Earticle

향상된 프리앰블 탐지기술인 Message In Message (MIM) 기능을 적용한 무선 센서 노드들은 캡처 효과에 의한 동시전송 기회를 최대화하여 IEEE 802.15.4를 기반으로 동작하는 기존 센서들에 비해 시스템 성능을 크게 향상시킬 수 있다. 본 논문에서는 MIM 기능을 무선 센서 노드에 적용할 경우 얻을 수 있는 성능 이득을 분석하기 위해 MIM 캡처 확률 모델을 제안하였다. 그리고 MIM 캡처 효과에 따른 성능이득을 확인하기 위해 IEEE 802.15.4 및 MIM 동시전송 기능을 파이썬으로 구현하여 시뮬레이션을 수행하였다. 성능 평가를 통해 MIM 기법 을 적용한 센서 노드는 IEEE 802.15.4 방식의 센서 노드에 비해 시스템 처리량은 34% 향상되었고 전송 지연은 31% 개선되어 전반적으로 MIM 캡처 확률 모델의 분석결과와 일치함을 확인할 수 있었다.

Wireless sensor nodes adopting the advanced preamble detection function, Message-In-Mesage (MIM), maximize the concurrent transmission opportunities due to the capture effect, result in improving the system performance significantly compared to the legacy IEEE 802.15.4 based sensor devices. In this paper, we propose an MIM capture probability model to analyze the performance gains by applying the MIM function to the wireless sensor nodes. We implemented the IEEE 802.15.4 and MIM by Python and performed extensive simulations to verify the performance gains through MIM capture effects. The evaluation results show that the MIM sensors achieve 34% system throughput gains and 31% transmission delay gains over the legacy IEEE 802.15.4-based sensors, which confirm that it was consistent with the analysis result of the proposed MIM capture probability model.

무선 센서 네트워크(WSN: Wireless Sensor Network)는 감시(surveillance), 재난 대응, 환경 모니터링 등 다양한 분야에서 활용되고 있으나, 대부분 배터리로 구동되기 때문에 에너지 효율성 확보가 핵심 과제로 부상하고 있다. 특히, 중앙집 중식 구조(centralized architecture)는 모든 센서 노드의 데이터를 중앙 처리 장치로 전송해야 하므로 통신 부하와 전력 소모가 크고, 네트워크 수명이 단축되는 문제가 있다. 이에 따라, 정확한 추적 성능을 유지하면서 에너지 소비를 최소화할 수 있는 분산형 구조(distributed architecture)의 필요성이 제기되고 있다. 본 논문에서는 비콘(beacon) 센서를 기반으로 한 WSN을 구성하고, 이동 표적을 효율적으로 추적하기 위한 에너지 효율형 분산 추적 필터(distributed tracking filter)를 제안한다. 제안된 기법은 각 센서 노드에서 실행되는 분산 칼만 필터(distributed Kalman filter)를 기반으로 하며, Wake-up/Sleeping(WuS) 메커니즘과 Valid Measurement(VM) 선별 기법을 결합하여 불필요한 센서 활성화 및 통신을 최소화한다. 시뮬레이션 결과, 제안된 방법은 통신 부하를 약 35% 감소, 에너지 소비를 최대 42% 절감하였으며, 표적의 위치 및 속도 추정에 대한 RMS 오차가 기존 중앙집중식 방식 대비 각각 18% 및 22% 개선되는 것으로 나타났다. 따라서 제안된 알고리즘은 에너지 효율성과 추적 정확도를 동시에 만족시키며, 향후 다중 표적 환경과 비선형 필터(UKF, PF) 기반 확장 등 다양한 실제 환경으로의 응용 가능성을 제시한다.

Wireless Sensor Networks (WSNs) have been widely used in surveillance, disaster monitoring, and environmental observation. However, since most WSNs operate on limited battery power, achieving energy efficiency has become a critical challenge. Centralized architectures often suffer from high communication overhead and power consumption, leading to shortened network lifetime. Therefore, a distributed architecture capable of maintaining tracking accuracy while minimizing energy usage is required. This paper proposes an energy-efficient distributed tracking filter for mobile target tracking in a beacon-based WSN. The proposed method is built upon a distributed Kalman filter and integrates a Wake-up/Sleeping (WuS) mechanism with a Valid Measurement (VM) selection scheme to reduce unnecessary sensing and communication. Simulation results show that the proposed algorithm reduces communication load by about 35% and total energy consumption by up to 42%, while improving RMS position and velocity errors by 18% and 22%, respectively, compared with the centralized method. The proposed approach effectively balances tracking accuracy and energy efficiency, and can be extended to multi-target and nonlinear filtering frameworks for practical WSN applications.

Wireless sensor networks (WSNs) operate under challenging conditions, such as maintaining message latency and the reliability of data transmission and maximizing the battery life of sensor nodes. The aim of this study is to propose a fuzzy logic algorithm for solving these issues, which are difficult to address with traditional techniques. The idea, in this study, is to employ a fuzzy logic scheme to optimize energy consumption and minimize packet drops. We demonstrated how fuzzy logic can be used to tackle this specific communication problem with minimal computational complexity. In this context, the implementation of a fuzzy logic in the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanism is achieved through filling the queue length and the traffic rate at each node. Through simulations, we show that our proposed technique has a better performance in terms of energy consumption compared to the basic implementation of CSMA/CA.

최근 무선 센서 네트워크는 다양한 분야에 적용되고 있다. 무선 센서 네트워크는 안정적인 네트워크 설계 뿐만 아니라 보안이나, 군 그리고 병원의 응급 처리에도 적용되고 있다. 이러한 다양한 응용 중에서 어떤 침입자나 위기 상황이 발생했을 경우 이를 신속히 위치를 추적하는 방법이 아주 필수적인 연구 분야가 되고 있다. 이러한 방법을 측위라고 정의하고, 센서 노드의 전파범위를 기반으로 측위를 효율적으로 처리하는 기법을 제안한다. 또한 측위를 위하여 필수적인 효율적인 클러스터링 방법과 알고리즘을 제안한다.

The use of Wireless Sensor Networks in many applications require not only efficient network design butalso broad aspects of security, military and health care for hospital. Among many applications of WSNs,target tracking is an essential research area in WSNs. We need to track a target quickly as well as findthe lost target in WSNs. In this paper, we propose an efficient target tracking method. We also propose anefficient clustering method and algorithm for target tracking.

In recent years, with the further development and more applications emerging, WSNs is no longer confined to the traditional area. Because WSNs is dynamic, distribution, resource constrained, uncertainty, complexity and heterogeneity, meanwhile distinct WSNs applications have distinct characteristics and requirements in the respective field, which both urge us to further research, especially performance evaluation of WSNs. In this paper, we expand the range of performance index which exceeds time delay, packet loss rate, and throughput. Meanwhile, put forward a non-equilibrium statistical mechanics model for integrated WSNs performance evaluation from an evolutionary perspective. A non-linear information dynamics mode is introduced based on the maximum flux principle during the modeling process. The integrated performance evaluation of WSNs can be done by giving reasonable weights of each evaluation index to stabilize the system. The new model reveals the formation pattern and the dynamics law of evolution. The proposed method has been serviced in complex simulation, and the results have indicated that the model is objective and effective.

Wireless sensor networks (WSNs) are a new kind of data acquisition technology for danger area warning to ensure the safety of personnel production operation. In order to apply the suitable wireless node localization algorithm for danger area warning,an improved CT-IPIT+ algorithm is proposed in this paper.Considered the "edge effect", the algorithm improved the interior point judgment rules which reduces the error rate of Out-To-In effectively.Through the selection of reasonable restriction threshold, the In-To-Out error is eliminated.By counting number of inside and outside judgement results, the purpose of reducing the total error rate of misjudgment is further realized.Simulation results show that the proposed algorithm can reduce the rate of two types of errors and the total error rate can be controlled under 6.3%.

Wireless Sensor Network (WSN) has become one of the cutting edge technologies, more attention has been paid to the further development and more applications emerging, WSNs is no longer confined to the traditional area. Due to the characters of dynamic, distribution, resource constrained, uncertainty, complexity and heterogeneity, we need a whole evaluation framework of WSNs performance, which can allow users choose and monitor the operation state. In this paper, we construct WSNPI architecture to rank and observe WSNs, which includes WSNPI Broker, Monitoring and WSNs Catalogue. We offer a more comprehensive evaluation index system including accountability, agility, cost, security and privacy, then build a cloud model and entropy weight method to evaluate WSNs performance. Finally, the proposed method has been serviced to complex simulation, and the results have indicated that the model is objective and effective. The first part is the research status and related problems. The second part is the establishment of an evaluation framework and model. The last part is the numerical example analysis and conclusion.

Wireless sensor network consists of a huge quantity of less-price sensor nodes. These nodes has restricted power of battery, and the replacement of battery is not a simple task in wireless sensor networks because there are a huge quantity of nodes. Data Aggregation is a significant method to attain power efficiency in wireless sensor network. Data aggregation at the sink by all the nodes results in flooding of the data which causes greatest energy utilization. Though a lot of protocols are planned so far to get better the energy efficiency further but still a lot improvement can be made. In this paper, various data aggregation techniques have been discussed. The overall purpose of this survey is to explain data aggregation techniques and to find limitations of General Self-Organized Tree-Based Energy-Balance Routing Protocol (GSTEB).

In recent years, wireless sensor network is becoming the hottest research fields, which opens up a wealth of opportunities for many application domains. Comprehensive performance of WSNs is important for planning and management of a construction network. In order to deal with the deficiency of existing evaluation methods for WSNs performance, an intelligent evaluation model based on fuzzy optimization neural network model is proposed, which introduces genetic algorithm to optimize the connection weight of the neural network model to achieve approximate optimal solution. The weights are to be regarded as initial values for the next step that a neural network is tuned finely further. Fuzzy optimization model is as activation function of the neural network, therefore the model has explicit physical meanings. This model is applied to evaluate WSNs performance of some samples, and the comparative analysis with other models shows that the model improves evaluation precision and efficiency and is practical. The first part is the research status and related problems. The second part is the establishment of evaluation model. The last part is the experimental analysis and conclusion.

Failures are inevitable in wireless sensor networks due to the fragile features and unattended deployment. To explore an effectual technique for node’s fault detection caused by energy consumption, a new algorithm, Fault Detection Technique based on Numerical Taxonomy (FDNT) is proposed in this paper. The algorithm is deployed on the sink node with unconstrained energy consumption and is on the basis of dividing WSNs into clusters according to their geographical distribution. Simulation results indicate that this algorithm can get high detection accuracy and will consume less energy.

Fault recovery is vital to WSNs since node death is a typical fault. Aiming to recover the “coverage hole”, a Recovery Algorithm based on Minimum Distance Redundant Nodes (MDRN) is proposed in this paper. By employing redundant nodes carefully, the recovery algorithm is deployed on the sink node with unconstrained energy consumption which knows the locations of all active nodes and redundant nodes in the WSNs. Simulation results demonstrate that, by choosing appropriate number of redundant nodes, this algorithm will have great recovery accuracy and coverage quality, also achieve the purpose of prolonging the lifecycle of WSNs.

Energy efficiency is one of the primary performance parametersin wireless sensor network (WSN). The data collected by neighboring nodesin the high density WSN tend to have a high correlation which isdirectly transmitted to the sink node (DGN) will seriously reduce the energy efficiency of wireless sensor networks.For improving the energy efficiency of high node density WSN, We introduce distributed source coding (DSC) which can compress the high correlation source data into WSNbased on virtual MIMO. In the simulationresults indicate thatDSC can effectively reduce the energy consumption in data transmission and improve the energy efficiencyof the whole WSN.

With maximizing the coverage time by designing effective algorithm being the core problem for large-scale network, a kind of distributed energy-aware and coverage-aware full-coverage WSN routing protocol (DEAOP) is proposed in this paper. Protocol put forward in this paper adopts the cluster technology. Firstly, divide the sensor nodes into different clusters, with each cluster selecting the cluster head (CH) according to residual energy of the nodes and overlapping degree of the coverage area, and other nodes serve as member nodes of the cluster. Secondly, establish the main data transmission line constituted by cluster head CH. The transmitted data, together with the cluster head CH, is applied to calculate the cost of neighbor cluster head, and nodes with higher cost can be taken as the forwarding node for next group of data. The cost function contains relevant information on residual energy of the nodes and path loss; hence, the higher the cost is, the greater the residual energy and the lower the path loss will be. In this case, nodes with less residual energy will not become invalid prematurely due to being selected as the cluster head CH, thus avoiding the resulting short service life of network and balancing the network energy consumption. Finally, simulate the protocol and analyze its performance in network service life, coverage rate and energy consumption. The simulation results indicate that protocol proposed in this paper can lower the energy consumption and prolong the network service life, thus improving the coverage rate.

Energy and bandwidth of the sensors in wireless sensor networks are highly valuable resources so must be used efficiently. Data aggregation on base station via entity nodes is the starting point of overflow of the information, which effect utmost power utilization. To reduce such obstacle, new data aggregation technique has been proposed called ERA which has improved the act of the wireless sensor network through the use of group-based data aggregation but still a lot improvement can be made. This term paper presents a review on various energy algorithms within clustering. And it has been found that none of the technique performs effectively in all fields. The major task of this survey is to find out the drawbacks in existing techniques and ERA. So this paper makes conclusion along with the future scope to overcome these problems.

In wireless sensor networks (WSNs), localization is one of the most important topics because the location information is typically useful for many applications. The primary data used in a localization process include the locations of anchor nodes and the distances between neighboring nodes. However, these data may contain outliers that deviate from their true values. The existence of the outliers might make the estimated positions not accurate. Thus, it is important to detect and handle outliers in order to achieve high localization accuracy. In this paper, we survey the existing outlier detection techniques for localization in wireless sensor networks. We provide taxonomy for classifying outlier detection techniques in WSNs localization based on different features. In addition, we present comparisons of these techniques. Finally, we discuss the future research directions in this area.

The single-channel wireless sensor networks (WSNs) exists the problem of low efficiency of monitoring data transmission, however the multi-channel WSNs exists the problem of communication collision caused by the sensor node’s wireless channel competition. The paper at first introduces the causes of the above problems and selects a reasonable wireless channel resources allocation method of the multi-channel WSNs. Then to solve these questions, the theory of compressive sensing and spectrum sensing are adopted to improve the existing multi-channel WSNs. Finally, a new sensor node of the multi-channel WSNs is designed based on the above improvement. By analyzing the monitoring data of the field test, the improved multi-channel WSNs could complete monitoring mission efficiently and accurately, meanwhile it reduced power consumption of the WSNs effectively.

As we all know, virtual MIMO technology is an efficient way for energy saving in wireless sensor networks (WSNs). The present virtual MIMO communication strategies in WSNs depend on cluster heads collecting and forwarding source data, which causes big energy consumption. Aiming at this problem, we propose a new virtual-MIMO communication strategy based on cooperative group (CG) in this paper, called Group Collaboration MIMO (GCMIMO). GCMIMO clusters the WSN into several clusters. Each cluster is managed by two cluster heads, master cluster head (MCH) and vice cluster head (VCH). MCH divides the source nodes into several cooperative groups, every two nodes as a group. A CG can constitute a virtual dual-antenna transmitter for sending source data of both nodes directly. VCH and MCH are always seen as a CG, called master cooperative group (MCG), which can receive and forward the data from CGs of other clusters. Unlike the existing virtual MIMO communication strategy, GCMIMO doesn’t require the cluster heads collecting the data of the source nodes, which can reduce the times of source data transmission and improve the energy efficiency. In the simulation, we analyze the energy consumption in each communication phase of GCMIMO. The results indicate that GCMIMO can effectively decrease the energy consumption in data transmission and improve energy efficiency.

With the rapid development of network information technology, manufacturing presents a development trend of networking, virtualization, intelligence and servitization. Cloud manufacturing (CMg) with a new type of service-oriented manufacturing model is put forward and excellently satisfies the development requirements of modern manufacturing enterprises. With considering the complex characteristics of cloud manufacturing, firstly, we construct Cloud manufacturing resource scheduling system architecture to schedule service task and allocate manufacturing resource, which includes user requirements, task plan, global task scheduling, service collaboration allocation, virtualization and cloud manufacturing resource. Secondly, we propose a comprehensive resource allocation model based on auctions theory to satisfy different users’ request, and then the greedy method is used to search the optimal bid in the bid set. Finally, we implement some simulation experiments, and simulation results show that the solution algorithm of CARA’s winner determination problem gets the same solution as the M-HEU algorithm with less time complexity, and it is more applicable, efficient and effective for online multi-resource allocation.