# Efficient Node Deployment of Large-Scale Heterogeneous Wireless Sensor Networks
###### Abstract  
Wireless Sensor Networks (WSNs) became essential in developing many applications, including smart cities and Internet of Things (IoT) applications. WSN has been used in many critical applications such as healthcare, military, and transportation. Such applications depend mainly on the performance of the deployed sensor nodes. Therefore, the deployment process has to be perfectly arranged. However, the deployment process for a WSN is challenging due to many of the constraints to be taken into consideration. For instance, mobile nodes are already utilized in many applications, and their localization needs to be considered during the deployment process. Besides, heterogeneous nodes are employed in many recent applications due to their efficiency and cost-effectiveness. Moreover, the development areas might have different properties due to their importance. Those parameters increase the deployment complexity and make it hard to reach the best deployment scheme. This work, therefore, seeks to discover the best deployment plan for a WSN, considering these limitations throughout the deployment process. First, the deployment problem is defined as an optimization problem and mathematically formulated using Integer Linear Programming (ILP) to understand the problem better. The main objective function is to maximize the coverage of a given field with a network lifetime constraint. Nodes' mobility and heterogeneity are added to the deployment constraints. The importance of the monitored field subareas is also introduced in this paper, where some subareas could have more importance than others. The paper utilizes Swarm Intelligence as a heuristic algorithm for the large-scale deployment problem. Simulation experiments show that the proposed algorithm produces efficient deployment schemes with a high coverage rate and minimum energy consumption compared to some recent algorithms. The proposed algorithm shows more than a 30% improvement in coverage and network lifetime. wireless sensor networks; deployment optimization; swarm intelligence; coverage; lifetime +
Footnote †: journal: Applied Sciences  
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Footnote 0: _Applied Sciences_  
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Footnote 0: _Applied Sciences_  
obtained data is then transmitted through the network to one or more sink nodes for processing, as shown in Figure 1. Figure 1 is the traditional view of WSN; however, in this paper, the traditional concept of WSNs is extended to cover mobile nodes such as robotics and Unmanned Aerial Vehicles (UAVs), as shown in Figure 2.  
To process the sensed data and transmit it to various locations, many nodes must be appropriately deployed. Hence, the minimum number of nodes to be deployed to attain full coverage is enormous [1; 2; 3; 4; 5; 6; 7]. The deployment of nodes is a fundamental but critical aspect that affects the WSN's performance. Certain nodes are placed randomly, while others are distributed deterministically. In general, random node deployment is preferred in harsh environmental or hostile situations. The deployment of nodes should be done by considering some crucial parameters such as connectivity, coverage, and energy consumption. The Field of Interest (FoI) is declared fully covered if every region's pixel is covered by a node or more. Nodes are designed to detect events in their sensing ranges and pass the event data to the sink node(s). Communication range defines the range across which nodes communicate with one other. When a network is configured with at least one route to the sink node from each deployed node, it is said to be connected. The WSN is supposed to have coverage with full connectivity for better performance [1]. Power limitation is considered as the one of the critical challenges of WSNs. Since WSNs are often deployed in remote areas such as deserts, forests, or military zones, their nodes are usually powered by AA batteries with a limited lifetime. Recharging such batteries may not be feasible. Some of these nodes could be stationary, while others could be mobile.