4,688 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
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
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
Multihop clustering algorithm for load balancing in wireless sensor networks
The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach
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
A Scale-Free Topology Construction Model for Wireless Sensor Networks
A local-area and energy-efficient (LAEE) evolution model for wireless sensor
networks is proposed. The process of topology evolution is divided into two
phases. In the first phase, nodes are distributed randomly in a fixed region.
In the second phase, according to the spatial structure of wireless sensor
networks, topology evolution starts from the sink, grows with an
energy-efficient preferential attachment rule in the new node's local-area, and
stops until all nodes are connected into network. Both analysis and simulation
results show that the degree distribution of LAEE follows the power law. This
topology construction model has better tolerance against energy depletion or
random failure than other non-scale-free WSN topologies.Comment: 13pages, 3 figure
Sidelobe Control in Collaborative Beamforming via Node Selection
Collaborative beamforming (CB) is a power efficient method for data
communications in wireless sensor networks (WSNs) which aims at increasing the
transmission range in the network by radiating the power from a cluster of
sensor nodes in the directions of the intended base station(s) or access
point(s) (BSs/APs). The CB average beampattern expresses a deterministic
behavior and can be used for characterizing/controling the transmission at
intended direction(s), since the mainlobe of the CB beampattern is independent
on the particular random node locations. However, the CB for a cluster formed
by a limited number of collaborative nodes results in a sample beampattern with
sidelobes that severely depend on the particular node locations. High level
sidelobes can cause unacceptable interference when they occur at directions of
unintended BSs/APs. Therefore, sidelobe control in CB has a potential to
increase the network capacity and wireless channel availability by decreasing
the interference. Traditional sidelobe control techniques are proposed for
centralized antenna arrays and, therefore, are not suitable for WSNs. In this
paper, we show that distributed, scalable, and low-complexity sidelobe control
techniques suitable for CB in WSNs can be developed based on node selection
technique which make use of the randomness of the node locations. A node
selection algorithm with low-rate feedback is developed to search over
different node combinations. The performance of the proposed algorithm is
analyzed in terms of the average number of trials required to select the
collaborative nodes and the resulting interference. Our simulation results
approve the theoretical analysis and show that the interference is
significantly reduced when node selection is used with CB.Comment: 30 pages, 10 figures, submitted to the IEEE Trans. Signal Processin
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