Earticle

Over a wireless sensor network (WSN), accurate localization of sensor nodes is an important factor in enhancing the association between location information and sensory data. There are many research works on the development of a localization algorithm over three-dimensional (3D) space. Recently, the complexity-reduced 3D trilateration localization approach (COLA), simplifying the 3D computational overhead to 2D trilateration, was proposed. The method provides proper accuracy of location, but it has a high computational cost. Considering practical applications over resource constrained devices, it is necessary to strike a balance between accuracy and computational cost. In this paper, we present a novel 3D localization method based on the received signal strength indicator (RSSI) values of four anchor nodes, which are deployed in the initial setup process. This method provides accurate location estimation results with a reduced computational cost and a smaller number of anchor nodes.

The wireless sensor networks (WSNs) became a very essential tool in borders and military zones surveillance, for this reason specific applications have been developed. Surveillance is usually accomplished through the deployment of nodes in a random way providing heterogeneous topologies. However, the process of the identification of all nodes located on the network's outer edge is very long and energy-consuming. Before any other activities on such sensitive networks, we have to identify the border nodes by means of specific algorithms. In this paper, a solution is proposed to solve the problem of energy and time consumption in detecting border nodes by means of node selection. This mechanism is designed with several starter nodes in order to reduce time, number of exchanged packets and then, energy consumption. This method consists of three phases: the first one is to detect triggers which serve to start the mechanism of boundary nodes (BNs) detection, the second is to detect the whole border, and the third is to exclude each BN from the routing tables of all its neighbors so that it cannot be used for the routing.

Dynamic sensor network(DSN) technology which is based on swarming flight type air node offers analyzed and acquired information on target data gathered by air nodes in rotation flight or 3 dimension array flight. Efficient operation of dynamic sensor network based on air node is possible when problems of processing time, data transmission reliability, power consumption and intermittent connectivity are solved. Delay tolerant network (DTN) can be a desirable alternative to solve those problems. DTN using store-and-forward message switching technology is a solution to intermittent network connectivity, long and variable delay time, asymmetric data rates, and high error rates. However, all processes are performed at the bundle layer, so high power consumption, long processing time, and repeated reliability technique occur. DSN based on swarming flight type air node need to adopt store-and-forward message switching technique of DTN, the cancelation scheme of repeated reliability technique, fast processing time with simplified layer composition.

Various design schemes for network using wireless sensor nodes have been widely studied on the several application areas ranging from the real world information collection to environmental monitor. Currently, the schemes are focused on the design of sensor network for low power consumption, power-aware routing protocol, micro miniature operating system and sensor network middleware. The indoor localization system that identifies the location of the distributed nodes in a wireless sensor network requires features dealing with mobility, plurality and other environmental constraints of a sensor node. In this paper, we present an efficient location system to cope with mobility of multiple mobile nodes by designing a location handler that processes location information selectively depending on the nodes' density in a specific region. In order to resolve plurality of multiple mobile nodes, a routing method for the location system is also proposed to avoid the occurrence of overlapped location data.

본 논문은 오래된 옹벽과 같은 건축물이나 잠재적 위험을 내재한 건설 및 토목 구조물 등에 부착 가능한 블루투스 비콘 센서 노드를 활용하여 위험감지 및 대피/대처 서비스를 제공해줄 수 있는 스마트 안전 계측 시스템을 설계한다. 제안한 시스템은 블루투스 비콘을 활용하여 비콘이 설치된 지점의 가속도, 자이로, 지자계, 압력/고도, 온도/습도 등의 다양한 센서 데이터를 전송할 수 있으며 이러한 데이터를 활용하여 위험 감지, 예측, 경고 등의 다양한 서비스에 활용할 수 있다. 제안한 시스템의 실효성을 검증하기 위해 필드 테스트를 수행하였으며 옹벽의 변위값이 허용변위 38.5 mm 내에 존재한다는 것을 확인하였다.

This paper designs a smart safety measurement system with Bluetooth beacon sensor nodes that can provide risk detection and evacuation/countermeasure services. The Bluetooth beacon sensor nodes is easily able to be attached to old building wall or construction or civil structure with potential danger. The proposed smart safety measurement system transmits various sensor data such as acceleration, gyroscope, geomagnetic, pressure, altitude, temperature, humidity at the spot where Bluetooth beacon sensor nodes are installed, and we can use them for risk perception, prediction, and warning services. To verify the effectiveness of the proposed system, we performed filed tests which showed that measured displacement values of precast retaining walls were within the permitted displacement value of 38.5 mm.

본 논문에서는 센서 네트워크를 위한 Radical line을 기반으로 한 센서 노드간의 Range-free 지역화 알고리 즘에 대해 연구한다. 무선 센서 네트워크에서 라우팅 기법은 센서 네트워크의 전체적인 에너지 소모량을 감소시키거 나 모든 센서 노드들의 균등한 에너지 소비를 유도해야 한다. 특히 데이터가 전송할 데이터의 양이 많아지면 에너지 소모가 심해지는데 이를 극복하기 위한 새로운 방식들이 제안되었다. 그 결과 전체적인 에너지 소모량을 균등하게 조절할 수 있게 되었다. 이를 위해 논문에서도 적은 연산으로 주변 노드의 위치정보를 획득할 수 있는 지역화 알고 리즘을 설계한다. 알고리즘의 연산을 위해 Radical Line을 적용한다. 실험환경은 운영체제는 윈도우 7, 플랫폼은 Visual C++ 2010으로 실험하였다. 실험결과 0.1837의 에러율로 지역화를 수행할 수 있었다.

In this paper, we studied the range-free localization algorithm between sensor nodes based on the Radical Line for sensor networks. Routing in wireless sensor networks should reduce the overall energy consumption of the sensor network, or induce equivalent energy consumption of all the sensor nodes. In particular, when the amount of data to send more data, the energy consumption becomes worse. New methods have been proposed to address this. So as to allow evenly control the overall energy consumption. For this, the paper covers designing a localization algorithm that can obtain the location information of the peripheral nodes with fewer operations. For the operation of the algorithm is applicable Radical Line. The experimental environment is windows 7, the Visual C ++ 2010, MSSQL 2008. The experimental results could be localized to perform an error rate of 0.1837.

IETF에서 표준화한 6LoWPAN(IPv6 over Low Power Wireless Sensor Network)는 무선 센서 노드들의 이동성을 지원 하지 못한다. 무선 센서 노드가 CPU, 메모리, 배터리 사용에 있어 많은 제약을 받기 때문에 Mobile IPv6와 같은 기존의 프로토콜들을 적용하기 쉽지 않다. 본 논문에서는 이러한 센서 노드들의 이동성을 지원하기 위 해 핸드오버 절차 수행을 호스트가 하지 않는 FPMIPv6(Fast PMIPv6)에 대한 기존 연구 분석을 바탕으로 6LoWPAN와 연동하는 새로운 이동성 관리 구조와 방안을 제안하였다. 연동을 위해 6LoWPAN에서 현재 사용되지 않는 dispatch code pattern의 사용을 제안하였으며, 핸드오버 과정에서 인증 지연으로 발생하는 패킷 손실을 줄이고 재전송으로 인해 발생하는 센서 노드의 전력 소모를 최소화하기 위해 MAG과 MAC, MAC와 AAA 사이에 임시 보 증(temporary guarantee) 및 트러스트 관계(trust relationship)라는 새로운 개념을 도입하였다. 새롭게 제안된 인증 절차와 구조는 인증 지연으로 인한 핸드오버 절단과 패킷 손실 및 재전송을 크게 줄일 것으로 예상된다.

6LoWPAN (IPv6 over Low Power Wireless Sensor Network) standardized by IETF does not support the mobility of wireless sensor nodes. Since the wireless sensor node, subject to a lot of constraints in the CPU, memory, a battery is not easy to apply to existing protocols such as Mobile IPv6. In this paper, we propose a novel mobility management architecture and methods to work with 6LoWPAN based on the analysis on FPMIPv6 (Fast PMIPv6) the host is not a handover procedure performed in order to support the mobility of such sensor nodes. It was suggested the use of a dispatch code pattern that is not currently used in 6LoWPAN for inter-working, MAG and MAC, MAC in order to reduce packet loss caused as the authentication delay in the handover process to minimize the power consumption of a sensor node that is caused by the re-transmission the new concept of temporary guarantee (temporary guarantee) and trust relationships (trust relationship) between AAA and introduced.

사물 인터넷을 구성하는 센서 네트워크는 주변 환경의 여러 정보들을 효율적으로 수집하여 앵커 노드로 보 내기 위해서 최적의 경로를 선택하여 센서 간의 통신비용 및 수명 연장을 위해 많은 연구가 필요하다. 센서 네트워 크에서 센서노드는 저전력, 저용량을 갖는 확장 장치이다. 이들 노드들 간의 데이터 전송을 위한 라우팅 방법을 위 해 인접한 지역에 있는 앵커와 노드간의 연결은 적은 오류로 비교적 정확해야 한다. 이러한 지역화를 위한 기존의 방법 중 CA(Centroid Algorithm)는 자주 사용하는 방법이기는 하지만 오류가 자주 일어난다. 본 논문에서는 이러한 오류 발생의 문제점을 최소화하기 위해 Radical Line을 기반으로 한 센서 노드 간에 range-free 지역화 방법을 제안한다 .

The sensor network that is component of the Internet of Things require a lot of research to select the best route to send information to the anchor node, to collect a number of environment and cost efficient for communication between the sensor life. On the sensor network in one of the components of IOT's environment, sensor nodes are an extension device with low power low capacity. For routing method for data transmission between the sensor nodes, the connection between the anchor and the node must be accurate with in adjacent areas relatively. Localization CA (Centroid Algorithm) is often used although an error frequently occurs. In this paper, we propose a range-free localization method between sensor nodes based on the Radical Line in order to solve this problem.

센서 네트워크 환경에서는 센서 노드들이 수집한 정보를 전달하기 위해서 위치 정보를 필요로 한다. 무선 센서 네트워크 환경에서 각각의 센서들은 라우팅 절차를 통하여 데이터를 기지국으로 전송한다. 따라서 정확한 위치 정보를 제공하는 것이 무선 센서 네트워크에서는 가장 중요한 요인이다. 기존에 제안된 대부분의 라우팅 기법들은 주변의 1-홉(1-hop) 거리의 모든 노드의 위치 정보를 저장한다. 이러한 정보의 저장을 위해서 빈번한 정보 교환으로 불필요한 에너지 소모와 트래픽을 발생시킨다. 따라서 본 논문이 제안하는 라우팅 프로토콜은 노드의 위치 정보를 저장하지 않고, 에너지 소모를 감소시키기 위하여 주기적으로 위치 정보를 교환하지 않는다. 그리고 주변의 1-홉 거 리의 노드들을 라우팅에 참여시키지 않고 소스 노드의 전파 범위와 노드의 위치 정보에 의해 해당되는 노드들을 대 상으로 라우팅에 참여시키는 방법을 제안한다.

In order for location information to deliver the collected information, it needs Sensor Nodes in an environment of Sensor Network. Each sensor sends data to a base station through the process of routing in a wireless sensor network environment. Therefore, Offering accurate location information is very important in a wireless sensor network environment. Most of existed routing methods save all the informations of nodes at the area of 1-hop. In order to save these informations, unnecessary wasted energy and traffics are generated. Routing Protocol proposed in this paper doesn't save node's location information, and doesn't exchange any periodic location information to reduce wasted energy. It includes transmission range of source nodes and nodes with the location information, however it doesn't include any nodes' routing near 1-hope distance.

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.

Maximize coverage and prolong the network lifetime for wireless sensor networks has become one of the key topics of research. For this, put forward a kind of node scheduling strategy based on covering algorithm. The algorithm by Poisson distribution model structure node density formula, according to the node density formula in the monitoring region deploying to effective coverage; On the other hand, through the node state scheduling mechanism updates as well as to the neighbor node, can be made of residual energy of nodes and monitoring the area sensor the node energy consumption balance, so as to prolong the network lifetime goal. The simulation results show that, the algorithm cans not only useless nodes completely too effective coverage, improve the coverage while optimizing the cyber source configuration, prolong the network lifetime.

Due to the complexity of the algorithm own limitations and environmental parameters, makes for complex work in the process of localization is bigger, computational complexity, a larger error. In order to ensure the reliability and effectiveness of communication data, ensure that improve the localization accuracy, the proposed multi-channel data transmission mechanism, to realize the collection of real-time data information effectively. Based on the traditional localization algorithm principle and error source is analyzed, combined with Bayesian filtering probability model for RSSI localization algorithm was improved, the received signal strength indicator effectively restrain random fluctuations. Through to the node coordinates between areas corrections, make the final balance of signal strength. Experiments show that improved the reliability of the improved algorithm has higher localization accuracy, and shows the validity and the correctness of the algorithm.

Coverage under certain conditions, with minimum sensor nodes to complete the coverage area and connectivity in wireless sensor networks has become a challenging one with the core issues. To this end, we propose a target associated with optimal coverage and connectivity control method using a double square to the target node within the planning area within the square, correlation model obtained by the sensor node and the destination node, for the entire coverage area is the use of probability determined to meet the minimum expectations of sensor nodes under cover conditions, and gives a probability model and the reasoning process connectivity square area outside edge node. Experimental results show that the error theoretical values with the simulation results of the method is less than 7.02%, to verify the effectiveness of the algorithm, reducing the allocation of network resources, you can better assess the performance of network coverage and connectivity.

Wireless underground sensor networks (WUSN) has wide applications in environmental information monitoring. It plays a vital role in the handling and management of water resources for irrigation. Because it prevents radio interference, improves real-time acquisition of information and reduces energy consumptions. In this work, WUSN was used to collect soil temperature and moisture information of an irrigation system. The base station used the sensor nodes to collect the data in a particular area. All nodes in the networks were the same and energies were constrained. According to the schedule, WUSN nodes turn on or off their radio module to save energy. When the collected data was less than the threshold value, the base station would inform the controller perform a motor control action through setting the corresponding. In this paper, system used data fusion method for saving energy to send collected data to the base station. The testing showed that the system was successfully implemented on a real-time remote monitoring for irrigation. The result was a low cost, highly reliable and simple infrastructure for the collection of soil data over a distributed area in agricultural environments.

The deterministic energy efficient protocol for adjustable sensing range (ADEEPS) is one of the important protocols for enhancing the lifetime of a wireless sensor network. This protocol however considers the underlying network of homogeneous nature. In this paper, we propose hetADEEPS (heterogeneous ADEEPS) protocol that considers the underlying network of heterogeneous nature. The heterogeneous network model is parameterized that has 3-level heterogeneity. The proposed model can describe 1-level, 2-level and 3-leel heterogeneity and accordingly the hetADEEPS is referred as hetADEEPS-1, hetADEEPS-2 and hetADEEPS-3. The performance of the hetADEEPS is compared with that of the hetALBP. The hetALBP is Load Balancing Protocol with Adjustable sensing range (ALBP) that has the underlying network of heterogeneous nature. As the level of heterogeneity increases, the network lifetime increases. Furthermore, decreasing the value of the model parameter increases the network lifetime.

This paper presents a study of the different vulnerabilities, threats and attacks for Wireless Sensor Networks. Effective management of the threats associated with wireless technology requires a sound and thorough assessment of risk given the environment and development of a plan to mitigate identified threats. An analysis to help network managers understand and assess the various threats associated with the use of wireless technology and a number of available solutions for countering those threats are discussed.

In wireless sensor networks, network connectivity problems and sensor coverage are mainly affected by the restricted communication and sensing range of the nodes. To solve all these problems, many studies have been undertaken till now but most of these works is limited to be applied to the real environments because these do not consider various environmental factors that affect wireless sensor network deployment. In this paper, we propose a node deployment strategy that considers environmental factors and the number of nodes for surveillance .Deployment of the sensor nodes, and relay nodes considering all features of the surveillance and reconnaissance sensor networks as well as environmental factors. Smarty deploying the sensor nodes is very important if we are considering the performance of wireless sensor nodes (wsn). This paper focuses on real time deployment of sensor nodes using unmanned aerial vehicle (UAV). Smart deployment has importance in battlefield surveillance, disaster monitoring, environmental and habitat monitoring etc. It plays a very important role mainly in disasters affecting areas like flood affected or fire affected forests for sensing different conditions and physical data out there. The objective of this paper is to deploy sensor nodes smartly only in terrain of interest not in fire or water so that it can conserve environment and can reduce the loss of sensor nodes from being deploy in fire or water. Image segmentation of the images captured by camera situated on a board of UAV.. Comparison of these optimization tools SA and GFA are presented here for different images. Simulation results show that GFA performs better than SA when compared with no. of individuals and SA is faster than GFA.