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Copyright 2000 IEEE. Published in the Proceedings of the Hawaii International Conference on System Sciences, January 4-7, 2000, Maui, Hawaii.

Energy-Efficient Communication Protocol for Wireless Microsensor Networks
Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan
Massachusetts Institute of Technology
Cambridge, MA 02139
wendi, anantha, hari @mit.edu
 

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Abstract

seismic, and video sensors can be used to form an ad hoc
network to detect intrusions. Microsensors can also be used
to monitor machines for fault detection and diagnosis.
Microsensor networks can contain hundreds or thousands of sensing nodes. It is desirable to make these nodes
as cheap and energy-efficient as possible and rely on their
large numbers to obtain high quality results. Network protocols must be designed to achieve fault tolerance in the
presence of individual node failure while minimizing energy consumption. In addition, since the limited wireless
channel bandwidth must be shared among all the sensors
in the network, routing protocols for these networks should
be able to perform local collaboration to reduce bandwidth
requirements.
Eventually, the data being sensed by the nodes in the network must be transmitted to a control center or base station,
where the end-user can access the data. There are many possible models for these microsensor networks. In this work,
we consider microsensor networks where:

Wireless distributed microsensor systems will enable the
reliable monitoring of a variety of environments for both
civil and military applications. In this paper, we look at
communication protocols, which can have significant impact on the overall energy dissipation of these networks.
Based on our findings that the conventional protocols of
direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for
sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that
utilizes randomized rotation of local cluster base stations
(cluster-heads) to evenly distribute the energy load among
the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH
can achieve as much as a factor of 8 reduction in energy
dissipation compared with conventional routing pro...
Copyright 2000 IEEE. Published in the Proceedings of the Hawaii International Conference on System Sciences, January 4-7, 2000, Maui, Hawaii.
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan
Massachusetts Institute of Technology
Cambridge, MA 02139
wendi, anantha, hari @mit.edu
Abstract
Wireless distributed microsensor systems will enable the
reliable monitoring of a variety of environments for both
civil and military applications. In this paper, we look at
communication protocols, which can have significant im-
pact on the overall energy dissipation of these networks.
Based on our findings that the conventional protocols of
direct transmission, minimum-transmission-energy, multi-
hop routing, and static clustering may not be optimal for
sensor networks, we propose LEACH (Low-Energy Adap-
tive Clustering Hierarchy), a clustering-basedprotocol that
utilizes randomized rotation of local cluster base stations
(cluster-heads) to evenly distribute the energy load among
the sensors in the network. LEACH uses localized coordi-
nation to enable scalability and robustness for dynamic net-
works, and incorporates data fusion into the routing proto-
col to reduce the amount of information that must be trans-
mitted to the base station. Simulations show that LEACH
can achieve as much as a factor of 8 reduction in energy
dissipation compared with conventional routing protocols.
In addition, LEACH is able to distribute energy dissipation
evenly throughout the sensors, doubling the useful system
lifetime for the networks we simulated.
1. Introduction
Recent advances in MEMS-based sensor technology,
low-power analog and digital electronics, and low-power
RF design have enabled the development of relatively in-
expensive and low-power wireless microsensors [2, 3, 4].
These sensors are not as reliable or as accurate as their ex-
pensive macrosensor counterparts, but their size and cost
enable applications to network hundreds or thousands of
these microsensors in order to achieve high quality, fault-
tolerant sensing networks. Reliable environment monitor-
ing is important in a variety of commercial and military
applications. For example, for a security system, acoustic,
seismic, and video sensors can be used to form an ad hoc
network to detect intrusions. Microsensors can also be used
to monitor machines for fault detection and diagnosis.
Microsensor networks can contain hundreds or thou-
sands of sensing nodes. It is desirable to make these nodes
as cheap and energy-efficient as possible and rely on their
large numbers to obtain high quality results. Network pro-
tocols must be designed to achieve fault tolerance in the
presence of individual node failure while minimizing en-
ergy consumption. In addition, since the limited wireless
channel bandwidth must be shared among all the sensors
in the network, routing protocols for these networks should
be able to perform local collaboration to reduce bandwidth
requirements.
Eventually, the data being sensed by the nodes in the net-
work must be transmitted to a control center or base station,
where the end-user can access the data. There are many pos-
sible models for these microsensor networks. In this work,
we consider microsensor networks where:
The base station is fixed and located far from the sen-
sors.
All nodes in the network are homogeneous and energy-
constrained.
Thus, communication between the sensor nodes and the
base station is expensive, and there are no “high-energy”
nodes through which communication can proceed. This is
the framework for MIT’s -AMPS project, which focuses
on innovative energy-optimized solutions at all levels of the
system hierarchy, from the physical layer and communica-
tion protocols up to the application layer and efficient DSP
design for microsensor nodes.
Sensor networks contain too much data for an end-user
to process. Therefore, automated methods of combining or
aggregatingthe data into a small set of meaningful informa-
tion is required [7, 8]. In addition to helping avoid informa-
tion overload, data aggregation, also known as data fusion,
can combine several unreliable data measurements to pro-
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