31,302 research outputs found
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
Analyzing Energy-efficiency and Route-selection of Multi-level Hierarchal Routing Protocols in WSNs
The advent and development in the field of Wireless Sensor Networks (WSNs) in
recent years has seen the growth of extremely small and low-cost sensors that
possess sensing, signal processing and wireless communication capabilities.
These sensors can be expended at a much lower cost and are capable of detecting
conditions such as temperature, sound, security or any other system. A good
protocol design should be able to scale well both in energy heterogeneous and
homogeneous environment, meet the demands of different application scenarios
and guarantee reliability. On this basis, we have compared six different
protocols of different scenarios which are presenting their own schemes of
energy minimizing, clustering and route selection in order to have more
effective communication. This research is motivated to have an insight that
which of the under consideration protocols suit well in which application and
can be a guide-line for the design of a more robust and efficient protocol.
MATLAB simulations are performed to analyze and compare the performance of
LEACH, multi-level hierarchal LEACH and multihop LEACH.Comment: NGWMN with 7th IEEE Inter- national Conference on Broadband and
Wireless Computing, Communication and Applications (BWCCA 2012), Victoria,
Canada, 201
Homology-based Distributed Coverage Hole Detection in Wireless Sensor Networks
Homology theory provides new and powerful solutions to address the coverage
problems in wireless sensor networks (WSNs). They are based on algebraic
objects, such as Cech complex and Rips complex. Cech complex gives accurate
information about coverage quality but requires a precise knowledge of the
relative locations of nodes. This assumption is rather strong and hard to
implement in practical deployments. Rips complex provides an approximation of
Cech complex. It is easier to build and does not require any knowledge of nodes
location. This simplicity is at the expense of accuracy. Rips complex can not
always detect all coverage holes. It is then necessary to evaluate its
accuracy. This work proposes to use the proportion of the area of undiscovered
coverage holes as performance criteria. Investigations show that it depends on
the ratio between communication and sensing radii of a sensor. Closed-form
expressions for lower and upper bounds of the accuracy are also derived. For
those coverage holes which can be discovered by Rips complex, a homology-based
distributed algorithm is proposed to detect them. Simulation results are
consistent with the proposed analytical lower bound, with a maximum difference
of 0.5%. Upper bound performance depends on the ratio of communication and
sensing radii. Simulations also show that the algorithm can localize about 99%
coverage holes in about 99% cases
Giant Magnetoresistive Biosensors for Time-Domain Magnetorelaxometry: A Theoretical Investigation and Progress Toward an Immunoassay.
Magnetorelaxometry (MRX) is a promising new biosensing technique for point-of-care diagnostics. Historically, magnetic sensors have been primarily used to monitor the stray field of magnetic nanoparticles bound to analytes of interest for immunoassays and flow cytometers. In MRX, the magnetic nanoparticles (MNPs) are first magnetized and then the temporal response is monitored after removing the magnetic field. This new sensing modality is insensitive to the magnetic field homogeneity making it more amenable to low-power portable applications. In this work, we systematically investigated time-domain MRX by measuring the signal dependence on the applied field, magnetization time, and magnetic core size. The extracted characteristic times varied for different magnetic MNPs, exhibiting unique magnetic signatures. We also measured the signal contribution based on the MNP location and correlated the coverage with measured signal amplitude. Lastly, we demonstrated, for the first time, a GMR-based time-domain MRX bioassay. This approach validates the feasibility of immunoassays using GMR-based MRX and provides an alternative platform for point-of-care diagnostics
Magnetoresistive biosensors with on-chip pulsed excitation and magnetic correlated double sampling.
Giant magnetoresistive (GMR) sensors have been shown to be among the most sensitive biosensors reported. While high-density and scalable sensor arrays are desirable for achieving multiplex detection, scalability remains challenging because of long data acquisition time using conventional readout methods. In this paper, we present a scalable magnetoresistive biosensor array with an on-chip magnetic field generator and a high-speed data acquisition method. The on-chip field generators enable magnetic correlated double sampling (MCDS) and global chopper stabilization to suppress 1/f noise and offset. A measurement with the proposed system takes only 20 ms, approximately 50× faster than conventional frequency domain analysis. A corresponding time domain temperature correction technique is also presented and shown to be able to remove temperature dependence from the measured signal without extra measurements or reference sensors. Measurements demonstrate detection of magnetic nanoparticles (MNPs) at a signal level as low as 6.92 ppm. The small form factor enables the proposed platform to be portable as well as having high sensitivity and rapid readout, desirable features for next generation diagnostic systems, especially in point-of-care (POC) settings
An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks
Maximizing the lifetime of wireless sensor networks (WSNs) is a challenging problem. Although some methods exist to address the problem in homogeneous WSNs, research on this problem in heterogeneous WSNs have progressed at a slow pace. Inspired by the promising performance of ant colony optimization (ACO) to solve combinatorial problems, this paper proposes an ACO-based approach that can maximize the lifetime of heterogeneous WSNs. The methodology is based on finding the maximum number of disjoint connected covers that satisfy both sensing coverage and network connectivity. A construction graph is designed with each vertex denoting the assignment of a device in a subset. Based on pheromone and heuristic information, the ants seek an optimal path on the construction graph to maximize the number of connected covers. The pheromone serves as a metaphor for the search experiences in building connected covers. The heuristic information is used to reflect the desirability of device assignments. A local search procedure is designed to further improve the search efficiency. The proposed approach has been applied to a variety of heterogeneous WSNs. The results show that the approach is effective and efficient in finding high-quality solutions for maximizing the lifetime of heterogeneous WSNs
- …