## 4 Proposed Adaptive Scheduling Technique  
We propose a novel adaptive and autonomous scheduling technique for the network with non-periodic traffic patterns. Like ALICE, the proposed scheme utilizes node addresses to generate the schedule autonomously. The novelty of the proposed scheme lies in its dynamic allocation of Tx cells based on key network metrics such as queue backlog, link PDR, and hop count. Furthermore, the algorithm employs slotframe segmentation to ensure successive segment allocation for each link along the end-to-end communication path, thereby enhancing transmission efficiency and reliability. Moreover, by estimating the total number of transmissions required for nodes at a given hop distance, the scheme dynamically adjusts the slotframe segment size in accordance with the number of nodes and their respective hop distances. A data collection mesh network containing 60 nodes is considered for analysis, representing a typical scenario in IIoT applications. For simplicity, Figure 3 shows a partial network structure of 14 nodes. RPL converts the mesh topology into a tree structure, where the root node acts as the sink for data packets transmitted by its descendant nodes. In such a configuration, nodes situated closer to the root experience significantly higher traffic loads, as they are responsible for forwarding packets generated by their respective subtrees. The end-to-end latency in packet transmission is mainly affected by the number of slotframes required to forward a packet to its destination. The proposed technique utilizes the node's hop count to schedule cells within the slotframe, allocating a dedicated segment for all links at a specific hop distance in the RPL tree. This slotframe segmentation approach significantly reduces end-to-end latency by ensuring packet delivery within a single slotframe. Additionally, by minimizing contention probability, the technique enhances both the PDR and overall transmission reliability. Given a maximum hop distance, \(H\), in the network, the slotframe is partitioned into \(H\) segments of variable lengths, as illustrated in Figure 4. Cells for each link between nodes at a specific hop distance are allocated within the designated segment of the slotframe. The number of cells scheduled for a particular link is determined by the packet count in the sender's queue. Let \(child(k)\) denote the set of child nodes of node \(k\), and \(P_{rec}(i)\) represent the number of packets received from a child node \(i\). If the number of packets generated at sender node \(k\) is denoted as \(P_{gen}(k)\), then the total number of packets \(P_{k}\) at node \(k\) is given by  
\[P_{k}=P_{gen}(k)+\sum\
olimits_{\forall i\in child(k)}P_{rec}(i) \tag{2}\]  
Under ideal conditions with 100% link-layer PDR, a single transmission is sufficient for successful delivery. However, when the PDR is lower, retransmissions are required. If \(A_{kl}\) denotes the average number of transmissions required per packet over the link (\(k\to l\)), which is the reciprocal of the average link-layer PDR, represented by \(PDR_{kl}\). Accordingly, the total number of transmissions \(D_{Tk}\) over the link can be expressed as  
\[D_{Tk}=A_{kl}\cdot P_{k} \tag{3}\]  
Each node is assigned a specific segment for cell allocation. The total number of available cells within any segment is constrained by the segment length and the number of channel offsets. Although a segment in a longer slotframe offers more available cells, it can adversely impact end-to-end transmission latency. The pending packet count in the sender's queue determines the number of cells scheduled for a given link. However, in dense networks with high traffic, overprovisioning cells equal to the queue size may lead to cell collisions and increased energy consumption. Hence, to ensure the minimum collision and packet drop with optimal slotframe length, the number of Tx cells \(B_{Tkl}\) allocated to node \(k\) is computed as the floor of the logarithm of the transmission traffic \(D_{Tk}\).