Hamilton Circuit-Based Algorithm for Improving Coverage of Hybrid Sensor Network

Selection and navigation of mobile sensor nodes using a sensor network

Unknown target search, in an unknown environment, is a complex problem in Wireless Sensor Network (WSN). It does not have a linear solution when target’s location and searching space is unknown. For the past few years, many researchers have invented novel techniques for finding a target using either Static Sensor Node (SSN) or Mobile Sensor Node (MSN) in WSN i.e. Hybrid WSN. But there is a lack of research to find a solution using hybrid WSN. In the current research, the problem has been addressed mostly using non-biological techniques. Due to its complexity and having a non-linear solution, Bio-inspired techniques are most suited to solve the problem. This paper proposes a solution for searching of randomly moving target in unknown area using only Mobile sensor nodes and combination of both Static and Mobile sensor nodes. In proposed technique coverage area is determined and compared. To perform the work, novel algorithms like MSNs Movement Prediction Algorithm (MMPA), Leader Selection Algorithm (LSA), Leader’s Movement Prediction Algorithm (LMPA) and follower algorithm are implemented. Simulation results validate the effectiveness of proposed work. Through the result, it is shown that proposed hybrid WSN approach with less number of sensor nodes (combination of Static and Mobile sensor nodes) finds target faster than only MSN approach.

Hybrid sensor networks consisting of both static and mobile sensor nodes attract more research interests with their enhanced capability. As mobile nodes generally have more power than static nodes, they are preferable to be used as cluster heads. In this paper, we study the mobile node deployment problem with the objective of maximizing the number of static nodes covered by the mobile nodes with minimized moving distance. We prove that this problem is NP-complete and propose a distributed deployment protocol to solve it. In the proposed protocol, different policies of selecting the moving nodes are considered to cover more static nodes with less moving distance. Simulation results show that the proposed protocol achieves high coverage ratio with acceptable moving distance.

In hybrid wireless sensor networks composed of both static and mobile sensor nodes, the random deployment of stationary nodes may cause coverage holes in the sensing field. Hence, mobile sensor nodes are added after the initial deployment to overcome the coverage holes problem. To achieve optimal coverage, an efficient algorithm should be employed to find the best positions of the additional mobile nodes. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the coverage holes problem. The proposed algorithm determines the minimum number and the best locations of the mobile nodes that need to be added after the initial deployment of the stationary nodes. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of the overall coverage ratio and the number of additional mobile nodes.

A testbed for coverage control using mixed wireless sensor networks

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and fisheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

A grid-based coverage approach for target tracking in hybrid sensor networks

Success of Wireless Sensor Networks largely depends whether the deployed network can provide desired coverage with acceptable network lifetime. This paper proposes a distributed protocol for ensuring area coverage using a combination of mobile and static sensor nodes. Most of the assumptions made in our approach are realistic (sensing model, movement thresholds based on real radio characteristics etc.) and implementable in real-life applications. We demonstrate that, for different type of initial deployments, our proposed movement algorithms consume only 30-40% of the energy consumed by the basic virtual force algorithm. We formulated our problem as Integer Linear Program to arrive at idealistic optimal solutions that form basis of our performance comparison. We validated our results through extensive discrete event simulations.

In large scale Wireless Sensor Networks (WSNs), the random deployment of the sensor nodes does not guarantee the desired level of the area coverage especially when the network is sparse. One of the solutions to overcome this problem is to use a mobile robot that is equipped with, in addition to the sensing unit, an actuator unit that controls its movement. In this case, the mobile robot is considered as a mobile sensor node that has the capability to monitor the uncovered regions in the sensor field. However, the main challenge in this case is how to control the movement of the mobile robot such that the area coverage is maximized and the time required to sample the uncovered regions is minimized. In this paper, we propose a fuzzy logic-based approach that controls the mobile robot movement in the sensor field in order to maximize the area coverage. The inputs of the fuzzy system determine the next point that the mobile node will select when it moves in the sensor field. Simulation results have shown that the proposed approach outperforms the random and standard moving patterns.

Wireless Sensor Networks (WSNs) is composed of sinks and sensor nodes, which can monitor large-scale environment. The sensor nodes have several advantages, such as low cost, small size, and capability of mobility, and they can do data sensing, data processing and wireless communication. However, the greatest challenge is the constraints of energy. The most critical issue is how to minimize the energy consumption and keep tracking the mobile target in WSNs. In this paper, we propose a tracking approach for tracking mobile target in hybrid wireless sensor network which consisting of static and mobile node. While static nodes are random distributed in the Field of Interested (FoI) and mobile nodes are moved to fill the coverage hole. We predict the area where the target may cross and construction the local barrier coverage to detect the target. In order to reduce the energy consumption, we wakeup the portion of constructed local barrier coverage to tracking the target. The simulation shows the proposed scheme can reduce the energy consumption and missing rate.

The quality of service (QoS) and lifetime of wireless sensor networks (WSNs) are severely degraded by coverage holes generated by random deployment or battery exhaustion of sensors. This work firstly introduces a novel confident information coverage CIC) model to dramatically reduce the density of sensor nodes and accurately detect confident information coverage holes (CICHs). Then, the problem of repairing confident information coverage holes (RCICHs) for big data collection in a large-scale heterogeneous WSN (LS-HWSN) which widely spreads over a geographic area with thousands of stationary sensor nodes and mobile sensor nodes is formulated, called as RCICH problem, which is to effectively repair CICHs considering that the transmitted data velocity of sensor nodes is different. Furthermore, we prove it to be NP-completeness. The target of the problem is to find a subset of mobile sensor nodes from all mobile sensor nodes while minimizing the amount of lost throughputs LTs) of all dispatched mobile sensor nodes or maximizing the amount of repairing transmission times (RTTs) for all dispatched mobile sensor nodes, with different objectives. Finally, based on the CIC model and the data-centric perspective, two heuristic schemes including a centralized dispatch scheme and a distributed dispatch scheme are proposed to effectively solve the RCICH problem. Simulation results show that the proposed schemes effectively repair CICHs while increasing the QoS and lifetime of the LS-HWSN with the topology control of a fan-shaped clustering (FSC) protocol.

Mobile sensor nodes are featured with node mobility along with standard sensor functions. They can move around after being deployed. In many situations placement of static sensor nodes might not be possible and human intervention is not feasible. Mobile sensor nodes are very useful in such hazardous and disastrous situations. When a group of mobile sensor nodes are deployed to cover an area for search operations, coordination among the deployed nodes is very important. A mobile sensor node (MSN) depletes more energy during the traversal. Whenever there arises a failure, in one of the deployed mobile sensor nodes, the remaining fault-free mobile sensor nodes should travel to cover the remaining uncovered area. In this work we propose a Mobile Traversal Algorithm (MTA), for mobile sensor nodes to cover a rectangular region of interest (ROI). It makes MSNs to travel shorter distances to extend effective operational duration of the network and also to provide fault tolerance mechanism.

With the advancements in information, communication, and sensing technologies, structural health monitoring (SHM) has matured into a substantial pillar of infrastructure maintenance. In particular, wireless sensor networks have gradually been incorporated into SHM, leveraging new opportunities towards reduced installation efforts and enhanced flexibility and scalability, as compared to cable-based SHM systems. However, wireless sensor nodes are installed at fixed locations and need to be employed at high density to reliably monitor large infrastructure, which may cause high installation costs. Furthermore, the limited power autonomy of wireless sensor networks, installed at fixed locations for unattended long-term operation, still represents a significant constraint when deploying stationary wireless sensor nodes for SHM. To resolve the critical constraints stemming from costly high-density deployment and limited power autonomy, a mobile structural health monitoring concept based on legged robots is proposed in the study reported in this paper. The study explores the accuracy and cost-efficiency of deploying legged robots in dense measurement setups for wireless SHM of civil infrastructure, aiming to gain insights into the advantages of mobile wireless sensor nodes in general and of legged robots in particular, in terms of obtaining rich information on the structural condition. As is shown in this paper, the legged robots, as compared to stationary wireless sensor nodes, require a smaller number of nodes to be deployed in civil infrastructure to achieve rich sensor information, entailing more cost-efficient, yet accurate, SHM. In conclusion, this study represents a first step towards autonomous robotic fleets advancing structural health monitoring.

Cooperative localization for disconnected sensor networks and a mobile robot in friendly environments

When detecting a target or monitoring a physical phenomenon in a region, the deployment problem is fundamental in these applications. Traditionally, stationary sensor networks are deployed to carry out the sensing operations. It is well known that the mobility of sensor nodes can improve the coverage and the probability of the detecting, so we deal with the problem of detecting a target using hybrid sensor networks which contain both stationary sensors and mobile sensors. In this paper, to begin with, we prove that the node deployment problem is NP-complete. Then, one polynomial algorithm for node deployment in hybrid wireless sensor networks is proposed, which aims at minimizing the number of all sensors to reduce the cost. The simulations verify the efficiency of our algorithm.