Smooth path construction for data mule tours in wireless sensor networks

Wichmann, Andrew; Chester, J.D.; Korkmaz, Turgay

doi:10.1109/glocom.2012.6503095

Cited by 12 publications

(6 citation statements)

References 20 publications

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“…With this mobility comes many new issues and benefits that have been researched including path-planning [40,59,73,74] and speed control [75]. Much of the early research uses only one controlled mobile robot, however, researchers have also looked into the use of multiple coordinated robots [60,9].…”

Section: Robotics and Mobility In Wsnsmentioning

confidence: 98%

“…In fact, one such system, called the ALERT system [39] is already used in practice in the US. Many military and security applications can be considered as well, such as border monitoring applications or battlefield monitoring applications [40]. Healthcare is another possibility for the use of WSNs and this has a possible cross utilization with teleoperation in telecare for patients, especially the elderly, as studied in [41] and [42].…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

See 1 more Smart Citation

The integration of mobile (tele) robotics and wireless sensor networks: A survey

Wichmann

Okkalıoğlu

Korkmaz

2014

Computer Communications

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Section: Robotics and Mobility In Wsnsmentioning

confidence: 98%

Section: Wireless Sensor Networkmentioning

confidence: 99%

The integration of mobile (tele) robotics and wireless sensor networks: A survey

Wichmann

Okkalıoğlu

Korkmaz

2014

Computer Communications

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“…It widens the application usage of wireless sensor networks. It is interesting to focus on fully controllable mobility since it is possible to compute the node's trajectory to optimize the collection process [19]. The contributions of this paper lie under this category.…”

Section: Global Positioning Of Our Contributionmentioning

confidence: 99%

“…The contributions of this paper lie under this category. Unlike the paper from Wichmann et al [19], we use multiple mobile nodes for data gathering. Unlike other works such as the one presented by Huang et al [10], the data gathering process in this paper is time and space dependent since the data producers (sensors) are mobile and should therefore, be tracked and covered during the deployment procedure.…”

Section: Global Positioning Of Our Contributionmentioning

confidence: 99%

Efficient data collection and tracking with flying drones

2019

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Data collection is an important mechanism for wireless sensor networks to be viable. This paper addresses the Aerial Data Collection Problem (ADCP) from a set of mobile wireless sensors located on the ground, using a fleet of flying devices. The objective is i) to deploy a set of Unmanned Aerial Vehicles (UAVs) in a 3D space to cover and collect data from all the mobile wireless sensors at each time step through a ground-to-air communication, ii) to send these data to a central base station using multi-hop wireless air-to-air communications through the network of UAVs, iii) while minimizing the total deployment cost (communication and deployment) over time. The Aerial Data Collection Problem (ADCP) is a complex time and space coverage, and connectivity problem. We first present a mixed-integer linear program solving ADCP optimally for small instances. Then, we develop a second model solved by column generation for larger instances, with optimal or heuristic pricing programs. Results show that our approach provides very accurate solutions minimizing the data collection cost. Moreover, only a very small number of columns are generated throughout the resolution process, showing the efficiency of our approach.

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“…Each node i has a unique location denoted by (x i , y i ). The wireless charger moves in the network area with a self-driving car [15,16] or a Unmanned Aerial Vehicle (UAV) [17,18,19], where the maximum speed is limited to s t . To minimize the charging completion time, we need to 1) identify the charging spots where the charger stops for charging, 2) the path visiting all charging spots, and 3) the corresponding speed on the path.…”

Section: Overviewmentioning

confidence: 99%