywords
Internet of Things, Communication Protocols, IoT Security, Energy Efficiency
References
Abdul, A. S. Skew variation analysis in distributed battery management systems using CAN FD and chained SPI for 192-cell architectures. Journal of Electrical Systems, 2024, 20(6s), 3109–3117.
Adafruit. All the Internet of Things—Episode Two: Protocols. Available online: https://learn.adafruit.com/alltheiot-protocols?view=all
Alibaba Cloud. Connect Devices to IoT Platform over CoAP—Device Connection. Available online: https://partners-intl.aliyun.com/help/docdetail/57697.htm
Alduais, N.; Abdullah, J.; Jamil, A.; Audah, L. An efficient data collection and dissemination for IoT based WSN. Proceedings of the IEEE Annual Information Technology, Electronics and Mobile Communication Conference, 2016.
Bosch IoT Suite. Bosch IoT Hub: Deprecation of AMQP Specific Message Header. Available online: https://bosch-iot-suite.com/news/bosch-iothub-deprecation-of-amqp-specific-message-header/
Cassia Networks. How to Deploy Cassia’s Bluetooth (BLE) Gateways over Cellular. Available online: https://www.cassianetworks.com/blog/how-to-deploy-cassias-bluetooth-ble-gateways-over-cellular-networks-with-soracom/
International Security Journal. What Is Data Poisoning and Why Should We Be Concerned. Available online: https://internationalsecurityjournal.com/what-is-data-poisoning/
Li, J.; Liu, W.; Wang, T.; Song, H.; Li, X.; Liu, F.; Liu, A. Battery-friendly relay selection scheme for prolonging the lifetimes of sensor nodes in the Internet of Things. IEEE Access, 2019.
Li, Q.; Gochhayat, S. P.; Conti, M.; Liu, F. Energiot: A solution to improve network lifetime of IoT devices. Pervasive and Mobile Computing, 2017.
Li, Z.; Zhang, W.; Qiao, D.; Peng, Y. Lifetime balanced data aggregation for the Internet of Things. Computers and Electrical Engineering, 2017.
Neshenko, N.; Bou-Harb, E.; Crichigno, J.; Kaddoum, G.; Ghani, N. Demystifying IoT Security: An exhaustive survey on IoT vulnerabilities and a first empirical look on Internet-scale IoT exploitations. IEEE Communications Surveys and Tutorials, 2019.
Qiu, T.; Liu, X.; Feng, L.; Zhou, Y.; Zheng, K. An efficient tree-based self-organizing protocol for Internet of Things. IEEE Access, 2016.
Radware. IoT Attack: Fraggle Attack. Available online: https://www.radware.com/security/ddos-knowledge-center/ddospedia/fraggle-attack/
Sharma, C.; Gondhi, N. K. Communication protocol stack for constrained IoT systems. Proceedings of the International Conference on Internet of Things: Smart Innovation and Usages, 2018.
Shin, D.; Yun, K.; Kim, J.; Astillo, P. V.; Kim, J.; You, I. A security protocol for route optimization in DMM-based smart home IoT networks. IEEE Access, 2019.
Techjury. How Many IoT Devices Are There in 2021? Available online: https://techjury.net/blog/how-many-iotdevices-are-there/
Thota, P.; Kim, Y. Implementation and comparison of M2M protocols for Internet of Things. Proceedings of the International Conference on Applied Computing and Information Technology, 2016.
Venafi. Top 10 Vulnerabilities That Make IoT Devices Insecure. Available online: https://www.venafi.com/blog/top-10-vulnerabilities-make-iot-devices-insecure.
Article Statistics
Downloads
Copyright License
Copyright (c) 2025 Dr. Jonathan M. Keller (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright of all articles published in (GMJ) Journal is retained by the authors. The articles are licensed under the open access Creative Commons CC BY 4.0 license, which means that anyone can download and read the paper for free.