## 3 Proposed Scheme
### GTS Allocation Procedure
#### 3.3.1 Topsis  
If the number of GTS requests received by the PAN coordinator is less than its available slot capacity, then all the GTS requests will be entertained by informing all the successful nodes about their time slot information. Due to adaptive data slot requirements with varying channel conditions and the waiting time to transmit data, a technique for order performance by similarity to ideal solution (TOPSIS) is applied to determine the priority of the GTS-requesting nodes. The node with a higher TOPSIS value will be assigned GTSs before the other nodes. In this work, the TOPSIS value is calculated by considering the following parameters. * **Trust value:** The trust value of the requesting nodes is accorded the highest weight in the TOPSIS calculation, as detailed in Section 3.2. This ensures that nodes with a higher level of trustworthiness are given precedence in GTS allocation. * **Emergency data:** Priority is assigned to nodes presenting emergency data, such as critical patient health parameters. This proactive approach ensures that nodes with urgent data transmission requirements are prioritized for GTS allocation. * **Channel capacity:** Considering the communication channel's pivotal role in data transfer from IoT nodes to the PAN coordinator, the TOPSIS algorithm factors in the channel capacity. A superior communication channel is favored, as it enables the PAN coordinator to achieve better data rates during the data transfer process. * **Data request failure:** Nodes that were not allocated GTS in the last session receive preferential treatment in the TOPSIS calculation. This ensures a fair and adaptive allocation strategy, taking into account the historical performance and needs of the nodes. By integrating the TOPSIS algorithm into our GTS allocation framework, we aim to optimize the prioritization process, considering dynamic data slot requirements and varying channel conditions. This adaptive approach enhances the efficiency and responsiveness of our PAN coordinator in managing GTS requests, ultimately contributing to the overall robustness of our wireless communication system. The TOPSIS algorithm is applied to guaranteed time slot (GTS) allocation, where the goal is to rank alternatives (nodes) based on their performance across multiple criteria, as shown in Algorithm 2. In the first step, each criterion value for each alternative is normalized to bring them to a comparable scale. This is achieved by dividing each criterion value by the square root of the sum of the squared values for that criterion across all alternatives. Next, the normalized values are then multiplied by their respective weights and summed to obtain a weighted normalized value for each alternative. This step incorporates the importance of each criterion in the decision-making process. Further, for each criterion, the maximum (ideal solution) and minimum (negative-ideal solution) values across all alternatives are determined. These values represent the best and worst possible performances for each criterion. Then, Euclidean distances are calculated for each alternative based on the differences between the weighted normalized values and the ideal and negative-ideal solutions. This step quantifies how close or far each alternative is from the ideal and negative-ideal solutions for each criterion.