scholarly journals Energy and Distance-Aware Hopping Sensor Relocation for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1567 ◽  
Author(s):  
Moonseong Kim ◽  
Sooyeon Park ◽  
Woochan Lee
Keyword(s):  
Shortest Path ◽  
Mobile Sensors ◽  
Wireless Sensor ◽  
Theoretical Studies ◽  
Valuable Data ◽  
The Past ◽  
Topology Information ◽  
Network Technologies ◽  
Big Data Technology ◽  
Sensor Relocation

Recent advances in big data technology collecting and analyzing large amounts of valuable data have attracted a lot of attention. When the information in non-reachable areas is required, IoT wireless sensor network technologies have to be applied. Sensors fundamentally have energy limitations, and it is almost impossible to replace energy-depleted sensors that have been deployed in an inaccessible region. Therefore, moving healthy sensors into the sensing hole will recover the faulty sensor area. In rough surfaces, hopping sensors would be more appropriate than wheel-driven mobile sensors. Sensor relocation algorithms to recover sensing holes have been researched variously in the past. However, the majority of studies to date have been inadequate in reality, since they are nothing but theoretical studies which assume that all the topology in the network is known and then computes the shortest path based on the nonrealistic backing up knowledge—The topology information. In this paper, we first propose a distributed hopping sensor relocation protocol. The possibility of movement of the hopping sensor is also considered to recover sensing holes and is not limited to applying the shortest path strategy. Finally, a performance analysis using OMNeT++ has demonstrated the solidification of the excellence of the proposed protocol.

A Recursive Shortest Path Routing Algorithm With Application for Wireless Sensor Network Localization

2016 ◽  
Vol 16 (11) ◽  
pp. 4631-4637 ◽  
Author(s):  
Juan Cota-Ruiz ◽  
Pablo Rivas-Perea ◽  
Ernesto Sifuentes ◽  
Rafael Gonzalez-Landaeta
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Shortest Path ◽  
Routing Algorithm ◽  
Wireless Sensor ◽  
Sensor Network Localization ◽  
Shortest Path Routing ◽  
Network Localization

Handling Failures of Static Sensor Nodes in Wireless Sensor Network by Use of Mobile Sensors

2011 ◽  
Author(s):  
Edison Pignaton de Freitas ◽  
Tales Heimfarth ◽  
Ivayr Farah Netto ◽  
Carlos Eduardo Pereira ◽  
Armando Morado Ferreira ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Mobile Sensors ◽  
Wireless Sensor

Gradient-Free Optimization in Thermoacoustics: Application to A Low-Order Model

2021 ◽  
Author(s):  
Johann Moritz Reumschüssel ◽  
Jakob G. R. von Saldern ◽  
Yiqing Li ◽  
Christian Oliver Paschereit ◽  
Alessandro Orchini
Keyword(s):  
Optimization Algorithms ◽  
Optimization Methods ◽  
Theoretical Studies ◽  
Order Model ◽  
Output Data ◽  
Fuel Injectors ◽  
Solution Strategies ◽  
The Past ◽  
Downhill Simplex ◽  
Low Order

Abstract Machine learning and automatized routines for parameter optimization have experienced a surge in development in the past years, mostly caused by the increasing availability of computing capacity. Gradient-free optimization can avoid cumbersome theoretical studies as input parameters are purely adapted based on output data. As no knowledge about the objective function is provided to the algorithms, this approach might reveal unconventional solutions to complex problems that were out of scope of classical solution strategies. In this study, the potential of these optimization methods on thermoacoustic problems is examined. The optimization algorithms are applied to a generic low-order thermoacoustic can-combustor model with several fuel injectors at different locations. We use three optimization algorithms — the well established Downhill Simplex Method, the recently proposed Explorative Gradient Method, and an evolutionary algorithm — to find optimal fuel distributions across the fuel lines while maintaining the amount of consumed fuel constant. The objective is to have minimal pulsation amplitudes. We compare the results and efficiency of the gradient-free algorithms. Additionally, we employ model-based linear stability analysis to calculate the growth rates of the dominant thermoacoustic modes. This allows us to highlight general and thermoacoustic-specific features of the optimization methods and results. The findings of this study show the potential of gradient-free optimization methods on combustor design for tackling thermoacoustic problems, and motivate further research in this direction.

scholarly journals AToM: Active topology monitoring for the bitcoin peer-to-peer network

2021 ◽  
Author(s):  
Federico Franzoni ◽  
Xavier Salleras ◽  
Vanesa Daza
Keyword(s):  
Reference Model ◽  
Peer To Peer ◽  
Network Protocol ◽  
P2p Network ◽  
Malicious Nodes ◽  
The Past ◽  
Side Channels ◽  
Peer Network ◽  
Topology Information ◽  
Peer To Peer Network

AbstractOver the past decade, the Bitcoin P2P network protocol has become a reference model for all modern cryptocurrencies. While nodes in this network are known, the connections among them are kept hidden, as it is commonly believed that this helps protect from deanonymization and low-level attacks. However, adversaries can bypass this limitation by inferring connections through side channels. At the same time, the lack of topology information hinders the analysis of the network, which is essential to improve efficiency and security. In this paper, we thoroughly review network-level attacks and empirically show that topology obfuscation is not an effective countermeasure. We then argue that the benefits of an open topology potentially outweigh its risks, and propose a protocol to reliably infer and monitor connections among reachable nodes of the Bitcoin network. We formally analyze our protocol and experimentally evaluate its accuracy in both trusted and untrusted settings. Results show our system has a low impact on the network, and has precision and recall are over 90% with up to 20% of malicious nodes in the network.

scholarly journals Improving the Quality of Service and Privacy by Integrating Dijkstra‟s, SafeQ and Extended Watchdog Algorithm in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 5409-5414
Keyword(s):  
Wireless Sensor Networks ◽  
Quality Of Service ◽  
Sensor Networks ◽  
Shortest Path ◽  
Clustering Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Destination Node ◽  
Hop Count

The fundamental issue is framing the sensor nodes and steering the information from sender node to receiver node in wireless sensor networks (WSN). To resolve this major difficulty, clustering algorithm is one of the accessible methods employed in wireless sensor networks. Still, clustering concept also faces some hurdles while transmitting the data from source to destination node. The sensor node is used to sense the data and the source node helps to convey the information and the intended recipient receives the sensed information. The clustering proposal will choose the cluster head depending on the residual energy and the sensor utility to its cluster members. The cluster heads will have equal cluster number of nodes. The complexity is generated in computing the shortest path and this can be optimized by Dijkstra’s algorithm. The optimization is executed by Dijkstra’s shortest path algorithm that eliminates the delay in packet delivery, energy consumption, lifetime of the packet and hop count while handling the difficulties. The shortest path calculation will improve the quality of service (QoS). QoS is the crucial problem due to loss of energy and resource computation as well as the privacy in wireless sensor networks. The security can be improvised in this projected work. The preventive metrics are discussed to upgrade the QoS facility by civilizing the privacy parameter called as Safe and Efficient Query Processing (SAFEQ) and integrating the extended watchdog algorithm in wireless sensor networks.

A High Density WSN Cluster Positioning Approach

2021 ◽  
Vol 12 (2) ◽  
pp. 1-17
Author(s):  
Qinqing Kang
Keyword(s):  
Large Scale ◽  
Attenuation Factor ◽  
Cluster Head ◽  
High Density ◽  
Wireless Sensor ◽  
Programming Algorithm ◽  
Localization Algorithm ◽  
Network Applications ◽  
Topology Information ◽  
Cluster Location

Node self-positioning is one of the supporting technologies for wireless sensor network applications. In this paper, a clustering localization algorithm is proposed for large-scale high-density wireless sensor networks. Firstly, the potential of the node is defined as the basis for the election of the cluster head. The distance between the nodes in the network is calculated indirectly by the relationship between the received signal strength and the communication radius. The topology information in each cluster is saved by the cluster head, and the linear programming method is used in the cluster head to implement the cluster internal relative positioning. Then, from the sink node, the inter-cluster location fusion is gradually implemented, and finally the absolute positioning of the whole network is realized. Compared with the centralized convex programming algorithm, the proposed algorithm has low computational complexity, small traffic, high positioning accuracy, and does not need to know the signal attenuation factor in the environment in advance, and there is anti-noise ability.

A Genetic Algorithms Approach for Inverse Shortest Path Length Problems

2014 ◽  
Vol 4 (4) ◽  
pp. 36-54 ◽  
Author(s):  
António Leitão ◽  
Adriano Vinhas ◽  
Penousal Machado ◽  
Francisco Câmara Pereira
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Path Length ◽  
Shortest Paths ◽  
Research Subject ◽  
Relevant Research ◽  
Real Cost ◽  
Shortest Path Problems ◽  
The Past ◽  
Specific Outcome

Inverse Combinatorial Optimization has become a relevant research subject over the past decades. In graph theory, the Inverse Shortest Path Length problem becomes relevant when people don't have access to the real cost of the arcs and want to infer their value so that the system has a specific outcome, such as one or more shortest paths between nodes. Several approaches have been proposed to tackle this problem, relying on different methods, and several applications have been suggested. This study explores an innovative evolutionary approach relying on a genetic algorithm. Two scenarios and corresponding representations are presented and experiments are conducted to test how they react to different graph characteristics and parameters. Their behaviour and differences are thoroughly discussed. The outcome supports that evolutionary algorithms may be a viable venue to tackle Inverse Shortest Path problems.

A greedy constructing tree algorithm for shortest path in perpetual wireless recharging wireless sensor network

2019 ◽  
Vol 75 (9) ◽  
pp. 5930-5945 ◽  
Author(s):  
Guolong Chen ◽  
Zhenghua Xin ◽  
Han Li ◽  
Tonghai Zhu ◽  
Maodi Wang ◽  
...  
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Shortest Path ◽  
Wireless Sensor ◽  
Tree Algorithm
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