1 research outputs found
Challenges, Designs, and Performances of a Distributed Algorithm for Minimum-Latency of Data-Aggregation in Multi-Channel WSNs
In wireless sensor networks (WSNs), the sensed data by sensors need to be
gathered, so that one very important application is periodical data collection.
There is much effort which aimed at the data collection scheduling algorithm
development to minimize the latency. Most of previous works investigating the
minimum latency of data collection issue have an ideal assumption that the
network is a centralized system, in which the entire network is completely
synchronized with full knowledge of components. In addition, most of existing
works often assume that any (or no) data in the network are allowed to be
aggregated into one packet and the network models are often treated as tree
structures. However, in practical, WSNs are more likely to be distributed
systems, since each sensor's knowledge is disjointed to each other, and a fixed
number of data are allowed to to be aggregated into one packet. This is a
formidable motivation for us to investigate the problem of minimum latency for
the data aggregation without data collision in the distributed WSNs when the
sensors are considered to be assigned the channels and the data are compressed
with a flexible aggregation ratio, termed the minimum-latency
collision-avoidance multiple-data-aggregation scheduling with multi-channel
(MLCAMDAS-MC) problem. A new distributed algorithm, termed the distributed
collision-avoidance scheduling (DCAS) algorithm, is proposed to address the
MLCAMDAS-MC. Finally, we provide the theoretical analyses of DCAS and conduct
extensive simulations to demonstrate the performance of DCAS.Comment: IEEE Transactions on Network and Service Management (accepted with
minor revisions