## 6 Performance Evaluation
At a slotframe size of 31, the end-to-end latency achieved by AAS is 32% lower than A\({}^{3}\), 63% lower than ALICE, and 75% lower than Orchestra. For a slotframe with 101 timeslots, AAS exhibits 53% lower latency than A\({}^{3}\) and 67% lower than ALICE. Overall, AAS consistently achieves the lowest end-to-end latency among the compared techniques. Contention probability is evaluated across varying slotframe sizes and packet intervals. The traffic load on each timeslot was estimated based on the traffic generated by the node and the slot duration, as described in \((11)\). In larger slotframes with sparser cell distributions, high network traffic leads to increased contention due to the limited availability of cells per unit time. Figure 6 presents the contention probability for different scheduling techniques across multiple slotframe sizes, with a packet interval of 1 s. It is observed to be lower in AAS compared to other schedulers due to its adaptive cell allocation strategy, which enables more efficient resource utilization. At a slotframe size of 101, the contention probability in AAS is 30% lower than A\({}^{3}\), 58% lower than ALICE, and 71% lower than Orchestra. In A\({}^{3}\), contention is comparatively more due to the dispersion of primary and secondary cells across the slotframe. In Orchestra and ALICE, contention remains high as they schedule a single Tx cell in a slotframe for every node. Figure 7 shows the reduction in contention in AAS with increasing packet intervals. At a slotframe length of 31 timeslots, the contention is 72% lower when the packet interval is 5 s compared to an interval of 0.5 s.  
The average end-to-end PDR of the network is the ratio of the total number of packets received by the sink to the total number of packets transmitted by the sender. PDR in a network is affected with the increasing slotframe size, as a lesser number of cells are available for transmission. The results in Figure 8 show the end-to-end PDR of AAS for a slotframe size of 59 timeslots, and packet intervals are varied from 2 s to 15 s. The PDR of the AAS is 27% higher than A\({}^{3}\) when the packet interval is set to 2 s; however, it is 14% higher than Orchestra and 11% higher than ALICE when an interval is set to 10 s. PDR in Orchestra and ALICE is reduced due to the limited transmission opportunities within a  
Figure 6: Contention probability versus slotframe length. slotframe. In the case of A\({}^{3}\), transmission opportunity is increased by using multiple zones; however, for higher traffic conditions, PDR is dropped below AAS due to higher congestion probability. AAS assigns the cells within a specified segment as per traffic requirement and links PDR, resulting in a lower congestion problem. The life of the network is decided by the node with the highest energy consumption. Nodes consume energy during active slots, used for data transmission, reception, and acknowledgment. The entire network may go down if any node, specifically closer to the root, runs out of energy. Nodes in Orchestra consume energy in idle listening at most of the time, as every node has a single Tx cell and Rx cells per neighbor. However, in A\({}^{3}\), the allocated cells are doubled when its utilization is above a threshold value, which leads to more energy consumption. The proposed AAS algorithm improves energy efficiency by adapting to traffic conditions, hop count, and link reliability. It avoids over-provisioning by allocating a logarithmic number of cells based on the estimated queue backlog, which significantly reduces idle listening and channel contention. Similarly, the slotframe segmentation based on hop distance ensures that nodes closer to the root, typically experiencing higher traffic accumulation, are allocated more communication resources, while other nodes save energy by operating with fewer active slots. Moreover, by incorporating link quality into the slot allocation strategy, AAS minimizes retransmissions due to poor links, further reducing unnecessary energy consumption.