Mobile Wireless Sensor Networks Research Articles

An Assessment of Data Transmission Reliability in Mobile Wireless Sensor Networks

An Assessment of Data Transmission Reliability in Mobile Wireless Sensor Networks

A novel adaptive deployment method for the single-target tracking of mobile wireless sensor networks

Single-target tracking is an important application of mobile wireless sensor networks. It is imperative to adaptively adjust the network deployment to achieve a satisfactory comprehensive tracking performance incorporating reliability, energy efficiency, connectivity, and tracking accuracy, which are all significant aspects for target tracking. However, the existing methods cannot ensure the optimization of the comprehensive tracking performance. Moreover, they are inapplicable to the realistic scenario with the common uncertainties, including the randomness of sensing, the randomness of received signal power, and the correlation between received signal powers. To solve these problems, a network model is proposed by modeling the common uncertainties to properly capture the characteristics of sensing and wireless communication. The reliability-energy index is defined to assess the comprehensive tracking performance. Furthermore, an adaptive deployment method is proposed to dynamically optimize the comprehensive tracking performance. Especially, to determine the optimal deployment at a sensing instant, an optimization algorithm is proposed by analyzing the monotonicity of the reliability-energy index and the impact of the positional relationship of nodes. Finally, a scenario of habitat monitoring is considered, and simulations are conducted to compare the proposed method with the existing methods to demonstrate the effectiveness of the proposed method.

Coverage Control of Mobile Wireless Sensor Network with Distributed Location of High Interest

Formation control is an important part of any system that utilizes multiple mobile agent to achieve its particular goals. One of those application is the mobile wireless network sensor. A field which becomes increasingly more popular in recent times due to advancement of technology especially in the fields of miniaturization and telecommunications. The main problem of this research is the relatively untested sensing capability of a mobile wireless sensor network in an operating area which has distributed and/or multiple locations of high interest. The purpose of this research is to discover the compatibility of a multiple-agent coverage control system under several examples of interest functions that has multiple and/or distributed points of global maximum value in order to explore more thoroughly the performance of a given system in a varying environments.

An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network.

The mobile node location method can find unknown nodes in real time and capture the movement trajectory of unknown nodes in time, which has attracted more and more attention from researchers. Due to their advantages of simplicity and efficiency, intelligent optimization algorithms are receiving increasing attention. Compared with other algorithms, the black hole algorithm has fewer parameters and a simple structure, which is more suitable for node location in wireless sensor networks. To address the problems of weak merit-seeking ability and slow convergence of the black hole algorithm, this paper proposed an opposition-based learning black hole (OBH) algorithm and utilized it to improve the accuracy of the mobile wireless sensor network (MWSN) localization. To verify the performance of the proposed algorithm, this paper tests it on the CEC2013 test function set. The results indicate that among the several algorithms tested, the OBH algorithm performed the best. In this paper, several optimization algorithms are applied to the Monte Carlo localization algorithm, and the experimental results show that the OBH algorithm can achieve the best optimization effect in advance.

Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks

Hybridized Dragonfly and Jaya algorithm for optimal sensor node location identification in mobile wireless sensor networks

A Recursive Robust Set-Membership Estimator for WSN-Assisted Moving Targets Tracking With UBB Anchor Location Uncertainty

In this paper, a recursive robust set-membership fusion estimator (RSMFE) is presented to track the moving targets treated as the mobile nodes in a mobile wireless sensor network (MWSN) system with unknown but bounded (UBB) anchor location uncertainty. Firstly, the accurate ellipsoidal set containing the Lagrange remainder of nonlinear distance measurement, which contains the effect of anchor location uncertainty, is estimated and adopted to improve the stability and accuracy of the moving target tracking. Secondly, the recursive RSMFE-based tracking formulae of reduced computation complexity, consisting of the prediction formulae and the fusion update formulae, are derived to estimate the robust minimized or optimal ellipsoidal set containing the actual moving target state by appropriately fusing the measured distances from the nearby anchors subject to the UBB anchor location uncertainty, where the computation complexity of the fusion update formulae is reduced substantially based on the decoupled techniques and the equivalent transformation. Finally, the numerical simulation and experiment of the WSN-assisted moving target tracking system with various anchor location uncertainty settings are performed to verify the effectiveness and superiority of the proposed recursive RSMFE-based moving target tracking or localization method.

Review on energy conservation and congestion mechanism in mobile WSN: taxonomy, software programs, challenges, and future trends

Review on energy conservation and congestion mechanism in mobile WSN: taxonomy, software programs, challenges, and future trends

MMSCM: A multiple mobile sinks coverage maximization based hierarchical routing protocol for mobile wireless sensor networks

AbstractMobile wireless sensor network (MWSN) adapts to the requirements of mobility of civil and military network devices and has received a lot of attention. Designing an efficient, low‐energy, and fault‐tolerant routing protocol for the frequently changing topology of highly mobile MWSNs is challenging. Most routing protocols today only support the movement of sensor nodes or only sink. This paper proposes a Multiple Mobile Sinks Coverage Maximization based hierarchical routing protocol for mobile wireless sensor networks (MMSCM), which allows sensor nodes and sinks to move simultaneously. The MMSCM divides the monitoring area into virtual grids and deploys a movable sink in each grid cell. Sink selects the appropriate next hop for each cluster head in the area to build an optimal routing forest and collects data from all routing tree root nodes at a uniform speed along the specified path with maximum coverage. Simulation results show that, compared with current advanced routing algorithms, the MMSCM protocol can better solve the network delay problem and improve data throughput while extending the network life cycle, which is more suitable for time‐sensitive application scenarios.

NMSFRA: Heterogeneous routing protocol for balanced energy consumption in mobile wireless sensor network

Wireless sensor networks are widely used in various fields and consist of a large number of sensor nodes that are powered by batteries. As a result, energy efficiency is crucial for the effective operation of these networks. With the advancement of cross technology communication (CTC), the presence of heterogeneous wireless nodes, especially mobile nodes, in wireless sensor networks has increased, making traditional routing protocols for homogeneous wireless sensor networks inapplicable. To overcome the above issues, this paper proposes a heterogeneous wireless sensor network routing protocol for a balanced energy consumption, NMSFRA (NGO based mean shift fuzzy clustering routing algorithm). In order to mitigate the impact of uneven cluster distribution and unstable network links due to the mobility of nodes, the proposed protocol first divides the network into balanced clusters using the Mean Shift (MS) method. The Mamdani fuzzy inference system is then used to take node mobility into account. The protocol dynamically selects different parameters as inputs to the fuzzy logic, enabling it to choose cluster heads (CHs) based on the overall location of the clusters. Additionally, to extend the network lifetime, the protocol generates multi-hop forwarding paths using the Northern Goshawk Optimization (NGO) method. Finally, the paper presents experimental simulations carried out on three different network topologies and compares the results with existing protocols such as LEACH, EETPF, E-FUCA, and DE-SEP. The results show that the NMSFRA protocol extends the survival period of nodes by 235 rounds, 240 rounds, 364 rounds, and 190 rounds, on average, compared to the LEACH, EETPF, E-FUCA, and DE-SEP protocols, respectively. The network throughput also increased by 154.92%, 48.74%, 84.77%, and 106.77%, respectively. The NMSFRA protocol also showed better performance in terms of total residual energy, FND, HND, and average speed difference between nodes in the first 5 rounds. Therefore, the proposed NMSFRA protocol demonstrates superior performance in terms of network lifetime, energy utilization, throughput, and network stability.

Environmentally Adaptive Event-Driven Robust Cubature Kalman Filter for RSS-Based Targets Tracking in Mobile Wireless Sensor Network

This article presents an environmentally adaptive event-driven robust square root cubature Kalman filter (EAERCKF) for received-signal-strength-based (RSS-based) moving targets tracking in resource-constrained mobile wireless sensor network (MWSN) under the motion modeling and RSS quantization uncertainties. First, an environmentally adaptive event-driven mechanism, scheduling dynamically and approximately the desired amount of anchors regardless of the anchors distribution density near the moving target, is designed to reduce energy consumption, communication rates, and computation complexity of the MWSN system. Second, a robust square root cubature Kalman filter is developed to estimate the motion state of the moving target, where the covariances of the process noise and the measurement noise assumed to be time-varying uniform distributions are generated randomly. Third, the bounds of the uniformly distributed covariances describing the motion modeling and RSS quantization uncertainties are given to improve the stability, accuracy, and consistency of the estimator. Finally, the results of numerical simulations demonstrate that our proposed EAERCKF estimation method has superiority in simplifying the determination of the random noise covariances with satisfactory target tracking performance and approximating the desired number of triggered anchors.

An hybrid cluster-based data centric routing protocol assisted by mobile sink for IoT system

Nowadays, using mobile computing devices and the Internet of Things (IoT) in networks have posed several challenges to match up the forthcoming technological requirements. Wireless Sensors Network (WSN) is considered as an important component of the IoT which produces a massive amount of data (big data). However, dealing with limited capacities of the elementary components of a network in an IoT enabled WSN, is a key challenge. The existing approaches in the literature are inadequate for large networks and cannot be applied to IoT platform without adaptation. Data Centric Network (DCN) is an important notion for the future Internet architecture to resolve the problems related to big data manipulation. In fact, using a DCN strategy for the resource limited capacities WSN enabled IoT networks is beneficial to manage densely deployed and mobile components to enhance the data gathering mechanism. In this context, this paper proposes an IoT cluster based routing protocol for data centric mobile wireless sensors networks named ICMWSN. The proposed algorithm fits with a WSN belonging a large number of mobile sensors as well as a mobile sink. It is based on a clustering technique to form multi-hops clusters around fixed pre-elected CHs. Besides, an effective tour construction method is involved for the mobile sink to collect data from the eventual cluster heads. The extensive simulation results proved that ICMWSN outperformed the compared methods in terms of energy consumption, network lifetime and data delivery rate.

Reliable Data Transmission in Underwater Wireless Sensor Networks Using a Cluster-Based Routing Protocol Endorsed by Member Nodes

Considering Underwater Wireless Sensor Networks (UWSNs) have limited power resources (low bandwidth, long propagation delays, and non-rechargeable batteries), it is critical that they develop solutions to reduce power usage. Clustering is one solution because it not only saves energy consumption but also improves scalability and data integrity. The design of UWSNs is vital to the development of clustering algorithms. The limited energy of sensor nodes, narrow transmission bandwidth, and unpredictable topology of mobile Underwater Acoustic Wireless Sensor Networks (UAWSNs) make it challenging to build an effective and dependable underwater communication network. Despite its success in data dependability, the acoustic underwater communication channel consumes the greatest energy at a node. Recharging and replacing a submerged node’s battery could be prohibitively expensive. We propose a network architecture called Member Nodes Supported Cluster-Based Routing Protocol (MNS-CBRP) to achieve consistent information transfer speeds by using the network’s member nodes. As a result, we use clusters, which are produced by dividing the network’s space into many minute circular sections. Following that, a Cluster Head (CH) node is chosen for each circle. Despite the fact that the source nodes are randomly spread, all of the cluster heads are linked to the circle’s focal point. It is the responsibility of the MNS-CBRP source nodes to communicate the discovered information to the CH. The discovered data will then be sent to the CH that follows it, and so on, until all data packets have been transferred to the surface sinks. We tested our techniques thoroughly using QualNet Simulator to determine their viability.

Novel metaheuristic routing algorithm with optimized energy and enhanced coverage for WSNs

The distribution of sensor nodes is the key factor in mobile wireless sensor networks (WSNs) to enhance the functionality of the network. The effectiveness of a wireless sensor network can be increased by the efficient distribution of several sensor nodes. Previously researchers considered existing algorithms or their hybrid for the effective distribution of sensor nodes. Those only optimize energy or enhance network coverage none of them considered both aspects with the minimum cost of equipment. This piece of work proposes a novel bio-inspired ruminant algorithm. The algorithm is developed as a result of the in- spiration of the efficient digestive system of ruminant animals. That takes a large amount of raw food as input and produces an optimal value of food that is full of energy. The proposed algorithm is validated on several benchmark functions. By keeping inspiration in mind, the proposed algorithm not only applied to enhance network coverage of WSNs with optimized energy and sensor nodes distribution, which increases the lifetime of the equipment. Furthermore, the results of the algorithm show that if network coverage enhances more optimized value of energy is achieved with no increase in the number of deployed sensors. That proves the no increase in the cost of the equipment with more network coverage on enhanced lifetime.

Modelling and Characterization Piezoelectric Transducer for Sound Wave Energy Harvesting

Energy harvesting system is using ambient energy conversion in the environment. The environmental energy will be converted into usable electrical energy that can be used in controlling wireless electronic devices. The available mechanical vibration from the sound energy will then be converted to electrical energy by using a piezoelectric transducer. The size of the piezoelectric represents the surface area of the electrode on the piezoelectric model. A smaller size piezoelectric transducer is unable to produce a good vibration due to the smaller surface area. The bigger dimension of the piezoelectric model would be able to harvest more electrical energy output because the vibration from the bigger piezoelectric model which would able to produce more sound wave energy. The piezoelectric material Lead Zirconate Titanate (PZT-5H) vibration is focused on the resonance frequency at below 1 kHz with sound level decibel is between the range of 35-100 dB. This research is to concentrate on rectangular and trapezium-shaped cantilever. The trapezium shaped cantilever produces higher energy output due to its shape which has better in terms of stress and strain distribution. In addition, researchers have modelled and validated energy harvesters with different proof masses shapes. The improved piezoelectric vibrational energy harvester has a trapezoidal beam and an added triangular proof mass. The arrangement of the piezoelectric tested in parallel, series, combination series and parallel configuration to investigate the performance of the output power generated from the sound wave. The rectangular and trapezium shaped cantilever are resulted in a resonant frequency of 269.4 Hz and 269.88 Hz, respectively. The rectangular and trapezium shaped cantilever produced a maximum output voltage of 3.105 V and 3.635 V respectively. The piezoelectric output during the parallel array configuration, which is 5.636 V, 0.497 mA and 2.803 mW. The output power produced by parallel is 81 % higher than compare in series array configuration and 35.8 % higher than combination of series and parallel. Thus, the produced energy output 5 V would be able to apply at several low power supply applications such as mobile phones, power bank or wireless sensor networks (WSN).

Optimization of the operational state's routing for mobile wireless sensor networks

Optimization of the operational state's routing for mobile wireless sensor networks

An Energy-Efficient T-Based Routing Topology for Target Tracking in Battery Operated Mobile Wireless Sensor Networks.

Real-time smart applications are now possible because to developments in communication and sensor technology. Wireless sensor networks (WSNs) are used to collect data from specific disaster sites, such as fire events, gas leaks, land mines, earthquake, landslides, etc., where it is necessary to know the exact location of the detected information to safely rescue the people. For instance, the detection and disposal of explosive materials is a difficult task because land mines consistently threaten human life. Here, the T-based Routing Topology (TRT) is suggested to gather data from sensors (metal detectors, Ground Penetrating Radars (GPR), Infra-Red sensors, etc.), Global Positioning System (GPS), and cameras in land mine-affected areas. Buried explosive materials can be found and located with high accuracy. Additionally, it will be simpler to eliminate bombs and reduce threats to humans. The efficiency of the suggested data collection method is evaluated using Network Simulator-2 (NS-2). Also, the proposed T-based routing topology requires a minimal number of nodes to cover the entire searching area and establish effective communication. In contrast, the number of nodes participating in the sensing area grows, as the depth of the tree increases in the existing tree topology-based data gathering. And for cluster topology, the number of nodes deployment depends on the transmission range of the sensor nodes.

Optimized UAV-based data collection from MWSNs

In this paper, we formulate an Energy Efficient (EE) deployment for Mobile Wireless Sensor Networks (MWSNs) that consists of multiple clusters of sensor nodes, one mobile sink in each of them, and an Unmanned Aerial Vehicle (UAV) for the whole MWSN. The UAV receives the collected sensed data from the mobile sinks wirelessly in order to deliver them to various IoT-based users’ devices. Experimental results show that the proposed model can achieve optimization in terms of energy consumption minimization and network lifetime enhancement.

Minimal Exposure Paths in Time-Varying Fields: A Semi-Lagrangian Approach

In the context of Wireless Sensor Networks (WSNs), the Minimal Exposure Path (MEP) represents an important metric to evaluate the quality of network services. Most of the current literature is concentrated on stationary sensors, while few works have addressed the existence of moving nodes. Mobile Wireless Sensor Networks (MWSNs) present a great potential for detecting invaders compared to static ones, but dealing with dynamic sensors significantly increases the coverage complexity since the overall exposure of the sensor field depends on time. Therefore, in this letter, we propose an approach to compute Minimal Exposure Paths in time-varying fields based on a control optimization method called semi-Lagrangian (SL) scheme, in such a way that an intruder will be able to penetrate the dynamic field with the lowest exposure. The SL has already been proven to reach the optimal Minimal Exposure Path (MEP) on static WSNs, but concerning dynamic nodes, the proof is much more complicated. Then, we propose a heuristics that provides convergence of the SL algorithm to a result we conjecture to be the optimal one. Results with different time-varying sensor models in obstacle-free and cluttered environments have been presented and discussed.

Evaluation of the functionality of mobile wireless sensor networks using stochastic reward nets

Evaluation of the functionality of mobile wireless sensor networks using stochastic reward nets

SEEK Mobility Adaptive Protocol Destination Seeker Media Access Control Protocol for Mobile WSNs

The mobile wireless sensor network (WSN) is an emerging field as it widens the scope of applications where sensor networks can be applied. Generally, mobility in wireless communications degrades how well each pair of nodes communicate with one another. In WSN, the effect is higher because nodes have limited communication and computational capabilities. Those limitations create a challenging environment for the operation of sensor node communications. This paper proposes an energy-efficient media access control (MAC) protocol with mobility adaptive throughput based on a carrier-sense multiple access with collision avoidance MAC mechanism called the SEEK-mobility adaptive protocol (SEEK-MADP). SEEK-MADP uses a unique control packet operation to transfer data packets through as many nodes as possible in one duty cycle. The control packets, SYNC and RTS, are merged into one packet (SEEK). SEEK is then transferred to the downstream nodes to establish a connection between a stream of nodes in a duty cycle. This process minimizes the energy consumed by the handshaking process between the connected nodes. To increase throughput, the data period is adaptive to minimize/maximize the data packets according to the movement speed of the sender/receiver nodes. The proposed algorithm is assessed via extensive simulations in mobile scenarios using Network Simulator version 2. The final results show that the SEEK-MADP outperforms MAC protocols, sensor MAC (S-MAC), and SMAC with adaptive listening, which have shown good performance in mobile scenarios. The performance of the proposed algorithm is better than that of IEEE 802.15.4 standard MAC mechanism at mobile scenarios.