222 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
TRASA: TRaffic Aware Slot Assignment Algorithm in Wireless Sensor Networks
International audienceIn data gathering applications which is a typical application paradigm in wireless sensor networks, sensor nodes may have different traffic demands. Assigning equal channel access to each node may lead to congestion, inefficient use of the bandwidth and decrease of the application performance. In this paper, we prove that the time slot assignment problem is NP-complete when p-hop nodes are not assigned the same slot, with 1 <= p <= h for any strictly positive integer h. We propose TRASA, a TRaffic Aware time Slot Assignment algorithm able to allocate slots to sensors proportionally to their demand. We evaluate the performance of TRASA for different heuristics and prove that it provides an optimized spatial reuse and a minimized cycle length
Joint optimization for wireless sensor networks in critical infrastructures
Energy optimization represents one of the main goals in wireless sensor network design
where a typical sensor node has usually operated by making use of the battery with
limited-capacity. In this thesis, the following main problems are addressed: first, the
joint optimization of the energy consumption and the delay for conventional wireless sensor networks is presented. Second, the joint optimization of the information quality and
energy consumption of the wireless sensor networks based structural health monitoring
is outlined. Finally, the multi-objectives optimization of the former problem under several constraints is shown. In the first main problem, the following points are presented:
we introduce a joint multi-objective optimization formulation for both energy and delay
for most sensor nodes in various applications. Then, we present the Karush-Kuhn-Tucker
analysis to demonstrate the optimal solution for each formulation. We introduce a method
of determining the knee on the Pareto front curve, which meets the network designer interest for focusing on more practical solutions. The sensor node placement optimization has
a significant role in wireless sensor networks, especially in structural health monitoring.
In the second main problem of this work, the existing work optimizes the node placement
and routing separately (by performing routing after carrying out the node placement).
However, this approach does not guarantee the optimality of the overall solution. A joint
optimization of sensor placement, routing, and flow assignment is introduced and is solved
using mixed-integer programming modelling. In the third main problem of this study, we
revisit the placement problem in wireless sensor networks of structural health monitoring by using multi-objective optimization. Furthermore, we take into consideration more
constraints that were not taken into account before. This includes the maximum capacity
per link and the node-disjoint routing. Since maximum capacity constraint is essential
to study the data delivery over limited-capacity wireless links, node-disjoint routing is
necessary to achieve load balancing and longer wireless sensor networks lifetime. We list
the results of the previous problems, and then we evaluate the corresponding results
Clustering objectives in wireless sensor networks: A survey and research direction analysis
Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio
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