• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.11
• /
• pp.2172-2178
• /
• 2007

In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.423-438
• /
• 2010

Wireless smart sensors enable new approaches to improve structural health monitoring (SHM) practices through the use of distributed data processing. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While much of the technology associated with smart sensors has been available for nearly a decade, there have been limited numbers of fulls-cale implementations due to the lack of critical hardware and software elements. This research develops a flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements. The Imote2 smart sensor platform is employed, providing the computation and communication resources that support demanding sensor network applications such as SHM of civil infrastructure. A multi-metric Imote2 sensor board with onboard signal processing specifically designed for SHM applications has been designed and validated. The framework software is based on a service-oriented architecture that is modular, reusable and extensible, thus allowing engineers to more readily realize the potential of smart sensor technology. Flexible network management software combines a sleep/wake cycle for enhanced power efficiency with threshold detection for triggering network wide operations such as synchronized sensing or decentralized modal analysis. The framework developed in this research has been validated on a full-scale a cable-stayed bridge in South Korea.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10B
• /
• pp.964-972
• /
• 2009

Wireless mesh network (WMN) is emerging a future core technology to resolve many problems derived from exist wireless networks by employing multi-interface and multi-channel. Ability to utilize multiple channels in WMNs substantially increases the effective bandwidth available to wireless network nodes. However, minimum interference channel assignment algorithms are required to use the effective bandwidth in multi-channel environments. This paper proposes a cluster-based minimum interference channel assignment (MI-CA) algorithm to improve the performance of WMN. The MI-CA algorithm is consists of Inter-Cluster and Intra-Cluster Intrchannel assignment between clusters and in the internal clusters, respectively. The Inter-Cluster channel assignment assigns a barebone channel to cluster heads and border nodes based on minimum spanning tree (MST) and the Intra-Cluster channel assignment minimizes channel interference by reassigning ortasgonal channels between cluster mespann. Our simheation results show that MI-CA can improve the performance of WMNs by minimizing channel interference.

• Journal of Communications and Networks
• /
• v.18 no.3
• /
• pp.340-350
• /
• 2016

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.2
• /
• pp.1070-1088
• /
• 2017

Recently, the applications of Internet of Things (IoTs) are growing rapidly. Wireless Sensor Network (WSN) becomes an emerging technology to provide the low power wireless connectivity for IoTs. The IPv6 over low-power wireless personal area networks (6LoWPAN) has been proposed by IETF, which gives each WSN device an IPv6 address to connect with the Internet. The transmission congestion in IoTs could be a problem when a large numbers of sensors are deployed in the field. Therefore, it is important to consider whether the WSN devices have be completely integrated into the Internet with proper quality of service (QoS) requirements. The Software Defined Network (SDN) is a new architecture of network decoupling the data and control planes, and using the logical centralized control to manage the forwarding issues in large-scale networks. In this research, the SDN-based 6LoWPAN Border Router (6LBR) is proposed to integrate the transmission from WSNs to Internet. The proposed SDN-based 6LBR communicating between WSNs and the Internet will bring forward the requirements of end-to-end QoS with bandwidth guarantee. Based on our experimental results, we have observed that the selected 6LoWPAN traffic flows achieve lower packet loss rate in the Internet. Therefore, the 6LoWPAN traffic flows classified by SDN-based 6LBR can be reserved for the required bandwidth in the Internet to meet the QoS requirements.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.2
• /
• pp.245-252
• /
• 2020

Unexpected equipment defects can cause a huge economic losses in the society at large. Although condition monitoring can provide solutions, the signal processing algorithms must be developed to predict mechanical failures using data acquired from various sensors attached to the equipment. The signal processing algorithms used in a condition monitoring requires high computing efficiency and resolution. To improve condition monitoring on a wireless sensor network(WSN), data visualization can maximize the expressions of the data characteristics. Thus, this paper proposes the extraction of visual feature from temperature data over time using condition monitoring based on a WSN to identify environmental conditions of equipment in a large-scale infrastructure. Our results show that time-frequency analysis can visually track temperature changes over time and extract the characteristics of temperature data changes.

• Smart Structures and Systems
• /
• v.7 no.3
• /
• pp.229-240
• /
• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.519-522
• /
• 2005

Decentralized Dynamic Surface Control(DDSC) for a class of nonlinear system interconnected via sensor network is presented in this paper. While a centralized design approach of DSC was developed in [1], the decentralized approach to deal with complex large-scale systems is proposed under the assumption that interconnected functions among subsystems are known via sensor network. As shown in [2], the separation principle for DDSC will allow us to design an estimation filter independently. Furthermore, the theoretical results are used to design and simulate an active vibration isolator under the assumption that many embedded sensors are distributed and communicate each other via wireless communication.

• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.6
• /
• pp.358-370
• /
• 2007

Software simulations have been widely used for the design and application development of a wireless sensor network that is an infrastructure of ubiquitous computing. In this study, we develop a sensor network simulator that can verify the behavior of sensor network applications, estimate execution time and power consumption, and simulate a large-scale sensor network. To implement the simulator, we use an instruction-level parallel discrete-event simulation method. Instruction-level simulation uses executable images loaded into a real sensor board as workload, such that it results in the high degree of details. Parallel simulation makes simulation of a large-scale sensor network possible by distributing workload into multiple computers. The simulator can predict the amount of power consumption based on operating time of modules in a sensor node and counting the number of executed instructions by kind. Also it can simulate ubiquitous applications with various scenarios and debug programs. Instruction traces used as workload for simulations are executable images produced by the cross-compiler for ATmega128L microcontroller.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.9
• /
• pp.1250-1256
• /
• 2018

Recently, wireless networks are becoming an important infrastructure for the critical large-scale applications such as cyber-physical systems and next generation industrial automations. However, the fundamental performance uncertainty of wireless networks may incur the serious instability problem of the overall systems. This paper proposes the proactive network optimizer to guarantee the application demands without any real-time link monitoring information of the networks. In particularly, the proposed proactive optimizer is the cross-layer approach to jointly optimize the routing path and traffic distribution in order to guarantee the performance demand within a maximum k number of link faults. Through the simulations, the proposed proactive network optimizer provides better robustness than the traditional existing reactive networks. Furthermore, the proactive network does not expose to the major weakness of the reactive networks such as the performance degradation due to the erroneous link monitoring information and the network reconfiguration cost.