الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Wireless Sensor Network (WSN) is one of the emerging networks that attracted
academia and industry alike. It is a wireless network consisting of a large number of small
size, inexpensive, and battery operated sensor nodes. Such nodes are essential for
monitoring physical or environmental conditions such as temperature and humidity,
performing simple computation, and communicating via wireless multi-hop transmission
technique to report the collected data to sink node.
WSNs can be readily deployed in various environments to collect information in an
autonomous manner, and thus can support abundant applications. Object tracking is widely
referred as one of the most interesting applications of WSNs. This application is able to
detect and track objects, and report information about these objects to a central base
station. Many recent works have been dedicated to localization of objects; however, few of
these works were concentrated on the reliability of network data reporting along with
object localization. In this thesis, an efficient data reporting method is proposed for object
tracking in WSNs.
Energy is considered as one of the most critical resources for WSN. Data
transmission from the nodes to the sink along with the minimum energy path could be one
of the solutions to minimize the overall network energy consumption. However, this might
lead to unbalanced energy among sensor nodes resulting in energy hole problem.
Moreover, the reliable data transmission is an essential aspect that should be considered
when designing a WSN for object tracking application, where the loss of data packets will
affect the accuracy of the tracking and location estimation of a mobile object. Furthermore,
congestion in WSNs has negative impact on the performance, namely, decreased
throughput, increased per-packet energy consumption and delay. Thus, congestion control
is an important issue in WSNs.
Multi-sink WSNs are being used in many applications due to their significant
advantages over single sink, since it becomes inefficient to collect all information with a
single sink in large-scale WSNs.
This thesis aims at achieving both minimum energy consumption in reporting
operation and balanced energy consumption among sensor nodes for WSN lifetime
extension. In addition, data reliability is considered in our model, where the sensed data
can reach the sink node in a more reliable way. Finally, it presents a solution that
sufficiently exerts the underloaded nodes to alleviate congestion and improve the overall
throughput in WSNs. This thesis formulates the problem as 0/1 Integer Linear
Programming (ILP) problem and first proposes Reliable Energy Balance Traffic Aware
data reporting approach based Swarm Intelligence (REBTASI) to solve the optimization
problem. Then, it proposes Reliable Energy Balance Traffic Aware (REBTA) data
reporting algorithm as another solution to the optimization problem and to overcome the
limitations of the swarm intelligence. from the obtained simulation results, the proposed
solutions have proved to be able to enhance the network performance in terms of network
lifetime, throughput, end-to-end delay, and energy balance for both homogeneous and
heterogeneous networks.
In addition, this thesis considers multi-sink WSNs and proposes a new scheme to
select the optimal sink node for data transmission. Then, it formulates the object tracking
problem in large scale multi-sink WSNs into 0/1 integer programming with previously
mentioned parameters. In addition, the proposed REBTASI and REBTA approaches are
developed for multi-sink WSNs. Computer simulations confirm that the performance of the
proposed schemes for multi-sink WSNs outperforms that of the proposed schemes for
single sink and that of the previous work which is related to this proposal for both
homogeneous and heterogeneous networks.