24-07-2012, 12:35 PM
End-To-End Delay Optimization in Wireless Sensor Network
[attachment=28655]
INTRODUCTION
In the present era of network communication, the
wireless sensor network due to their unique features and
capability can remotely sense the environment very
efficiently and effectively. These wireless sensor network
systems are often deployed in remote or hard to reach
areas. Hence, it is critical that such networks might be
unattended for long durations. Therefore, extending
network lifetime through the efficient use of energy has
been a key issue in the development of wireless sensor
networks.
PROBLEM DEFINITION
The usage of wireless sensor networks gives rise to several
factors that affect the efficiency of the entire system. Some
of the factors are - Limited bandwidth, Limited battery
power, Energy consumption, Fault tolerance, Self
organization, scalability and reliability. The main objective
of this paper is to focus on one of the fundamental
resources: “energy consumed during data transmission”.
The sensor nodes have to transmit the data to the sink node
each time on occurrence of an event. Since they are
generally battery-powered, usage of large amount of energy
during data transmission eventually decreases the life time
of the sensor nodes. This paper aims at decreasing the
energy consumption by implementing multihop routing at
the shortest path between the source and destination so that
the delay between nodes can be minimized and in turn
saves the energy consumption significantly.
WIRELESS SENSOR NETWORK (WSN) MODEL
As discussed in the earlier section, the proposed model
will focus on event-driven asynchronous sensor networks,
where events occur rarely. This is an important class of
sensor networks and has many applications such as
environmental monitoring, intrusion detection, etc.
In such systems, there are four main sources of energy
consumption:
• energy required to keep the communication radios
on;
• energy required for the transmission and reception
of control packets;
• energy required to keep sensors on; and
• energy required for actual data transmission and
reception.
RESULTS AND DISCUSSIONS
The end-to-end delay has been simulated using NS2,
the comparison between Existing scheme and proposed
scheme has been discussed in the following section. The
figure 2 shows node delay for proposed scheme and figure
3 shows node delay for Existing scheme, the node delay in
proposed scheme has been reduced significantly in the
proposed scheme when system is operating for 5 ms node
mobility.
CONCLUSIONS
Following conclusions are made from the proposed scheme
used in this paper are:
• Proposed scheme has been developed to reduce the
event-reporting delay and to prolong the lifetime of
wireless sensor networks employing asynchronous
sleep-wake scheduling.
• Proposed scheme also resulted in to maximize the
network lifetime subject to a upper limit on the
expected end-to-end delay.
• Our numerical results suggest that the proposed
scheme can substantially outperform prior heuristic
solutions in the literature under practical scenarios
where there are obstructions in the coverage area of the
wireless sensor network.
[attachment=28655]
INTRODUCTION
In the present era of network communication, the
wireless sensor network due to their unique features and
capability can remotely sense the environment very
efficiently and effectively. These wireless sensor network
systems are often deployed in remote or hard to reach
areas. Hence, it is critical that such networks might be
unattended for long durations. Therefore, extending
network lifetime through the efficient use of energy has
been a key issue in the development of wireless sensor
networks.
PROBLEM DEFINITION
The usage of wireless sensor networks gives rise to several
factors that affect the efficiency of the entire system. Some
of the factors are - Limited bandwidth, Limited battery
power, Energy consumption, Fault tolerance, Self
organization, scalability and reliability. The main objective
of this paper is to focus on one of the fundamental
resources: “energy consumed during data transmission”.
The sensor nodes have to transmit the data to the sink node
each time on occurrence of an event. Since they are
generally battery-powered, usage of large amount of energy
during data transmission eventually decreases the life time
of the sensor nodes. This paper aims at decreasing the
energy consumption by implementing multihop routing at
the shortest path between the source and destination so that
the delay between nodes can be minimized and in turn
saves the energy consumption significantly.
WIRELESS SENSOR NETWORK (WSN) MODEL
As discussed in the earlier section, the proposed model
will focus on event-driven asynchronous sensor networks,
where events occur rarely. This is an important class of
sensor networks and has many applications such as
environmental monitoring, intrusion detection, etc.
In such systems, there are four main sources of energy
consumption:
• energy required to keep the communication radios
on;
• energy required for the transmission and reception
of control packets;
• energy required to keep sensors on; and
• energy required for actual data transmission and
reception.
RESULTS AND DISCUSSIONS
The end-to-end delay has been simulated using NS2,
the comparison between Existing scheme and proposed
scheme has been discussed in the following section. The
figure 2 shows node delay for proposed scheme and figure
3 shows node delay for Existing scheme, the node delay in
proposed scheme has been reduced significantly in the
proposed scheme when system is operating for 5 ms node
mobility.
CONCLUSIONS
Following conclusions are made from the proposed scheme
used in this paper are:
• Proposed scheme has been developed to reduce the
event-reporting delay and to prolong the lifetime of
wireless sensor networks employing asynchronous
sleep-wake scheduling.
• Proposed scheme also resulted in to maximize the
network lifetime subject to a upper limit on the
expected end-to-end delay.
• Our numerical results suggest that the proposed
scheme can substantially outperform prior heuristic
solutions in the literature under practical scenarios
where there are obstructions in the coverage area of the
wireless sensor network.