Provenance is the information about the origin of the data inputs and the data manipulations to a obtain a
final result. With the huge amount of information input and potential processing available in sensor networks,
provenance is crucial for understanding the creation, manipulation and quality of data and processes. Thus
maintaining provenance in a sensor network has substantial advantages. In our paper, we will concentrate on
showing how provenance improves the outcome of a multi-modal sensor network with fusion. To make the ideas
more concrete and to show what maintaining provenance provides, we will use a sensor network composed of
binary proximity sensors and cameras to monitor intrusions as an example. Provenance provides improvements
in many aspects such as sensing energy consumption, network lifetime, result accuracy, node failure rate. We
will illustrate the improvements in accuracy of the position of the intruder in a target localization network by
The management of sensor networks in coalition settings has been treated in a piecemeal fashion in the current literature
without taking a comprehensive look at the complete life cycle of coalition networks, and determining the different
aspects of network management that need to be taken into account for the management of sensor networks in those
contexts. In this paper, we provide a holistic approach towards managing sensor networks encountered in the context of
coalition operations. We describe how the sensor networks in a coalition ought to be managed at various stages of the
life cycle, and the different operations that need to be taken into account for managing various aspects of the networks.
In particular, we look at the FCAPS model for network management, and assess the applicability of the FCAPS model
to the different aspects of sensor network management in a coalition setting.
The ability of a sensor device is affected significantly by the surroundings and environment in which it is placed.
In almost all sensor modalities, some directions are better observed by a sensor than others. Furthermore, the
exact impact on the sensing ability of the device is dependent on the position assigned to the sensor. While
the problem of determining good coverage schemes for sensors of a field have many good solutions, not many
approaches are known to address the challenges arising due to location specific distortion. In this paper, we look
at the problem of incorporating terrain specific challenges in sensor coverage, and propose a geometric solution
to address them.
Ad-hoc sensor networks need to create their own network after deployment. Various schemes have been suggested
for sensors to create a better coverage pattern than if they are randomly deployed. A better coverage pattern
translates into a geometry of having disks cover an area completely and even redundantly. In this paper, we
present two coverage arrangements which turn out to be equivalent to grid lattice arrangements and analyze
One of the main goals of sensor networks is to provide accurate information about a sensing field for an extended
period of time. This requires collecting measurements from as many sensors as possible to have a better view
of the sensor surroundings. However, due to energy limitations and to prolong the network lifetime, the number
of active sensors should be kept to a minimum. To resolve this conflict of interest, sensor selection schemes
are used. In this paper, we survey different schemes that are used to select sensors. Based on the purpose of
selection, we classify the schemes into (1) coverage schemes, (2) target tracking and localization schemes, (3)
single mission assignment schemes and (4) multiple missions assignment schemes. We also look at solutions to
relevant problems from other areas and consider their applicability to sensor networks. Finally, we take a look
at the open research problems in this field.