5,475 research outputs found
Lifetime Maximization of Monitoring Sensor Networks
We study the problem of maximizing the lifetime of a sensor network assigned to monitor a given area. Our main result is a linear time dual approximation algorithm that comes arbitrarily close to the optimal solution if we additionally allow the sensing ranges to increase by a small factor. The best previous result is superlinear and has a logarithmic approximation ratio. We also provide the first proof of the NP completeness of this specific problem
Distributed Optimal Rate-Reliability-Lifetime Tradeoff in Wireless Sensor Networks
The transmission rate, delivery reliability and network lifetime are three
fundamental but conflicting design objectives in energy-constrained wireless
sensor networks. In this paper, we address the optimal
rate-reliability-lifetime tradeoff with link capacity constraint, reliability
constraint and energy constraint. By introducing the weight parameters, we
combine the objectives at rate, reliability, and lifetime into a single
objective to characterize the tradeoff among them. However, the optimization
formulation of the rate-reliability-reliability tradeoff is neither separable
nor convex. Through a series of transformations, a separable and convex problem
is derived, and an efficient distributed Subgradient Dual Decomposition
algorithm (SDD) is proposed. Numerical examples confirm its convergence. Also,
numerical examples investigate the impact of weight parameters on the rate
utility, reliability utility and network lifetime, which provide a guidance to
properly set the value of weight parameters for a desired performance of WSNs
according to the realistic application's requirements.Comment: 27 pages, 10 figure
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
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
Optimal Compression and Transmission Rate Control for Node-Lifetime Maximization
We consider a system that is composed of an energy constrained sensor node
and a sink node, and devise optimal data compression and transmission policies
with an objective to prolong the lifetime of the sensor node. While applying
compression before transmission reduces the energy consumption of transmitting
the sensed data, blindly applying too much compression may even exceed the cost
of transmitting raw data, thereby losing its purpose. Hence, it is important to
investigate the trade-off between data compression and transmission energy
costs. In this paper, we study the joint optimal compression-transmission
design in three scenarios which differ in terms of the available channel
information at the sensor node, and cover a wide range of practical situations.
We formulate and solve joint optimization problems aiming to maximize the
lifetime of the sensor node whilst satisfying specific delay and bit error rate
(BER) constraints. Our results show that a jointly optimized
compression-transmission policy achieves significantly longer lifetime (90% to
2000%) as compared to optimizing transmission only without compression.
Importantly, this performance advantage is most profound when the delay
constraint is stringent, which demonstrates its suitability for low latency
communication in future wireless networks.Comment: accepted for publication in IEEE Transactions on Wireless
Communicaiton
Lifetime Maximization of Wireless Sensor Networks with a Mobile Source Node
We study the problem of routing in sensor networks where the goal is to
maximize the network's lifetime. Previous work has considered this problem for
fixed-topology networks. Here, we add mobility to the source node, which
requires a new definition of the network lifetime. In particular, we redefine
lifetime to be the time until the source node depletes its energy. When the
mobile node's trajectory is unknown in advance, we formulate three versions of
an optimal control problem aiming at this lifetime maximization. We show that
in all cases, the solution can be reduced to a sequence of Non- Linear
Programming (NLP) problems solved on line as the source node trajectory
evolves.Comment: A shorter version of this work will be published in Proceedings of
2016 IEEE Conference on Decision and Contro
PSA: The Packet Scheduling Algorithm for Wireless Sensor Networks
The main cause of wasted energy consumption in wireless sensor networks is
packet collision. The packet scheduling algorithm is therefore introduced to
solve this problem. Some packet scheduling algorithms can also influence and
delay the data transmitting in the real-time wireless sensor networks. This
paper presents the packet scheduling algorithm (PSA) in order to reduce the
packet congestion in MAC layer leading to reduce the overall of packet
collision in the system The PSA is compared with the simple CSMA/CA and other
approaches using network topology benchmarks in mathematical method. The
performances of our PSA are better than the standard (CSMA/CA). The PSA
produces better throughput than other algorithms. On other hand, the average
delay of PSA is higher than previous works. However, the PSA utilizes the
channel better than all algorithms
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