## 2 Related Works  
In addition to the research of [12; 13], there is a number of studies that examine the TSCH centralized scheduling algorithm, directly related to TASA or not. There are studies directly related to TASA [14; 15; 16], and studies not related to TASA [17; 18]. Specific to [12; 13], this research refers to studies conducted by [PERSON] [19] and [PERSON] [20]. [PERSON] et al. provide an example of how a scheduling algorithm is built and tested for its performance, while [PERSON]'s study introduces the term \"scheduling decision\", which is one of the topics discussed in this research. The latest research that refers to TASA was conducted by [PERSON] et al. [14], who produced a scheduling algorithm called matching scheduling algorithm optimization of MSA (MSA-OSA), which has almost the same characteristics as IRByTSA. The only difference is that MSA-OSA gives transmission priority to leaf nodes, while IRByTSA gives transmission priority to high-ranking nodes. Nonetheless, the research conducted by [PERSON] does not discuss the achievement of duty cycles that can be generated by MSA-OSA. It also does not discuss the mechanism of multihop data transfer to be collected at the master node. To test the scheduling algorithm they created, [PERSON] et al. did not mention the use of simulators or specific programming languages. Other research that refers to TASA is a study conducted by [PERSON] et al. [15], who developed a scheduling algorithm for TSCH networks to maximize energy efficiency. The scheduling algorithm was developed using the energy consumption model on TSCH nodes and nonlinear programming (NLP). However, similar to [14], the study conducted by [PERSON] et al. also did not mention the simulator/tool used in their research. Some studies that examined the 802.15.4e TSCH network were conducted by [PERSON] et al. [17], [PERSON] et al. [18], and [PERSON] [21]. In Reference [17], a centralized scheduling algorithm called centralized link scheduling (CLS) was proposed, which utilized the RPL routing protocol to produce its scheduling decisions. The target of this research was to make scheduling algorithms that required fewer control messages. To test the performance of the proposed CLS algorithm, [PERSON] et al. used an OPNET simulator. However, this research did not clearly describe how the OPNET simulator was used to carry out the tests. Meanwhile, [PERSON] et al. [18] examined the signaling mechanism of the multichannel optimized delay timeslot assignment (MODESA) centralized scheduling algorithm, comparing the number of messages needed to install and upgrade a scheduling scheme on the TSCH network. However, they did not explain what simulators or software were used to do the testing. Research by [PERSON] et al. [21] examined the mechanism of TSCH network formation and how long it took to form a network, using the NS3 simulator as a performance test tool against the proposed mechanism. That study showed that NS3 had a TSCH module even though it did not have sufficient support for the development of a centralized scheduling algorithm. One of the aims of this research was to develop a research support tool. To explain how the tool was designed, written, and developed, this research referred to the work of [PERSON] et al. [22] and [PERSON] et al. [23]. The research of [PERSON] et al. [22] developed a new simulator using the JAVA language with the ability to model an information exchange on a nano scale. This simulator provided a toolkit for simulating any types of nano networks. Nanonetworking is a new interdisciplinary area that combines the materials of nanotechnology, biotechnology, and ICT in one unit of research. The first part of this research explained how this simulator was developed, starting from the identification of the main features of the nanonetwork communication. It then explained the simulator's architecture, which is comprised of classes, and lastly explained the specific aspects of the simulator's architecture. Meanwhile, research by [PERSON] et al.