scholarly journals Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2458
Author(s):  
Paula Verde ◽  
Javier Díez-González ◽  
Rubén Ferrero-Guillén ◽  
Alberto Martínez-Gutiérrez ◽  
Hilde Perez
Keyword(s):  
Autonomous Navigation ◽  
Large Scale ◽  
Ad Hoc ◽  
Indoor Localization ◽  
Memetic Algorithms ◽  
Variable Neighborhood Descent ◽  
Positioning Systems ◽  
Node Location ◽  
Urban Scenario ◽  
Design Requirements

Local Positioning Systems (LPS) have become an active field of research in the last few years. Their application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization, or low-level flights in restricted environments. LPS consists of ad-hoc deployments of sensors which meets the design requirements of each activity. Among LPS, those based on temporal measurements are attracting higher interest due to their trade-off among accuracy, robustness, availability, and costs. The Time Difference of Arrival (TDOA) is extended in the literature for LPS applications and consequently we perform, in this paper, an analysis of the optimal sensor deployment of this architecture for achieving practical results. This is known as the Node Location Problem (NLP) and has been categorized as NP-Hard. Therefore, heuristic solutions such as Genetic Algorithms (GA) or Memetic Algorithms (MA) have been applied in the literature for the NLP. In this paper, we introduce an adaptation of the so-called MA-Solis Wets-Chains (MA-SW-Chains) for its application in the large-scale discrete discontinuous optimization of the NLP in urban scenarios. Our proposed algorithm MA-Variable Neighborhood Descent-Chains (MA-VND-Chains) outperforms the GA and the MA of previous proposals for the NLP, improving the accuracy achieved by 17% and by 10% respectively for the TDOA architecture in the urban scenario introduced.

scholarly journals Node Distribution Optimization in Positioning Sensor Networks through Memetic Algorithms in Urban Scenarios

2020 ◽  
Vol 2 (1) ◽  
pp. 73
Author(s):  
Paula Verde ◽  
Rubén Ferrero-Guillén ◽  
Rubén Álvarez ◽  
Javier Díez-González ◽  
Hilde Perez
Keyword(s):  
Ad Hoc ◽  
Fitness Function ◽  
Memetic Algorithms ◽  
Complex Problem ◽  
Function Evaluation ◽  
Heuristic Solution ◽  
Positioning Systems ◽  
Node Distribution ◽  
Node Location ◽  
Local Search Strategy

Local Positioning Systems rely on ad-hoc node deployments which fit the environment characteristics in order to reduce system uncertainties. The obtainment of competitive results through these systems requires the solution of the Node Location Problem. This problem has been assigned as NP-Hard; therefore, a heuristic solution is recommended for addressing this complex problem. Genetic Algorithms (GA) have shown an excellent trade-off between diversification and intensification in the literature. However, in Non-Line-of-Sight environments in which there is not continuity in the fitness function evaluation among contiguous solutions, challenges arise for the GA. Consequently, in this paper, we introduce a Memetic Algorithm (MA) with a Local Search strategy for exploring the most different individuals of the population in search of improving the NLP results in urban scenarios for the first time. Results show that the MA proposed outperforms the GA optimization and attains an improvement of 6.51% in accuracy in the scenario proposed.

scholarly journals To investigate the effect of Mobile IP on the performance of VANET through realistic channel conditions.

2015 ◽  
Vol 14 (7) ◽  
pp. 5911-5918
Author(s):  
Komal Sharma
Keyword(s):  
Traffic Safety ◽  
Ad Hoc Network ◽  
Large Scale ◽  
Network Performance ◽  
Ad Hoc ◽  
Mobile Ip ◽  
High Mobility ◽  
Comparative Performance ◽  
Urban Scenario

  Abstract Vehicular Ad hoc Network (VANET) is a specialized Ad hoc Network, which provides safety and comfort for passengers [1]. Due to the specific characteristic of VANET like high mobility and large scale node population [1], providing Quality of Service (QoS) in this type of wireless network is a challenging issue. As a result, we combine Mobile IP and VANET to improve QoS in terms of packet loss and throughput for traffic safety and entertainment applications. Comparative performance evaluation is done in terms of QOS parameters to show the network performance using different traffic types and by varying speed of the vehicles under urban scenario.

scholarly journals Local Wireless Sensor Networks Positioning Reliability Under Sensor Failure

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1426 ◽  
Author(s):  
Javier Díez-González ◽  
Rubén Álvarez ◽  
Natalia Prieto-Fernández ◽  
Hilde Perez
Keyword(s):  
Autonomous Navigation ◽  
Target Location ◽  
Operating Conditions ◽  
Sensor Failure ◽  
Algorithm Optimization ◽  
Convergence Region ◽  
System Availability ◽  
Positioning Systems ◽  
Normal Operating ◽  
Node Location

Local Positioning Systems are collecting high research interest over the last few years. Its accurate application in high-demanded difficult scenarios has revealed its stability and robustness for autonomous navigation. In this paper, we develop a new sensor deployment methodology to guarantee the system availability in case of a sensor failure of a five-node Time Difference of Arrival (TDOA) localization method. We solve the ambiguity of two possible solutions in the four-sensor TDOA problem in each combination of four nodes of the system by maximizing the distance between the two possible solutions in every target possible location. In addition, we perform a Genetic Algorithm Optimization in order to find an optimized node location with a trade-off between the system behavior under failure and its normal operating condition by means of the Cramer Rao Lower Bound derivation in each possible target location. Results show that the optimization considering sensor failure enhances the average values of the convergence region size and the location accuracy by 31% and 22%, respectively, in case of some malfunction sensors regarding to the non-failure optimization, only suffering a reduction in accuracy of less than 5% under normal operating conditions.

scholarly journals Comprehensive Investigation on Principle Component Large-Scale Wi-Fi Indoor Localization

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1678 ◽  
Author(s):  
Ahmed H. Salamah ◽  
Mohamed Tamazin ◽  
Maha A. Sharkas ◽  
Mohamed Khedr ◽  
Mohamed Mahmoud
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Indoor Localization ◽  
Principal Component ◽  
Machine Learning Techniques ◽  
Indoor Environments ◽  
Learning Approaches ◽  
Positioning Systems ◽  
Learning Techniques ◽  
And Performance

The smartphone market is rapidly spreading, coupled with several services and applications. Some of these services require the knowledge of the exact location of their handsets. The Global Positioning System (GPS) suffers from accuracy deterioration and outages in indoor environments. The Wi-Fi Fingerprinting approach has been widely used in indoor positioning systems. In this paper, Principal Component Analysis (PCA) is utilized to improve the performance and to reduce the computation complexity of the Wi-Fi indoor localization systems based on a machine learning approach. The experimental setup and performance of the proposed method were tested in real indoor environments at a large-scale environment of 960 m2 to analyze the performance of different machine learning approaches. The results show that the performance of the proposed method outperforms conventional indoor localization techniques based on machine learning techniques.

Designing a New Scalable Autoconfiguration Protocol with Optimal Header Selection for Large Scale MANETs

2019 ◽  
Vol 29 (05) ◽  
pp. 2050068
Author(s):  
Rajula Angelin Samuel ◽  
D. Shalini Punithavathani
Keyword(s):  
Large Scale ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Cluster Head ◽  
Mobile Node ◽  
Communication Overhead ◽  
Gray Wolf ◽  
Wired Networks ◽  
Node Location ◽  
Group Members

Autoconfiguration in mobile ad hoc network (MANET) is a challenging task to be accomplished in hostile environment. Moreover, a mobile node in MANET is usually configured with a unique IP address for providing better communication and to connect it with an IP network. Essentially, the nodes in wired networks are autoconfigured using a commonly known Dynamic Host Configuration Protocol (DHCP) server. However, MANET exhibits the intrinsic characteristics (i.e., distributed, dynamic and multi-hop) in nature; hence, it is hard to adopt DHCP server for autoconfiguration of nodes in MANET without applying significant modifications in auto-configuration scheme. This paper proposes an efficient IPV6 Duplicate address Elimination Autoconfiguration protocol for MANETs (IDEAM) which comprises the member and the cluster head (CH) nodes organized in a hierarchical fashion. Further, the proposed protocol considers the global connectivity exhibiting reduced communication overhead among the nodes. Initially, our proposed auto-configuration protocol encourages the Duplicate Address Detection (DAD) operation by selecting a controller node from the prefixed group members using a joining node in the network. In other words, the DAD operation is performed perfectly by a selected controller node on behalf of the new joining node. Thus, our proposed protocol becomes more effective and behaves better in the minimization of overhead by considerably eliminating the DAD messages broadcast in the network. Also, we imposed a new Flower pollination based gray wolf optimization (FPGWO) algorithm for selecting an optimal header among the group members by considering various node parameters (i.e., node location, resources and node density) to avoid unnecessary broadcasting of additional weight messages about each node in the network. The simulation results proved the efficiency of our proposed protocol in terms of scalability and in the minimization of overhead. Also, an effectual method provided by our proposed approach enhances the activity of marginal nodes over the group for healing the network that degrades its performance followed by the splitting and merging operation.

scholarly journals LMD-TShip*: Vision Based Large-Scale Maritime Ship Tracking Benchmark for Autonomous Navigation Applications

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Yunxiao Shan ◽  
Shanghua Liu ◽  
Yunfei Zhang ◽  
Min Jing ◽  
Huawei Xu
Keyword(s):  
Autonomous Navigation ◽  
Large Scale

scholarly journals Allometric Equations for Estimating Biomass and Carbon Stocks in Afforested Open Woodlands with Black Spruce and Jack Pine, in the Eastern Canadian Boreal Forest

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 59
Author(s):  
Olivier Fradette ◽  
Charles Marty ◽  
Pascal Tremblay ◽  
Daniel Lord ◽  
Jean-François Boucher
Keyword(s):  
Large Scale ◽  
Ad Hoc ◽  
Black Spruce ◽  
Tree Height ◽  
Jack Pine ◽  
Carbon Stocks ◽  
Allometric Equations ◽  
C Stocks ◽  
The Difference ◽  
Canadian Boreal Forest

Allometric equations use easily measurable biometric variables to determine the aboveground and belowground biomasses of trees. Equations produced for estimating the biomass within Canadian forests at a large scale have not yet been validated for eastern Canadian boreal open woodlands (OWs), where trees experience particular environmental conditions. In this study, we harvested 167 trees from seven boreal OWs in Quebec, Canada for biomass and allometric measurements. These data show that Canadian national equations accurately predict the whole aboveground biomass for both black spruce and jack pine trees, but underestimated branches biomass, possibly owing to a particular tree morphology in OWs relative to closed-canopy stands. We therefore developed ad hoc allometric equations based on three power models including diameter at breast height (DBH) alone or in combination with tree height (H) as allometric variables. Our results show that although the inclusion of H in the model yields better fits for most tree compartments in both species, the difference is minor and does not markedly affect biomass C stocks at the stand level. Using these newly developed equations, we found that carbon stocks in afforested OWs varied markedly among sites owing to differences in tree growth and species. Nine years after afforestation, jack pine plantations had accumulated about five times more carbon than black spruce plantations (0.14 vs. 0.80 t C·ha−1), highlighting the much larger potential of jack pine for OW afforestation projects in this environment.

scholarly journals Sensor System: A Survey of Sensor Type, Ad Hoc Network Topology and Energy Harvesting Techniques

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim
Keyword(s):  
Energy Harvesting ◽  
Large Scale ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor System ◽  
Wireless Sensor ◽  
The Internet ◽  
Original Research ◽  
Energy Scavenging ◽  
Term Operation

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.

Current State of (Dis)Integration: Public Health and Fusion Centers

2020 ◽  
Vol 17 (2) ◽  
Author(s):  
Cody Minks ◽  
Anke Richter
Keyword(s):  
Public Health ◽  
Law Enforcement ◽  
Information Sharing ◽  
Homeland Security ◽  
Large Scale ◽  
Ad Hoc ◽  
Limiting Factor ◽  
Fusion Centers ◽  
Public Health Emergencies ◽  
Public Health Information

AbstractObjectiveResponding to large-scale public health emergencies relies heavily on planning and collaboration between law enforcement and public health officials. This study examines the current level of information sharing and integration between these domains by measuring the inclusion of public health in the law enforcement functions of fusion centers.MethodsSurvey of all fusion centers, with a 29.9% response rate.ResultsOnly one of the 23 responding fusion centers had true public health inclusion, a decrease from research conducted in 2007. Information sharing is primarily limited to information flowing out of the fusion center, with little public health information coming in. Most of the collaboration is done on a personal, informal, ad-hoc basis. There remains a large misunderstanding of roles, capabilities, and regulations by all parties (fusion centers and public health). The majority of the parties appear to be willing to work together, but there but there is no forward momentum to make these desires a reality. Funding and staffing issues seem to be the limiting factor for integration.ConclusionThese problems need to be urgently addressed to increase public health preparedness and enable a decisive and beneficial response to public health emergencies involving a homeland security response.

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