251 research outputs found
A Hybrid Metaheuristic Algorithm for Stop Point Selection in Wireless Rechargeable Sensor Network
A wireless rechargeable sensor network (WRSN) enables charging of rechargeable sensor nodes (RSN) wirelessly through a mobile charging vehicle (MCV). Most existing works choose the MCV’s stop point (SP) at random, the cluster’s center, or the cluster head position, all without exploring the demand from RSNs. It results in a long charging delay, a low charging throughput, frequent MCV trips, and more dead nodes. To overcome these issues, this paper proposes a hybrid metaheuristic algorithm for stop point selection (HMA-SPS) that combines the techniques of the dragonfly algorithm (DA), firefly algorithm (FA), and gray wolf optimization (GWO) algorithms. Using FA and GWO techniques, DA predicts an ideal SP using the run-time metrics of RSNs, such as energy, delay, distance, and trust factors. The simulated results demonstrate faster convergence with low delay and highlight that more RSNs can be recharged with fewer MCV visits, further enhancing energy utilization, throughput, network lifetime, and trust factor
Solar energy harvesting and software enhancements for autonomous wireless smart sensor networks
Civil infrastructure is the backbone of modern society, and maintaining said infrastructure is critical in maintaining healthy society. Wireless smart sensors (WSSs) provide a means to effectively monitor the performance of buildings and bridges to improve maintenance practices, minimize the costs of repair, and improve public safety through a process called structural health monitoring (SHM). WSSs, traditionally powered by batteries, are limited in the length of time they can operate autonomously. The frequent need to change batteries in the networks can drive up maintenance costs and diminish the advantage first realized with WSSs. Efforts have been made to minimize the power consumption of WSSs operating in SHM networks, but there have been a limited number of new power supply options, such as energy harvesting, used in full-scale SHM applications. This research develops a solar energy harvesting system to provide power to Imote2 WSS platform and increase the long-term autonomy of wireless smart sensor networks (WSSNs). The approach is validated on a cable stayed bridge in South Korea. Additionally, software enhancements are introduced to allow sensor data to be stored in non-volatile memory, potentially further enhancing the efficacy of WSSNs. This research has resulted in greater overall autonomy of WSSNs
Decentralized Multi-Charger Coordination for Wireless Rechargeable Sensor Networks
International audienceWireless charging is a promising technology for provisioning dynamic power supply in wireless rechargeable sensor networks (WRSNs). The charging equipment can be carried by some mobile nodes to enhance the charging flexibility. With such mobile chargers (MCs), the charging process should simultaneously address the MC scheduling, the moving and charging time allocation, while saving the total energy consumption of MCs. However, the efficient solutions that jointly solve those challenges are generally lacking in the literature. First, we investigate the multi-MC coordination problem that minimizing the energy expenditure of MCs while guaranteeing the perpetual operation of WRSNs, and formulate this problem as a mixed-integer linear program (MILP). Second, to solve this problem efficiently, we propose a novel decentralized method which is based on Benders decomposition. The multi-MC coordination problem is then decomposed into a master problem (MP) and a slave problem (SP), with the MP for MC scheduling and the SP for MC moving and charging time allocation. The MP is being solved by the base station (BS), while the SP is further decomposed into several sub-SPs and being solved by the MCs in parallel. The BS and MCs coordinate themselves to decide an optimal charging strategy. The convergence of proposed method is analyzed theoretically. Simulation results demonstrate the effectiveness and scalability of the proposed method
LEVERAGING PEER-TO-PEER ENERGY SHARING FOR RESOURCE OPTIMIZATION IN MOBILE SOCIAL NETWORKS
Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of the another member) for the efficient utilization of scarce energy resources in the network. However, due to uncertain mobility and communication opportunities in the network, resource optimization in these opportunistic networks is very challenging. In this dissertation, we study energy utilization in three different applications in Mobile Social Networks and target to improve the energy efficiency in the network by benefiting from P2P energy sharing among the nodes. More specifi- xi cally, we look at the problems of (i) optimal energy usage and sharing between friendly nodes in order to reduce the burden of wall-based charging, (ii) optimal content and energy sharing when energy is considered as an incentive for carrying the content for other nodes, and (iii) energy balancing among nodes for prolonging the network lifetime. We have proposed various novel protocols for the corresponding applications and have shown that they outperform the state-of-the-art solutions and improve the energy efficiency in MSNs while the application requirements are satisfied
Methods and Tools for Battery-free Wireless Networks
Embedding small wireless sensors into the environment allows for monitoring physical processes with high spatio-temporal resolutions. Today, these devices are equipped with a battery to supply them with power. Despite technological advances, the high maintenance cost and environmental impact of batteries prevent the widespread adoption of wireless sensors. Battery-free devices that store energy harvested from light, vibrations, and other ambient sources in a capacitor promise to overcome the drawbacks of (rechargeable) batteries, such as bulkiness, wear-out and toxicity. Because of low energy input and low storage capacity, battery-free devices operate intermittently; they are forced to remain inactive for most of the time charging their capacitor before being able to operate for a short time. While it is known how to deal with intermittency on a single device, the coordination and communication among groups of multiple battery-free devices remain largely unexplored. For the first time, the present thesis addresses this problem by proposing new methods and tools to investigate and overcome several fundamental challenges
The lipmouse: a labially controlled mouse cursor emulation device for people with special needs
People with disabilities are part of the society. However, simple actions in their daily life, such as using a computer become a challenge. In many cases they need the assistance of another person. Assistive technologies help performing these tasks and help people with special needs to live more independently. In 2010, a collaborative project called "AsTeRICS" (Assistive Technology Rapid Integration and Construction Set) was initiated and partly funded by the European Commission, where 9 international partner organisations worked together to develop a free, open-source, flexible and affordable assistive technology tool.
A mouse cursor emulator controlled through the lips was developed for the AsTeRICS platform. This device was called "Lipmouse" and was intended to provide a way of accessing a computer, tablet or notebook to a person with an impairment in her/his upper limbs. This thesis is a continuation and enhancement of the Lipmouse development.
The improvements accomplished can be summarized in three blocks: The first part of this thesis consisted of the development of a portable version of the Lipmouse. The initial version worked via USB cable. For that purpose, the new version incorporates a Bluetooth module and a battery power supply system. The second part was focused on the design of a PCB where all electronic components of the Lipmouse were integrated. Finally, the Lipmouse source code was enhanced in two ways: The firmware of the Lipmouse was modified for supporting the new functionalities described above. On the other hand, a specific software plugin for the integration of the Lipmouse into the AsTeRICS framework has been developed.IngenierĂa TĂ©cnica de TelecomunicaciĂłn, especialidad Sonido e ImagenTelekomunikazio Ingeniaritza Teknikoa. Soinua eta Irudia Berezitasun
Recent Advances in Multi Robot Systems
To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems
Innovative energy-efficient wireless sensor network applications and MAC sub-layer protocols employing RTS-CTS with packet concatenation
of energy-efficiency as well as the number of available applications. As a consequence there
are challenges that need to be tackled for the future generation of WSNs. The research work
from this Ph.D. thesis has involved the actual development of innovative WSN applications contributing
to different research projects. In the Smart-Clothing project contributions have been
given in the development of a Wireless Body Area Network (WBAN) to monitor the foetal movements
of a pregnant woman in the last four weeks of pregnancy. The creation of an automatic
wireless measurement system for remotely monitoring concrete structures was an contribution
for the INSYSM project. This was accomplished by using an IEEE 802.15.4 network enabling for
remotely monitoring the temperature and humidity within civil engineering structures. In the
framework of the PROENEGY-WSN project contributions have been given in the identification
the spectrum opportunities for Radio Frequency (RF) energy harvesting through power density
measurements from 350 MHz to 3 GHz. The design of the circuits to harvest RF energy
and the requirements needed for creating a WBAN with electromagnetic energy harvesting and
Cognitive Radio (CR) capabilities have also been addressed. A performance evaluation of the
state-of-the art of the hardware WSN platforms has also been addressed. This is explained by
the fact that, even by using optimized Medium Access Control (MAC) protocols, if the WSNs
platforms do not allow for minimizing the energy consumption in the idle and sleeping states,
energy efficiency and long network lifetime will not be achieved.
The research also involved the development of new innovative mechanisms that tries and solves
overhead, one of the fundamental reasons for the IEEE 802.15.4 standard MAC inefficiency. In
particular, this Ph.D. thesis proposes an IEEE 802.15.4 MAC layer performance enhancement by
employing RTS/CTS combined with packet concatenation. The results have shown that the use
of the RTS/CTS mechanism improves channel efficiency by decreasing the deferral time before
transmitting a data packet. In addition, the Sensor Block Acknowledgment MAC (SBACK-MAC)
protocol has been proposed that allows the aggregation of several acknowledgment responses
in one special Block Acknowledgment (BACK) Response packet. Two different solutions are
considered. The first one considers the SBACK-MAC protocol in the presence of BACK Request
(concatenation) while the second one considers the SBACK-MAC in the absence of BACK Request
(piggyback). The proposed solutions address a distributed scenario with single-destination and
single-rate frame aggregation. The throughput and delay performance is mathematically derived
under both ideal conditions (a channel environment with no transmission errors) and non
ideal conditions (a channel environment with transmission errors). An analytical model is proposed,
capable of taking into account the retransmission delays and the maximum number of
backoff stages. The simulation results successfully validate our analytical model. For more
than 7 TX (aggregated packets) all the MAC sub-layer protocols employing RTS/CTS with packet
concatenation allows for the optimization of channel use in WSNs, v8-48 % improvement in the
maximum average throughput and minimum average delay, and decrease energy consumption
Quality-Aware Scheduling Algorithms in Renewable Sensor
Wireless sensor network has emerged as a key technology for various applications
such as environmental sensing, structural health monitoring, and area surveillance.
Energy is by far one of the most critical design hurdles that hinders the deployment
of wireless sensor networks. The lifetime of traditional battery-powered sensor
networks is limited by the capacities of batteries. Even many energy conservation
schemes were proposed to address this constraint, the network lifetime is still inherently
restrained, as the consumed energy cannot be replenished easily. Fully
addressing this issue requires energy to be replenished quite often in sensor networks
(renewable sensor networks). One viable solution to energy shortages is enabling
each sensor to harvest renewable energy from its surroundings such as solar energy,
wind energy, and so on. In comparison with their conventional counterparts, the network
lifetime in renewable sensor networks is no longer a main issue, since sensors
can be recharged repeatedly. This results in a research focus shift from the network
lifetime maximization in traditional sensor networks to the network performance optimization
(e.g., monitoring quality). This thesis focuses on these issues and tackles
important problems in renewable sensor networks as follows.
We first study the target coverage optimization in renewable sensor networks
via sensor duty cycle scheduling, where a renewable sensor network consisting of
a set of heterogeneous sensors and a stationary base station need to be scheduled
to monitor a set of targets in a monitoring area (e.g., some critical facilities) for a
specified period, by transmitting their sensing data to the base station through multihop
relays in a real-time manner. We formulate a coverage maximization problem
in a renewable sensor network which is to schedule sensor activities such that the
monitoring quality is maximized, subject to that the communication network induced
by the activated sensors and the base station at each time moment is connected. We
approach the problem for a given monitoring period by adopting a general strategy.
That is, we divide the entire monitoring period into equal numbers of time slots and perform sensor activation or inactivation scheduling in the beginning of each
time slot. As the problem is NP-hard, we devise efficient offline centralized and
distributed algorithms for it, provided that the amount of harvested energy of each
sensor for a given monitoring period can be predicted accurately. Otherwise, we
propose an online adaptive framework to handle energy prediction fluctuation for
this monitoring period. We conduct extensive experiments, and the experimental
results show that the proposed solutions are very promising.
We then investigate the data collection optimization in renewable sensor networks
by exploiting sink mobility, where a mobile sink travels around the sensing field to
collect data from sensors through one-hop transmission. With one-hop transmission,
each sensor could send data directly to the mobile sink without any relay, and thus no
energy are consumed on forwarding packets for others which is more energy efficient
in comparison with multi-hop relays. Moreover, one-hop transmission particularly is
very useful for a disconnected network, which may be due to the error-prone nature
of wireless communication or the physical limit (e.g., some sensors are physically
isolated), while multi-hop transmission is not applicable. In particular, we investigate
two different kinds of mobile sinks, and formulate optimization problems under
different scenarios, for which both centralized and distributed solutions are proposed
accordingly. We study the performance of the proposed solutions and validate their
effectiveness in improving the data quality.
Since the energy harvested often varies over time, we also consider the scenario of
renewable sensor networks by utilizing wireless energy transfer technology, where a
mobile charging vehicle periodically travels inside the sensing field and charges sensors
without any plugs or wires. Specifically, we propose a novel charging paradigm
and formulate an optimization problem with an objective of maximizing the number
of sensors charged per tour. We devise an offline approximation algorithm which
runs in quasi-polynomial time and develop efficient online sensor charging algorithms,
by considering the dynamic behaviors of sensors’ various sensing and transmission
activities. To study the efficiency of the proposed algorithms, we conduct
extensive experiments and the experimental results demonstrate that the proposed
algorithms are very efficient. We finally conclude our work and discuss potential research topics which derive
from the studies of this thesis
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