Networked infomechanical systems: a mobile embedded networked sensor platform

Pon, Richard T.; Rahimi, Mohammed; Hansen, Mark; Kaiser, William J.; Pottie, Gregory; Srivastava, Mani; Sukhatme, Gaurav S.; Estrin, Deborah

doi:10.1109/ipsn.2005.1440952

Cited by 56 publications

(47 citation statements)

References 9 publications

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“…We observe that mobile node rotation is particularly suitable for mobile sensor platforms with limited mobility as we can impose mobility constraints on individual nodes. For example, we can model the constraints of the NIMS sensors [10] that are only capable of moving along fixed cables by only allowing such sensors to exchange with other sensors on the same set of cables. Likewise, mobile node rotation does not require powerful nodes capable of performing complex motion planning calculations or developing new mobility-aware routing topologies since all movements are to known positions and the topology does not change.…”

Section: Introductionmentioning

confidence: 99%

Maximizing Network Topology Lifetime Using Mobile Node Rotation

El-Moukaddem

Torng

Xing

2015

IEEE Trans. Parallel Distrib. Syst.

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Abstract. One of the key challenges facing wireless sensor networks (WSNs) is extending network lifetime due to sensor nodes having limited power supplies. Extending WSN lifetime is complicated because nodes often experience differential power consumption. For example, nodes closer to the sink in a given routing topology transmit more data and thus consume power more rapidly than nodes farther from the sink. Inspired by the huddling behavior of emperor penguins where the penguins take turns on the cold extremities of a penguin "huddle", we propose mobile node rotation, a new method for using low-cost mobile sensor nodes to address differential power consumption and extend WSN lifetime. Specifically, we propose to rotate the nodes through the high power consumption locations. We propose efficient algorithms for single and multiple rounds of rotations. Our extensive simulations show that mobile node rotation can extend WSN topology lifetime by more than eight times on average in a which is significantly better than existing alternatives.

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Section: Introductionmentioning

confidence: 99%

Maximizing Network Topology Lifetime Using Mobile Node Rotation

El-Moukaddem

Torng

Xing

2015

IEEE Trans. Parallel Distrib. Syst.

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“…The total expected number of moves, L 0 (λ 2 , S) and L 1 (λ 2 , S), which are needed to compute the cost defined by (4), are given by:…”

Section: B Second-phase Detectionmentioning

confidence: 99%

“…First, practical mobile sensors are only capable of slow-speed movement, which may lead to long detection delays. The typical speed of mobile sensor systems (e.g., NIMs [4], Packbot [5] and Robomote [6]) is about 0.2−2 m/s. Therefore, the movement of sensors must be efficiently scheduled in order to reduce detection latency.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Target Detection in Wireless Sensor Networks with Reactive Mobility

Tan

Xing

Wang

et al. 2008

2008 16th Interntional Workshop on Quality of Service

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Abstract-Recent years have witnessed the deployments of wireless sensor networks in a class of mission-critical applications such as object detection and tracking. These applications often impose stringent QoS requirements including high detection probability, low false alarm rate and bounded detection delay. Although a dense all-static network may initially meet these QoS requirements, it does not adapt to unpredictable dynamics in network conditions (e.g., coverage holes caused by death of nodes) or physical environments (e.g., changed spatial distribution of events). This paper exploits reactive mobility to improve the target detection performance of wireless sensor networks. In our approach, mobile sensors collaborate with static sensors and move reactively to achieve the required detection performance. Specifically, mobile sensors initially remain stationary and are directed to move toward a possible target only when a detection consensus is reached by a group of sensors. The accuracy of final detection result is then improved as the measurements of mobile sensors have higher signal-to-noise ratios after the movement. We develop a sensor movement scheduling algorithm that achieves near-optimal system detection performance within a given detection delay bound. The effectiveness of our approach is validated by extensive simulations using the real data traces collected by 23 sensor nodes.

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“…Such approaches are currently being implemented using the Stack Sensor Platform [15] at the MIT Media Lab. The Networked InfoMechanical Systems research area at the Center for Embedded Networked Sensing at UCLA conducts research and builds systems to investigate adaptive sensing [14] and mobility for distributed sensor networks [16].…”

Section: Related Workmentioning

confidence: 99%

Parasitic Mobility for Pervasive Sensor Networks

Laibowitz¹,

Paradiso²

2005

Lecture Notes in Computer Science

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Abstract. Distributed sensor networks offer many new capabilities for contextually monitoring environments. By making such systems mobile, we increase the application-space for the distributed network mainly by providing dynamic context-dependent deployment, continual relocatability, automatic node recovery, and a larger area of coverage. In existing models, the addition of actuation to the nodes has exacerbated three of the main problems with distributed systems: power usage, node size, and node complexity. In this paper we propose a solution to these problems in the form of parasitically actuated nodes that harvest their mobility and local navigational intelligence by selectively engaging and disengaging from mobile hosts in their environment. We analyze the performance of parasitically mobile distributed networks through software simulations and design, implement, and demonstrate hardware prototypes.

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Networked infomechanical systems: a mobile embedded networked sensor platform

Cited by 56 publications

References 9 publications

Maximizing Network Topology Lifetime Using Mobile Node Rotation

Maximizing Network Topology Lifetime Using Mobile Node Rotation

Collaborative Target Detection in Wireless Sensor Networks with Reactive Mobility

Parasitic Mobility for Pervasive Sensor Networks

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