# Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
## 2 Related Work
Table 2 provides an overall comparison of the two algorithms mentioned earlier [27; 28] and the proposed one. Motivated by the above discussion, the following points are advanced in this paper:  
1. We present a unique data collecting path planning technique that considers environmental effect parameters to reduce mobile sink environmental impact. It achieves this by calculating each node's environmental effect. Then, it avoids cluster heads in dangerous zones by choosing cluster heads with a higher final environmental impact measure to participate in path planning. Moreover, the zone priority is considered to avoid the excessive routing of urgent data, which would negatively influence the  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**Path Planning**} & \multicolumn{6}{c}{**Cluster Head Selection**} \\ \cline{2-10}  & & & & **Parameters** & & & & & **Parameters** \\ \hline
**Paper ID** & **\(\surd\)** & \(\surd\)** & \(\surd\)** & \(\times\) & \(\times\) & \(\times\) & \(\surd\) & \(\times\) &  
latency and/or throughput of a high-priority data flow. A new zone priority metric function is proposed to integrate the zone priority into the path planning process. The movement cost is thought to reduce the amount of wasted energy during movement, which will make the mobile sink last longer. The movement delay is also considered for real-time urgent data transmission and decreases the chance of buffer overflow of sensor nodes owing to its restricted buffer capacity;
2. Secondly, we propose an energy-efficient clustering technique considering the average intra-cluster distance, residual energy, and reliability of intra-cluster data transmission. In the cluster hierarchy, aggregating the data by each cluster head from its members causes imbalanced energy loss. A novel energy weight function is presented to pick the most energy-efficient node as a cluster head and avoid selecting low-residual-energy nodes. To achieve reliable intra-cluster data transmission, a new link quality metric function is suggested to express the quality of links between each candidate cluster head and its member nodes. We assess the average intra-cluster distance to improve end-to-end latency, as with many previous clustering approaches;
3. Third, we offer a real-time, reliable, energy-efficient, and environment-aware routing approach. The suggested routing strategy minimizes the external environment's impact on data transmission. Link quality is also considered to prevent data forwarding over unstable paths; a novel function that combines sensor node residual energy and traffic load balances energy usage is proposed. It provides real-time WSN transmission. Only qualified neighbors who can deliver urgent data on time participate in the routing procedure. Moreover, it calculates the relaying delay for each eligible candidate neighbor to reduce route latency. The suggested routing approach uses more realistic parameters than prior systems;
4. Lastly, these problems involve 0/1 integer linear programming. Then, swarm intelligence is proposed for optimization problems.