  Node localization algorithms that can be easily integrated into deployed
wireless sensor networks (WSNs) and which run seamlessly with proprietary lower
layer communication protocols running on off-the-shelf modules can help
operators of large farms and orchards avoid the difficulty, cost and/or time
involved with manual or satellite-based node localization techniques. Even
though the state-of-the-art node localization algorithms can achieve low error
rates using distributed techniques such as belief propagation (BP), they are
not well suited to WSNs deployed for precision agriculture applications with
large number of nodes, few number of landmarks and lack real time update
capability. The algorithm proposed here is designed for applications such as
pest control and irrigation in large farms and orchards where greater power
efficiency and scalability are required but location accuracy requirements are
less demanding. Our algorithm uses received signal strength indicator (RSSI)
values to estimate the distribution of distance between nodes then updates the
location probability mass function (pmf) of nodes in a distributed manner. At
every time step, the most recently communicated path loss samples and location
prior pmf received from neighbouring nodes is sufficient for nodes with unknown
location to update their location pmf. This renders the algorithm recursive,
hence results in lower computational complexity at each time step. We propose a
particular realization of the method in which only one node multicasts at each
time step and neighbouring nodes update their location pmf conditioned on all
communicated samples over previous time steps. This is highly compatible with
realistic WSN deployments, e.g., ZigBee which are based upon the ad hoc
on-demand distance vector (AODV) where nodes flood route request (RREQ) and
route reply (RREP) packets in the network.
