Different Types Of Sensor Nodes Research Articles

Characteristic evaluation via multi-sensor information fusion strategy for spherical underwater robots

Currently, most of the existing fusion methods ignore the rich multi-source information of different types of sensor nodes in the underwater unknown environment, which makes it challenging for Autonomous Underwater Vehicles (AUVs) to accurately perceive the external environment and make actionable decisions. Considering the key issues such as attitude estimation, positioning and obstacle avoidance involved in performing AUV tasks, this paper proposed a Multi-Source Information Fusion (MSIF) model for Spherical Underwater Robots (SURs) we developed based on various low-cost sensors. Multi-source information from an Inertial Measurement Unit (IMU), Pressure Sensor Array (PSA), Obstacle Avoidance Sensor Array (OASA), Depth Sensor (DS), Looking-Down Camera (LDC) and Acoustic Communication System (ACS) were fused to enable SUR to obtain high-precision estimated data for attitude estimation, positioning and obstacle avoidance, etc. More precisely, according to the correlation between the sensors, the optimized model was constructed to compensate for angle errors, velocity errors, orientation errors, etc. Subsequently, a machine learning method using Back Propagation Neural Network (BPNN) was proposed to improve the accuracy and effectiveness of the MSIF model through feature selection, data training, and feature estimation, etc. Finally, a series of experiments were performed under different scenarios, such as motion and obstacle avoidance experiments. The theoretical derivation and comprehensive evaluations demonstrated the effectiveness and feasibility of the proposed model, which provided a new reference value for solving issues such as attitude estimation, positioning and obstacle avoidance of AUVs.

DynGATT: A dynamic GATT-based data synchronization protocol for BLE networks

Bluetooth Low Energy (BLE) is a wireless communication technology for power-constrained Internet of Things (IoT) applications. BLE data can be transmitted via either the IPv6 or the Generic ATTribute (GATT) Profile protocol, with the former supporting dynamic IoT structures and the latter being application-friendly. In fact, GATT requires the data layout to be known in advance by peer devices, in order to properly interpret the received data. In this paper, we introduce DynGATT, a protocol that achieves the benefits of both IPv6 and GATT, by extending GATT in a seamless fashion to support dynamic IoT structures. The key idea of DynGATT is to use GATT descriptors, originally intended to specify data in static IoT scenarios, to also specify IoT systems whose structures may dynamically evolve. Peer devices reading these descriptors will know how to interpret the data of GATT characteristics provided by devices joining the IoT network. Because no additional data have to be transmitted, the connection time is then reduced with respect to classical BLE. DynGATT has been implemented and tested in an agricultural IoT application, with different types of sensor nodes. Our experimental evaluation shows that DynGATT is very power-efficient, despite its added flexibility. Its worst-case power consumption is only around 19.37µA per data transmission and around 41.37µA overall. This consumption can be further reduced by using the methods discussed in this paper. To the best of our knowledge, this work is the first to support dynamic IoT structures in a GATT-based setting.

RegPrice: Region-Based Pricing Scheme for Provisioning Safety-as-a-Service in IoT Applications

In this paper, we propose a region-based pricing scheme, named as RegPrice, for provisioning safety-related decisions dynamically to the end-users. Typically, heterogeneous type of sensor nodes are present in the device layer of Safe-aaS. Considering the case of safety in road transportation, we compute the fixed and variable costs incurred in procurement, deployment, and maintenance for each of these different types of sensor nodes. We introduce the concept of tariff cost, which varies with the type of road in different regions and presence of similar homogeneous sensor nodes deployed in that region. Finally, we estimate the utility of a sensor node, which is a function of the sensing area, ratio of the fixed cost to total cost incurred, responsiveness factor, and rating given by an end-user for that sensor node. The SSPs provide rent to the sensor/vehicle owners for taking their sensor nodes on lease. In order to formulate the interactions among the SSPs and sensor owners, we apply first-price, sealed-bid auction-based game theoretic approach, where SSPs act as bidders. Exhaustive simulation results depict that the proposed pricing scheme, RegPrice, is capable of reducing the expenses of a SSP by 7.51% and 9.71% compared to the existing pricing schemes [1] and [2].

A multi-objective bi-level location problem for heterogeneous sensor networks with hub-spoke topology

An heterogeneous sensor network (hSN) consists of different types of sensor nodes with varying coverage capability, range, and sensing quality. hSNs are used by military and other defense organizations for a number of purposes such as monitoring critical facilities, surveilling an area of interest, tracking enemies, or protecting borders. Therefore, the deployment problem of such networks to form an effective coverage and surveillance is of high importance. In this study, we consider the problem of locating an hSN along a two-dimensional belt-shaped border region which includes a number of critical facilities that need protection against intruders. Assuming a hub-spoke location topology, we allow the use of cooperative and gradual covering, multiple types of sensors, critical facilities and intruders. We developed two competing multi-objective mixed integer non-linear program formulations as well as their equivalent mixed integer linear program (MILP) reformulations which adopt a goal programming approach. The MILP formulations are then solved by a commercial optimizer for a set of problem instances using the branch-and-cut (B&C) procedure with various branching and node selection strategies as well as different user defined optimality gap and goal settings. Our results indicate that the performance of formulations are significantly affected by the B&C variable selection strategy as well as the goal levels determined by the decision-makers. We also observe that, using proper settings, the majority of the problem instances can be solved within a maximum of 10% optimality gap in reasonable computing times.

Energy-Aware Constrained Relay Node Deployment for Sustainable Wireless Sensor Networks

This paper considers the problem of communication coverage for sustainable data forwarding in wireless sensor networks, where an energy-aware deployment model of relay nodes (RNs) is proposed. The model used in this paper considers constrained placement and is different from the existing one-tiered and two-tiered models. It supposes two different types of sensor nodes to be deployed, i) energy rich nodes (ERNs), and ii) energy limited nodes (ELNs). The aim is thus to use only the ERNs for relaying packets, while ELN's use will be limited to sensing and transmitting their own readings. A minimum number of RNs is added if necessary to help ELNs. This intuitively ensures sustainable coverage and prolongs the network lifetime. The problem is reduced to the traditional problem of minimum weighted connected dominating set (MWCDS) in a vertex weighted graph. It is then solved by taking advantage of the simple form of the weight function, both when deriving exact and approximate solutions. Optimal solution is derived using integer linear programming (ILP), and a heuristic is given for the approximate solution. Upper bounds for the approximation of the heuristic (versus the optimal solution) and for its runtime are formally derived. The proposed model and solutions are also evaluated by simulation. The proposed model is compared with the one-tiered and two-tiered models when using similar solution to determine RNs positions, i.e., minimum connected dominating set (MCDS) calculation. Results demonstrate the proposed model considerably improves the network life time compared to the one-tiered model, and this by adding a lower number of RNs compared to the two-tiered model. Further, both the heuristic and the ILP for the MWCDS are evaluated and compared with a state-of-the-art algorithm. The results show the proposed heuristic has runtime close to the ILP while clearly reducing the runtime compared to both ILP and existing heuristics. The results also demonstrate scalability of the proposed solution.

FNN based Adaptive Route Selection Support System

This paper presents Fuzzy Neural Network (FNN) based Adaptive Route Selection Support System (ARSSS) for assisting drivers of vehicles. The aim of the proposed ARSSS system is to select path based on shortest possible time. The proposed system intakes traffic information, such as volume to capacity ratio, traffic flow, vehicle queue length and green cycle length, passenger car unit etc using different types of sensor nodes, remote servers, CCTVs and the road information such as path length, signalized junctions, intersection points between source-destination pair are captured using GPS service. A FNN has been employed to select an optimal path having shortest time. The input parameters of FNN are distance, signal point delay, road type and traffic flow whereas the output parameter is path selection probability which paves the way to identify the best suitable path. The simulation result revels that FNN based ARSSS outperforms more accurate than that of other route selection support system (webster delay model) and artificial neural network (ANN) in estimating path delay.

Reliability-Oriented Single-Path Routing Protocols in Wireless Sensor Networks

Wireless sensor networks (WSNs) bring significant advantages over traditional communications in today's applications, such as environmental monitoring, homeland security, and health care. However, harsh and complex environments pose great challenges in the reliability of WSN communications. To achieve reliable wireless communications within WSNs, it is essential to have a reliable routing protocol and to have a means to evaluate the reliability performance of different routing protocols. In this paper, we first model the reliability of two different types of sensor nodes: 1) energy harvesting sensor nodes and 2) battery-powered sensor nodes. We then present wireless link reliability models for each type of sensor nodes, where effects of different parameters, such as battery life-time, shadowing, noise, and location uncertainty, are considered for analyzing the wireless link reliability. Based on the sensor node and wireless link reliability models, we compare the performance of different routing algorithms in terms of end-to-end path reliability and number of hops. A dynamic routing approach is then proposed to achieve the most reliable end-to-end path in WSNs. Furthermore, to facilitate a fair and comprehensive comparison among different routing algorithms, a cost function approach that integrates the end-to-end path reliability and number of hops is proposed, providing an indicator of quality of service of applications running on WSNs.

A Local World Evolving Model for Energy-Constrained Wireless Sensor Networks

Energy efficiency is one of the basic requirements of wireless sensor networks (WSNs) yet this problem has not been sufficiently explored in the context of cluster-based sensor networks. Specifically, the interaction of different types of sensor nodes is one of the major factors of energy efficiency in large-scale heterogeneous networks. In this paper, we aim at improving the interactions among sensor nodes, and we present a heterogeneous local-world model to form large-scale wireless sensor networks based on complex network theory. Two types of nodes, normal nodes and cluster nodes, are added to the networks. The degree distribution for this model is obtained analytically by mean-field theory. This approach depicts the evolution of the network as having a topological feature that is not completely exponential and not completely power law; instead, it behaves between them. The experiment and simulation indicate that the control method has excellent robustness and a satisfactory control effect (interaction of different types of sensor nodes). Furthermore, the results also show that the higher the generation rate of the cluster nodes is, the closer the degree distribution follows the power-law distribution.

A Secured Grid Based Route Driven PKC Scheme for Heterogeneous Sensor Network

Ongoing research work shows that homogeneous sensor networks have poor security, connectivity, performance and scalability. Heterogeneous sensor network (HSN) consists of physically different types of sensor nodes. The feasibility of implementing Elliptic Curve Diffe-Helmen (ECDH) in HSN is simulated in this approach. Under dynamic condition of sensor node, implementation of grid-based coordinate route driven scheme has been proposed. This route driven scheme is highly adaptable for public key management scheme for HSN. It also compares the energy and throughput efficiency for dynamic position of sensor nodes. The proposed method is compared with the existing routing techniques like AODV and DSR. The proposed method dramatically increases network lifetime based on the elected coordinator nodes and the size of the grid area.

Secure Message Distribution Scheme with Configurable Privacy in Heterogeneous Wireless Sensor Networks

Security and privacy of wireless sensor networks are key research issues recently. Most existing researches regarding wireless sensor networks security consider homogenous sensor networks. To achieve better security and performance, we adopt a heterogeneous wireless sensor network (HWSN) model that consists of physically different types of sensor nodes. This paper presents a secure message distribution scheme with configurable privacy for HWSNs, which takes advantage of powerful high-end sensor nodes. The scheme establishes a message distribution topology in an efficient and secure manner. The sensor node only need generate one signature for all the messages for all the users, which can greatly save the communication and computation cost of the sensor node. On the other hand, the user can only know the messages that let him know based on a pre-set policy, which can meet the requirement of the privacy. We show that the scheme has small bandwidth requirements and it is resilient against the node compromise attack.

CollECT: Collaborative event detection and tracking in wireless heterogeneous sensor networks

Tracking is an important application in wireless sensor networks (WSNs), especially for the urgent event of interest. Recent research has paid much attention to the WSN wherein all sensor nodes are identical in sensing units, but the utilization of different types of sensor nodes has not been widely explored. In the paper, we propose a fully distributed protocol, CollECT, to event detection and tracking in wireless heterogeneous sensor networks (WHSNs), which consists of various types of sensor nodes with different sensing units. The main idea of CollECT is collaboration, by which the same type of sensor nodes construct the attribute region, represented by a convex polygon, whereas the different types of sensor nodes determine whether the event occurs. In CollECT, three procedures, vicinity triangulation, event determination, and border sensor node selection, are proposed to construct the attribute region, to determine the occurrence of the event, and to select border sensor nodes to stand for the event boundary, respectively. Simulation results validate the performance of CollECT in terms of accuracy of event tracking and fitness of the border sensor nodes selected. Approximately 87% sensor nodes within the event region can be correctly identified on average. Additionally, the border sensor nodes selected by CollECT are beneficial to efficiently stand for the event boundary.

BiSNET: A biologically-inspired middleware architecture for self-managing wireless sensor networks

This paper describes BiSNET (Biologically-inspired architecture for Sensor NETworks), a middleware architecture that addresses several key issues in multi-modal wireless sensor networks (MWSNs) such as autonomy, scalability, adaptability, self-healing and simplicity. Based on the observation that various biological systems have developed mechanisms to overcome these issues, BiSNET follows certain biological principles such as decentralization, food gathering/storage and natural selection to design MWSN applications. In BiSNET, each application consists of multiple software agents, which operate on the BiSNET middleware platform in individual sensor nodes, and each agent exploits certain biologically-inspired mechanisms such as energy exchange, pheromone emission, replication, migration and death. This is analogous to a bee colony (application) consisting of multiple bees (agents). This paper describes the biologically-inspired mechanisms in BiSNET, and evaluates their impacts on the autonomy, scalability, adaptability, self-healing and simplicity of MWSNs. Simulation results show that BiSNET allows sensor nodes (agents and platforms) to be scalable with respect to network size, autonomously adapt their sleep periods for power efficiency and responsiveness of data collection, adaptively aggregate data from different types of sensor nodes, and collectively self-heal (i.e., detect and eliminate) false positive sensor data. The BiSNET platform is implemented simple in its design and lightweight in its memory footprint.