3,234 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
Lifetime Improvement in Wireless Sensor Networks via Collaborative Beamforming and Cooperative Transmission
Collaborative beamforming (CB) and cooperative transmission (CT) have
recently emerged as communication techniques that can make effective use of
collaborative/cooperative nodes to create a virtual
multiple-input/multiple-output (MIMO) system. Extending the lifetime of
networks composed of battery-operated nodes is a key issue in the design and
operation of wireless sensor networks. This paper considers the effects on
network lifetime of allowing closely located nodes to use CB/CT to reduce the
load or even to avoid packet-forwarding requests to nodes that have critical
battery life. First, the effectiveness of CB/CT in improving the signal
strength at a faraway destination using energy in nearby nodes is studied.
Then, the performance improvement obtained by this technique is analyzed for a
special 2D disk case. Further, for general networks in which
information-generation rates are fixed, a new routing problem is formulated as
a linear programming problem, while for other general networks, the cost for
routing is dynamically adjusted according to the amount of energy remaining and
the effectiveness of CB/CT. From the analysis and the simulation results, it is
seen that the proposed method can reduce the payloads of energy-depleting nodes
by about 90% in the special case network considered and improve the lifetimes
of general networks by about 10%, compared with existing techniques.Comment: Invited paper to appear in the IEE Proceedings: Microwaves, Antennas
and Propagation, Special Issue on Antenna Systems and Propagation for Future
Wireless Communication
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
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
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
Guest Editorial: Nonlinear Optimization of Communication Systems
Linear programming and other classical optimization techniques have found important applications in communication systems for many decades. Recently, there has been a surge in research activities that utilize the latest developments in nonlinear optimization to tackle a much wider scope of work in the analysis and design of communication systems. These activities involve every “layer” of the protocol stack and the principles of layered network architecture itself, and have made intellectual and practical impacts significantly beyond the established frameworks of optimization of communication systems in the early 1990s. These recent results are driven by new demands in the areas of communications and networking, as well as new tools emerging from optimization theory. Such tools include the powerful theories and highly efficient computational algorithms for nonlinear convex optimization, together with global solution methods and relaxation techniques for nonconvex optimization
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