Impact of Node Deployment and Routing for Protection of Critical Infrastructures

Subhan, Fazlı; Noreen, Madiha; Imran, Muhammad; Tariq, Moeenuddin; Khan, Ashiq; Shoaib, Muhammad

doi:10.1109/access.2019.2891667

Cited by 9 publications

(6 citation statements)

References 40 publications

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“…Multiple tiers of defense at component/system level, and security operation center are introduced, while for a given component vulnerability vector, the model assesses key security parameters. In [28] the impact of node placement and clustering on LWSN network lifetime is analyzed. Existing node placement and clustering schemes are classified for LWSN and various topologies for disparate applications are introduced.…”

Section: Related Workmentioning

confidence: 99%

Real Time Threat Assessment of Truck Cargos Carrying Dangerous Goods for Preventing Terrorism Attacks on Neighboring Critical Infrastructures

2022

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Critical infrastructures are assets of invaluable importance, essential for the whole world. Since they serve core functions of our societies, they often become targets of terrorists. Many critical infrastructures are vulnerable, due to their short distance from public roads and in the past years, several vehicle-bomb incidents have been recorded. This paper focuses on the case of truck-bombs, which can either be created from scratch, or terrorists can easily hijack truck cargos carrying dangerous goods and turn them into bombs. The latter are typically called ADR truck cargos, according to the respective agreement of the 30th of September 1957, concerning the international carriage of dangerous goods by road. The proposed scheme performs threat assessment of neighboring critical infrastructures, aiming at preventing explosions of truck-bombs. To do so, each crucial point of a critical infrastructure is initially associated with a level of importance. Next, three scenarios are analyzed: (a) single-attack single-infrastructure, (b) multiple-attack single-infrastructure, and (c) multiple-attack multiple-infrastructure. To reduce computational complexity, the third scenario is simplified to one of the two other scenarios, by introducing a novel fusion technique for the non-overlapping segments of the Voronoi tessellation. By this way, an area of threat assessment is estimated for each critical infrastructure. Then, the threat level is assessed in real time by an innovative algorithm, which: (a) estimates the impact of multiple consecutive explosions, (b) uses five adapted threat levels and (c) introduces multiple criteria and minimum classification conditions based on the number of crucial points and their levels of importance. Extensive real world experimental results and comparisons to other works, exhibit the pros and cons of the proposed scheme. In particular the proposed scheme improves: (a) computational time by 74.5%, compared to [69], (b) threat notification time by 86.9% compared to [70] and (c) estimated surveillance cost by 98.6% compared to [71].

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Section: Related Workmentioning

confidence: 99%

Real Time Threat Assessment of Truck Cargos Carrying Dangerous Goods for Preventing Terrorism Attacks on Neighboring Critical Infrastructures

2022

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“…However, it is impossible to achieve a homogeneous power consumption among wireless nodes in a pipeline network due to its unique architecture [5]. The two major WSN drawbacks in a pipeline network are; (1) independent node energy optimisation and (2) network lifetime [1,[9][10][11][12].…”

Section: Factors Affecting the Power Consumption In A Pipeline Networkmentioning

confidence: 99%

“…The authors in [1] highlighted network lifetime as a critical factor that is influenced by limited energy source, particularly in a large WSN implementation. The research has investigated on node placement and the relative elements on network lifetime especially in WSN clusters.…”

Section: Literature Review On Wsn Energy Modelmentioning

confidence: 99%

“…The wireless sensor network (WSN) is an accessible technology and has been a popular option for remote monitoring application such as in agriculture, industrial shopfloor, oil and gas industry [1,2]. The adoption and deployment of WSN for remote monitoring is performance driven in the oil and gas industry particularly on pipelines.…”

Section: Introduction To Wsn Energy Modelmentioning

confidence: 99%

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Active High Transmitter-receiver energy model for heterogeneous energy optimisation in a pipeline network

Subramaniam

Feroz

Ibrahim

et al. 2022

J. Phys.: Conf. Ser.

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A network energy management and optimisation are frequently associated to the network lifetime (maximum operation of nodes in a network) that is contributed by heterogeneous energy consumption pattern among nodes arranged in a pipeline layout. This scenario becomes even more critical in a remote monitoring application of an oil and gas pipeline network where a series of sensing points (commonly battery powered wireless nodes) are needed to communicate the measurements to a centralised monitoring station. This paper introduces the Active High Transmitter-receiver energy model (AHiT) which was designed as an adaptive sleep/wake for sensor nodes to optimise energy consumption in the long run. Implementing AHiT energy model on sensor nodes improves the energy consumption based on data transfer activity in a multi-hop pipeline layout wireless sensor network (WSN). In this research, the proposed AHiT energy model optimises node energy by the demand that is unlike to the conventional sleep and wake energy model that is operated on a predefined scheduling scheme that accommodates the data traffic pattern in a network. Generally, in a pipeline network where sensor nodes connectivity is considered critical among neighbouring nodes to support data transfer from one end to the other end of a network. Simulations results in NS2 has indicated node energy consumption is approximately 60% with extended network lifetime around 30% subjected to the data traffic pattern as compared to the conventional energy model.

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“…In SIL-IoTs, the deployment of SIL nodes is one of the fundamental problems, which has a direct impact on the effectiveness of routing [7]- [9] and data fusion [10], [11] operations as well as on the accuracy of anticipated coverage in several agricultural scenarios [12], e.g., mono-crop and mixedcrop farmlands. Generally, the coverage can be classified into three groups: 1) barrier coverage, 2) target coverage and 3) area coverage [13].…”

Section: Introductionmentioning

confidence: 99%

Optimal Deployment of Solar Insecticidal Lamps Over Constrained Locations in Mixed-Crop Farmlands

Yang

Shu

Yang

et al. 2021

IEEE Internet Things J.

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Solar Insecticidal Lamps (SILs) play a vital role in green prevention and control of pests. By embedding SILs in Wireless Sensor Networks (WSNs), we establish a novel agricultural Internet of Things (IoT), referred to as the SIL-IoTs. In practice, the deployment of SIL nodes is determined by the geographical characteristics of an actual farmland, the constraints on the locations of SIL nodes, and the radio-wave propagation in complex agricultural environment. In this paper, we mainly focus on the constrained SIL Deployment Problem (cSILDP) in a mixed-crop farmland, where the locations used to deploy SIL nodes are a limited set of candidates located on the ridges. We formulate the cSILDP in this scenario as a Connected Set Cover (CSC) problem, and propose a Hole Aware Node Deployment Method (HANDM) based on the greedy algorithm to solve the constrained optimization problem. The HANDM is a two-phase method. In the first phase, a novel deployment strategy is utilised to guarantee only a single coverage hole in each iteration, based on which a set of suboptimal locations is found for the deployment of SIL nodes. In the second phase, according to the operations of deletion and fusion, the optimal locations are obtained to meet the requirements on complete coverage and connectivity. Experimental results show that our proposed method achieves better performance than the peer algorithms, specifically in terms of deployment cost. Index Terms-Solar insecticidal lamp -internet of things (SIL-IoTs), constrained SIL deployment problem (cSILDP), connected set cover (CSC) problem, approximation algorithm, wireless sensor network (WSN), path loss model, mixed-crop farmland.

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Impact of Node Deployment and Routing for Protection of Critical Infrastructures

Cited by 9 publications

References 40 publications

Real Time Threat Assessment of Truck Cargos Carrying Dangerous Goods for Preventing Terrorism Attacks on Neighboring Critical Infrastructures

Real Time Threat Assessment of Truck Cargos Carrying Dangerous Goods for Preventing Terrorism Attacks on Neighboring Critical Infrastructures

Active High Transmitter-receiver energy model for heterogeneous energy optimisation in a pipeline network

Optimal Deployment of Solar Insecticidal Lamps Over Constrained Locations in Mixed-Crop Farmlands

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