## 2 Related Work
### Sensing Scheduling Strategies
Lightweight deployment-aware scheduling (LDAS) [15], probing environment and adaptive sensing (PEAS) [16], probing environment and collaborating adaptive sleeping (PECAS) [17], and so forth, make relatively loose assumptions. LDAS assumes that the sensor nodes do not own a positioning device, such as GPS, thus forces the sensors achieving the desired coverage by static sensing. PEAS consists of two mechanisms: sensing and adaptive sleep scheduling, and requires high sensor density. PECAS is an updated version of the PEAS. It posts its remaining/available hours in response to neighbors to avoid misperceptions. This leads to an increase in communication energy depletion. Balanced-energy scheduling (BS) [20] is a balanced-energy scheduling model designed for dense sensor networks. It distributes the sensing and communication tasks to all sensor nodes in the cluster. The assumptions made by the reviewed studies are listed in Table 1.  
Applications differ in their necessities. Hence, the served sensor networks have diverse design objectives and priorities. We summarize these design objectives as follows:  
* Maximizing Network Lifetime. This is a goal that is hard not to consider. * Sensing Coverage. A network is said to achieve \(k\)-coverage if any event occurs within the jurisdiction of at least \(k\) sensors. 1-overage is a minimum requirement for WSN. * Network Connectivity. The developers applaud a model that offers a particular network connectivity needed by the application, but this requires a very high sensor density. * Balanced Energy Usage. In the case of a sensing coverage breach, when a node runs out of power before others, some studies endeavor to spread the energy utilization evenly among each node. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Strategies**} & \multirow{2}{*}{**Network**} & \multirow{2}{*}{**Sensor**} & \multirow{2}{*}{**High**} & \multirow{2}{*}{**Sensing**} & \multicolumn{3}{c}{**Assumptions**} & \multirow{2}{*}{**Frequent**} & \multirow{2}{*}{**Mobility**} & \multirow{2}{*}{**Known**} & \multirow{2}{*}{**Known**} \\  & & & & & & & & & & Location \\ \hline \multirow{2}{*}{RIS [18]} & \multirow{2}{*}{Flat} & Uniform, & & & & & & & \\  & & Poisson & & & & & & & \\ BS [20] & Hierarchical & Poisson & N & 2-D & Y & N & N & N & Y \\ LDAS [15] & Flat & Uniform & N & 2-D & N & N & N & N & N \\ PEAS [16] & Flat & Uniform & Y & Any & N & Y & N & N & N \\ PECAS [17] & Flat & Uniform & N & Any & N & Y & N & N & N \\ CCP [21] & Flat & Any & N & 2-D & N & N & N & Y & N \\ ASCENT [18] & Flat & Any & Y & Any & N & N & N & N & N \\ CSS [22] & Flat & Any & Y & 2-D & Y & N & N & Y & N \\ LEACH-GA [23] & Hierarchical & Any & N & Any & Y & N & N & N & N \\ IBLEACH [24] & Hierarchical & Any & N & Any & Y & N & N & N & N \\ ESS [25] & Hierarchical & Any & N & Any & Y & N & N & N & N \\ DSS [26] & Hierarchical & Poisson & N & 2-D & Y & N & N & N & Y \\ IDCA [27] & Flat & Any & N & 2-D & N & N & N & Y & N \\ \hline \hline \end{tabular}  
Y yes; N: no.  
\end{table} 
Table 1: The studies’ classifications according to their assumptions. * Simplicity. Sensors have exceptionally restricted memory space and limited computation power. For this reason, simple schemes are more popular. * Robustness: Robustness measures how well a network can withstand downtime and crashes. Adaptive self-configuring sEnsor networks topologies (ASCENT) [18], PEAS, PECAS, Low-energy adaptive clustering hierarchy (LEACH-GA) [23], IBLEACH [24], energy-efficient surveillance system (ESS) [25] and BS [20] do not take complete coverage of the region as their primary goal. Cooperative spectrum sensing (CSS) [22], however, is the opposite. The coverage configuration protocol (CCP) [21] introduced the concept of interconnected sensor coverage. It devised an approximation algorithm to construct a topology with near-optimal sensor coverage. The central controller periodically selects sensors along a trajectory until the target area is fully covered.