Utility companies (electricity, gas, and water suppliers), governments, and
researchers recognize an urgent need to deploy communication-based systems to
automate data collection from smart meters and sensors, known as Smart Metering
Infrastructure (SMI) or Automatic Meter Reading (AMR). A smart metering system
is envisaged to bring tremendous benefits to customers, utilities, and
governments. The advantages include reducing peak demand for energy, supporting
the time-of-use concept for billing, enabling customers to make informed
decisions, and performing effective load management, to name a few.
A key element in an SMI is communications between meters and utility servers.
However, the mass deployment of metering devices in the grid calls for studying
the scalability of communication protocols. SMI is characterized by the
deployment of a large number of small Internet Protocol (IP) devices sending
small packets at a low rate to a central server. Although the individual
devices generate data at a low rate, the collective traffic produced is
significant and is disruptive to network communication functionality. This
research work focuses on the scalability of the transport layer
functionalities. The TCP congestion control mechanism, in particular, would be
ineffective for the traffic of smart meters because a large volume of data
comes from a large number of individual sources. This situation makes the TCP
congestion control mechanism unable to lower the transmission rate even when
congestion occurs. The consequences are a high loss rate for metered data and
degraded throughput for competing traffic in the smart metering network.
To enhance the performance of TCP in a smart metering infrastructure (SMI), we
introduce a novel TCP-based scheme, called Split- and Aggregated-TCP (SA-TCP).
This scheme is based on the idea of upgrading intermediate devices in SMI
(known in the industry as regional collectors) to offer the service of
aggregating the TCP connections. An SA-TCP aggregator collects data packets
from the smart meters of its region over separate TCP connections; then it
reliably forwards the data over another TCP connection to the utility server.
The proposed split and aggregated scheme provides a better response to traffic
conditions and, most importantly, makes the TCP congestion control and flow
control mechanisms effective. Supported by extensive ns-2 simulations, we show
the effectiveness of the SA-TCP approach to mitigating the problems in terms of
the throughput and packet loss rate performance metrics.
A full mathematical model of SA-TCP is provided. The model is highly accurate
and flexible in predicting the behaviour of the two stages, separately and
combined, of the SA-TCP scheme in terms of throughput, packet loss rate and
end-to-end delay. Considering the two stages of the scheme, the modelling
approach uses Markovian models to represent smart meters in the first stage and
SA-TCP aggregators in the second. Then, the approach studies the interaction of
smart meters and SA-TCP aggregators with the network by means of standard
queuing models. The ns-2 simulations validate the math model results.
A comprehensive performance analysis of the SA-TCP scheme is performed. It
studies the impact of varying various parameters on the scheme, including the
impact of network link capacity, buffering capacity of those RCs that act as
SA-TCP aggregators, propagation delay between the meters and the utility
server, and finally, the number of SA-TCP aggregators. The performance results
show that adjusting those parameters makes it possible to further enhance
congestion control in SMI. Therefore, this thesis also formulates an
optimization model to achieve better TCP performance and ensures satisfactory
performance results, such as a minimal loss rate and acceptable end-to-end
delay. The optimization model also considers minimizing the SA-TCP scheme
deployment cost by balancing the number of SA-TCP aggregators and the link
bandwidth, while still satisfying performance requirements.
| Identifer | oai:union.ndltd.org:WATERLOO/oai:uwspace.uwaterloo.ca:10012/7559 |
| Date | 21 May 2013 |
| Creators | Khalifa, Tarek |
| Source Sets | University of Waterloo Electronic Theses Repository |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
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