• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1568-1589
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• 2021

Deployment of access point (AP) is a problem that must be considered in network planning. However, this problem is usually a NP-hard problem which is difficult to directly reach optimal solution. Thus, improved AP deployment optimization scheme based on swarm intelligence algorithm is proposed to research on this problem. First, the scheme estimates the number of APs. Second, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the location and transmit power of APs. Finally, the greedy algorithm is used to remove the redundant APs. Comparing with multi-objective whale swarm optimization algorithm (MOWOA), particle swarm optimization (PSO) and grey wolf optimization (GWO), the proposed deployment scheme can reduce AP's transmit power and improves energy efficiency under different numbers of users. From the experimental results, the proposed deployment scheme can reduce transmit power about 2%-7% and increase energy efficiency about 2%-25%, comparing with MOWOA. In addition, the proposed deployment scheme can reduce transmit power at most 50% and increase energy efficiency at most 200%, comparing with PSO and GWO.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1611-1629
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• 2016

Recently, deploying WiFi access points (APs) for facilitating indoor localization has attracted increasing attention. However, most existing mechanisms in this aspect are typically simulation based and further they did not consider how to jointly utilize pre-existing APs in target environment and newly deployed APs for achieving high localization performance. In this paper, we propose a measurement-based AP deployment mechanism (MAPD) for placing APs in target indoor environment for assisting fingerprint based indoor localization. In the mechanism design, MAPD takes full consideration of pre-existing APs to assist the selection of good candidate positions for deploying new APs. For this purpose, we first choose a number of candidate positions with low location accuracy on a radio map calibrated using the pre-existing APs and then use over-deployment and on-site measurement to determine the actual positions for AP deployment. MAPD uses minimal mean location error and progressive greedy search for actual AP position selection. Experimental results demonstrate that MAPD can largely reduce the localization error as compared with existing work.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.169-170
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• 2007

In this paper, we analyze the effect of access point (AP) deployment on the accuracy of indoor localization. Two representative geometrical arrangements of AP deployment are selected. One is that a Tag is centered at the regular triangle composed of 3 AP's, and the other is that a Tag is set apart from the straight line composed of 3 AP's. As a result of simulation, the first case has a probability of 93% with distance errors within 1m, while the second case has a 32% of probability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.847-856
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• 2013

This paper presents an AP placement technique considering indoor location-awareness and examines its performance. The proposed AP placement technique is addressed from three performance metrics: location-awareness and AP-based wireless network performance as well as its cost. The proposed AP placement technique consists of meta-heuristic algorithms that yield a near optimal AP configuration for given performance metrics, and deterministic algorithms that improve the fast convergence of the near optimal AP configuration. The performance of the AP placement technique presented in this paper is measured under the environments simulating indoor space, and numerical results obtained by experimental evaluation yield the fast convergence of a near-optimal solution to a given performance metric.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.2014-2023
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• 2016

Web presence is one of the key issues for extensive deployment of Internet-of-Things (IoT). An obstacle to overcome for Web presence is relatively low computing power of IoT devices. In this paper, we present implementation of an IoT platform based on Constrained Application Protocol (CoAP) which is a web transfer protocol proposed by Internet Engineering Task Force (IETF) for the low performance IoT devices such as Wireless Sensor Network (WSN) nodes and micro-controllers. To qualify the performance of CoAP-based IoT system for such an application as smart grid, we designed a test platform consisting of Raspberry Pi2, Kmote WSN node and a desktop PC. Using open source softwares, CoAP was implemented on top of the platform. Leveraging the GET command defined at CoAP specification, performance of the system was measured in terms of round-trip time (RTT) from web application to the Kmote sensor node. To investigate abnormal cases among the test results, hop-by-hop delays were measured to analyze resulting data. The average response time of CoAP-based communication except the abnormal data was reduced by 23% smaller than the previous research result.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.11-18
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• 2016

Accessing unauthorized rogue APs in WiFi environments is a very dangerous behavior which may lead WiFi users to be exposed to the various cyber attacks such as sniffing, phishing, and pharming attacks. Therefore, prompt and precise detection of rogue APs and properly alarming to the corresponding users has become one of most essential requirements for the WiFi security. This paper proposes a new rogue AP detection method which is mainly using the installation information of authorized APs and the DHCP snooping information of the corresponding switches. The proposed method detects rogue APs promptly and precisely, and notify in realtime to the corresponding users. Since the proposed method is simple and does not require any special devices, it is very cost-effective comparing to the wireless intrusion prevention systems which are normally based on a number of detection sensors and servers. And it is highly precise and prompt in rogue AP detection and flexible in deployment comparing to the existing rogue AP detection methods based on the timing information, location information, and white list information.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.183-187
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• 2020

The general Wi-Fi network connection structure is that a number of IoT (Internet of Things) sensor nodes are directly connected to one AP (Access Point) node. In this structure, the range of the network that can be established within the specified specifications such as the range of signal strength (RSSI) to which the AP node can connect and the maximum connection capacity is limited. To overcome these limitations, multiple middleware bridge technologies for dynamic scalability and load balancing were studied. However, these network expansion technologies have difficulties in terms of the rules and conditions of AP nodes installed during the initial network deployment phase In this paper, an intelligent edge computing IoT device is developed for constructing an intelligent autonomous cluster edge computing network and applying it to real-time road danger context aware and notification system through an intelligent risk situation recognition algorithm.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.63-69
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• 2020

In this paper, we propose an indoor positioning technique using the landmark based on relative Access Point (AP) signal strengths. The absolute values of AP signals are used to conventional indoor positioning technologies, but they may be different because of the difference of the measuring device, the measuring environment, and the timing of the measurements. However, we found the fact that the flow of the AP's RSSI in certain places shows almost constant patterns. Based on theses characteristics, we identify the relative strength between the APs and store the certain places as landmarks where they show certain patterns. Once the deployment of the landmark map is complete, system calculate position of user using the IMU sensor of smartphone and calibrate it with stored landmarks. Our system shows 75.2% improvement over technology that used only sensors, and 39.6% improvement over technology that used landmarks that were selected with absolute values.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.64-68
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• 2007

Commercial WiBro and 3G HSDPA services are launched last year in order to provide high speed wireless Internet access and multimedia service. Currently mobile communication service providers concentrate on the deployment of indoor mobile network since indoor traffic is remarkably increased. For fine indoor wireless communication, an installation of access point system via Public IP network which is called Femtocell is required. The development of indoor Femtocell system must be considered in the viewpoint of low hardware complexity, cost reduction, interlocking with WiBro/HSDPA network without change of network component and easy element management. In this paper, we review the implementation issue and technology of dual mode AP which provides WiBro and HSDPA signal to the user simultaneously. Especially, we describe on the HSDPA Femtocell standardization status and possible 3 types of HSDPA communication module development design. Furthermore we analyze the merits and demerits of each HSDPA Femtocell design type and propose a system which enables handover between indoor HSDPA Femtocell and outdoor commercial HSDPA mobile network.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.1-7
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• 2020

Over the past few years, Wi-Fi signal based indoor positioning system (IPS) has been researched extensively because of its low expenses of infrastructure deployment. There are two major aspects of location-related information contained in Wi-Fi signals. One is channel state information (CSI), and one is received signal strength indicator (RSSI). Compared to the RSSI, the CSI has been widely utilized because it is able to reveal fine-grained information related to locations. However, the conventional IPS that employs a single access point (AP) does not exhibit decent performance especially in the environment of non-line-of-sight (NLOS) situations due to the reliability degeneration of signals caused by multipath fading effect. In order to address this problem, in this paper, we propose a novel method that utilizes multiple APs instead of a single AP to enhance the robustness of the IPS. In our proposed method, a hybrid neural network is applied to the CSIs collected from multiple APs. By relying more on the fingerprint constructed by the CSI collected from an AP that is less affected by the NLOS, we find that the performance of the IPS is significantly improved.