Pub Date : 2018-06-01DOI: 10.1109/ISNCC.2018.8530997
Husam Rajab, T. Cinkler
The massive deployment of Internet of Things (IoT) is allowing Smart City projects and initiatives all over the world. The IoT is a modular approach to merge various sensors with all the ICT solutions. With over 50 billion objects will be connected and deployed in smart cities in 2020. The heart of smart cities operations is the IoT communications. IoT is designed to support Smart City concept, which aims at utilizing the most advanced communication technologies to promote services for the administration of the city and the citizens. This paper is presenting a comprehensive review of the concepts of IoT and smart cities and their motivations and applications. Moreover, this paper describes the main challenges and weaknesses of applying the IoT technologies based on smart city paradigms,
{"title":"IoT based Smart Cities","authors":"Husam Rajab, T. Cinkler","doi":"10.1109/ISNCC.2018.8530997","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530997","url":null,"abstract":"The massive deployment of Internet of Things (IoT) is allowing Smart City projects and initiatives all over the world. The IoT is a modular approach to merge various sensors with all the ICT solutions. With over 50 billion objects will be connected and deployed in smart cities in 2020. The heart of smart cities operations is the IoT communications. IoT is designed to support Smart City concept, which aims at utilizing the most advanced communication technologies to promote services for the administration of the city and the citizens. This paper is presenting a comprehensive review of the concepts of IoT and smart cities and their motivations and applications. Moreover, this paper describes the main challenges and weaknesses of applying the IoT technologies based on smart city paradigms,","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127426383","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8530964
Ryo Nakamura, Y. Sekiya, Daisuke Miyamoto, Kazuya Okada, Tomohiro Ishihara
As is the case for recently networked systems, traffic analysis that detects malicious hosts is one of the most important issues in achieving better security. Many methods for detecting cyber attacks have been proposed; however, methods that specialize in detecting and identifying specific attacks will be obsolete in the near future. Instead of identifying types of cyber attacks, we propose a novel method to detect malicious hosts based on their behavior characteristics when they send SYN packets. Our method does not identify types of cyber attacks. It detects malicious hosts suspiciously sending SYN packets. This paper shows that (1) we have developed a method to convert a series of SYN packets to a visual image as input for neural networks, (2) the image represents distinctive features of the behavior of the hosts, and (3) our convolutional neural network model successfully distinguishes malicious host from normal ones. Our preliminary evaluation using real-word traffic shows that the detection accuracy for identifying malicious hosts is over 98% regardless of types of attack.
{"title":"Malicious Host Detection by Imaging SYN Packets and A Neural Network","authors":"Ryo Nakamura, Y. Sekiya, Daisuke Miyamoto, Kazuya Okada, Tomohiro Ishihara","doi":"10.1109/ISNCC.2018.8530964","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530964","url":null,"abstract":"As is the case for recently networked systems, traffic analysis that detects malicious hosts is one of the most important issues in achieving better security. Many methods for detecting cyber attacks have been proposed; however, methods that specialize in detecting and identifying specific attacks will be obsolete in the near future. Instead of identifying types of cyber attacks, we propose a novel method to detect malicious hosts based on their behavior characteristics when they send SYN packets. Our method does not identify types of cyber attacks. It detects malicious hosts suspiciously sending SYN packets. This paper shows that (1) we have developed a method to convert a series of SYN packets to a visual image as input for neural networks, (2) the image represents distinctive features of the behavior of the hosts, and (3) our convolutional neural network model successfully distinguishes malicious host from normal ones. Our preliminary evaluation using real-word traffic shows that the detection accuracy for identifying malicious hosts is over 98% regardless of types of attack.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131356260","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8531051
E. Pencheva, D. Kireva, I. Atanasov, V. Trifonov
Multi-access Edge Computing (MEC) is a cloud technology that places storage and computing resources at the edge of the mobile network. The MEC platform provides services for radio network information, bandwidth management and device location. In this paper, we propose a new mobile edge service that enables 3rd party control on intersystem handover. The proposed service allows authorized applications to initiate device pre-registration in the target access network and then based on application-specific policy to initiate intersystem handover. Description of information flows, data models and actual interface definition are provided. Handover state models consider some implementation issues.
{"title":"Open Access to Intersystem Handover Control Using Multi-access Edge Computing","authors":"E. Pencheva, D. Kireva, I. Atanasov, V. Trifonov","doi":"10.1109/ISNCC.2018.8531051","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8531051","url":null,"abstract":"Multi-access Edge Computing (MEC) is a cloud technology that places storage and computing resources at the edge of the mobile network. The MEC platform provides services for radio network information, bandwidth management and device location. In this paper, we propose a new mobile edge service that enables 3rd party control on intersystem handover. The proposed service allows authorized applications to initiate device pre-registration in the target access network and then based on application-specific policy to initiate intersystem handover. Description of information flows, data models and actual interface definition are provided. Handover state models consider some implementation issues.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126362711","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8530977
Raed Al-Aaridhi, I. Dlikman, Newton Masinde, Kalman Graffi
The search problem in distributed systems has been evaluated and various proposals have been made to solve them. The problem is particularly pronounced when considering P2P networks, because the different types of P2P network topologies used to dictate the search mechanisms that are used. Specifically, search mechanisms may be key-based, as in structured P2P networks that use distributed data structures such as Distributed Hash Tables (DHTs), Sets, Links, and Trees, or keyword-based for unstructured P2P networks. Online systems today utilize metadata to support search algorithms. Metadata searches are trivial in unstructured networks but are a challenge to the structured networks because of the distributed data structures (DDS). This work proposes to introduce algorithms that support metadata searches in structured P2P networks that utilize DHT overlays. DDSs are introduced into the system as storage layers that support complex data structures. We show that this can be done and searching can be achieved with acceptable performance.
{"title":"Search Algorithms for Distributed Data Structures in P2P Networks","authors":"Raed Al-Aaridhi, I. Dlikman, Newton Masinde, Kalman Graffi","doi":"10.1109/ISNCC.2018.8530977","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530977","url":null,"abstract":"The search problem in distributed systems has been evaluated and various proposals have been made to solve them. The problem is particularly pronounced when considering P2P networks, because the different types of P2P network topologies used to dictate the search mechanisms that are used. Specifically, search mechanisms may be key-based, as in structured P2P networks that use distributed data structures such as Distributed Hash Tables (DHTs), Sets, Links, and Trees, or keyword-based for unstructured P2P networks. Online systems today utilize metadata to support search algorithms. Metadata searches are trivial in unstructured networks but are a challenge to the structured networks because of the distributed data structures (DDS). This work proposes to introduce algorithms that support metadata searches in structured P2P networks that utilize DHT overlays. DDSs are introduced into the system as storage layers that support complex data structures. We show that this can be done and searching can be achieved with acceptable performance.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115253880","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8530970
Yang Liu, C. Wu, M. Wang, Aiqin Hou, Yongqiang Wang
Hadoop is one of the most popular distributed systems for big data computing in both industry and science communities. The default data placement strategy of Hadoop Distributed File System (HDFS), which was initially designed for homogenous environments, may suffer from performance degradation when deployed in heterogeneous clusters comprised of data nodes with disparate computing power and disk capacity, hence undermining the performance of MapReduce applications. In this paper, we use a Grey Forecast model to predict data hotness dynamically and determine an appropriate number of data block replicas on the fly. Based on such information, we further propose a dynamic data placement strategy (DDPS) to decide the best location for new replicas according to their hotness. The proposed method is able to dynamically adjust data replicas stored on each node in a heterogeneous Hadoop cluster and reduce the response time of big data applications. Experimental results on a heterogeneous Hadoop cluster show that DDPS together with the prediction model significantly increases application execution efficiency and improve MapReduce performance over the default HDFS configuration.
{"title":"On a Dynamic Data Placement Strategy for Heterogeneous Hadoop Clusters","authors":"Yang Liu, C. Wu, M. Wang, Aiqin Hou, Yongqiang Wang","doi":"10.1109/ISNCC.2018.8530970","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530970","url":null,"abstract":"Hadoop is one of the most popular distributed systems for big data computing in both industry and science communities. The default data placement strategy of Hadoop Distributed File System (HDFS), which was initially designed for homogenous environments, may suffer from performance degradation when deployed in heterogeneous clusters comprised of data nodes with disparate computing power and disk capacity, hence undermining the performance of MapReduce applications. In this paper, we use a Grey Forecast model to predict data hotness dynamically and determine an appropriate number of data block replicas on the fly. Based on such information, we further propose a dynamic data placement strategy (DDPS) to decide the best location for new replicas according to their hotness. The proposed method is able to dynamically adjust data replicas stored on each node in a heterogeneous Hadoop cluster and reduce the response time of big data applications. Experimental results on a heterogeneous Hadoop cluster show that DDPS together with the prediction model significantly increases application execution efficiency and improve MapReduce performance over the default HDFS configuration.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122577244","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8531070
Abdulrahman S. Alturki
Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. In this paper, a new traffic sign detection and recognition approach is presented by using Fuzzy Neural Network (FNN) and it is including three stages. The first stage segments the images to extract ROIs. The segmentation is usually performed based on Adaptive thresholding to overcome the color segmentation problems. The second one detects traffic shapes. Given that the geometric form of traffic signs is limited to triangular, circular, rectangular and octagonal forms, the geometric information is used to identify traffic shapes from ROIs provided by the first stage. The third stage recognizes the traffic signs based on the information including included in their pictograms. Moreover, in this work, six types of features are extracted. These features were provided to the FNN classifier to perform the recognition. As a classifier, FNN, Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers have been tested together with the new descriptor. The proposed method has been tested on both the German Traffic Sign Detection and Recognition Benchmark dataset. The results obtained are satisfactory when compared to the state-of-the-art methods.
{"title":"Traffic Sign Detection and Recognition Using Adaptive Threshold Segmentation with Fuzzy Neural Network Classification","authors":"Abdulrahman S. Alturki","doi":"10.1109/ISNCC.2018.8531070","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8531070","url":null,"abstract":"Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. In this paper, a new traffic sign detection and recognition approach is presented by using Fuzzy Neural Network (FNN) and it is including three stages. The first stage segments the images to extract ROIs. The segmentation is usually performed based on Adaptive thresholding to overcome the color segmentation problems. The second one detects traffic shapes. Given that the geometric form of traffic signs is limited to triangular, circular, rectangular and octagonal forms, the geometric information is used to identify traffic shapes from ROIs provided by the first stage. The third stage recognizes the traffic signs based on the information including included in their pictograms. Moreover, in this work, six types of features are extracted. These features were provided to the FNN classifier to perform the recognition. As a classifier, FNN, Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers have been tested together with the new descriptor. The proposed method has been tested on both the German Traffic Sign Detection and Recognition Benchmark dataset. The results obtained are satisfactory when compared to the state-of-the-art methods.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122704117","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8530966
M. Mondin, F. Daneshgaran, F. D. Stasio
In this paper, a MIMO-OFDM system operating with SFBC encoded signals and affected by inter-cell interference is analyzed, and the performances of Interference Aware-Minimum Mean Square Error (IA-MMSE) symbol estimators are discussed in presence of realistic estimation of the interference auto-correlation matrix. Different estimation techniques are described and compared, based both on a system description using a $4times 2$ channel matrix (requiring the estimation and inversion of a $4times 4$ auto-correlation matrix), or using two $2times 2$ matrices (requiring the estimation and inversion of two $2times 2$ auto-correlation matrices). The first approach offers better performances, but the second approach has a very limited loss, counterbalanced by a simpler implementation complexity, characteristics that makes it an interesting solution in practical applications. An extensive simulation campaign using realistic system level parameters has been used for performance assessment.
{"title":"Performance of IA-MMSE Iterative Structures for SFBC Decoding in MIMO Systems Using Realistic System Parameters","authors":"M. Mondin, F. Daneshgaran, F. D. Stasio","doi":"10.1109/ISNCC.2018.8530966","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530966","url":null,"abstract":"In this paper, a MIMO-OFDM system operating with SFBC encoded signals and affected by inter-cell interference is analyzed, and the performances of Interference Aware-Minimum Mean Square Error (IA-MMSE) symbol estimators are discussed in presence of realistic estimation of the interference auto-correlation matrix. Different estimation techniques are described and compared, based both on a system description using a $4times 2$ channel matrix (requiring the estimation and inversion of a $4times 4$ auto-correlation matrix), or using two $2times 2$ matrices (requiring the estimation and inversion of two $2times 2$ auto-correlation matrices). The first approach offers better performances, but the second approach has a very limited loss, counterbalanced by a simpler implementation complexity, characteristics that makes it an interesting solution in practical applications. An extensive simulation campaign using realistic system level parameters has been used for performance assessment.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131985973","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8531048
A. Salam, C. Roseti, F. Zampognaro
Contention Resolution Diversity Slotted ALOHA (CRDSA) random access scheme, introduced in the DVB-RCS2/NG standard, is specifically designed to support the transfer of a variety of traffic profiles that Machine to Machine (M2M) and Internet of Things (IoT) applications may generate. Protocols for M2M and IoT has recently receiver substantial upgrades, but still mainly designed with an underlying terrestrial network in mind. If clusters of sensor nodes exchange data via satellite terminals toward a sink via short-lived TCP/IP connections, many shortcomings may incur. This work aims at investigating in details the behavior for such data transfer in presence of a shared random access channel, and the advantages when using a new TCP version specifically designed for satellite links, namely TCP Wave. In particular, through a detailed simulation campaign based on the NS3 simulator, this work assesses the completion time of data delivery for M2M elastic traffic via CRDSA satellite random access, when standard TCP (NewReno) or dedicated satellite TCP (Wave) is adopted.
{"title":"TCP performance for Satellite M2M applications over Random Access links","authors":"A. Salam, C. Roseti, F. Zampognaro","doi":"10.1109/ISNCC.2018.8531048","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8531048","url":null,"abstract":"Contention Resolution Diversity Slotted ALOHA (CRDSA) random access scheme, introduced in the DVB-RCS2/NG standard, is specifically designed to support the transfer of a variety of traffic profiles that Machine to Machine (M2M) and Internet of Things (IoT) applications may generate. Protocols for M2M and IoT has recently receiver substantial upgrades, but still mainly designed with an underlying terrestrial network in mind. If clusters of sensor nodes exchange data via satellite terminals toward a sink via short-lived TCP/IP connections, many shortcomings may incur. This work aims at investigating in details the behavior for such data transfer in presence of a shared random access channel, and the advantages when using a new TCP version specifically designed for satellite links, namely TCP Wave. In particular, through a detailed simulation campaign based on the NS3 simulator, this work assesses the completion time of data delivery for M2M elastic traffic via CRDSA satellite random access, when standard TCP (NewReno) or dedicated satellite TCP (Wave) is adopted.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113993888","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8530911
Chengjie Li, Lidong Zhu, Zhongqiang Luo
The problem of underdetermined blind source separation for satellite communications is proposed in this paper. In underdetermined blind separation, people suppose the source is sparse and the number of source signals is known when they estimate the mixture matrix. In fact, the sparsity is often not satisfied and the number of source signals is unknown. This paper presents a novel Rough Set algorithm (RS algorithm) based on rough set theory, which can get the source signal sparse points and accurately estimate the number of sources and the mixture matrix respectively, by which source signals can be reconstructed. The last simulations show the good performance of the paper's algorithm.
{"title":"Underdetermined Blind Separation Via Rough Equivalence Clustering for Satellite Communications","authors":"Chengjie Li, Lidong Zhu, Zhongqiang Luo","doi":"10.1109/ISNCC.2018.8530911","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530911","url":null,"abstract":"The problem of underdetermined blind source separation for satellite communications is proposed in this paper. In underdetermined blind separation, people suppose the source is sparse and the number of source signals is known when they estimate the mixture matrix. In fact, the sparsity is often not satisfied and the number of source signals is unknown. This paper presents a novel Rough Set algorithm (RS algorithm) based on rough set theory, which can get the source signal sparse points and accurately estimate the number of sources and the mixture matrix respectively, by which source signals can be reconstructed. The last simulations show the good performance of the paper's algorithm.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114019315","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 : 2018-06-01DOI: 10.1109/ISNCC.2018.8530996
S. Romano, C. Roseti, A. Tulino
In this paper we look after the secure delivery of multimedia content across an innovative Content Delivery Network comprising both satellite and terrestrial trunks. The CDN in question leverages state-of-the-art technologies both at the edges and in the core of the integrated distribution architecture and highly relies upon in-network caching strategies in order to improve its performance. We propose an architecture envisaging a combination of multicast, simulcast and unicast communication scenarios where satellite links are exploited to support local in-network caching. We analyse integrated network deployment scenarios where the satellite acts as the interconnection link between distributed in-network caches and a terrestrial CDN and/or feeds edge-network caches at micro-centre locations.
{"title":"SHINE: Secure Hybrid In Network caching Environment","authors":"S. Romano, C. Roseti, A. Tulino","doi":"10.1109/ISNCC.2018.8530996","DOIUrl":"https://doi.org/10.1109/ISNCC.2018.8530996","url":null,"abstract":"In this paper we look after the secure delivery of multimedia content across an innovative Content Delivery Network comprising both satellite and terrestrial trunks. The CDN in question leverages state-of-the-art technologies both at the edges and in the core of the integrated distribution architecture and highly relies upon in-network caching strategies in order to improve its performance. We propose an architecture envisaging a combination of multicast, simulcast and unicast communication scenarios where satellite links are exploited to support local in-network caching. We analyse integrated network deployment scenarios where the satellite acts as the interconnection link between distributed in-network caches and a terrestrial CDN and/or feeds edge-network caches at micro-centre locations.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115680058","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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