  We present a bulk data collection service, Harvest, for energy constrained
wireless sensor nodes. To increase spatial reuse and thereby decrease latency,
Harvest performs concurrent, pipelined exfiltration from multiple nodes to a
base station. To this end, it uses a distance-k coloring of the nodes, notably
with a constant number of colors, which yields a TDMA schedule whereby nodes
can communicate concurrently with low packet losses due to collision. This
coloring is based on a randomized CSMA approach which does not exploit location
knowledge. Given a bounded degree of the network, each node waits only O$(1)$
time to obtain a unique color among its distance-k neighbors, in contrast to
the traditional deterministic distributed distance-k vertex coloring wherein
each node waits O$(\Delta^{2})$ time to obtain a color.
  Harvest offers the option of limiting memory use to only a small constant
number of bytes or of improving latency with increased memory use; it can be
used with or without additional mechanisms for reliability of message
forwarding. We experimentally evaluate the performance of Harvest using 51
motes in the Kansei testbed. We also provide theoretical as well as
TOSSIM-based comparison of Harvest with Straw, an extant data collection
service implemented for TinyOS platforms that use one-node at a time
exfiltration. For networks with more than 3-hops, Harvest reduces the latency
by at least 33% as compared to that of Straw.
