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Jongtack Jung
School of Electrical Engineering, Korea University, Seoul 02841, Korea.

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Journal article
Published: 14 June 2018 in Sensors
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Most surveillance systems only contain CCTVs. CCTVs, however, provide only limited maneuverability against dynamic targets and are inefficient for short term surveillance. Such limitations do not raise much concern in some cases, but for the scenario in which traditional surveillance systems do not suffice, adopting a fleet of UAVs can help overcoming the limitations. In this paper, we present a surveillance system implemented with a fleet of unmanned aerial vehicles (UAVs). A surveillance system implemented with a fleet of UAVs is easy to deploy and maintain. A UAV fleet requires little time to deploy and set up, and removing the surveillance is also virtually instant. The system we propose deploys UAVs to the target area for installation and perform surveillance operations. The camera mounted UAVs act as surveillance probes, the server provides overall control of the surveillance system, and the fleet platform provides fleet-wise control of the UAVs. In the proposed system, the UAVs establish a network and enable multi-hop communication, which allows the system to widen its coverage area. The operator of the system can control the fleet of UAVs via the fleet platform and receive surveillance information gathered by the UAVs. The proposed system is described in detail along with the algorithm for effective placement of the UAVs. The prototype of the system is presented, and the experiment carried out shows that the system can successfully perform surveillance over an area set by the system.

ACS Style

Jongtack Jung; Seungho Yoo; Woong Gyu La; Dongkyu Roy Lee; Mungyu Bae; Hwangnam Kim. AVSS: Airborne Video Surveillance System. Sensors 2018, 18, 1939 .

AMA Style

Jongtack Jung, Seungho Yoo, Woong Gyu La, Dongkyu Roy Lee, Mungyu Bae, Hwangnam Kim. AVSS: Airborne Video Surveillance System. Sensors. 2018; 18 (6):1939.

Chicago/Turabian Style

Jongtack Jung; Seungho Yoo; Woong Gyu La; Dongkyu Roy Lee; Mungyu Bae; Hwangnam Kim. 2018. "AVSS: Airborne Video Surveillance System." Sensors 18, no. 6: 1939.

Journal article
Published: 24 May 2018 in Sensors
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Over the past decades, hardware and software technologies for wireless sensor networks (WSNs) have significantly progressed, and WSNs are widely used in various areas including Internet of Things (IoT). In general, existing WSNs are mainly used for applications that require delay-tolerance and low-computation due to the poor resources of traditional sensor nodes in WSNs. However, compared to the traditional sensor nodes, today’s devices for WSNs have more powerful resource. Thus, sensor nodes these days not only conduct sensing and transmitting data to servers but also are able to process many operations, so more diverse applications can be applied to WSNs. Especially, many applications using audio data have been proposed because audio is one of the most widely used data types, and many mobile devices already have a built-in microphone. However, many of the applications have a requirement that heavy-operations should be done by a tight deadline, so it is difficult for a single node in WSNs to run relatively heavy applications by itself. In this paper, to overcome this limitation of WSNs, we propose a new emerging system, HeaLow, a cooperative computing system for heavy-computation and low-latency processing in WSNs. We designed HeaLow and carried out the practical implementation on real devices. We confirmed the effectiveness of HeaLow through various experiments using the real devices and simulations. Using HeaLow, nodes in WSNs are able to perform heavy-computation processes while satisfying a completion time requirement.

ACS Style

Jongtack Jung; Woonghee Lee; Hwangnam Kim. Cooperative Computing System for Heavy-Computation and Low-Latency Processing in Wireless Sensor Networks. Sensors 2018, 18, 1686 .

AMA Style

Jongtack Jung, Woonghee Lee, Hwangnam Kim. Cooperative Computing System for Heavy-Computation and Low-Latency Processing in Wireless Sensor Networks. Sensors. 2018; 18 (6):1686.

Chicago/Turabian Style

Jongtack Jung; Woonghee Lee; Hwangnam Kim. 2018. "Cooperative Computing System for Heavy-Computation and Low-Latency Processing in Wireless Sensor Networks." Sensors 18, no. 6: 1686.

Journal article
Published: 19 February 2018 in Sensors
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Vast applications and services have been enabled as the number of mobile or sensing devices with communication capabilities has grown. However, managing the devices, integrating networks or combining services across different networks has become a new problem since each network is not directly connected via back-end core networks or servers. The issue is and has been discussed especially in wireless sensor and actuator networks (WSAN). In such systems, sensors and actuators are tightly coupled, so when an independent WSAN needs to collaborate with other networks, it is difficult to adequately combine them into an integrated infrastructure. In this paper, we propose drone-as-a-gateway (DaaG), which uses drones as mobile gateways to interconnect isolated networks or combine independent services. Our system contains features that focus on the service being provided in the order of importance, different from an adaptive simple mobile sink system or delay-tolerant system. Our simulation results have shown that the proposed system is able to activate actuators in the order of importance of the service, which uses separate sensors’ data, and it consumes almost the same time in comparison with other path-planning algorithms. Moreover, we have implemented DaaG and presented results in a field test to show that it can enable large-scale on-demand deployment of sensing and actuation infrastructure or the Internet of Things (IoT).

ACS Style

Mungyu Bae; Seungho Yoo; Jongtack Jung; Seongjoon Park; Kangho Kim; Joon Yeop Lee; Hwangnam Kim. Devising Mobile Sensing and Actuation Infrastructure with Drones. Sensors 2018, 18, 624 .

AMA Style

Mungyu Bae, Seungho Yoo, Jongtack Jung, Seongjoon Park, Kangho Kim, Joon Yeop Lee, Hwangnam Kim. Devising Mobile Sensing and Actuation Infrastructure with Drones. Sensors. 2018; 18 (3):624.

Chicago/Turabian Style

Mungyu Bae; Seungho Yoo; Jongtack Jung; Seongjoon Park; Kangho Kim; Joon Yeop Lee; Hwangnam Kim. 2018. "Devising Mobile Sensing and Actuation Infrastructure with Drones." Sensors 18, no. 3: 624.

Journal article
Published: 26 October 2015 in Wireless Personal Communications
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With the exception of solid state drive, the network I/O generally increases at a faster pace than the I/O capacity of hard disk drive. If the gap between the disk I/O and the network I/O continues to grow, current technologies that are tuned to current state may not be the optimal choices anymore. One of such technologies may be virtual machine migration (VMM). VMM is one of the most frequently mentioned operations in datacenters. One of the purposes of VMM is to ensure the data used by the virtual machine (VM) and the VM using the data are close to each other. However, if the VMMs require longer period of freeze time, VMM under certain situations may be unnecessary. In this paper, a series of simulations are carried out to show that VMM of some cases may not be necessary with enhanced network capacity.

ACS Style

Jongtack Jung; Kangho Kim; Hwangnam Kim. On the Necessity of VM Migration: Simulation on Datacenter Network Resources. Wireless Personal Communications 2015, 86, 1797 -1812.

AMA Style

Jongtack Jung, Kangho Kim, Hwangnam Kim. On the Necessity of VM Migration: Simulation on Datacenter Network Resources. Wireless Personal Communications. 2015; 86 (4):1797-1812.

Chicago/Turabian Style

Jongtack Jung; Kangho Kim; Hwangnam Kim. 2015. "On the Necessity of VM Migration: Simulation on Datacenter Network Resources." Wireless Personal Communications 86, no. 4: 1797-1812.