Mission-critical Wireless Sensor Networks Research Articles

An one-time pad cryptographic algorithm with Huffman Source Coding based energy aware sensor node design

Recently, the security-based algorithms for energy-constrained sensor nodes are being developed to consume less energy for computation as well as communication. For the mission critical wireless sensor network (WSN) applications, continuous and secure data collection from WSN nodes is an essential task on the deployed field. Therefore, in this manuscript, One-Time Pad Cryptographic Algorithm with Huffman Source Coding Based Energy Aware sensor node Design is proposed (EA-SND-OTPCA-HSC). Before transmission, the distance among transmitter and receiver is rated available in mission critical WSN for lessen communication energy consume of sensor node. For the mission critical WSN applications, continuous and secure data collection from WSN nodes is an essential task on the deployed field. The periodic sleep/wake up scheme with Huffman source coding algorithm is used to save energy at the node level. Then, one-time pad cryptographic algorithm in each sensor node, the vernam cipher encryption technique is applied to the compact payload. The proposed technique is executed and efficacy of proposed method is assessed using Payload Vs Energy consume for one sensor node, communication energy consume for one sensor node with different distances, energy consume for one sensor node under various methods, Throughput, delay and Jitter are analyzed. Then the proposed method provides 90.12 %, 89.78 % and 91.78 % lower delay and 88.25 %, 95.34 % and 94.12 % lesser energy consumption comparing to the existing EA-SND-Hyb-MG-CUF, EA-SND-PVEH and EA-SND-PIA techniques respectively.

Trust-Based Intelligent Routing Protocol with Q-Learning for Mission-Critical Wireless Sensor Networks.

Mission-critical wireless sensor networks require a trustworthy and punctual routing protocol to ensure the worst-case end-to-end delay and reliability when transmitting mission-critical data collected by various sensors to gateways. In particular, the trustworthiness of mission-critical data must be guaranteed for decision-making and secure communications. However, it is a challenging issue to meet the requirement of both reliability and QoS in sensor networking environments where cyber-attacks may frequently occur and a lot of mission-critical data is generated. This study proposes a trust-based routing protocol that learns the trust elements using Q-learning to detect various attacks and ensure network performance. The proposed mechanism ensures the prompt detection of cyber threats that may occur in a mission-critical wireless sensor network and guarantees the trustworthy transfer of mission-critical sensor data. This paper introduces a distributed transmission technology that prioritizes the trustworthiness of mission-critical data through Q-learning results considering trustworthiness, QoS, and energy factors. It is a technology suitable for mission-critical wireless sensor network operational environments and can reliably operate resource-constrained devices. We implemented and performed a comprehensive evaluation of our scheme using the OPNET simulator. In addition, we measured packet delivery rates, throughput, survivability, and delay considering the characteristics of mission-critical sensor networks. The simulation results show an enhanced performance when compared with other mechanisms.

Performance evaluation of ADMC-MAC mission critical protocol for wireless sensor networks

Mission-critical MAC protocol is an attractive research area since past few years as the wireless sensor networks have developed their utility in mission-critical applications like border surveillance, Tsunami alert systems, and earthquake safety systems, fire fighting applications, industrial automation, pipeline leakage detection system, critical health monitoring, etc. The Wireless sensor networks are deployed for this purpose may be termed as Mission-critical wireless sensor networks, and MAC protocols designed are termed as Mission Critical MAC Protocols for WSN. ADMC-MAC protocol is one of these latest developed protocols. In previous work, the protocol is tested for 40% duty cycle. This paper does the performance evaluation of this protocol in NS-2.35 for different missioncritical scenarios at different duty cycles for mission-critical performance parameters where the actual novelty lies. The results show that the proposed protocol gives best performance when set at 40% duty cycle. It is adaptive to the mission-critical applications and maintains the mission-critical data transport performance along with the energy of the wireless sensor networks. Simulation results confirm that ADMC-MAC model can further be enhanced to reduce data processing delay and for improving data delivery performance. The model may be enhanced by including intelligent nodes only for analyzing and data processing to reduce processing delay .The enhanced model suggested may be used for Mission-critical Wireless Sensor networks in integration with IoT for quick actions in mission-critical application.

Medium Access Control for Unmanned Aerial Vehicle Based Mission Critical Wireless Sensor Networks in 3D Monitoring Networks

In this paper, a novel medium access control (MAC) layer protocol is introduced for unmanned aerial vehicle (UAV)-based mission critical wireless sensor networks (MC-WSN), which is an important application of mission critical sensor and sensor networks (MC-SSN). The UAVs hovering in the three-dimensional monitoring networks are distributed in subsets according to their distance from the center station. UAVs in the same subset are contending for access and transmission, while each subset is allotted a slot based on adaptive time division multiple access (TDMA) scheme. As a multi-channel system, a novel channel allocation algorithm is presented for subset relay transmission period to optimize the performance of networks. The UAV returning period for charging is utilized in the protocol to enhance the transmission throughput and mitigate delay. Detection slot and position prediction algorithm are designed in the UAV returning period to improve the throughput and reduce the delay. The simulation results verify the improvement on throughput and delays of the proposed protocol for UAV-based MC-WSN.

Software Defined Mission-Critical Wireless Sensor Network: Architecture and Edge Offloading Strategy

Mission-critical wireless sensor networks are attractive for information gathering in various complex environments and support many mission-critical applications, such as industrial automation and security surveillance. However, in order to fully exploit these networks for such applications, agile and scalable network management for data transfer and computing task implementation are essential. Thus, in this paper, we propose a software-defined mission-critical wireless sensor network (MC-SDWSN) which can solve the existing challenging issues in tradition WSNs, such as resource utilization, data processing, system compatibility, and strict latency requirement. The architecture is based on the idea of SDN architecture, combining the hierarchical cloud and edge computing technologies. Based on the MC-SDWSN architecture, a novel centralized computation offload strategy in sensor network application is proposed to show the feasibility. The simulation results in confirm the MC-SDWSN architecture, and the edge offloading strategy could support the critical missions effectively.

FRP: A novel fast rerouting protocol with multi-link-failure recovery for mission-critical WSN

Fast rerouting requires that a backup route is already available at each node so that traffic can immediately be shifted on it without new path discovery and convergence time delay. Handling multiple failures with least possible delay, high throughput and least overhead with regard to memory and battery is a real challenge in Wireless Sensor Networks (WSN). Current fast rerouting techniques that handle multiple failures do not specifically target mission-critical WSN applications. Fast Rerouting techniques use spanning trees, backup topologies or configurations to shift traffic immediately as and when error is detected. These techniques do not focus on finding least hop count on the backup path and therefore, end-to-end delay on the backup paths is higher than on the primary path. The proposed Fast Rerouting Protocol (FRP) establishes primary and backup routes before the start of data transfer. It creates at least one backup path towards destination from every node on the primary path. FRP therefore has the ability to handle multiple failures in mission-critical WSN environment. NS-2 simulation results of FRP against the competitor reveal that, FRP takes least time and control messages to establish shorter fast rerouting paths, produces minimum end-to-end delay, least energy consumption and higher network life time.

Mobility assisted localization for mission critical Wireless Sensor Network applications using hybrid area exploration approach

Sensor node location information is critical in many Wireless Sensor Network (WSN) applications with random sensor node deployment. In such applications, node localization using a faster area exploration mechanism is needed to initiate precise sensing and communication. In this paper, faster area exploration approach for mobility-assisted localization scheme is proposed for mission-critical WSN applications. Each Mobile Anchor (MA) node embedded with a localization module moves in the sensor field in a coordinated manner while localizing the deployed static nodes. The proposed area exploration scheme is implemented using a hybrid of max-gain approach and cost-utility based frontier (HMF) approach. The paper addresses the issue of sparse anchor node condition during the localization process. The simulation results obtained using Cooja simulator shows that the proposed mobility-assisted localization scheme results in accurate localization with minimum delay. The proof-of-concept of the proposed scheme is demonstrated using Berkeley static nodes and custom designed MA nodes.

Formal probabilistic performance verification of randomly-scheduled wireless sensor networks

Energy efficiency in wireless sensor networks (WSN) is one of the most critical issue regardless of the target application. While scheduling sensors by partitions to preserve energy is a simple and intuitive approach in this context, it is also important to not compromise on the main performance requirements of the considered application. For mission-critical WSN applications, different quality of service (QoS) requirements on network performance have to be met. Besides, various assumptions, may effectively impact the sensing performance capabilities of the network. Nevertheless, most analysis techniques focus on the average performance values, and do not consider neither the targeted QoS requirements, nor the probabilistic feature of the algorithm. Based on the theorem proving approach, we first provide, in this paper, an accurate formal analysis of the network lifetime maximisation problem, under QoS constraints, for randomly-scheduled wireless sensor networks. After that, we tackle the higher-order-logic formalisation of the intrusion coverage intensity, for a modified version of the randomised scheduling, with more realistic assumptions for the intrusion object, in a two or three dimensional plane.

Fault Recovery in Time-Synchronized Mission Critical ZigBee-Based Wireless Sensor Networks

Reliability and precise timestamping of events that occur are two of the most important requirements for mission critical wireless sensor networks. Accurate timestamping is obtained by synchronizing the nodes to each other while reliability can be obtained by eliminating single points of failure (SPF). In this paper, we address the SPF problem of a ZigBee-based wireless sensor network by means of using multiple coordinators with different personal area network identifiers (PAN IDs). We propose a solution where members of a network switch from one coordinator to another in case of failure by changing their respective PAN ID. We verify experimentally that our solution provides gains in terms of recovery speed and, therefore, synchronization accuracy with respect to a solution proposed in the literature.

Safety-critical wireless sensor networks under a polyphase spreading sequences scenario

Reliable communication is a vital issue for safety- and mission-critical wireless sensor network environments such as industrial monitoring, medical care, and battlefield surveillance. These networks require highly accurate and delay-intolerant wireless communications. Under such critical conditions, the chip sequences used in these networks become vulnerable because of channel impairments and other interferences, thereby significantly decreasing overall system performance. In this paper, polyphase sequences are employed at the physical layer of IEEE Standard 802.15.4 to enhance the communication reliability of wireless sensor networks. Through an extensive simulation, it is found that upon applying polyphase sequences, the chip errors are reduced to $2.94\times {10}^{-6}$ in comparison to $1.18\times {10}^{-5}$ of conventional binary sequences (PN sequences).

Fusion-based surveillance WSN deployment using Dempster–Shafer theory

In mission-critical Wireless Sensor Networks surveillance applications, a high detection rate coupled with a low false alarm rate is essential. Additionally, fusion methods can be employed with the hope that aggregation of uncertain information from multiple sensors enhances the quality of surveillance provided by the network. This paper investigates the following fundamental problem: what is the best way to deploy a finite number of unreliable sensors characterized by uncertain readings in order to satisfy the user detection requirements. Unlike prior efforts that rely on simple fusion schemes, we use the Dempster–Shafer theory to define a generic evidence fusion scheme that captures several characteristics of real-world applications. The fusion-based uncertainty-aware sensor networks deployment problem is formulated as a binary non-linear and non-convex optimization problem that is NP-hard, and an efficient heuristic using genetic algorithms is investigated. The effectiveness and efficiency of the proposed approach are evaluated using both simulations and experiments. The obtained results demonstrate the appropriateness of the evidence fusion model that considers in a meaningful way the information on the quality of sensors decisions as well as the reliability of these sensors along with their uncertain and imprecise decisions. Also, the proposed approach outperforms state-of-the-art deployment strategies.

A novel coverage and connectivity preserving routing protocol for mission-critical wireless sensor networks

Mission-critical wireless sensor networks (WSNs) have been found to be very useful for many military and civil applications such as disaster management, surveillance of battle fields and e-healthcare. Coverage preservation and connectivity are the most essential functions to guarantee quality of service (QoS) in mission-critical WSNs. By optimizing coverage, the deployment strategy would guarantee that optimum area in the sensing field is covered by sensors, as required by various types of mission-critical applications. Whereas by ensuring that the network is connected, it is ensured that the sensed information is transmitted to other nodes and possibly to a centralized base station which makes valuable decisions for the applications. However, a trade-off exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this paper, we propose a Coverage and Connectivity Preserving Routing Protocol for mission-critical WSNs (CCPRP) to accommodate connectivity, energy-balance and coverage-preservation for sensor nodes in WSNs that are hierarchically clustered. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a data from elected cluster head to the base station through elected gateway. We define a cost metric to favour nodes with high energy-redundantly covered as better candidates for cluster heads in a way to improve the performance of sensing coverage, reduce communications energy and prolonging the effective network lifetime with optimal data delivery. Furthermore, we propose a novel area coverage protocol called CCPRP-AC for scheduling the sensing activity of sensor nodes that are deployed to sense point-targets in WSN using information coverage. The simulation results demonstrate that the proposed protocol CCPRP is able to increase the duration of the on-duty network and provide up to 124.76% of extra service time with 100% sensing coverage ratio comparing with other existing protocols, and the protocol CCPRP-AC achieves k-coverage of a field, where every point is covered by at least k sensors with a minimum number of sensors.

Performance Analysis of Real-Time Detection in Fusion-Based Sensor Networks

Real-time detection is an important requirement of many mission-critical wireless sensor network applications such as battlefield monitoring and security surveillance. Due to the high network deployment cost, it is crucial to understand and predict the real-time detection capability of a sensor network. However, most existing real-time analyses are based on overly simplistic sensing models (e.g., the disc model) that do not capture the stochastic nature of detection. In practice, data fusion has been adopted in a number of sensor systems to deal with sensing uncertainty and enable efficient collaboration among resource-limited sensors. However, real-time performance analysis of sensor networks designed based on data fusion has received little attention. In this paper, we bridge this gap by investigating the fundamental real-time detection performance of large-scale sensor networks under stochastic sensing models. In particular, we consider two basic data fusion schemes, i.e., value fusion and decision fusion. Our results show that data fusion is effective in achieving stringent performance requirements such as short detection delay and low false alarm rates. Moreover, value fusion and decision fusion are suitable for low and high signal-to-noise ratio scenarios, respectively. Our results help understand the impact of data fusion and provide important guidelines for the design of real-time wireless sensor networks for intrusion detection. Our analyses are verified through extensive simulations based on both synthetic data sets and data traces collected in a real deployment for vehicle detection. The results show that data fusion can reduce the network density by about 60 percent compared with the disc model while detecting any intruder within one detection period at a false alarm rate lower than five percent.

Poly: A reliable and energy efficient topology control protocol for wireless sensor networks

Energy efficiency and reliability are the two important requirements for mission-critical wireless sensor networks. In the context of sensor topology control for routing and dissemination, Connected Dominating Set (CDS) based techniques proposed in prior literature provide the most promising efficiency and reliability. In a CDS-based topology control technique, a backbone – comprising a set of highly connected nodes – is formed which allows communication between any arbitrary pair of nodes in the network. In this paper, we show that formation of a polygon in the network provides a reliable and energy-efficient topology. Based on this observation, we propose Poly, a novel topology construction protocol based on the idea of polygons. We compare the performance of Poly with three prominent CDS-based topology construction protocols namely CDS-Rule K, Energy-efficient CDS (EECDS) and A3. Our simulation results demonstrate that Poly performs consistently better in terms of message overhead and other selected metrics. We also model the reliability of Poly and compare it with other CDS-based techniques to show that it achieves better connectivity under highly dynamic network topologies.

Group-based intrusion detection system in wireless sensor networks

Many mission critical wireless sensor networks require an efficient, lightweight and flexible intrusion detection algorithm to identify malicious attackers. In this paper, we propose a distributed group-based intrusion detection scheme that meets all the above requirements by partitioning the sensor networks into many groups in which the sensors in each group are physically close to each other and are equipped with the same sensing capability. Our intrusion detection algorithm takes simultaneously into consideration of multiple attributes of the sensor nodes to detect malicious attackers precisely. We show through experiments with real data that our algorithm can decrease the false alarm rate and increase the detection accuracy compared with existing intrusion detection schemes while lowering the computation and transmission power consumption.