Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323629
M. Al-Absi, A. Al-Absi, Young Jin Kang, Hoon-Jae Lee
In Vanet, Secure and Smart Intelligent Transport System (SSITS) support both safety and non-safety applications in terms of throughput and collision performance. In vehicle to vehicle (V2V) communication, the network should provide a good throughput and should reduce collision. To provide an efficient throughput for V2V communication under different environments (such as City, Highway, and Rural), a good radio propagation model is required in order to support the real-time implementation. The existing radio propagation path loss models for V2V network adopt mean additional attenuation sophisticated obstacle fading model such as Nakagami, Log normal and so on. These models do not consider the effects of the vehicle in modeling LOS among transmitter and receiver and also do not consider evaluation under different environments. The presence of Line of sight (LOS) component (such as reflection or diffraction) requires the amplification of signal or power. Due to this, here we present an efficient radio propagation path loss model considering the obstacle in LOS (vehicle) under different environmental conditions in the presence of LOS. The experiments are conducted to evaluate the performance of the proposed model in terms of throughput and collision considering a varied number of vehicles under City, Highway and rural environments. The result shows that the proposed model is efficient considering varied density.
{"title":"Obstacles effects on signal attenuation in line of sight for different environments in V2V communication","authors":"M. Al-Absi, A. Al-Absi, Young Jin Kang, Hoon-Jae Lee","doi":"10.23919/ICACT.2018.8323629","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323629","url":null,"abstract":"In Vanet, Secure and Smart Intelligent Transport System (SSITS) support both safety and non-safety applications in terms of throughput and collision performance. In vehicle to vehicle (V2V) communication, the network should provide a good throughput and should reduce collision. To provide an efficient throughput for V2V communication under different environments (such as City, Highway, and Rural), a good radio propagation model is required in order to support the real-time implementation. The existing radio propagation path loss models for V2V network adopt mean additional attenuation sophisticated obstacle fading model such as Nakagami, Log normal and so on. These models do not consider the effects of the vehicle in modeling LOS among transmitter and receiver and also do not consider evaluation under different environments. The presence of Line of sight (LOS) component (such as reflection or diffraction) requires the amplification of signal or power. Due to this, here we present an efficient radio propagation path loss model considering the obstacle in LOS (vehicle) under different environmental conditions in the presence of LOS. The experiments are conducted to evaluate the performance of the proposed model in terms of throughput and collision considering a varied number of vehicles under City, Highway and rural environments. The result shows that the proposed model is efficient considering varied density.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123771737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323819
Antoine Gnansounou, S. Ouya, Raimy Abd. Toure
This work describes the dimensioning process of LTE access network for an ISP, its models, methods and the tool used to dimension the network. LTE is a system with larger bandwidths (up to 20 MHz), low latency and Packet optimized radio access technology having peak data rates of 100 Mbps in downlink and 50 Mbps in the uplink. Radio access technology for LTE is OFDM (Orthogonal frequency division multiplexing) that provides higher spectral efficiency and more robustness against mulitpath and fading, as compared to CDMA (Code division multiple access). In order to offer the operators increased flexibility in network deployment, the LTE system supports bandwidth scalability and both FDD and TDD duplexing methods. The main objectives of our research was the identification of LTE features relevant for the dimensioning, to define the basic models for Access Network Dimensioning to estimate Coverage needs of the infrastructure, the Network Element Count Estimation and the Capacity Evaluation.
{"title":"Advanced LTE network deployment methodology: A case study for Dakar region","authors":"Antoine Gnansounou, S. Ouya, Raimy Abd. Toure","doi":"10.23919/ICACT.2018.8323819","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323819","url":null,"abstract":"This work describes the dimensioning process of LTE access network for an ISP, its models, methods and the tool used to dimension the network. LTE is a system with larger bandwidths (up to 20 MHz), low latency and Packet optimized radio access technology having peak data rates of 100 Mbps in downlink and 50 Mbps in the uplink. Radio access technology for LTE is OFDM (Orthogonal frequency division multiplexing) that provides higher spectral efficiency and more robustness against mulitpath and fading, as compared to CDMA (Code division multiple access). In order to offer the operators increased flexibility in network deployment, the LTE system supports bandwidth scalability and both FDD and TDD duplexing methods. The main objectives of our research was the identification of LTE features relevant for the dimensioning, to define the basic models for Access Network Dimensioning to estimate Coverage needs of the infrastructure, the Network Element Count Estimation and the Capacity Evaluation.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126994716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323645
Nishat I. Mowla, Inshil Doh, K. Chae
Biometric features are widely used for user authentication and equally important to national and global technology systems. Various forms of biometric features, such as face, iris, fingerprint, are commonly used while more recently palm, vein and gait are also getting attention. Simultaneously various spoofing approaches have also been developed over time, which are capable of failing traditional biometric detection systems. Image synthesis with play-doh, gelatin, ecoflex etc. are some of the ways used in spoofing bio-identifiable property. Success of traditional detection systems are related to custom tailored solutions where feature engineering for each attack type must be developed. This is not a feasible process when we consider countless attack possibilities. Also, a slight change in the attack can cause the whole system to be redesigned and therefore becomes a limiting constraint. The recent success of machine learning inspires this paper to explore weak and strong learners with ensemble learning approaches using AdaBoost. Therefore, the paper proposes a selective ensemble fuzzy learner approach using Ada Boost, feature selection and combination of weak and strong learners to enhance the detection of bio-identifiable modality spoofing. Our proposal is verified on real dataset, LiveDet 2015, with a focus on fingerprint modality spoofing detection that can be used for authentication in Medical Cyber Physical Systems (MCPS).
{"title":"Selective fuzzy ensemble learner for cognitive detection of bio-identifiable modality spoofing in MCPS","authors":"Nishat I. Mowla, Inshil Doh, K. Chae","doi":"10.23919/ICACT.2018.8323645","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323645","url":null,"abstract":"Biometric features are widely used for user authentication and equally important to national and global technology systems. Various forms of biometric features, such as face, iris, fingerprint, are commonly used while more recently palm, vein and gait are also getting attention. Simultaneously various spoofing approaches have also been developed over time, which are capable of failing traditional biometric detection systems. Image synthesis with play-doh, gelatin, ecoflex etc. are some of the ways used in spoofing bio-identifiable property. Success of traditional detection systems are related to custom tailored solutions where feature engineering for each attack type must be developed. This is not a feasible process when we consider countless attack possibilities. Also, a slight change in the attack can cause the whole system to be redesigned and therefore becomes a limiting constraint. The recent success of machine learning inspires this paper to explore weak and strong learners with ensemble learning approaches using AdaBoost. Therefore, the paper proposes a selective ensemble fuzzy learner approach using Ada Boost, feature selection and combination of weak and strong learners to enhance the detection of bio-identifiable modality spoofing. Our proposal is verified on real dataset, LiveDet 2015, with a focus on fingerprint modality spoofing detection that can be used for authentication in Medical Cyber Physical Systems (MCPS).","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127625015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323811
Abdelhamied A. Ateya, A. Muthanna, A. Koucheryavy
There is no doubt that the release of the fifth generation of the mobile cellular system (5G) becomes a great demand year by year, especially with the massive increase of heterogeneous Wireless devices. The 5G network will be a platform for wide variety of industries. Designing of 5G cellular system faces various challenges related to the capacity and traffic. One way to solve these challenges is to employ device-to-device (D2D) communication and mobile edge computing (MEC). Employing these technologies offload the core network and increase the capacity of the system. In this work, we propose a frame work for the 5G cellular system based on D2D communication and multi-level cloud units employed at the edge of the cellular network. The system employs four levels of cloud units with various hardware capabilities. The D2D communication is used as the communication technology in the first level of clouds. Employing D2D together with multi-level edge cloud units achieves varies benefits to the system as the system level simulation provides.
{"title":"5G framework based on multi-level edge computing with D2D enabled communication","authors":"Abdelhamied A. Ateya, A. Muthanna, A. Koucheryavy","doi":"10.23919/ICACT.2018.8323811","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323811","url":null,"abstract":"There is no doubt that the release of the fifth generation of the mobile cellular system (5G) becomes a great demand year by year, especially with the massive increase of heterogeneous Wireless devices. The 5G network will be a platform for wide variety of industries. Designing of 5G cellular system faces various challenges related to the capacity and traffic. One way to solve these challenges is to employ device-to-device (D2D) communication and mobile edge computing (MEC). Employing these technologies offload the core network and increase the capacity of the system. In this work, we propose a frame work for the 5G cellular system based on D2D communication and multi-level cloud units employed at the edge of the cellular network. The system employs four levels of cloud units with various hardware capabilities. The D2D communication is used as the communication technology in the first level of clouds. Employing D2D together with multi-level edge cloud units achieves varies benefits to the system as the system level simulation provides.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133675619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323669
Kwihoon Kim, Yong-Geun Hong, Youn-Hee Han
Artificial Intelligence (AI) technology has made remarkable achievements in various fields. Especially, deep learning technology that is the representative technology of AI, showed high accuracy in speech recognition, image recognition, pattern recognition, natural language processing and translation. In addition, there are many interesting research results such as art, literature and music that cannot be distinguished whether it was made by human or AI. In the field of networks, attempts to solve problems that have not been able to be solved or complex problems using AI have started to become a global trend. However, there is a lack of data sets to apply machine learning to the network and it is difficult to know network problem to solve. So far, there have been a lot of efforts to study network machine learning, but there are few studies to make a necessary dataset. In this paper, we introduce basic network machine learning technology and propose a method to easily generate data for network machine learning. Based on the data generation framework proposed in this paper, the results of automatic generation of labelled data and the results of learning and inferencing from the corresponding dataset are also provided.
{"title":"General labelled data generator framework for network machine learning","authors":"Kwihoon Kim, Yong-Geun Hong, Youn-Hee Han","doi":"10.23919/ICACT.2018.8323669","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323669","url":null,"abstract":"Artificial Intelligence (AI) technology has made remarkable achievements in various fields. Especially, deep learning technology that is the representative technology of AI, showed high accuracy in speech recognition, image recognition, pattern recognition, natural language processing and translation. In addition, there are many interesting research results such as art, literature and music that cannot be distinguished whether it was made by human or AI. In the field of networks, attempts to solve problems that have not been able to be solved or complex problems using AI have started to become a global trend. However, there is a lack of data sets to apply machine learning to the network and it is difficult to know network problem to solve. So far, there have been a lot of efforts to study network machine learning, but there are few studies to make a necessary dataset. In this paper, we introduce basic network machine learning technology and propose a method to easily generate data for network machine learning. Based on the data generation framework proposed in this paper, the results of automatic generation of labelled data and the results of learning and inferencing from the corresponding dataset are also provided.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"5 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130655305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323761
Minkyu Kim, Kihwan Kim, Hoonjae Lee
Recently, industrial and national infrastructure suffered economic losses due to internal leaks caused by insider leaks and key data leaks. As a result, many companies applying not only physical external and internal penetration methods, but also software, machine learning, and other methods to detect people's abnormal behaviour. This paper surveys trends and forecasts of the intrusion detection techniques by categorizing into basic software and machine learning technique.
{"title":"Development trend of insider anomaly detection system","authors":"Minkyu Kim, Kihwan Kim, Hoonjae Lee","doi":"10.23919/ICACT.2018.8323761","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323761","url":null,"abstract":"Recently, industrial and national infrastructure suffered economic losses due to internal leaks caused by insider leaks and key data leaks. As a result, many companies applying not only physical external and internal penetration methods, but also software, machine learning, and other methods to detect people's abnormal behaviour. This paper surveys trends and forecasts of the intrusion detection techniques by categorizing into basic software and machine learning technique.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130662132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323683
WooNam Sung, Hyeong-Geun Ahn, Jong-Beom Kim, S. Choi
In this paper, we propose a method to protect end-device by using RSSI and Hand-Shaking technique using Proprietary Message. One of the frequently used attacks in LoRaWAN is replay attack. It is so easy to sniff packets in a wireless network environment. If an attacker intrudes a service provided by LoRaWAN, the usage pattern of the end-device may be exposed, or a replay attack may cause a problem in connection with the user. To prevent replay attack, LoRaWAN standard uses user identification method by using the value known as DevNonce, but this is not a complete countermeasure. In order to complement these vulnerabilities, we propose a method to protect users by using the physical characteristics of a network called RSSI and a new technique called Proprietary Hand-Shaking.
{"title":"Protecting end-device from replay attack on LoRaWAN","authors":"WooNam Sung, Hyeong-Geun Ahn, Jong-Beom Kim, S. Choi","doi":"10.23919/ICACT.2018.8323683","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323683","url":null,"abstract":"In this paper, we propose a method to protect end-device by using RSSI and Hand-Shaking technique using Proprietary Message. One of the frequently used attacks in LoRaWAN is replay attack. It is so easy to sniff packets in a wireless network environment. If an attacker intrudes a service provided by LoRaWAN, the usage pattern of the end-device may be exposed, or a replay attack may cause a problem in connection with the user. To prevent replay attack, LoRaWAN standard uses user identification method by using the value known as DevNonce, but this is not a complete countermeasure. In order to complement these vulnerabilities, we propose a method to protect users by using the physical characteristics of a network called RSSI and a new technique called Proprietary Hand-Shaking.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134225589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323895
Weidong Feng, Yong Sun, Zheng Zhou, Qiang Rao, Di Chen, Linhui Yang, Yawei Wang
Network traffic model is the basis for network performance analysis, dynamic allocation of network bandwidth and network planning and construction. A good traffic model and prediction method is great significance for the design of a new generation of network protocols, network management and diagnosis, design of high performance routers, load balancers Network hardware equipment and improving the quality of the network services. With the construction of energy smart grid, especially in the distribution network is particularly evident. Increasing the variety of electrical equipment, which make distribution and communication network structure more complex and changeable, including a variety of communication systems, more Equipment, a larger scale and communication traffic characteristics. It can cause a great impact on the backbone network capacity. Considering the reliability and security of the power grid, this paper analyzes the characteristics of conventional traffic model based on the traffic characteristics of the distribution network and establishes a multi-convergence traffic prediction model to be used in the distribution network to improve the accuracy of network traffic prediction. Provide a reliable theoretical basis.
{"title":"Study on multi-network traffic modeling in distribution communication network access service","authors":"Weidong Feng, Yong Sun, Zheng Zhou, Qiang Rao, Di Chen, Linhui Yang, Yawei Wang","doi":"10.23919/ICACT.2018.8323895","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323895","url":null,"abstract":"Network traffic model is the basis for network performance analysis, dynamic allocation of network bandwidth and network planning and construction. A good traffic model and prediction method is great significance for the design of a new generation of network protocols, network management and diagnosis, design of high performance routers, load balancers Network hardware equipment and improving the quality of the network services. With the construction of energy smart grid, especially in the distribution network is particularly evident. Increasing the variety of electrical equipment, which make distribution and communication network structure more complex and changeable, including a variety of communication systems, more Equipment, a larger scale and communication traffic characteristics. It can cause a great impact on the backbone network capacity. Considering the reliability and security of the power grid, this paper analyzes the characteristics of conventional traffic model based on the traffic characteristics of the distribution network and establishes a multi-convergence traffic prediction model to be used in the distribution network to improve the accuracy of network traffic prediction. Provide a reliable theoretical basis.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323679
Da-Yu Kao, Shou-Ching Hsiao
The global ransomware cyberattacks cripples the national hospital system across the United Kingdom, and causes waves of appointments and operations to be cancelled. Similar attacking methods have come to sweep over the world. Such trend of highprofile cyberattack sheds the lights on rapid defence through the malware information sharing platform. A complete malware analysis process is quite a time-consuming campaign. The dynamic analysis of WannaCry ransomware explores behavioural indicators and extracts important IOCs (Indicators of Compromise). Utilizing Yara tool to create customized patterns is useful for malware information sharing mechanism. Also, such mechanism help reduce time and human resource spent on detecting or finding similar malware families. We aim to generate effective cyber threat intelligence by formulating collected IOCs into structured formations. The positive effects show on immediate defensive response to security breaches, and meanwhile the integrated information security protection is consolidated.
{"title":"The dynamic analysis of WannaCry ransomware","authors":"Da-Yu Kao, Shou-Ching Hsiao","doi":"10.23919/ICACT.2018.8323679","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323679","url":null,"abstract":"The global ransomware cyberattacks cripples the national hospital system across the United Kingdom, and causes waves of appointments and operations to be cancelled. Similar attacking methods have come to sweep over the world. Such trend of highprofile cyberattack sheds the lights on rapid defence through the malware information sharing platform. A complete malware analysis process is quite a time-consuming campaign. The dynamic analysis of WannaCry ransomware explores behavioural indicators and extracts important IOCs (Indicators of Compromise). Utilizing Yara tool to create customized patterns is useful for malware information sharing mechanism. Also, such mechanism help reduce time and human resource spent on detecting or finding similar malware families. We aim to generate effective cyber threat intelligence by formulating collected IOCs into structured formations. The positive effects show on immediate defensive response to security breaches, and meanwhile the integrated information security protection is consolidated.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"646 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122957849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-01DOI: 10.23919/ICACT.2018.8323665
Phan Thi The, Vu Nhu Manh, Tran Cong Hung, Le Dien Tam
The issues related to energy consumption and prolonging the lifetime of wireless sensor networks(WSNs) have been studied. The deployment of a transceiver station in a WSN is a major concern. Supposing the base stations are static (fixed), however they are capable of moving in some situations to collect data from sensor nodes. In order to achieve higher energy efficiency results, the mobility of the base station to increase the lifetime of the WSN is considered in this article. We propose a strategy that combines moving sinks by fixed-path sink with fuzzy clustering algorithm that results the proposed algorithm has better performance in terms of network life, stability and packet delivery compared to Leach, Cluster Head Election mechanism using Fuzzy logic (CHEF) in performance evaluation through simulation software MATLAB.
对无线传感器网络的能量消耗和寿命延长等问题进行了研究。无线传感器网络中收发站的部署是一个主要问题。假设基站是静态的(固定的)，但是它们能够在某些情况下移动以从传感器节点收集数据。为了达到更高的能效效果，本文考虑了基站的移动性来增加无线传感器网络的寿命。我们提出了一种将固定路径sink移动sink与模糊聚类算法相结合的策略，通过仿真软件MATLAB进行性能评价，结果表明所提出的算法在网络寿命、稳定性和数据包传输方面都优于采用模糊逻辑(CHEF)的Leach、Cluster Head Election机制。
{"title":"Improving network lifetime in wireless sensor network using fuzzy logic based clustering combined with mobile sink","authors":"Phan Thi The, Vu Nhu Manh, Tran Cong Hung, Le Dien Tam","doi":"10.23919/ICACT.2018.8323665","DOIUrl":"https://doi.org/10.23919/ICACT.2018.8323665","url":null,"abstract":"The issues related to energy consumption and prolonging the lifetime of wireless sensor networks(WSNs) have been studied. The deployment of a transceiver station in a WSN is a major concern. Supposing the base stations are static (fixed), however they are capable of moving in some situations to collect data from sensor nodes. In order to achieve higher energy efficiency results, the mobility of the base station to increase the lifetime of the WSN is considered in this article. We propose a strategy that combines moving sinks by fixed-path sink with fuzzy clustering algorithm that results the proposed algorithm has better performance in terms of network life, stability and packet delivery compared to Leach, Cluster Head Election mechanism using Fuzzy logic (CHEF) in performance evaluation through simulation software MATLAB.","PeriodicalId":228625,"journal":{"name":"2018 20th International Conference on Advanced Communication Technology (ICACT)","volume":"55 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115977814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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