# Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins
## 2 Related Work  
This section provides an overview of the current research on orchestration architectures based on IoT in the context of smart grid and healthcare applications. Recognizing the predictable attributes inherent in mission-critical systems, such as the real-time power allocation to smart grid infrastructure, holds substantial importance [19]. The successful implementation of the Internet of Things (IoT) enabled applications crucial for mission-critical operations, which necessitate the ability to respond to events in real-world situations promptly. The emergence of the Internet of Things (IoT) has greatly increased the prevalence of devices equipped with intelligent sensors [18]. Consequently, this development has enhanced performance in various fields, such as smart cities [20; 21] and enterprise systems [22]. The progress made in the Internet of Things (IoT) field has created new avenues for creating and enhancing highly effective IoT applications. In service-oriented architecture, orchestration has gained significant importance in design [23; 24]. Its primary objective is to automate the complete execution process. There has been considerable scholarly interest in orchestration, specifically focusing on its use in service-oriented architecture (SOA) [25; 26]. IoT has become an essential element in both conventional and modern applications. A study by [27] introduced the concept of \"IoT ProSe\", incorporating task orchestration within mobile nodes. Additional methodologies, such as ProFun [28] and Makesense [29], were developed to enhance task execution efficiency. It is important to note that these methodologies primarily emphasized the dynamic features of orchestration rather than its autonomous behavior. The healthcare industry and other industries successfully utilized the potential of IoT technology by integrating orchestration [4]. In reference [6], a proposed architecture known as MDMT-MOA was presented for IoT enterprise designs, primarily focusing on orchestration. In a separate investigation, a scholarly article [30] presented the notion of cyber-physical systems as a service (CPSaaS) to achieve efficient task coordination in smart urban environments. The paper [31] introduced a mission-critical architecture designed to detect mountain fires, utilizing IoT task orchestration and integrating essential modules, including microservices and predictive analysis. Various scholarly investigations, such as healthcare research [32; 33], utilized sensors to identify patient motion in IoT health monitoring systems. The study by [33] also introduced a healthcare monitoring architecture that utilized cloud and fog-based computing systems to facilitate effective healthcare data administration. In [4], a research study introduced the concept of IoT task orchestration to monitor patient health. This study also proposed using an optimized scheduling technique to execute healthcare jobs efficiently. The study employed a hierarchical methodology for the coordination of tasks, involving the stages of task generation, task mapping, task scheduling, task allocation, and task deployment. The aforementioned methodology resulted in notable enhancements in response time and diminished latency. Furthermore, recent scholarly investigations on orchestration within the domain emphasized the automation of providing services. Several research projects were conducted to implement task-level orchestration, providing various benefits like increased flexibility, robustness, and dynamic management of the overall system execution [5; 6; 7]. Scheduling tasks was of great importance in orchestrating tasks within the Internet of Things (IoT) framework, and optimizing this process could substantially impact the system's overall performance. Recently, various efforts were made in terms of energy efficiency. The research [34] focused on the topic of secrecy of energy efficient hybrid beamforming in integrated satellite-terrestrial networks.