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The recent interest in sensor networks has led to a number of routing schemes that use the limited resources available at sensor nodes more efficiently. These schemes typically try to find the minimum energy path to optimize energy usage at a node. In this paper we take the view that always using lowest energy paths may not be optimal from the point of view(More)
This paper presents and analyzes a three-tier architecture for collecting sensor data in sparse sensor networks. Our approach exploits the presence of mobile entities (called MULEs) present in the environment. When in close range, MULEs pick up data from the sensors, buffer it, and deliver it to wired access points. This can lead to substantial power(More)
Different opportunistic routing protocols have been proposed recently for routing in sensor networks. These protocols exploit the redundancy among nodes by using a node that is available for routing at the time of packet transmission. This mitigates the effect of varying channel conditions and duty cycling of nodes that make static selection of routes not(More)
One of the most compelling challenges of the next decade is the " last-meter " problem, extending the expanding data network into end-user data-collection and monitoring devices. PicoRadio supports the assembly of an ad hoc wireless network of self-contained mesoscale, low-cost, low-energy sensor and monitor nodes. While technology advances have made it(More)
— In this paper, a detailed study of the performance of geographic routing protocols in the presence of localization errors is carried out. Both analytical and simulation results illustrate the major impact of localization errors on the protocol goodput and route discovery energy. The performance metrics observed were the packet delivery ratio and the power(More)
Opportunistic routing protocols have been proposed as efficient methods to exploit the high node densities in sensor networks to mitigate the effect of varying channel conditions and non-availability of nodes that power down periodically. They work by integrating the network and data link layers so that they can take a joint decision as to the next hop(More)
Determining the mode of transport of an individual is an important element of contextual information. In particular, we focus on differentiating between different forms of motorized transport such as car, bus, subway etc. Our approach uses location information and features derived from transit route information (schedule information, not real-time)(More)