Introduction - Energy Harvesting Autonomous Sensor Systems - page 7

saving modes of operation can be implemented. The most obvious means of
power conservation is to turn the transceiver off when it is not required. By
using a random wake-up schedule during the connection phase and by turn-
ing the radio off during idle time slots, power conservation can be achieved.
A dynamic power management scheme for WSNs has been discussed [7]; five
power-saving modes were proposed, and intermode transition policies were
investigated.
The network layer takes care of routing the data supplied by the trans-
port layer. In WSN deployment, the routing protocols in the network layer
are important because an efficient routing protocol can help to serve various
applications and save energy. By setting appropriate energy and time delay
thresholds for data relay, the protocol can help prolong the lifetime of sensor
nodes. Hence, the network layer is another layer in the WSN to reduce power
consumption. The transport layer helps to maintain the flow of data if the sen-
sor network application requires it. Depending on the sensing tasks, different
types of application software can be built and used on the application layer.
In contrast to traditional networks that focus mainly on how to achieve high
quality-of-service (QoS) provisions, WSN protocols tend to focus primarily
on power conservation and power management for sensor nodes [7, 8] as
well as the design of energy-aware protocols and algorithms for WSNs [5, 9]
to reduce the power consumption of the overall wireless sensor network. By
doing so, the lifetime of the WSN can be extended.
However, there must be some embedded trade-off mechanisms that give
the end user the option of prolonging the WSN lifetime but at the cost of
lower throughput or higher transmission delay. Conversely, the power con-
sumption of the WSN can be reduced by sacrificing the QoS provisions, that
is, by lowering the data throughput or having a higher transmission delay.
Among the several challenging requirements posed on the design of the un-
derlying algorithms and protocols of the WSNs, it is well known among
academia as well as industry [10-12] that energy constraint is one of the most
significant challenges in the WSN research field [13]. The functionalities of
the WSN are highly dependent on the amount of energy that is available
to be expended by each sensor node in the network. As such, the energy
constraint challenge of WSN is substantial enough to be investigated and
discussed in this topic. It is a multiobjective optimization problem concern-
ing various WSN parameters like QoS, transmission delays, lifetime, energy,
and more.
In 2000, two standards groups, ZigBee, a HomeRF spinoff, and IEEE
(Institute for Electrical and Electronics Engineers) 802 Working Group 15,
combined efforts to address the need for low-power, low-cost wireless net-
working in the residential and industrial environments. Furthermore, the
IEEE New Standards Committee (NesCom) sanctioned a new task group
to begin the development of a Low Rate-Wireless Personal Area Network
(LR-WPAN) standard, to be called 802.15.4. The goal of this group is to provide