Earticle

This paper describes self-sustainable IoT sensor node using 263 MHz wireless power harvesting and dynamic power management techniques. Wireless power harvesting system charges the sensor node battery using the master node’s output signal. The output voltage of the RF-DC converter, based on the injection-locked oscillator, is higher than the input peak voltage. Therefore, the sensor node’s power harvesting range is improved to –10dBm, which is the power input (when the sensor node is located) at 13meter from the master node (263MHz, 26dBm output). when the input ID matched with the slave node, the power switch is turned on to the main operation devices (sensor, MCU, transmission), otherwise, the power switch is turned to battery charging.

본 논문은 최근 저전력 요구가 중요시되는 센서네트워크의 센서 노드에 사용되는 프로세서에 관한 것이다. TI 사의 MSP430 프로세서 코어와 호환되는 프로세서를 비동기식 설계 기법을 적용하여 마이크로 컨트롤러 자체를 저전력화한다. 프로세서 코어 내부의 제어 로직을 AFSM (Asynchronous Finite State Machine)으로 기술하고 비동기전용 합성툴을 사용하여 게이트 수준으로 설계하였으며, 데이터 패스 로직은 동기식의 것과 동일하게 설계 하였다. 마지막으로 설계된 프로세서 코어를 게이트 수준에서 동기식 방법과 성능 및 에너지 소모를 비교하였다. 또한, 특화된 비동기식 언어를 사용한 상위수준 합성 방법으로 설계된 동일한 프로세서 코어와도 성능, 에너지 소모을 비교하였다. 0.13 um 공정에서 ideal 클록을 가정한 시뮬레이션 결과, 동기식에 비해서는 성능은 동일하였고 에너지는 31.9 % 덜 소모하였다. 상위수준 합성 방법의 비동기식 설계 방법과는 2.7배 성능이 향상되었고, 28.8 % 에너지를 덜 소모하는 것을 확인하였다.

With clockless design method an asynchronous version of MSP430 processor core was designed to pursuethe reduction of power consumption. We use data path of synchronous design without change, and, for controlpath, we described inner control logics using asynchronous finite state machine (AFSM) and generated gatelevel netlist. The asynchronous version of MSP430 core was compared with an already designedasynchronous MSP430 core which employed the high-level asynchronous tool flow based on a specializedlanguage and a clock based synchronous MSP430 core at 0.13 um CMOS technology. The maximumperformance of the high-level tool flow version was only 40.6 % of the synchronous or the AFSM version.The AFSM version saves the energy consumption of the synchronous version and the TiDE tool version byabout 31.9 % and 28.8 %, respectively.

A context-aware services platform supporting mobile agents consists of sensor nodes and a sensor coordinator. Sensor nodes collect environmental information and transmit the collected information to the sensor coordinator through wireless sensor networks. The sensor coordinator passes the information to the context-aware service module, and the mobile agent. The context-aware service module or the mobile agent performs services suitable for a user's situation based on the environmental information and a service actuation message is delivered to an actuation node through the sensor coordinator. In this paper, we present a context-aware services platform structure employed in our project, and describe context-aware services platform interfaces with a context-aware service module and mobile agents.

Wireless sensor networks(WSN) technology has various applications such as surveillance and information gathering in the uncontrollable area of human. One of major issues in WSN is the research for reducing the energy consumption and reliability of data. A system with forward error correction(FEC) can provide an objective reliability while using less transmission power than a system without FEC. In this paper, we propose to use LDPC codes of various code rate(0.53, 0.81, 0.91) for FEC for WSN. Also, we considered node-to-node interference in addition to AWGN channel. The proposed system has not only high reliable data transmission at low SNR, but also reduced transmission power usage.

무선 센서 네트워크의 수명 및 성능은 각 센서 노드들의 에너지 효율과 밀접한 관련이 있다. 본 논문에서는 센서 노드의 에너지 효율을 높이기 위해 센서 노드의 동작 상태를 정상, 절전, 및 비활성 모드로 나눈다. 정상 모드 로 동작하는 센서 노드는 정상 주기로 센싱 및 데이터 전송을 하지만, 절전 모드에서는 그 주기를 늘임으로써 에너 지 소비를 줄인다. 센싱 및 데이터 전송을 하지 않는 비활성 모드에서는 에너지 소비가 최소화된다. 또한, 제안 알고 리즘은 센싱 데이터가 이전의 값과 동일할 경우 전송을 하지 않음으로써 불필요한 에너지 소비를 줄일 수 있다. 제 안 알고리즘은 Tiny OS 기반의 ZigbeX 플랫폼에 구현되었으며, NS-2를 사용하여 그 성능을 분석하였다. 성능 분석 결과 제안 알고리즘이 전체 센서 노드의 에너지 소비 및 그 표준편차를 효율적으로 줄임으로써 무선 센서 네트워크 의 수명을 향상시킬 수 있음을 확인하였다.

The life-time and performance of a wireless sensor network is closely related to energy-efficiency of sensor nodes. In this paper, to increase energy-efficiency, each sensor node operates in one of three operational modes which are normal, power-saving, and inactive. In normal mode sensor nodes sense and transmit data with normal period, whereas sensor nodes in power-saving mode have three-times longer period. In inactive mode, sensor nodes do not sense and transmit any data, which makes the energy consumption to be minimized. Plus, the proposed algorithm can avoid unnecessary energy consumption by preventing transmitting duplicate sensed data. We implemented and simulated the proposed algorithm using Tiny OS based ZigbeX platfom and NS-2, respectively. Performance evaluation results show that the proposed algorithm can prolong sensor networks' lifespan by efficiently reducing energy consumption and its standard deviation of all sensor nodes.

최근 저가격의 소형화, 저전력 기술과 인터넷을 이용하여 통신이 가능한 스마트 센서의 기술의 발달에 힘입어 사물인터넷이 발전하고 있다. 특히 사물인터넷 (Internet of Things : IoT) 기반에서의 안전한 정보 전송을 위한 키 관리 관련 연구가 활발히 진행되고 있다. 그러나 사물인터넷은 센서를 이용한다. 그렇기 때문에 저전력과 저용량 등의 제약이 심하며, 결과적으로 일반적인 보안의 방법으로 키를 관리하기 어렵다. 그러나 사물인터넷의 지속적 발전을 위해서는 안전한 키 관리의 문제는 필수적 해결과제이다. Diffi-Hellman 키 교환방식은 센서노드에 적합하지 않아 본 논문에서는 효율적인 키 관리하는 것을 제안한다. 따라서 본 논문에서는 IoT기반에서 통신을 위한 키 생성을 통해 물리적 제약받지 않고 사물간 안전한 통신 기술을 제안한다.

Recently, the Internet of Things are developing in accordance with the technology of implementation in low-cost, small-size, low power consumption and smart sensor that can communicate using the internet. Especially, key management researches for secure information transmission based on the Internet of Things (IoT) are actively performing. But, Internet of Things(IoT) are uses sensor. Therefore low-power consumption and small-memory are restrictive condition. As a result, managing the key is difficult as a general security measure. However, The problem of secure key management is an essential challenge For the continuous development of the Internet of things. In this paper, we propose a key distribution and management technique in secure Internet of things. In the key generation and management stage, it satisfies the conditions and without physically constrained for IoT based communication.

기존 연구에서 에너지 소비의 효율성을 향상하기 위해 제시된 무선 센서 네트워크의 라우팅 기법은 다양하게 존재하지만 라우팅을 위해서는 자신의 위치 정보와 1 홉(hop) 거리에 인접한 주변 노드들의 위치 정보를 유지해야 한다. 그리고 BS 노드로 데이터를 전송하기 위하여 여러 노드를 경유하여 목적지까지 전송하는 다중 홉(Multi-hop) 전송 방식을 사용한다. 이러한 기법은 네트워크의 전체적인 에너지 소모와 센서 노드의 전력 소모를 발생시켜 효율적인 에너지 관리에 문제가 발생한다. 따라서 본 논문에서는 센서 노드의 전파 범위와 RSSI를 이용하여 소스 노드와 거리 ±α를 만족하는 BS 노드의 위치 기반 1-홉 라우팅 기법을 제안한다.

Routing technique of wireless sensor network that is presented to improve effectiveness of consumption in energy at the previous study is existing in various ways, however for routing, its own location data and nodes' location data close to with 1-hop distance should be kept. And it uses multi-hop transmission method that transmits data to BS node via several nodes. This technique makes electronic consumption of sensor node and entire network's energy consumption so that it makes effective energy management problem. Therefore, this paper suggests location based 1-hop routing technique of BS node that satisfies distance ±α with source node using RSSI and radio wave range of sensor node.

다양한 공격 대응을 위해 효과적이고 효율적인 방법으로 네트워크와 정보시스템의 취약성을 평가하는 일은 매우 중요하게 여겨지고 있다. 그러나 네트워크와 정보시스템의 취약성 및 위험 평가 방법론은 센서 네트워크에 직접 적용하기가 어렵다. 왜냐하면 센서 네트워크는 전통적인 네트워크와 정보시스템과 비교해 다른 특성을 지니고 있기 때문이다. 본 연구 논문은 클러스터 기반 센서 네트워크에서의 취약성 평가 프레임워크를 제안하고 있다. 센서 네트워크에서 취약성을 평가하며 몇 가지 케이스를 통해 클러스터 기반 센서 네트워크의 취약성 평가 프레임워크의 실효성을 증명해 보인다

is important to assess vulnerability of network and information system to countermeasure against a variety of attack in effective and efficient way. But vulnerability and risk assessment methodology for network and information systems could not be directly applied to sensor networks because sensor networks have different properties compared to traditional network and information system. This paper proposes a vulnerability assessment framework for cluster based sensor networks. The vulne-rability assessment for sensor networks is presented. Finally, the case study in cluster based sensor networks is described to show possibility of the framework.

With the technological development of the Internet of Things (IoT), a wide variety of IoT-based monitoring systems have been developed in various domains. An IoT-based monitoring system provides an administrator with efficient management and information collection. Due to such advantages, the demand for monitoring systems in the gas industry domain has dramatically increased. In this paper, we propose two kinds of novel gateways and sensor nodes that apply an object identifier (OID) to monitor gas facilities. The proposed gateways and sensor nodes collect gas and environment data with various sensors and communicate with a monitoring server. If an exceptional event happens at the inspection site where our devices are installed, sensor nodes can take action by issuing control commands from the monitoring server. Moreover, we have also designed an OID that provides resources and devices in a gas monitoring system with a unique identification. By applying an OID to each message for transmission among sensor nodes, gateways, and monitoring servers, gas facilities and related devices can be accurately and safely managed. To evaluate the proposed devices, we properly installed our gateways and sensor nodes near operating gas facilities and verified their operation.

A Wireless Sensor Network (WSN) is a network of distributed sensors that can collect information from a physical environment. Low-cost sensors are the backbone of a WSN. Maximizing the lifetime of sensor networks is the main challenge of a Wireless Sensor Network (WSN), such as the sensor node of the network needs to be prepared with limited battery power. This paper focuses on finding the optimal sink position. Relay nodes have been introduced in conjunction with the sensor nodes to mitigate network geometric deficiencies since in most other approaches the sensor nodes close to the sink become heavily involved in data forwarding and, thus, their batteries are quickly depleted. A Biogeography-Based Optimization (BBO) algorithm is used to locate the optimal sink position with respect to those relay nodes to make the network more energy efficient. The relay nodes communicate with the sink instead of the sensor nodes. Tests show that this approach can save at least 40% of the energy and prolong the network lifetime.

The separate situation of research has area coverage or target coverage in wireless sensor networks. Based on directional sensing model the algorithm used the virtual potential field to make the sensor nodes shift positions and change directions automatically in monitoring area, With the completion of multiple prior coverage of hot targets which needed higher quality requirements the algorithm could maximize the coverage rate throughout the monitoring area Simulation experiments show that the algorithm has a good ability of self-organizing. It can satisfy the requirements of coverage quality of the hot targets and the whole monitoring area and save resources effectively of the network.

Structural health monitoring (SHM) is the science of assessing the integrity of structures such as buildings, bridges and aerospace structures. SHM systems strive to detect and locate damage in structures as early as possible. Today most automated SHM system has been suggested that wireless sensing can potentially bring about a dramatic reduction in cost by doing away with the cabling cost. Self-organizing dense wireless sensor networks that are cheap and easy to install can potentially bring significant benefits to SHM systems. This paper introduces a wireless sensor network system based SHM, the system includes the self-developed sensor node for SHM and the artificial intelligence routing for data transmission. Using offline processing and online processing methods in artificial intelligence routing, it can discovery backbone for wireless sensor networks with low average dissipated energy and average delay.