A Survey of Geosensor Networks: Advances in Dynamic Environmental Monitoring <s> Aquatic Observing Systems <s> Traditional means of observing the ocean, like fixed mooring stations and radar systems, are difficult and expensive to deploy and provide coarse-grained and data measurements of currents and waves. In this paper, we explore the use of inexpensive wireless drifters as an alternative flexible infrastructure for fine-grained ocean monitoring. Surface drifters are designed specifically to move passively with the flow of water on the ocean surface and they are able to acquire sensor readings and GPS-generated positions at regular intervals. We view the fleet of drifters as a wireless ad-hoc sensor network with two types of nodes:i) a few powerful drifters with satellite connectivity, acting as mobile base-stations, and ii)a large number of low-power drifters with short-range acoustic or radio connectivity. Using real datasets from the Gulf of Maine (US) and the Liverpool Bay (UK), we study connectivity and uniformity properties of the ad-hoc mobile sensor network. We investigate the effect of deployment strategy, weather conditions as well as seasonal changes on the ability of drifters to relay readings to the end-users,and to provide sufficient sensing coverage of the monitored area. Our empirical study provides useful insights on how to design distributed routing and in-network processing algorithms tailored for ocean-monitoring sensor networks. <s> BIB001 </s> A Survey of Geosensor Networks: Advances in Dynamic Environmental Monitoring <s> Aquatic Observing Systems <s> Ad hoc networks formed by traveling vehicles are envisaged to become a common platform that will support a wide variety of applications, ranging from road safety to advertising and entertainment. The multitude of vehicular applications calls for routing schemes that satisfy user-defined delay requirements while at the same time maintaining a low level of channel utilization to allow their coexistence. This paper focuses on the development of carry-and-forward schemes that attempt to deliver data from vehicles to fixed infrastructure nodes in an urban setting. The proposed algorithms leverage local or global knowledge of traffic statistics to carefully alternate between the Data Muling and Multihop Forwarding strategies, in order to minimize communication overhead while adhering to delay constraints imposed by the application. We provide an extensive evaluation of our schemes using realistic vehicular traces on a real city map. <s> BIB002 </s> A Survey of Geosensor Networks: Advances in Dynamic Environmental Monitoring <s> Aquatic Observing Systems <s> Movement patterns, like flockingand converging, leadingand following, are examples of high-level process knowledge derived from low-level trajectory data. Conventional techniques for the detection of movement patterns rely on centralized "omniscient" computing systems that have global access to the trajectories of mobile entities. However, in decentralized spatial information processing systems, exemplified by wireless sensor networks, individual processing units may only have access to localinformation about other individuals in their immediate spatial vicinity. Where the individuals in such decentralized systems are mobile, there is a need to be able to detect movement patterns using collaboration between individuals, each of which possess only partial knowledge of the global system state. This paper presents an algorithm for decentralized detection of the movement pattern flock, with applications to mobile wireless sensor networks. The algorithm's reliability is evaluated through testing on simulated trajectories emerging from unconstrained random movement and correlated random walk. <s> BIB003
Mobile geosensor networks consist of individual sensor nodes that are mobile or attached to mobile objects such as cars BIB002 , animals BIB003 or ocean buoys BIB001 . Applications for mobile geosensor networks are tsunami early warning systems  , or coastal and ocean observations conducting contamination detection BIB001 . In the NAMOS project at UCLA, a 'hybrid' sensor network system was constructed, which consists of a wireless stationary buoy sensing system and a mobile robotic surface vehicle capable of sensing and sampling. This sensor network was deployed in Lake Fulmor on the James Reserve to obtain both high-resolution temporal information of environmental parameters (provided by the stationary buoys) and data from specific locations using the capabilities of the robotic boat to study plankton dynamics. Environmental and event information collected from the buoys was used to guide the robotic boat.