User's Manual

RK-5424-5 Reference Kit User’s Guide 1-11
MeshScape System Overview
Data Models
The MeshScape system provides built-in support for data movement profiles to speed
development including:
• data collection models
• bi-directional dialogue models
•broadcast models
These data models optimize the network for an application’s specific data requirements and
support a variety of classes for collection and bi-directional dialogue data models.
Data Collection Models
Data collection models describe monitoring applications where the data flows primarily from
the sensor node to the gateway. The MeshScape system supports the data collection models
described in this section.
Periodic Sampling
For applications where certain conditions or processes need to be monitored constantly, such as
the temperature in a conditioned space or pressure in a process pipeline, sensor data is acquired
from a number of remote sensor nodes and forwarded to the gateway or data collection center
on a periodic basis.
The sampling period mainly depends on how fast the condition or process varies and what
intrinsic characteristics need to be captured. In many cases, the dynamics of the condition or
process to be monitored can slow down or speed up from time to time. Therefore, if the sensor
node can adapt its sampling rate to the changing dynamics of the condition or process,
over-sampling can be minimized and power efficiency of the overall network system can be
further improved.
Another critical design issue associated with periodic sampling applications is the phase relation
among multiple sensor nodes. If two sensor nodes operate with identical or similar sampling
rates, collisions between packets from the two nodes is likely to happen repeatedly. It is
essential that sensor nodes can detect this repeated collision and introduce a phase shift
between the two transmission sequences in order to avoid further collisions resulting in optimal
network operation and minimized power usage.
Event Driven
There are many cases that require monitoring one or more crucial variables immediately
following a specific event or condition. Common examples include fire alarms, door and
window sensors, or instruments that are user activated. To support event-driven operations
with adequate power efficiency and speed of response, the sensor node must be designed such
that its power consumption is minimal in the absence of any triggering event, and the wake-up
time is relatively short when the specific event or condition occurs. Many applications require a
combination of event driven data collection and periodic sampling.