6,020 research outputs found
Physics-Based Swarm Intelligence for Disaster Relief Communications
This study explores how a swarm of aerial mobile vehicles can provide network
connectivity and meet the stringent requirements of public protection and
disaster relief operations. In this context, we design a physics-based
controlled mobility strategy, which we name the extended Virtual Force Protocol
(VFPe), allowing self-propelled nodes, and in particular here unmanned aerial
vehicles, to fly autonomously and cooperatively. In this way, ground devices
scattered on the operation site may establish communications through the
wireless multi-hop communication routes formed by the network of aerial nodes.
We further investigate through simulations the behavior of the VFPe protocol,
notably focusing on the way node location information is disseminated into the
network as well as on the impact of the number of exploration nodes on the
overall network performance.Comment: in International Conference on Ad Hoc Networks and Wireless, Jul
2016, Lille, Franc
Collaborative signal and information processing for target detection with heterogeneous sensor networks
In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
Pheromone-based In-Network Processing for wireless sensor network monitoring systems
Monitoring spatio-temporal continuous fields using wireless sensor networks (WSNs) has emerged as a novel solution. An efficient data-driven routing mechanism for sensor querying and information gathering in large-scale WSNs is a challenging problem. In particular, we consider the case of how to query the sensor network information with the minimum energy cost in scenarios where a small subset of sensor nodes has relevant readings. In order to deal with this problem, we propose a Pheromone-based In-Network Processing (PhINP) mechanism. The proposal takes advantages of both a pheromone-based iterative strategy to direct queries towards nodes with relevant information and query- and response-based in-network filtering to reduce the number of active nodes. Additionally, we apply reinforcement learning to improve the performance. The main contribution of this work is the proposal of a simple and efficient mechanism for information discovery and gathering. It can reduce the messages exchanged in the network, by allowing some error, in order to maximize the network lifetime. We demonstrate by extensive simulations that using PhINP mechanism the query dissemination cost can be reduced by approximately 60% over flooding, with an error below 1%, applying the same in-network filtering strategy.Fil: Riva, Guillermo Gaston. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas, FĂsicas y Naturales; Argentina. Universidad TecnolĂłgica Nacional; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba; ArgentinaFil: Finochietto, Jorge Manuel. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba. Instituto de Estudios Avanzados en IngenierĂa y TecnologĂa. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas FĂsicas y Naturales. Instituto de Estudios Avanzados en IngenierĂa y TecnologĂa; Argentin
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
The Deployment in the Wireless Sensor Networks: Methodologies, Recent Works and Applications
International audienceThe wireless sensor networks (WSN) is a research area in continuous evolution with a variety of application contexts. Wireless sensor networks pose many optimization problems, particularly because sensors have limited capacity in terms of energy, processing and memory. The deployment of sensor nodes is a critical phase that significantly affects the functioning and performance of the network. Often, the sensors constituting the network cannot be accurately positioned, and are scattered erratically. To compensate the randomness character of their placement, a large number of sensors is typically deployed, which also helps to increase the fault tolerance of the network. In this paper, we are interested in studying the positioning and placement of sensor nodes in a WSN. First, we introduce the problem of deployment and then we present the latest research works about the different proposed methods to solve this problem. Finally, we mention some similar issues related to the deployment and some of its interesting applications
Balancing the trade-off between cost and reliability for wireless sensor networks: a multi-objective optimized deployment method
The deployment of the sensor nodes (SNs) always plays a decisive role in the
system performance of wireless sensor networks (WSNs). In this work, we propose
an optimal deployment method for practical heterogeneous WSNs which gives a
deep insight into the trade-off between the reliability and deployment cost.
Specifically, this work aims to provide the optimal deployment of SNs to
maximize the coverage degree and connection degree, and meanwhile minimize the
overall deployment cost. In addition, this work fully considers the
heterogeneity of SNs (i.e. differentiated sensing range and deployment cost)
and three-dimensional (3-D) deployment scenarios. This is a multi-objective
optimization problem, non-convex, multimodal and NP-hard. To solve it, we
develop a novel swarm-based multi-objective optimization algorithm, known as
the competitive multi-objective marine predators algorithm (CMOMPA) whose
performance is verified by comprehensive comparative experiments with ten other
stateof-the-art multi-objective optimization algorithms. The computational
results demonstrate that CMOMPA is superior to others in terms of convergence
and accuracy and shows excellent performance on multimodal multiobjective
optimization problems. Sufficient simulations are also conducted to evaluate
the effectiveness of the CMOMPA based optimal SNs deployment method. The
results show that the optimized deployment can balance the trade-off among
deployment cost, sensing reliability and network reliability. The source code
is available on https://github.com/iNet-WZU/CMOMPA.Comment: 25 page
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