A Sensor Network for Real-Time Volcano Tomography: System Design and Deployment

Phillips, Dennis E.; Moazzami, Mohammad-Mahdi; Xing, Guoliang; Lees, Jonathan M.

doi:10.1109/icccn.2017.8038445

Cited by 10 publications

(5 citation statements)

References 17 publications

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“…The reason is that, in the proposed approach, the biggest chance is selected as the nearest uncongested sink node. As can be seen from Figures 5,6,7, and 8, the highest number of sink capacity violations are belonged to LEACH, SEP, and fuzzy method, respectively, while the proposed approach has no sink capacity violation.…”

Section: Simulation Resultsmentioning

confidence: 94%

“…Wireless sensor networks (WSNs) are one of the most applicable and widely used energy-constrained wireless networks. WSNs have numerous usages in the real world such as checking the vital signs of the patients in the body area networks in medical applications, 1,2 monitoring the movements of enemy soldiers in battlefields in military applications, 3,4 examining earth signals for detecting earthquakes, volcanic eruptions, geographical, and biological applications, 5,6 and sensing the sound, pressure, temperature, and motion in engineering applications. 7,8 WSNs are invented by integrating the latest technological advances in networking, micro-electronics circuits, and communications concepts.…”

Section: Introductionmentioning

confidence: 99%

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Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Shahidinejad

Barshandeh

2020

Int J Communication

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Summary Applying multiple sink nodes in a large‐scale wireless sensor networks (WSN) can increase the scalability and lifetime of the network. The current sink selection mechanisms assume an unlimited amount of buffer and bandwidth for the sink nodes. This can be problematic in real‐world applications, especially when many cluster heads select a specific sink node and send their data to the sink at the same time. In this situation, the sink node may not have enough buffer to receive and process data; consequently, some packets are dropped. To mitigate these occasions, a fuzzy‐based controller with reduced rules is proposed for sink selection by considering the capacity of the sink nodes. The capacity of the sink nodes is estimated using the long short‐term memory (LSTM) technique. Then another fuzzy‐based controller with reduced rules is designed to select the cluster head. The fuzzy rules are reduced by employing R‐implications method. Reducing the number of fuzzy rules decreases the complexity of the fuzzy controllers. The results show the efficiency of the proposed sink selection and clustering techniques in terms of consumed energy, remaining energy, first node dead (FND), half nodes dead (HND), last node dead (LND), packet loss, and delay.

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Section: Simulation Resultsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Shahidinejad

Barshandeh

2020

Int J Communication

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“…The transmission latency is required to be around or under 1 , to prevent oscillations and reaction coupling [52]. We employ Tmote Sky motes for this experiment, which are popular and have been used in several prior studies [45].…”

Section: Evaluation Scenarios and Setupsmentioning

confidence: 99%

ProMACs: Progressive and Resynchronizing MACs for Continuous Efficient Authentication of Message Streams

Armknecht

Walther

Tsudik

et al. 2020

Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security

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Efficiently integrity verification of received data requires Message Authentication Code (MAC) tags. However, while security calls for rather long tags, in many scenarios this contradicts other requirements. Examples are strict delay requirements (e.g., robot or drone control) or resource-scarce settings (e.g., LoRaWAN networks with limited battery capacity). Prior techniques suggested truncation of MAC tags, thus trading off linear performance gain for exponential security loss. To achieve security of full-length MACs with short(er) tags, we introduce Progressive MACs (ProMACs)-a scheme that uses internal state to gradually increase security upon reception of subsequent messages. We provide a formal framework and propose a provably secure, generic construction called Whips. We evaluate applicability of ProMACs in several realistic scenarios and demonstrate example settings where ProMACs can be used as a drop-in replacement for traditional MACs. CCS CONCEPTS • Security and privacy → Hash functions and message authentication codes; Formal security models; Domain-specific security and privacy architectures; • Theory of computation → Cryptographic primitives.

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“…In recent years sensor networks have been deployed to tackle some of the most fundamental problems facing human beings such as disaster warnings, climate change, and renewable energy. These emerging scientific applications include underwater or ocean sensor networks [9,22,28,35,43,60], wind and solar harvesting [34,40], seismic sensor networks [42,55], and monitoring of volcano eruption and glacial melting [18,47]. One common characteristic of these applications is that they are all deployed in challenging environments such as in remote or inhospitable regions, or under extreme weather, to continuously collect large volumes of data for a long period of time.…”

Section: Introductionmentioning

confidence: 99%

DAO2: Overcoming Overall Storage Overflow inIntermittently Connected Sensor Networks

Tang¹

2022

Preprint

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Many emerging sensor network applications operate in challenging environments wherein the base station is not available. Data generated from such intermittently connected sensor networks (ICSNs) therefore must be stored inside the network for some unpredictable period of time before uploading opportunities become available. Consequently, sensory data could overflow the limited storage capacity available in the entire network, making discarding valuable data inevitable. To overcome such overall storage overflow in ICSNs, we propose and study a new algorithmic framework called data aggregation for overall storage overflow (DAO2). Utilizing spatial data correlation that commonly exists among sensory data, DAO2 employs data aggregation techniques to reduce the overflow data size while minimizing the total energy consumption in data aggregation. At the core of our framework are two new graph theoretical problems that have not been studied. We refer to them as traveling salesmen placement problem (TSP2) and quota traveling salesmen placement problem (Q-TSP2). Different from the well-known multiple traveling salesman problem (mTSP) and its variants, which mainly focus on the routing of multiple salesmen initially located at fixed locations, TSP2 and Q-TSP2 must decide the placement as well as the routing of the traveling salesmen. We prove that both problems are NP-hard and design approximation, heuristic, and distributed algorithms. Our algorithms outperform the state-of-the-art data aggregation work with base stations by up to 71.8% in terms of energy consumption. The building blocks of our framework are two novel graph structures called aggregation network and minimum q-edge forest that accurately capture the information needed for energy-efficient data aggregation in ICSNs.

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A Sensor Network for Real-Time Volcano Tomography: System Design and Deployment

Cited by 10 publications

References 17 publications

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

Sink selection and clustering using fuzzy‐based controller for wireless sensor networks

ProMACs: Progressive and Resynchronizing MACs for Continuous Efficient Authentication of Message Streams

DAO2: Overcoming Overall Storage Overflow inIntermittently Connected Sensor Networks

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