• Title/Summary/Keyword: Network life-time

Search Result 601, Processing Time 0.031 seconds

Zigbee-based Local Army Strategy Network Configurations for Multimedia Military Service

  • Je, Seung-Mo
    • Journal of Multimedia Information System
    • /
    • v.6 no.3
    • /
    • pp.131-138
    • /
    • 2019
  • With the rapid evolution of communication technology, it became possible to overcome the spatial and temporal limitations faced by humans to some extent. Furthermore, the quality of personal life was revolutionized with the emergence of the personal communication device commonly known as the smart phone. In terms of defense networks, however, due to restrictions from the military and security perspectives, the use of smart phones has been prohibited and controlled in the army; thus, they are not being used for any defense strategy purposes as yet. Despite the current consideration of smart phones for military communication, due to the difficulties of network configuration and the high cost of the necessary communication devices, the main tools of communication between soldiers are limited to the use of flag, voice or hand signals, which are all very primitive. Although these primitive tools can be very effective in certain cases, they cannot overcome temporal and spatial limitations. Likewise, depending on the level of the communication skills of each individual, communication efficiency can vary significantly. As the term of military service continues to be shortened, however, types of communication of varying efficiency depending on the levels of skills of each individual newly added to the military is not desirable at all. To address this problem, it is essential to prepare an intuitive network configuration that facilitates use by soldiers in a short period of time by easily configuring the strategy network at a low cost while maintaining its security. Therefore, in this article, the author proposes a Zigbee-based local strategic network by using Opnet and performs a simulation accordingly.

Clustering Triangular Routing Protocol in Wireless Sensor Network (무선 센서 네트워크에서 삼각 클러스터링 라우팅 기법)

  • Nurhayati, Nurhayati;Lee, Kyung Oh;Choi, Sung Hee
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2010.11a
    • /
    • pp.913-916
    • /
    • 2010
  • Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors send data from CH (Cluster Head) and then to BS (Base Station). BCDCP works well in small-scale network but in large scale network it is not appropriated since it uses much energy for long distance wireless communication. We propose a routing protocol - Triangular Clustering Routing Protocol (TCRP) - to prolong network life time through the balanced energy consumption. TCRP selects cluster head of triangular shape. The sensor field is divided into energy level and in every level we choose one node as a gate node. This gate node collects data and sends it to the leader node. Finally the leader node sends the aggregated data to the BS. We show TCRP outperforms BCDCP with several experiments.

A Design of RFID based Product Lifecycle Management System (RFID 기반 상품의 효율적 라이프사이클관리를 위한 통합시스템 설계)

  • Kim, Dong-Min;Lee, Jong-Tae
    • IE interfaces
    • /
    • v.19 no.4
    • /
    • pp.333-341
    • /
    • 2006
  • RFID (Radio Frequency Identification) is a technology that can input identification information to microchip and make goods, animals, persons recognized, chased, and managed using radio frequency, and is founded on the core technology of ubiquitous environment of the future. In this paper, we propose a RFID integrated system designed to manage the lifecycle of an individual product efficiently. The proposed system can enable traceability and visibility of items through their entire life by integrating distribution and banking information on the basis of EPCglobal Network. It may provide the infra of Digital Manufacturing and RTE (Real Time Enterprise) and effective information sharing structure with existing legacy system (ERP, CRM, SCM) by real time.

Abnormal Crowd Behavior Detection Using Heuristic Search and Motion Awareness

  • Usman, Imran;Albesher, Abdulaziz A.
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.4
    • /
    • pp.131-139
    • /
    • 2021
  • In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

Analysis of Odor Data Based on Mixed Neural Network of CNNs and LSTM Hybrid Model

  • Sang-Bum Kim;Sang-Hyun Lee
    • International Journal of Advanced Culture Technology
    • /
    • v.11 no.4
    • /
    • pp.464-469
    • /
    • 2023
  • As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

Fault state detection and remaining useful life prediction in AC powered solenoid operated valves based on traditional machine learning and deep neural networks

  • Utah, M.N.;Jung, J.C.
    • Nuclear Engineering and Technology
    • /
    • v.52 no.9
    • /
    • pp.1998-2008
    • /
    • 2020
  • Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

A Study on The Phenomenal Space in The Contemporary Architecture - Focus on the analysis of The architecture of Swiss architects - (현대 건축에서 나타난 현상적 공간에 관한 연구 - 스위스건축가 작품을 중심으로 -)

  • Lee, Kil-Ho;Lee, Jung-Wook
    • Korean Institute of Interior Design Journal
    • /
    • v.22 no.6
    • /
    • pp.79-87
    • /
    • 2013
  • The purpose of this study clarifies an expression characteristic of the phenomenal space. The architecture is an interface between human and nature. Nature presents herself as phenomena. Thus, the phenomenal space should be approached as the essence of architecture that is to accommodate nature. Phenomenon is related to everyday life and shares flow naturally within it. The phenomenon and everyday life form a relationship through the mediating elements that are time, place, and image. If these mediating elements are developed as spatialized elements, time becomes the converse, place becomes the overlap, and shape becomes the revealing. Also, spatial components that are substituted with these elements are void/solid, form, and materials. The relational characteristics of phenomenal space can be identified through these, and such characteristics are one-ness, continuity, and coincidence of opposites. Phenomenal space is expressed with spatial tones and accepted as spatial atmospheres. For the analysis, 15 works of swiss architects were selected to which spatial elements were applied. And It were composed that analysis by arranging these components as the relational network found that expression characteristics. Trough the analysis, It was found that expression characteristics of phenomenal space of the architecture of Swiss architects were prototypicality, primitiveness, and originality. As a results, It is considered that the role of the space that contains the value of everyday life, the value of the phenomenon is necessary.

Ensemble Based Optimal Feature Selection Algorithm for Efficient Intrusion Detection in Wireless Sensor Network

  • Shyam Sundar S;R.S. Bhuvaneswaran;SaiRamesh L
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.18 no.8
    • /
    • pp.2214-2229
    • /
    • 2024
  • Wireless sensor network (WSN) consists of large number of sensor nodes that are deployed in geographical locations to collect sensed information, process data and communicate it to the control station for further processing. Due the unfriendly environment where the sensors are deployed, there exist many possibilities of malicious nodes which performs malicious activities in the network. Therefore, the security threats affect performance and life time of sensor networks, whereas various security aspects are there to address security issues in WSN namely Cryptography, Trust Management, Intrusion Detection System (IDS) and Intrusion Prevention Systems (IPS). However, IDS detect the malicious activities and produce an alarm. These malicious activities exploit vulnerabilities in the network layer and affect all layers in the network. Existing feature selection methods such as filter-based methods are not considering the redundancy of the selected features and wrapper method has high risk of overfitting the classification of intrusion. Due to overfitting, the classification algorithm fails to detect the intrusion in better manner. The main objective of this paper is to provide the efficient feature selection algorithm which was suitable for any type classification algorithm to detect the intrusion in an effective manner. This paper, the security of the network is addressed by proposing Feature Selection Algorithm using Chi Squared with Ensemble Method (FSChE). The proposed scheme employs the combination of decision tree along with the random forest classification algorithm to form ensemble classifier. The experimental results justify the feasibility of the proposed scheme in terms of attack detection, packet delivery ratio and time analysis by employing NSL KDD cup data Set. The obtained results shows that the proposed ensemble method increases the overall performance by 10% to 25% with respect to mentioned parameters.

Energy-Aware Routing Protocol for Mobile Ad Hoc Network (노드의 여유 에너지 기반 이동 Ad Hoc 네트워크의 라우팅 프로토콜)

  • Kwon, Soo-Kun
    • Journal of Korea Multimedia Society
    • /
    • v.8 no.8
    • /
    • pp.1108-1118
    • /
    • 2005
  • A mobile Ad Hoc network is a dynamic mobile wireless network that can be formed without the need for any pre-existing wired or wireless infrastructure. A mobile ad hoc node has limited battery capacity. Hence, Ad Hoc routing protocol ought to be energy conservative. Previous energy aware routing has limit in fairness among nodes and network wide power consumption. In this research, we propose a new routing protocol called Clustering Based Energy-Aware Routing(CBEAR) which can improve the problems. Simulation results show that the routing protocol improves fairness and network wide power consumption as well as life time of nodes.

  • PDF

Performance Evaluation of Transmitting Brainwave Signals in Ad-Hoc Network at Medical Center (의료센터의 애드혹망에서 뇌파전송 성능평가)

  • Jo, Jun-Mo
    • The Journal of the Korea Contents Association
    • /
    • v.10 no.12
    • /
    • pp.216-222
    • /
    • 2010
  • To improve the quality of life, wireless ad-hoc network technologies are considered as one of the key research areas in computer science and healthcare application industries. The ubiquitous healthcare systems also provide alerting mechanisms against ill conditions in real time. This minimizes the need for care-givers and helps the chronically ill and elderly to survive. For the application of the system, supporting the efficient and proper network system is essential. So in this paper, I suggest some hospital network environments including patient mobile nodes continuously sending brainwaves to the server of the hospital area. Finally, the network systems are simulated by OPnet simulator and evaluate the performance among various mobility of the mobile nodes and topologies of the network for the efficient system.