Pair Of Sensor Nodes Research Articles

Enhancing Wireless Sensor Network Security Through Mutual Information Analysis for Intrusion Detection and Resilience

Intrusion detection is a critical aspect of network security, involving the identification and response to unauthorized access or malicious activities within a system. It plays a crucial role in safeguarding networks and ensuring data integrity and confidentiality. The Mutual Information (MI) analysis is a vital component in the realm of intrusion detection and security within Wireless Sensor Networks (WSNs). By assessing the information shared between pairs of sensor nodes, MI analysis reveals underlying patterns and relationships in network data. This process involves calculating the mutual information for each node pair based on statistical properties of observed values. Strong correlations or dependencies between nodes are identified, aiding in the detection of critical nodes or clusters vulnerable to compromise. Additionally, MI analysis informs feature extraction by guiding the selection of informative features that capture network structure. It also serves as a proactive tool for identifying anomalies or deviations from expected patterns, which may signal intrusion attempts or malicious activities. Through monitoring changes in mutual information over time, MI analysis facilitates prompt responses to emerging threats, enhancing the resilience and security of WSNs. The work exhibits high accuracy, recall rates, and detection rates across various attack scenarios, underscoring its efficacy in identifying and mitigating security threats. The algorithm's efficiency, effectiveness, and reliability make it a promising solution for enhancing WSN security. Through sophisticated methodologies and adaptive defensive strategies, the proposed algorithm strengthens the robustness and dependability of WSNs, minimizing the risk of potential security vulnerabilities and ensuring comprehensive threat detection in real-world deployment scenarios.

PINC: Pickup Non-Critical Node Based k-Connectivity Restoration in Wireless Sensor Networks.

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors.

Coherent Measurements With MIMO Radar Networks of Incoherent FMCW Sensor Nodes

This work introduces a method for coherent multi-in multi-out (MIMO) processing over a network of frequency-modulated continuous wave (FMCW) radar sensor nodes with independent signal synthesis. The coherency between the bistatic channels is established algorithmically based on the frequency and phase-offset estimation from pairs of sensor nodes and subsequent least-squares estimation on the overdetermined equation system. For the chirp-sequence radar, the proposed processing allows range and speed measurements, as offsets are estimated and corrected for each individual ramp. The applicability of the method is demonstrated in a prototypical setup of a radar network with three sensor nodes comprising integrated 122-GHz transceivers. The obtained bistatic phase precisions of <; 0.1 rad approximately match those of the monostatic measurements of the same radar nodes. For a sequence of 30 ramps of 1-ms duration, this translates to ambiguous range precisions <; 10 μm and speed precision <; 1 mm/s. The absence of wired high-frequency links between the nodes makes the approach well suited for shortrange radar networks in cost-sensitive applications.

Performance Impact of Hardware Impairments on Wireless Powered Cognitive Radio Sensor Networks

In this letter, we investigate the performance of wireless powered cognitive radio sensor networks (CRSNs) in the presence of hardware impairments (HIs). Wireless powered CRSN can be a potential solution to address spectrum scarcity and power shortage in the wireless sensor networks. Herein, the spectrum sharing is exploited to compensate for the spectrum scarcity, whereas the radio frequency energy harvesting technique is utilized to prolong the lifetime. Specifically, we consider a CRSN scenario with two primary nodes and a pair of sensor nodes (SNs). The SNs are assumed to be low-cost devices in view of the Internet of Things infrastructure. Consequently, they are more prone to suffer from different HIs. For evaluating the system performance, we obtain accurate expressions of the outage probability and the system throughput over Nakagami- m fading in the presence of transceiver HIs.

Multichannel preamble sampling MAC protocol for wireless sensor networks

In this article, a multichannel preamble sampling MAC protocol, MCPS, especially tailored for wireless sensor networks, is proposed and thoroughly evaluated. MCPS is a low-power MAC protocol operating on multichannel using carrier sensing for collision avoidance. Specifically, MCPS exploits all the non-overlapping channels provided by IEEE 802.15.4 physical layer. Basically, MCPS uses one dedicated common control channel to wake up an intended receiver using a preamble sampling technique. However, data transmission takes place in a dedicated data channel. Indeed, MCPS allocates to every pair of sensor nodes a unique data channel that aims at being 2-hop conflict free. Hence, the probability of collision is highly reduced and even completely mitigated in some scenarios. Moreover, MCPS allows each sensor node to dynamically adjust its transmission power when sending strobed preamble or periodically generated data. Indeed, for each possible distance separating a pair of communicating nodes, MCPS adapts the appropriate transmission power and selects the appropriate data channel. Using multiple channels, MCPS allows multiple simultaneous data communications along with handshaking on the common control channel, hence reducing the end-to-end delay and improving the throughput while being energy efficient. MCPS has been implemented using OMNET++ simulator under INET framework, on top of the IEEE 802.15.4 physical layer, which was improved to support the multichannel communication. The authors compare the performance of MCPS with McMAC and X-MAC. Simulation results show that MCPS greatly improves the network performance especially in terms of throughput, waiting time, end-to-end delay, and energy per bit.

A Study on the Impact of Packet Length on Communication in Low Power Wireless Sensor Networks Under Interference

Reliability is nowadays considered a key requirement in wireless sensor networks for their increasing diffusion in various Internet of Things applications. However, radio interference from various sources may heavily affect the performance of wirelessly connected embedded devices, resulting into increased packet collisions and congestions. There is therefore a widely recognized need of both theoretical and practical investigations capable of shedding light on the factors affecting the operativeness of sensor networks subject to interference. In this paper, we investigate the role of packet length into the reliability and energy efficiency of low-power medium access protocols. Specifically, we propose a mathematical model to explore the functional dependence of the reliability of a pair of sensor nodes under interference from packet length. We also present a wide range of experimental evaluations aimed at validating the model and at providing novel insights on dependability issues. In particular, we assess the performance of Contiki's default medium access control layer (together with that of an always listening receiver, as a baseline) in terms of packet loss rate and energy efficiency for varying payload lengths. Experimental results highlight the interplay between packet size and interference and in particular the tradeoff between the robustness against interference and the overhead imposed to communication as a function of the length of data packets. The Pareto curve describing the energy efficiency as a function of the packet loss rate, demonstrates the existence of intermediate packet size representing an optimal choice for balancing energy consumption and communication reliability, enabling adequate system dimensioning at design-level.

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

Localization for a disconnected sensor network is highly unlikely to be achieved by its own sensor nodes, since accessibility of the information between any pair of sensor nodes cannot be guaranteed. In this paper, a mobile robot (or a mobile sensor node) is introduced to establish correlations among sparsely distributed sensor nodes which are disconnected, even isolated. The robot and the sensor network operate in a friendly manner, in which they can cooperate to perceive each other for achieving more accurate localization, rather than trying to avoid being detected by each other. The mobility of the robot allows for the stationary and internally disconnected sensor nodes to be dynamically connected and correlated. On one hand, the robot performs simultaneous localization and mapping (SLAM) based on the constrained local submap filter (CLSF). The robot creates a local submap composed of the sensor nodes present in its immediate vicinity. The locations of these nodes and the pose (position and orientation angle) of the robot are estimated within the local submap. On the other hand, the sensor nodes in the submap estimate the pose of the robot. A parallax-based robot pose estimation and tracking (PROPET) algorithm, which uses the relationship between two successive measurements of the robot's range and bearing, is proposed to continuously track the robot's pose with each sensor node. Then, tracking results of the robot's pose from different sensor nodes are fused by the Kalman filter (KF). The multi-node fusion result are further integrated with the robot's SLAM result within the local submap to achieve more accurate localization for the robot and the sensor nodes. Finally, the submap is projected and fused into the global map by the CLSF to generate localization results represented in the global frame of reference. Simulation and experimental results are presented to show the performances of the proposed method for robot-sensor network cooperative localization. Especially, if the robot (or the mobile sensor node) has the same sensing ability as the stationary sensor nodes, the localization accuracy can be significantly enhanced using the proposed method.

Selective geometry for near‐field three‐dimensional localisation using one‐pair sensor

Three-dimensional (3D) localisation of a single source in the near-field using one-pair sensor (a velocity-sensor triad and a pressure sensor) is considered. Recently, a new work has considered this problem and a method is developed with assumption that source target is closer to velocity-sensor triad than the pressure sensor. Since a prior knowledge of the target direction is not available in real situations, this algorithm cannot be applicable. In this study, a new geometry is proposed by adding another pressure sensor to the previous geometry to reduce its fundamental requirement of a known prior source direction. Then, a novel algorithm is proposed in which the velocity-sensor triad with only one of two pressure sensors is used for target localisation. By mathematical tractability of the proposed method, a selection rule for using suitable pair of sensor nodes is developed to hold the best estimation of the source location. It is shown that the proposed method not only has a solution in all target situations but also has better source estimation in comparison with the existing one. The simulation results on prototype data demonstrate the effectiveness of the proposed method in terms of existence and the accuracy of estimated target range.

Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks.

The -Nearest Neighbors (NN) query is an important spatial query in mobile sensor networks. In this work we extend kNN to include a distance constraint, calling it a -distant -nearest-neighbors (-NN) query, which finds the sensor nodes nearest to a query point that are also at or greater distance from each other. The query results indicate the objects nearest to the area of interest that are scattered from each other by at least distance l. The -NN query can be used in most NN applications for the case of well distributed query results. To process an -NN query, we must discover all sets of NN sensor nodes and then find all pairs of sensor nodes in each set that are separated by at least a distance . Given the limited battery and computing power of sensor nodes, this -NN query processing is problematically expensive in terms of energy consumption. In this paper, we propose a greedy approach for -NN query processing in mobile sensor networks. The key idea of the proposed approach is to divide the search space into subspaces whose all sides are . By selecting sensor nodes from the other subspaces near the query point, we guarantee accurate query results for -NN. In our experiments, we show that the proposed method exhibits superior performance compared with a post-processing based method using the NN query in terms of energy efficiency, query latency, and accuracy.

OR-based Block Combination for Asynchronous Asymmetric Neighbor Discovery Protocol

The neighbor discovery protocol (NDP) is one of the critical research subjects in wireless sensor networks (WSNs) for efficient energy management of sensor nodes. A block design concept can be applied to find a neighbor discovery schedule that guarantees at least one common active slot between any pair of sensor nodes. However, the block design-based solutions in literature are not flexible enough because block design cannot support asymmetric asynchronous operations. In this paper, we introduce a new approach for asymmetric asynchronous neighbor discovery protocol that combines two optimal block designs using the OR operation. OR-based block combination solves the problem of original block design, which cannot support asymmetric scenarios. We evaluate the performance of OR-based block combinations using a simulation study. According to our simulation results, OR-based block combination performs up to 71% better than other asymmetric algorithms, such as U-Connect and Disco with 10% and 1% duty cycles.

An Error-Aware Routing Protocol over Lossy Links in Wireless Sensor Networks

As Bit errors fluctuate wildly in di_erent environments and they fluctuate steadily for a given pair of sensor nodes, we propose an error-aware routing protocol (EARP). Compared to other estimators, bit errors can directly reflect the wireless channel state and can be used in complex regions. In this paper, we use parameter VerValue to choose appropriate correction codes and translate error degree to ER Dis(error distance). We propose local Dijkstra algorithm (LDA) in ER Dis graph, witch is a distributed routing protocol algorithm and can be easily implemented in WSNs, to choose a short ER Dis path for very sensor node. Simulation shows that compared to di_erent routing protocol schemes, LDA can choose an e_cient path to the base station and EARP scheme can indeed greatly reduce transmission energy and prolong WSNs lifetime.

Improved coverage in WSNs by exploiting spatial correlation: the two sensor case

One of the main applications of Wireless Sensor Networks (WSNs) is area monitoring. In such problems, it is desirable to maximize the area coverage. The main objective of this work is to investigate collaborative detection schemes at the local sensor level for increasing the area coverage of each sensor and thus increasing the coverage of the entire network. In this article, we focus on pairs of nodes that are closely spaced and can exchange information to decide their collective alarm status in a decentralized manner. By exploiting their spatial correlation, we show that the pair can achieve a larger area coverage than the two individual sensors acting alone. Moreover, we analyze the performance of different collaborative detection schemes for a pair of sensor nodes and show that the area coverage achieved by each scheme depends on the distance between the two sensors.

Multihop Range-Free Localization in Anisotropic Wireless Sensor Networks: A Pattern-Driven Scheme

This paper focuses on multihop range-free localization in anisotropic wireless sensor networks. In anisotropic networks, geometric distance between a pair of sensor nodes is not always proportional to their hop count distance, which undermines the assumption of many existing range-free localization algorithms. To tolerate network anisotropy, we propose a pattern-driven localization scheme, which is inspired by the observation that in an anisotropic network the hop count field propagated from an anchor exhibits multiple patterns, under the interference of multiple anisotropic factors. Our localization scheme therefore for different patterns adopts different anchor-sensor distance estimation algorithms. The average anchor-sensor distance estimation accuracy of our scheme, as demonstrated by both theoretical analysis and extensive simulations, is improved to be better than 0.4r when the average sensor density is above eight, and the sensor localization accuracy thus is approximately better than 0.5r. This localization accuracy can satisfy the needs of many location-dependent protocols and applications, including geographical routing and tracking. Compared with previous localization algorithms that declares to tolerate network anisotropy, our localization scheme excels in 1) higher accuracy stemming from its ability to tolerate multiple anisotropic factors, including the existence of obstacles, sparse and nonuniform sensor distribution, irregular radio propagation pattern, and anisotropic terrain condition, 2) localization accuracy guaranteed by theoretical analysis, rather than merely by simulations, and 3) a distributed solution with less communication overhead and enhanced robustness to different network topologies.

An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks

In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based) heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.

A branch-and-cut algorithm for the strong minimum energy topology in wireless sensor networks

This paper studies the strong minimum energy topology design problem in wireless sensor networks. The objective is to assign transmission power to each sensor node in a directed wireless sensor network such that the induced directed graph topology is strongly connected and the total energy consumption is minimized. A topology is defined to be strongly connected if there exists a communication path between each ordered pair of sensor nodes. This topology design problem with sensor nodes defined on a plane is an NP-Complete problem. We first establish a lower bound on the optimal power consumption. We then provide three formulations for a more general problem defined on a general directed graph. All these formulations involve an exponential number of constraints. Second formulation is stronger than the first one. Further, using the second formulation, we lift the connectivity constraints to generate stronger set of constraints that yield the third formulation. These lifted cuts turn out to be extremely helpful in developing an effective branch-and-cut algorithm. A series of experiments are carried out to investigate the performance of the proposed branch-and-cut algorithm. These computational results over 580 instances demonstrate the effectiveness of our approach.

Fault-Tolerant Relay Node Placement in Heterogeneous Wireless Sensor Networks

Existing work on placing additional relay nodes in wireless sensor networks to improve network connectivity typically assumes homogeneous wireless sensor nodes with an identical transmission radius. In contrast, this paper addresses the problem of deploying relay nodes to provide fault tolerance with higher network connectivity in heterogeneous wireless sensor networks, where sensor nodes possess different transmission radii. Depending on the level of desired fault tolerance, such problems can be categorized as: 1) full fault-tolerant relay node placement, which aims to deploy a minimum number of relay nodes to establish k(k ? 1) vertexdisjoint paths between every pair of sensor and/or relay nodes and 2) partial fault-tolerant relay node placement, which aims to deploy a minimum number of relay nodes to establish k(k ? 1) vertex-disjoint paths only between every pair of sensor nodes. Due to the different transmission radii of sensor nodes, these problems are further complicated by the existence of two different kinds of communication paths in heterogeneous wireless sensor networks, namely, two-way paths, along which wireless communications exist in both directions; and one-way paths, along which wireless communications exist in only one direction. Assuming that sensor nodes have different transmission radii, while relay nodes use the same transmission radius, this paper comprehensively analyzes the range of problems introduced by the different levels of fault tolerance (full or partial) coupled with the different types of path (one-way or two-way). Since each of these problems is NP-hard, we develop O(?k <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> )-approximation algorithms for both one-way and two-way partial fault-tolerant relay node placement, as well as O(?k <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> )-approximation algorithms for both one-way and two-way full fault-tolerant relay node placement (? is the best performance ratio of existing approximation algorithms for finding a minimum k-vertex connected spanning graph). To facilitate the applications in higher dimensions, we also extend these algorithms and derive their performance ratios in d-dimensional heterogeneous wireless sensor networks (d ? 3). Finally, heuristic implementations of these algorithms are evaluated via QualNet simulations.

Improved Key Predistribution Scheme in Wireless Sensor Networks Using Cell Splitting in Hexagonal Grid Based Deployment Model

Security in wireless sensor networks is an upcoming field which is quite different from traditional network security mechanisms. Many applications are dependent on the secure operation of a wireless sensor network, and have serious effects if the network is disrupted. Therefore, it is necessary to protect communication between sensor nodes. Key management plays an essential role in achieving security in wireless sensor networks. To achieve security, various key predistribution schemes have been proposed without deployment knowledge. Deployment knowledge can benefit the key predistribution scheme, as the nodes that are likely to be neighbors of each sensor node are assumed, and hence each node does not need to waste its memory to store unnecessary secret information. However, the existing key predistribution schemes require more memory and larger transmission range to achieve the desired connectivity. In order to enhance secure communication among sensor nodes, grid and hexagon deployment models are used. In both the deployment models, the sensor field is divided into equal grids. The keys are distributed from a large key pool randomly and pairwise keys are generated for each pair of sensor nodes. Once the pairwise keys are generated among neighboring nodes, they establish a secure connection and transmit data. We propose a new scheme based on cell splitting concept to improve the security level, in which a hexagon is subdivided in to smaller groups. The performance is evaluated in terms of connectivity and resilience against node capture. The analysis show that the performance is better using cell splitting concept compared to normal hexagon based scheme.

A New Approach for Time Synchronization in Wireless Sensor Networks: Pairwise Broadcast Synchronization

This letter proposes an energy-efficient clock synchronization scheme for Wireless Sensor Networks (WSNs) based on a novel time synchronization approach. Within the proposed synchronization approach, a subset of sensor nodes are synchronized by overhearing the timing message exchanges of a pair of sensor nodes. Therefore, a group of sensor nodes can be synchronized without sending any extra messages. This paper brings two main contributions: 1. Development of a novel synchronization approach which can be partially or fully applied for implementation of new synchronization protocols and for improving the performance of existing time synchronization protocols. 2. Design of a time synchronization scheme which significantly reduces the overall network-wide energy consumption without incurring any loss of synchronization accuracy compared to other well-known schemes.

Location-based design for secure and efficient wireless sensor networks

This paper studies a novel location-based design for secure and efficient wireless sensor networks. With this scheme, the sensing area is divided into a number of location cells and a logical group consists of four location cells. A pairwise key is established for each pair of sensor nodes in a logical group based on grid-based bivariate t-degree polynomials. An efficient en-route data authentication method is proposed to limit data authentication within a small neighboring range. In addition, a greedy location-based secure and energy-efficient data aggregation approach is integrated with the design. It further utilizes data aggregation by setting up control groups, applying pattern codes, selecting and switching control head nodes dynamically and periodically. The analysis demonstrate that our design is resilient to node compromise and decrease storage and communication overhead when compared with non location-based designs.

Relay Node Placement in Wireless Sensor Networks

A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy consumption is a superlinear function of the transmission distance. One approach to prolonging network lifetime while preserving network connectivity is to deploy a small number of costly, but more powerful, relay nodes whose main task is communication with other sensor or relay nodes. In this paper, we assume that sensor nodes have communication range r>0, while relay nodes have communication range Rgesr, and we study two versions of relay node placement problems. In the first version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting of relay and/or sensor nodes. In the second version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting solely of relay nodes. We present a polynomial time 7-approximation algorithm for the first problem and a polynomial time (5+epsi)-approximation algorithm for the second problem, where epsi>0 can be any given constant