# Distributed Reliable and Efficient Transmission Task Assignment for WSNs
## 5 Reliable and Efficient Task Allocation Algorithm for WSNs
### Distributed Task Assignment
#### 5.2.2 Distributed Reliable and Efficient Task Allocation in Planar Topology
Since the TRETA-Multi-Sink can be distributed to multiple sinks for local processing according to the task area, its success rate in the task assignment is better than TRETA and TRETA-Cluster. The higher the task arrival rate, the more prominent the advantage. (D) Energy Consumption and Delay of Task Assignments in the Dynamic Update of the Network

Figure 9 shows the energy consumption of the three proposed strategies for different network update ratios. It is noted that as the network update ratio increases, the energy consumption is significantly increased. Since the network update in TRETA is brought to the only sink through the long-distance multi-hop, the communication load of the network is increased. Moreover, the energy consumption of TRETA is higher than the other two strategies in most cases. With the network update ratio greater than 25%, the energy consumption of TRETA-Multi-Sink increases rapidly, surpassing TRETA and TRETA-Cluster, becoming the highest among the three strategies due to the exchange of global views between multiple sinks and the operation of ensuring global view consistency under a high network update rate. Figure 10 shows the delays of the three proposed strategies for different network update ratios. As the network update ratio increases, the delays in the three strategies increase. Under the current network simulation environment, analysis shows that the delays of TRETA-Cluster and TRETA-Multi-Sink are smaller than TRETA when the network update ratio is lower than 25%, which is due to the fact that TRETA-Cluster and TRETA-Multi-Sink have a small number of updates in the network, they are processed locally without affecting the reliability of the task target, and a complete network update is not required. Nevertheless, when the network update ratio exceeds 25%, the delay of TRETA-Multi-Sink increases rapidly and becomes higher than TRETA, which is caused by the operation of ensuring global view consistency at such a high update rate. Figure 8: The success rate of task assignment under different task arrival rates. Figure 9: Energy consumption of task assignment under different network update rates. (E) Energy Resilience of the Transmission for Task Assignments

In order to evaluate the energy resilience of the transmission in WSNs, we quoted an index \(\eta\) in [34]. Since TRETA-Cluster is a distributed modification of TRETA for clustering topologies, we compared TRETA-Cluster and LEACH (Low Energy Adaptive Clustering Hierarchy) with index \(\eta\). Simulation experiments were carried out under clustering topology. Let the number of initial active nodes be 500. For the same transmission task, we sample and count the number of packets received by sink nodes and the number of dead nodes at different time points. Then, we use Equation (22) to calculate the index \(\eta\). Figure 11 shows the variation of the index \(\eta\) of the two algorithms over time. It can be seen from Figure 11 that the index \(\eta\) of both methods increases with time. Compared with LEACH, the growth rate of index \(\eta\) of TRETA-Cluster is more prominent, since TRETA-Cluster adds more redundancy packets than LEACH to meet the target reliability. ## 7 Concluding Remarks and Future Work

To solve the problems of poor scalability and reliability, significant communication overheads and delays in centralized task assignment for WSNs, we propose two distributed reliable and efficient transmission task allocations for WSNs, namely TRETA-Cluster and TRETA-Multi-Sink. The performance of these strategies is analyzed and evaluated, then compared with the centralized task assignment TRETA. In TRETA-Cluster, the cluster head can perform local task assignment according to the stage target reliability constraint that reduces the communication cost and delay compared with TRETA.