01-12-2012, 01:21 PM
QoS-aware MAC protocols for wireless sensor networks: A survey
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ABSTRACT
The adoption of wireless sensor networks by applications that require complex operations,
ranging from health care to industrial monitoring, has brought forward a new challenge of
fulfilling the quality of service (QoS) requirements of these applications. However, providing
QoS support is a challenging issue due to highly resource constrained nature of sensor
nodes, unreliable wireless links and harsh operation environments. In this paper, we focus
on the QoS support at the MAC layer which forms the basis of communication stack and
has the ability to tune key QoS-specific parameters, such as duty cycle of the sensor
devices. We explore QoS challenges and perspectives for wireless sensor networks, survey
the QoS mechanisms and classify the state of the art QoS-aware MAC protocols together
with discussing their advantages and disadvantages. According to this survey, we observe
that instead of providing deterministic QoS guarantees, majority of the protocols follow a
service differentiation approach by classifying the data packets according to their type (or
classes) and packets from different classes are treated according to their requirements by
tuning the associated network parameters at the MAC layer.
Introduction
Wireless sensor networks (WSNs) have appeared as one
of the emerging technologies that combine automated
sensing, embedded computing and wireless networking
into tiny embedded devices. While the early research on
WSNs has mainly focused on monitoring applications, such
as agriculture [1] and environmental monitoring [2], based
on low-rate data collection, current WSN applications can
support more complex operations ranging from health care
[3] to industrial monitoring and automation [4]. Besides
these, the availability of low-cost hardware and rapid
development of tiny cameras and microphones have enabled
a new class of WSNs: multimedia or visual wireless
sensor networks [5,6] and this new class has contributed
to new potential WSN applications, such as surveillance.
Background and QoS perspectives
Internet was initially designed for providing the best effort
delivery of application data since average performance
guarantees were sufficient for initial types of applications
[13]. However, with the emergence of applications, such
as Internet telephony and video streaming, that require
high throughput, bounded delay, bounded delay jitter,
and high reliability, best effort delivery has become insufficient
to support these applications. Consequently, this
has driven and enabled the development of algorithms,
protocols and mechanisms that provide QoS support for diverse
set of applications. A similar situation is currently
observed in WSNs. Traditionally, WSNs have been used
for monitoring applications based on low-rate data collection
with low periods of operation. Current WSNs are considered
to support more complex operations ranging from
target tracking [14] to assisted living [15] which require
efficient, reliable and timely collection of large amounts
of data.
QoS provisioning and service differentiation in traditional
networks
Shortly, QoS is the ability of a network to satisfy the certain
requirements of the user or application. There are two
main types of QoS provision defined in wired and wireless
networks: Hard QoS and Soft QoS. The applications that require
hard QoS should be provided deterministic QoS guarantees,
such as strict bounds on packet delays, bandwidth
or packet losses. In soft QoS approach, again the application
has tight QoS requirements but the temporal violations
on QoS provisioning can be tolerated to a certain
extent [13].
Service differentiation is the widely adopted scheme in
both wired and wireless networks to provide hard/soft QoS
guarantees. There are two service differentiation models
proposed for conventional computer networks, Integrated
services (IntServ) [8] and differentiated services (DiffServ)
[16]. Aim of both the differentiation models are to prioritize
flows or packets, map their priorities into service qualities
and provide required service quality by sharing
limited resources among them.
QoS challenges in WSNs
WSNs inherit most of the well-known QoS challenges
from traditional wireless networks, such as time varying
channels and unreliable links [35]. However, typical characteristics
of WSNs, such as severe resource constraints
and harsh environmental conditions, pose additional unique
challenges for QoS-support. These QoS challenges for
WSNs are explained in this section:
Resource constraints: WSNs lack of bandwidth, memory,
energy and processing capability. However, limited
energy is the most crucial one since in many scenarios
it is impossible or impractical to replace or recharge
batteries of the sensor nodes. Although energy harvesting
via solar energy [36,37] seems to be a promising
solution to energy scarcity, present solar panels are still
too large for tiny sensor devices. Eventually, proposed
QoS support mechanisms must be lightweight and simple
in order to operate on a highly resource constrained
sensor node.
Node deployment: Deployment of the sensor nodes may
be either deterministic or random. In deterministic
deployment, sensor nodes are placed by hand and routing
can be performed through pre-scheduled paths. In a
random deployment, sensor nodes are deployed randomly
and organize themselves in an ad hoc manner.
Hence, neighbor discovery, path discovery, geographical
information of the nodes and clustering are the issues to
be solved.
QoS mechanisms in WSNs at MAC layer
Although each method contributing to improve the performance
of the MAC layer and to fulfill the QoS requirements
can be counted as QoS mechanism, there is a
bunch of them already proposed and applied in the literature.
In this section, properties of these mechanisms and
how they provide QoS will be investigated briefly. Examples
of QoS-aware MAC protocols in the literature utilizing
these techniques will be surveyed in Section 6.
Power control
The main idea of power control is simply adjusting the
transmission power of the sensor nodes according to the
minimum power required for successful transmission
[48]. Many factors affect the required minimal power
including frequency of the band, wireless channel conditions
(e.g. noise, path loss, shadowing) and distance to receiver.
Although power control is a physical layer related
issue, it has a significant impact on both MAC and network
layers since it has the ability to control the network connectivity.
Therefore, the power control mechanism can be
implemented in the MAC layer and a joint physical-MAC
layer solution can be derived.
We can count the reduction of energy consumption as a
primary contribution of power control to QoS provisioning.
Also, it increases the concurrent communications by
decreasing interference, hence improves the channel utilization.
However, dynamic nature of the wireless links
makes the implementation of power control mechanism
a challenging task.
Conclusions
Current WSNs are not only used for traditional low
data-rate applications but also for more complex operations
which require efficient, reliable and timely collection
of large amounts of data. Moreover, they are not only composed
of sensor devices which generate scalar data but also
the use of video and microphone sensors are becoming
common. Increasing capacities of the sensor nodes, variety
of the application fields and multimodal use of sensors require
efficient QoS provisioning mechanisms in WSNs.
With these requirements in mind, we have focused on
the perspectives, challenges, metrics, parameters and
requirements of QoS-aware MAC protocols for WSNs in
this paper and surveyed the existing protocols together
with their comparisons and classifications. According to
this survey, we observe that instead of providing deterministic
QoS guarantees, majority of the protocols follow a service
differentiation approach by classifying data packets
according to their type and packets of different types are
treated according to their requirements by tuning the associated
network parameters at the MAC layer.