Regardless of the classic barrier coverage used in WBC, the formation process
[4] is crucial because newly deployed sensor nodes lack a dependable infrastructure for communication and detection. The formation process in WBC is defined to form sensor nodes into
k barriers enclosing the region, thus detecting or warning unexpected visitors.
Researchers have put forward various solutions in the literature for classic barrier coverage formation for smart cities. For instance, Kumar
[1] proposed a centralized algorithm to determine weak
k-barrier coverage in a region using randomly deployed sensor networks. Later, ref.
[5] devised efficient algorithms to construct strong sensor barriers. And ref.
[6] studied the barrier coverage of line-based deployment. In addition, ref.
[7] funded a cluster-based barrier construction algorithm in mobile wireless sensor networks.
Different from the known region in classic barrier coverage, the boundary of a dangerous region in WBC is usually unknown. Hence, the classic formation approaches are not appropriate for WBC in smart cities. In addition, most existing works
[1,6][1][6] fall into the category that forms the barrier coverage by stationary sensor nodes. Nevertheless, if the stationary sensor nodes are stochastically deployed, many redundant nodes will be needed to ensure a strong barrier
[5]. On the other hand, if the stationary nodes are manually deployed, a significant amount of manpower and time are consumed. Especially in some cases for smart cities, the region is rather large in scale or hides dangers. Therefore, using stationary nodes is more of a hindrance than a help in WBC. A few state-of-the-art works also considered using mobile sensor nodes
[8,9,10][8][9][10] to facilitate the barrier coverage.
2. Automatic Barrier Coverage in Smart City
In the construction of smart cities, information and communication technologies are used to improve the living standards and management of citizens and governments
[13,14][11][12]. The Internet of Things (IoT) using sensors is widely used in smart cities
[15][13]. In particular, the coverage-related problem
[16,17][14][15] is a fundamental topic in WSNs to measure the monitoring quality of a sensor network deployed in a given region. Barrier coverage guarantees the detection of any intruder attempting to cross the barrier of sensor networks or penetrating the protected region. There are numerous studies on classical intrusion detection and avoidance
[18,19,20][16][17][18]. Ref.
[21][19] presents methods for intrusion detection and tracking with pan–tilt cameras. And ref.
[22][20] proposes a probabilistic sensor tasking algorithm in which cameras sense the environment independently of one another, thus reducing the communication overhead. In addition, diverse directions are excellently studied for coverage problems, such as barrier coverage
[1], sweep coverage
[23][21], surface coverage
[24][22], and trap coverage
[25][23].
In these directions, barrier coverage is one valuable and practical application for smart cities, which is advocated in
[1] for the purpose of intrusion detection in country borders, critical infrastructure protection, and battlefield perimeter surveillance. The barrier coverage formed by stationary nodes has been widely studied. For instance, the minimum cost for achieving
k-barrier coverage is calculated in
[26][24]. In
[5], strong sensor barriers were devised. Line-based and curve-based barrier coverage were studied by
[6[6][25],
27], respectively. Multi-round sensor deployment for guaranteed barrier coverage is proposed in
[28][26]. Nevertheless, a significant amount of resources such as redundant nodes in stochastic deployment and manpower cost in manual deployment will be needed due to the reliance on stationary nodes only.
Mobile nodes for barrier coverage was firstly introduced in
[4], in which the nodes with limited mobility (e.g., one-step move with one chance) are utilized to improve the quality of barrier coverage. With the rapid development of autonomous robot technology, sensor nodes with strong mobility
[29][27] become practical. In addition, a movement barrier formation algorithm MobiBar designed in
[11][28] presented distributed algorithms for barrier coverage using sensor relocation. Ref.
[30][29] proposed a heuristic target-barrier construction algorithm to solve the target-barrier coverage problem while satisfying the boundary constraint conditions. These works mainly focus on centralized analysis, which is not suitable for large-scale barrier coverage for smart cities.
Distributed algorithms for mobile barrier coverage were also investigated in the literature. The chain reaction algorithm
[31][30] was firstly developed for mobile barrier formation. But it totally ignores the situation of node failure, which may lead to certain loopholes in the barrier. Based on mobility and intruder prior information, PMS
[32][31] is able to improve the quality of barrier coverage. However, PMS assumes that the region knowledge is pre-known, which is not practical in most real WBC applications for smart cities. Moreover, ref.
[33][32] presented a distributed cellular automaton based algorithm for the autonomous deployment of mobile sensors. The limitation is that the number of sensors needs to be deployed in a fixed manner.