The great development of mobile wireless sensor networks has many very important
applications. One of the most important applications that has attracted scientists' attention
recently is to track animals in their homes to follow the behavior and li
ves of some
endangered animals, but monitoring animals activities in the forest is a very difficult task,
especially if the animals to be monitored are teeny, therefore we cannot use the traditional
tracking systems ) like GPS, As well as the harsh and dangerous nature of the forest make
the use of wireless sensor networks the best solution, especially that sensors are low-cost,
small size, which made them suitable for such tasks, in this research we will study new
way to track a group of partridge where sensors are placed on these birds to observe their
life and behavior ,The important challenge in this research is to know the location of these
mobile birds to be able to the help them in appropriate time , so will introduce a new
method that provides us with acceptable accuracy, a simple, easy, inexpensive and low
energy consumption compared with other methods of animals tracking ,based on a set of
predefined reference nodes, where sensors information is sent to a gathering center
through these reference nodes ,then Analyze it and use it to the approximate location of
the animals. We will evaluate this method using Network Simulator (NS2).
The dynamic clustering-based hierarchical routing protocols are one of the methods
used to save energy and increase the lifetime of wireless sensor networks, however, that
most of the researches are neglecting the energy expended in election of the
heads and
formation of clusters in the network.
In this paper, we examine the overhead energy caused by hierarchical routing
protocols based on dynamic clustering and study its impact on the stability period of the
wireless sensor networks. Also, we proposed a solution to limit this energy by reducing the
consumed energy in election of heads and clusters formation operations. It is shown
through the simulation results that the energy consumed in LEACH setup phase decreases
the stability period of these networks and increases the number of dead nodes. And the use
of the proposed solution reduced the energy consumption during the election of the heads
and the formation of clusters clearly compared to the normal way followed in LEACH,
which has increased stability period and the number of live nodes in the network.
The low cost, ease of deployment has exposed WSNs an attractive choice for numerous applications,like environmental monitoring applications , security applications, real time tracking, and so on.
But in reality, these networks are operated on batte
ry with limitations in their computation capabilities, memory, bandwidth ,so they called networks with resource constrained nature, and this impels various challenges in its design and its performance.
Limited battery capacity of sensor nodes makes energy efficiency a major and challenge problem in wireless sensor networks. Thus, the routing protocols for wireless sensor networks must be energy efficient in order to maximize the network lifetime.
In this paper we simulated LEACH,SEP,DEEC,TEEN routing protocols and evaluated their performance by comparing with DT routing protocol in Homogeneous and Heterogeneous Wireless Sensor Networks on MATLAB.
Compressive Sensing (CS) shows high promise for fully distributed
compression in wireless sensor networks (WSNs). In theory, CS
allows the approximation of the readings from a sensor field with
excellent accuracy, while collecting only a small fra
ction of them at
a data gathering point. However, the conditions under which CS
performs well are not necessarily met in practice. CS requires a
suitable transformation that makes the signal sparse in its domain.
Also, the transformation of the data given by the routing protocol
and network topology and the sparse representation of the signal
have to be incoherent, which is not straightforward to achieve in
real networks. In this paper we investigated the effectiveness of
data recovery through joint Compressive Sensing (CS) and
Principal Component Analysis (PCA) in actual WSN deployments.
We proposed a novel system, called CS-PCA that embeds a
feedback control mechanism to automatically change the
compression ratio through changing the number of transmitting
sensors, while bounding the reconstruction error. The considered
recovery techniques in the proposed system are: biharmonic Spline
(Spline), Deterministic Ordinary Least Square (DOLS),
Probabilistic Ordinary Least Square (POLS) and Joint CS and PCA
(CS-PCA). We found that the later outperform all other
interpolation technique in the case of slow varying signals, while
POLS was the most effective in case of fast varying signals that(
low correlation less than 0.45)
