A simple but efficient power conserving algorithm for the sensor networks is presented in this paper. The goal is to predict sleep time for the sensor networks based on statistics of data transfer. The proposed sensor...
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To our knowledge, at the time of writing no methodology exists to dimension a sensor network so that a worst case traffic scenario can be definitely supported. In this paper, the well known network calculus is tailore...
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A wide-area sensor system is a complex, dynamic, resource-rich collection of Internet-connected sensing devices. In this paper, we propose X-Tree Programming, a novel database-centric programming model for wide-area s...
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The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is ...
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ISBN:
(纸本)0769523315
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is often impractical due to time requirements, economic constraints or inherent limitations of deployment scenarios. We have developed a service for reliably localizing wireless sensor networks in environments conducive to ranging errors by using a custom hardware-software solution for acoustic ranging and a family of self-localization algorithms. The ranging solution improves on previous work, extending the practical measurement range threefold (20-30m) while maintaining a distance-invariant median measurement error of about 1% of maximum range (33cm). The localization scheme is based on least squares scaling with soft constraints. Evaluation using ranging results obtained from sensor network field experiments shows that the localization scheme is resilient against large-magnitude ranging errors and sparse range measurements, both of which are common in large-scale outdoor sensor network deployments.
Reprogramming of sensor networks is an important and challenging problem as it is often necessary to reprogram the sensors in place. In this paper we propose a multihop reprogramming service designed for Mica-2/XSM mo...
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ISBN:
(纸本)0769523315
Reprogramming of sensor networks is an important and challenging problem as it is often necessary to reprogram the sensors in place. In this paper we propose a multihop reprogramming service designed for Mica-2/XSM motes. One of the problems in reprogramming is the issue of message collision. To reduce the problem of collision and hidden terminal problem, we propose a sender selection algorithm that attempts to guarantee that in a neighborhood there is at most one source transmitting the program at a time. Further, our sender selection is greedy in that it tries to select the sender that is expected to have the most impact. We also use pipelining to enable fast data propagation. MNP is energy efficient because it reduces the active radio time of a sensor node by putting the node into "sleep" state when its neighbors are transmitting a segment that is not of interest. Finally, we argue that it is possible to tune our service according to the remaining battery level of a sensor i.e., it can be tuned so that the probability that a sensor is given the responsibility of transmitting the code is proportional to its remaining battery life.
In this paper, we propose a novel approach for efficiently sensing a remote field using wireless sensor networks. Our approach, the infer algorithm, is fully distributed, has low overhead and saves considerable energy...
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ISBN:
(纸本)0769523315
In this paper, we propose a novel approach for efficiently sensing a remote field using wireless sensor networks. Our approach, the infer algorithm, is fully distributed, has low overhead and saves considerable energy compared to using just the data aggregation communication paradigm. This is accomplished by using a distributed algorithm to put nodes into sleep mode for a given period of time, thereby trading off energy usage for the accuracy of the data received at the sink. Bayesian inference is used to infer the missing data from the nodes that were not active during each sensing epoch. As opposed to other methods that have been considered, such as wavelet compression and distributed source coding, our algorithm has lower overhead in terms of both inter-node communication and computational complexity. Our simulations show that on average our algorithm produces energy savings of 59% while still maintaining data that is accurate to within 7.9%. We also show how the parameters of the algorithm may be tuned to optimize network lifetime for a desired level of data accuracy.
sensor networks have emerged as a promising technology with various applications, and power consumption is one of the key issues. Since each full function device can act as a coordinator or a device in ieee 802.15.4 s...
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ISBN:
(纸本)0769523315
sensor networks have emerged as a promising technology with various applications, and power consumption is one of the key issues. Since each full function device can act as a coordinator or a device in ieee 802.15.4 standard, 802.15.4-based sensor networks have various possible network topologies. In this paper, we try to construct network topologies with small number of coordinators while still maintaining network connectivity. By reducing the number of coordinators, the average duty cycle is reduced and the battery life is prolonged. Three topology control algorithms are proposed in this paper. Self-pruning is the simplest one with O(1) running time. Ordinal pruning significantly improves self-pruning in terms of power saving with O(n) running time. Layered pruning is a tradeoff between the first two pruning algorithms with O(root n) running time and a little higher power consumption than ordinal pruning. Furthermore, all three algorithms are independent of the physical radio propagation characteristics.
This paper presents MobiQuery, a spatiotemporal query service that allows mobile users to periodically gather information from their surrounding areas through a wireless sensor network. A key advantage of MobiQuery li...
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ISBN:
(纸本)0769523315
This paper presents MobiQuery, a spatiotemporal query service that allows mobile users to periodically gather information from their surrounding areas through a wireless sensor network. A key advantage of MobiQuery lies in its capability to meet stringent spatiotemporal performance constraints crucial to many applications. These constraints include query latency, data freshness and fidelity, and changing query areas due to user mobility. A novel just-in-time prefetching algorithm enables MobiQuery to maintain robust spatiotemporal guarantees even when nodes operate under extremely low duty cycles. Furthermore, it significantly reduces the storage cost and network contention caused by continuous queries from mobile users. We validate our approach through both theoretical analysis and simulation results under a range of realistic settings.
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