5,045 research outputs found
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
Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks
In this paper, a family of ant colony algorithms called DAACA for data
aggregation has been presented which contains three phases: the initialization,
packet transmission and operations on pheromones. After initialization, each
node estimates the remaining energy and the amount of pheromones to compute the
probabilities used for dynamically selecting the next hop. After certain rounds
of transmissions, the pheromones adjustment is performed periodically, which
combines the advantages of both global and local pheromones adjustment for
evaporating or depositing pheromones. Four different pheromones adjustment
strategies are designed to achieve the global optimal network lifetime, namely
Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data
aggregation algorithms, DAACA shows higher superiority on average degree of
nodes, energy efficiency, prolonging the network lifetime, computation
complexity and success ratio of one hop transmission. At last we analyze the
characteristic of DAACA in the aspects of robustness, fault tolerance and
scalability.Comment: To appear in Journal of Computer and System Science
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