Natural Disaster Monitoring with Wireless Sensor Networks: A Case Study of Data-intensive Applications upon Low-Cost Scalable Systems

Chen, Dan; Liu, Zhixin; Wang, Lizhe; Dou, Maowei; Chen, Jingying; Li, Hui

doi:10.1007/s11036-013-0456-9

Cited by 174 publications

(79 citation statements)

References 37 publications

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“…(4) Delay of data aggregation: this challenge is crucial in many WSN applications [24], particularly when dealing with critical data that should be received without any delay. Examples of these data are heart pulses and electrocardiograms of patients [25], disaster detection alarms [26] and power supply requests in smart grids [27]. (5) Interference and fading: wireless devices mostly operate on license-free bands such as 2.4 GHz ISM band [28].…”

Section: Wireless Sensor Network Challengesmentioning

confidence: 99%

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The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

et al. 2018

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Prior studies in Wireless Sensor Network (WSN) optimization mostly concentrate on maximizing network coverage and minimizing network energy consumption. However, there are other factors that could affect the WSN Quality of Service (QoS). In this paper, four objective functions that affect WSN QoS, namely end-to-end delay, end-to-end latency, network throughput and energy efficiency are studied. Optimal value of packet payload size that is able to minimize the end-to-end delay and end-to-end latency, while also maximizing the network throughput and energy efficiency is sought. To do this, a smart grid application case study together with a WSN QoS model is used to find the optimal value of the packet payload size. Our proposed method, named Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP), along with other three state-of-the-art multi-objective optimization algorithms known as OMOPSO, NSGA-II and SPEA2, are utilized in this study. Different packet payload sizes are supplied to the algorithms and their optimal value is derived. From the experiments, the knee point and the intersection point of all the obtained Pareto fronts for all the algorithms show that the optimal packet payload size that manages the trade-offs between the four objective functions is equal to 45 bytes. The results also show that the performance of our proposed MOSFP method is highly competitive and found to have the best average value compared to the other three algorithms. Furthermore, the overall performance of MOSFP on four objective functions outperformed OMOPSO, NSGA-II and SPEA2 by 3%, 6% and 51%, respectively.

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Section: Wireless Sensor Network Challengesmentioning

confidence: 99%

“…Examples of these data are heart pulses and electrocardiograms of patients [25], disaster detection alarms [26] and power supply requests in smart grids [27]. (5) Interference and fading: wireless devices mostly operate on license-free bands such as 2.4 GHz ISM band [28].…”

Section: Network Modelingmentioning

confidence: 99%

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

et al. 2018

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“…(iii) Case III: Congestion Control and Prediction (Section 4.3). Similar to the second case, but with an additional weight (AW), here, we defined link score (LS) as a path selection criterion over EW and AW, as shown in (8). Here, is a weighted constant for determining a relationship between these two factors, which ranges between 0 and 1:…”

Section: Path Determinationmentioning

confidence: 99%

Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks

Aimtongkham

Nguyen

So-In

2018

Wireless Communications and Mobile Computing

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Network congestion is a key challenge in resource-constrained networks, particularly those with limited bandwidth to accommodate high-volume data transmission, which causes unfavorable quality of service, including effects such as packet loss and low throughput. This challenge is crucial in wireless sensor networks (WSNs) with restrictions and constraints, including limited computing power, memory, and transmission due to self-contained batteries, which limit sensor node lifetime. Determining a path to avoid congested routes can prolong the network. Thus, we present a path determination architecture for WSNs that takes congestion into account. The architecture is divided into 3 stages, excluding the final criteria for path determination: (1) initial path construction in a top-down hierarchical structure, (2) path derivation with energy-aware assisted routing, and (3) congestion prediction using exponential smoothing. With several factors, such as hop count, remaining energy, buffer occupancy, and forwarding rate, we apply fuzzy logic systems to determine proper weights among those factors in addition to optimizing the weight over the membership functions using a bat algorithm. The simulation results indicate the superior performance of the proposed method in terms of high throughput, low packet loss, balancing the overall energy consumption, and prolonging the network lifetime compared to state-of-the-art protocols.

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“…On the other hand, the energy consumed by communication should be minimized. In other words, the management of mobile nodes or dynamic routing based on redundant paths must ensure event transmission with low network maintenance costs [97] . Towards this approach, Miyazaki et al [26] proposed a WSN, denoted as diehard sensor network that provides continuous monitoring without any maintenance even if some sensor nodes fail.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

Survey on Simulation for Mobile Ad-Hoc Communication for Disaster Scenarios

Rosas

Hidalgo

Gil-Costa

et al. 2016

J. Comput. Sci. Technol.

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Natural Disaster Monitoring with Wireless Sensor Networks: A Case Study of Data-intensive Applications upon Low-Cost Scalable Systems

Cited by 174 publications

References 37 publications

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks

Survey on Simulation for Mobile Ad-Hoc Communication for Disaster Scenarios

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