Dynamic Streaming over HTTP is the main standard used for online video streaming, service that has about 1.1 billion subscribers around the world. That implies billions of streaming connections between video servers and client displays. These devices involved in the streaming connection use an Ethernet Interface Card that consumes energy. In order to reduce the energy consumption, the IEEE 802.3az Energy Efficient Ethernet has been proposed. In this study, the ethernet traffic pattern when transmitting online video content is characterized in order to analyze the efficiency of the IEEE 802.3az standard under video streaming scenarios, and to verify the convenience of activating this energy saving alternative at the network interface of billions of client devices.
{"title":"Study on the Impact of DASH Streaming Services using Energy Efficient Ethernet","authors":"T. R. Vargas, J. C. Guerri, P. Arce","doi":"10.1145/3479240.3488527","DOIUrl":"https://doi.org/10.1145/3479240.3488527","url":null,"abstract":"Dynamic Streaming over HTTP is the main standard used for online video streaming, service that has about 1.1 billion subscribers around the world. That implies billions of streaming connections between video servers and client displays. These devices involved in the streaming connection use an Ethernet Interface Card that consumes energy. In order to reduce the energy consumption, the IEEE 802.3az Energy Efficient Ethernet has been proposed. In this study, the ethernet traffic pattern when transmitting online video content is characterized in order to analyze the efficiency of the IEEE 802.3az standard under video streaming scenarios, and to verify the convenience of activating this energy saving alternative at the network interface of billions of client devices.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85766502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simulating urban mobility scenarios is a useful tool for researchers in multiple fields like Urban Planning, Traffic Optimization, CO$^2$ Emissions Analysis, Performance Evaluation of Protocols for Connected Vehicles, among others. SUMO handles microscopic traffic simulations and allows communication to Python language through an API which is also shared by VEINS. This communication channel lets researchers interact with the simulation on-live, facilitating the implementation of state-of-the-art algorithms from Machine Learning (ML) and Artificial Intelligence (AI). On the other hand, OMNeT++ is a framework to manage and analyze communication protocols of mobile networks. We experimentally evaluated the training of a Support Vector Machine (SVM) in the SUMO-VEINS-OMNeT++ framework. Our experiments show the best classification model for a particular traffic light assignment scenario.
{"title":"A Support Vector Machine Implementation for Traffic Assignment Problem","authors":"J. González-Vergara, N. Serrano, Cristhian Iza","doi":"10.1145/3479240.3488502","DOIUrl":"https://doi.org/10.1145/3479240.3488502","url":null,"abstract":"Simulating urban mobility scenarios is a useful tool for researchers in multiple fields like Urban Planning, Traffic Optimization, CO$^2$ Emissions Analysis, Performance Evaluation of Protocols for Connected Vehicles, among others. SUMO handles microscopic traffic simulations and allows communication to Python language through an API which is also shared by VEINS. This communication channel lets researchers interact with the simulation on-live, facilitating the implementation of state-of-the-art algorithms from Machine Learning (ML) and Artificial Intelligence (AI). On the other hand, OMNeT++ is a framework to manage and analyze communication protocols of mobile networks. We experimentally evaluated the training of a Support Vector Machine (SVM) in the SUMO-VEINS-OMNeT++ framework. Our experiments show the best classification model for a particular traffic light assignment scenario.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88738381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IEEE 802.11 (known as Wi-Fi) has emerged as a vital wireless network access technology for mobile devices. By providing the potential for high connectivity speeds, this technology has led to a dramatic rise in the number of access points (APs). In such environments, mobile devices have the choice to join several Wi-Fi networks. Despite its importance to user Quality of Experience (QoE), the AP selection is still trivial since it focuses at best on the received signal strength if not only the user's history. Crucial metrics that capture the overall dynamics of the AP load condition, such as the network load, are not taken into account. In this paper, we propose to use the Busy Time Fraction (BTF) as a metric to choose the best AP to attach to. The BTF level of a given channel is inferred based on the frame aggregation scheme proposed since the 802.11n standard. In this regard, we propose an analytical model based on a Discrete-Time Markov chain that discerns the theoretical DownLink aggregation levels for probe traffic concurrent to cross traffic. We validate the accuracy of our proposed approach against ns-3 simulations under several scenarios.
{"title":"Exploiting Frame Aggregation to Enhance Access Point Selection","authors":"Nour El Houda Bouzouita, A. Busson, H. Rivano","doi":"10.1145/3479240.3488507","DOIUrl":"https://doi.org/10.1145/3479240.3488507","url":null,"abstract":"IEEE 802.11 (known as Wi-Fi) has emerged as a vital wireless network access technology for mobile devices. By providing the potential for high connectivity speeds, this technology has led to a dramatic rise in the number of access points (APs). In such environments, mobile devices have the choice to join several Wi-Fi networks. Despite its importance to user Quality of Experience (QoE), the AP selection is still trivial since it focuses at best on the received signal strength if not only the user's history. Crucial metrics that capture the overall dynamics of the AP load condition, such as the network load, are not taken into account. In this paper, we propose to use the Busy Time Fraction (BTF) as a metric to choose the best AP to attach to. The BTF level of a given channel is inferred based on the frame aggregation scheme proposed since the 802.11n standard. In this regard, we propose an analytical model based on a Discrete-Time Markov chain that discerns the theoretical DownLink aggregation levels for probe traffic concurrent to cross traffic. We validate the accuracy of our proposed approach against ns-3 simulations under several scenarios.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80288103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vehicular Ad-hoc Networks (VANETs) are a set of mobile nodes that move on the road and connect via wireless. Due to the limited radio range, they send data to each other by collaborating. Some nodes drop the other nodes’ packets to save the network supplements; therefore, the network’s performance will reduce. So it is necessary to identify selfish nodes to prevent other nodes from cooperating with them. In the proposed scheme, a punishmentbased algorithm is presented to identify the selfish nodes used in Adaptive Resonance Theory (ART) clustering to monitor and control them. The cluster head determines if selfish behaviors occur in the cluster or not. If the cluster head discovers that there is a selfish behavior in the cluster, it begins to check the packets that were sent and received by all nodes. In the proposed method, each node in the network is equipped with learning automata, the probability of selecting each neighbor node to send the packet, which is rewarded or punished according to the performance. Simulation results have shown that the rate of detection of selfish nodes is more than other methods, and the false alarm rate (FAR) is less than other similar methods.
{"title":"DSVL: Detecting Selfish Node in Vehicular Ad-hoc Networks (VANET) by Learning Automata","authors":"Ainaz Nobahari, S. J. Mirabedini","doi":"10.32908/ahswn.v53.7989","DOIUrl":"https://doi.org/10.32908/ahswn.v53.7989","url":null,"abstract":"Vehicular Ad-hoc Networks (VANETs) are a set of mobile nodes that move on the road and connect via wireless. Due to the limited radio range, they send data to each other by collaborating. Some nodes drop the other nodes’ packets to save the network supplements; therefore, the network’s performance will reduce. So it is necessary to identify selfish nodes to prevent other nodes from cooperating with them. In the proposed scheme, a punishmentbased algorithm is presented to identify the selfish nodes used in Adaptive Resonance Theory (ART) clustering to monitor and control them. The cluster head determines if selfish behaviors occur in the cluster or not. If the cluster head discovers that there is a selfish behavior in the cluster, it begins to check the packets that were sent and received by all nodes. In the proposed method, each node in the network is equipped with learning automata, the probability of selecting each neighbor node to send the packet, which is rewarded or punished according to the performance. Simulation results have shown that the rate of detection of selfish nodes is more than other methods, and the false alarm rate (FAR) is less than other similar methods.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73900197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-20DOI: 10.21203/rs.3.rs-188928/v1
P. Sathyaraj, S. Rukmani Devi, K. Kannan
Background: Mobile Ad-hoc Networks (i.e.) MANETs are gaining rapid fame in recent days and are considered as very significant because of their easier implementation and growing property. Various types of attacks are prone to damage the networks due to the elastic property possessed by the network. And among different categories of attacks that can affect MANETs, black hole attack is considered as the commonly occurring one within a MANET. Chicken Swarm Optimization (CSO) algorithm is one among the technique used for the detection of black hole attacks occurring in the MANETs. But the CSO algorithm possesses some disadvantages and necessity rises for overcoming the weakness in the CSO algorithm. Objective: Therefore, in this research paper, to address the black hole attack in MANET, an Improved Crossover Chicken Swarm Optimization (ICCSO) algorithm and the concept of Enhanced Partially-Mapped Crossover operation proposed and the best fitness values obtained. Methods: In ICCSO algorithm, parameter initialization is carried out in step 1 of the algorithm, where the attacked nodes and non-attack nodes are created separately with the aid of parameters like PDR (i.e.) Packet Delivery Ratio and RSSI (i.e.) Received Signal Strength Indicator. Further, If the node is affected by any attack, then the nodes are discarded and the data is transmitted through the non-attacked node. Routing is carried by a protocol of AODV.Results: The effectiveness of the algorithm proposed in the work is evaluated using various performance measures like packet delivery ratio (PDR), end-to-end delay (EED) and throughput. The performance measures are compared with a different state of the art routing protocols and it can be inferred that the proposed methodology comes up with improved results.
背景:移动自组织网络(即)manet最近获得了迅速的名声，并且由于其更容易实现和不断增长的特性而被认为是非常重要的。由于网络所具有的弹性特性，各种攻击都容易对网络造成破坏。在影响MANET的不同类型的攻击中，黑洞攻击被认为是MANET中最常见的攻击。鸡群优化算法(CSO)是一种用于检测黑洞攻击的技术。但是CSO算法也存在一些缺点，需要克服CSO算法的缺点。为此，本文针对MANET中的黑洞攻击问题，提出了一种改进的交叉鸡群优化(ICCSO)算法和增强部分映射交叉操作的概念，并获得了最佳适应度值。方法:在ICCSO算法中，在算法的第一步进行参数初始化，通过PDR (Packet Delivery Ratio)、RSSI (Received Signal Strength Indicator)等参数分别创建受攻击节点和非受攻击节点。如果该节点受到任何攻击，则丢弃该节点，数据通过未受攻击的节点传输。路由由AODV协议承载。结果:使用各种性能指标，如分组传输比(PDR)、端到端延迟(EED)和吞吐量，对工作中提出的算法的有效性进行了评估。性能指标与不同状态的最先进的路由协议进行了比较，可以推断，所提出的方法提出了改进的结果。
{"title":"Host-based Detection and Prevention of Black Hole Attacks by AODV-ICCSO Algorithm for Security in MANETs","authors":"P. Sathyaraj, S. Rukmani Devi, K. Kannan","doi":"10.21203/rs.3.rs-188928/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-188928/v1","url":null,"abstract":"\u0000 Background: Mobile Ad-hoc Networks (i.e.) MANETs are gaining rapid fame in recent days and are considered as very significant because of their easier implementation and growing property. Various types of attacks are prone to damage the networks due to the elastic property possessed by the network. And among different categories of attacks that can affect MANETs, black hole attack is considered as the commonly occurring one within a MANET. Chicken Swarm Optimization (CSO) algorithm is one among the technique used for the detection of black hole attacks occurring in the MANETs. But the CSO algorithm possesses some disadvantages and necessity rises for overcoming the weakness in the CSO algorithm. Objective: Therefore, in this research paper, to address the black hole attack in MANET, an Improved Crossover Chicken Swarm Optimization (ICCSO) algorithm and the concept of Enhanced Partially-Mapped Crossover operation proposed and the best fitness values obtained. Methods: In ICCSO algorithm, parameter initialization is carried out in step 1 of the algorithm, where the attacked nodes and non-attack nodes are created separately with the aid of parameters like PDR (i.e.) Packet Delivery Ratio and RSSI (i.e.) Received Signal Strength Indicator. Further, If the node is affected by any attack, then the nodes are discarded and the data is transmitted through the non-attacked node. Routing is carried by a protocol of AODV.Results: The effectiveness of the algorithm proposed in the work is evaluated using various performance measures like packet delivery ratio (PDR), end-to-end delay (EED) and throughput. The performance measures are compared with a different state of the art routing protocols and it can be inferred that the proposed methodology comes up with improved results.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87689828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The 5G (fifth-generation) mobile networks, especially by exploiting higher bandwidth in the mmWave (millimeter wave) spectrum, is the leading candidate to be used as the coming generation for ubiquitous networks. The vast available bandwidth in mmWave can satisfy the high data rate and low latency expectations from 5G networks in order to provide new services and use cases. Although 5G mmWave networks come up with innovative and robust services, they suffer from a drawback. As the frequency rises, the penetration power and coverage area of the network decreases, so it results in having discontinuous communication between a base station and a user. This intermittent characteristic is caused due to an existing obstacle such as a car or a building on the communication path that can hurdle the establishment of a transmission, which is called NLoS (Non-Line of Sight) state. NLoS states can degrade the functionality of the network and prevent from having seamless connectivity by forcing fluctuations in the network's channels. The reason for this shortcoming is because of the susceptibility of high frequencies to the blockage that can be generated by obstacles. The intense negative effect of having a blockage in the network is on an end-to-end communication when other layers protocols such as the transport layer widely used protocol TCP (Transmission Control Protocol) are used. Having frequent disconnections in the network impairs the TCP's functionality with inducing congestion states and preventing it from achieving higher performance. In this paper, we present the performance evaluation and analysis of TCP in different situations in an urban area and find out how various conditions can affect the performance of the protocol. The simulation results indicate that conventional TCPs are not adequate enough to be exploited in 5G mmWave networks. For having them functioning in their full potential, some modifications should be made in order to adapt them to 5G mmWave networks. Some ML (Machine Learning) techniques such as Neural Networks and Reinforcement Learning can be deployed as the key enablers to network performance improvement.
5G(第五代)移动网络，特别是通过利用毫米波(毫米波)频谱的更高带宽，是用作下一代无处不在网络的主要候选网络。毫米波中巨大的可用带宽可以满足5G网络对高数据速率和低延迟的期望，从而提供新的服务和用例。虽然5G毫米波网络提供了创新和强大的服务，但它们有一个缺点。随着频率的升高，网络的渗透能力和覆盖面积会减小，从而导致基站与用户之间的通信不连续。这种间歇性特性是由于通信路径上存在障碍物(如汽车或建筑物)阻碍传输的建立而引起的，这种状态称为NLoS (Non-Line of Sight)状态。NLoS状态会降低网络的功能，并通过强迫网络信道的波动来阻止无缝连接。造成这一缺点的原因是由于高频容易受到障碍物产生的阻塞。当使用其他层协议(如广泛使用的传输层协议TCP(传输控制协议))时，网络阻塞对端到端通信产生强烈的负面影响。网络中频繁的断开连接会导致拥塞状态，从而损害TCP的功能，使其无法实现更高的性能。在本文中，我们提出了TCP在城市地区的不同情况下的性能评估和分析，并找出各种条件如何影响协议的性能。仿真结果表明，传统的tcp协议不足以在5G毫米波网络中得到充分利用。为了使它们充分发挥其潜力，应该进行一些修改，以使它们适应5G毫米波网络。一些ML(机器学习)技术，如神经网络和强化学习，可以作为网络性能改进的关键推动者。
{"title":"Open Trends On TCP Performance Over Urban 5G mmWave Networks","authors":"Reza Poorzare, A. C. Augé","doi":"10.1145/3416011.3424749","DOIUrl":"https://doi.org/10.1145/3416011.3424749","url":null,"abstract":"The 5G (fifth-generation) mobile networks, especially by exploiting higher bandwidth in the mmWave (millimeter wave) spectrum, is the leading candidate to be used as the coming generation for ubiquitous networks. The vast available bandwidth in mmWave can satisfy the high data rate and low latency expectations from 5G networks in order to provide new services and use cases. Although 5G mmWave networks come up with innovative and robust services, they suffer from a drawback. As the frequency rises, the penetration power and coverage area of the network decreases, so it results in having discontinuous communication between a base station and a user. This intermittent characteristic is caused due to an existing obstacle such as a car or a building on the communication path that can hurdle the establishment of a transmission, which is called NLoS (Non-Line of Sight) state. NLoS states can degrade the functionality of the network and prevent from having seamless connectivity by forcing fluctuations in the network's channels. The reason for this shortcoming is because of the susceptibility of high frequencies to the blockage that can be generated by obstacles. The intense negative effect of having a blockage in the network is on an end-to-end communication when other layers protocols such as the transport layer widely used protocol TCP (Transmission Control Protocol) are used. Having frequent disconnections in the network impairs the TCP's functionality with inducing congestion states and preventing it from achieving higher performance. In this paper, we present the performance evaluation and analysis of TCP in different situations in an urban area and find out how various conditions can affect the performance of the protocol. The simulation results indicate that conventional TCPs are not adequate enough to be exploited in 5G mmWave networks. For having them functioning in their full potential, some modifications should be made in order to adapt them to 5G mmWave networks. Some ML (Machine Learning) techniques such as Neural Networks and Reinforcement Learning can be deployed as the key enablers to network performance improvement.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90156573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Session 1: Vehicular Networks","authors":"Luis J. de la Cruz Llopis","doi":"10.1145/3436345","DOIUrl":"https://doi.org/10.1145/3436345","url":null,"abstract":"","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76897437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amel Chadda, Marija Stojanova, Thomas Begin, A. Busson, I. G. Lassous
With the aim of increasing wireless data rates, IEEE 802.11n introduced the possibility for WLAN nodes to bond two channels into a single channel. However, channel bonding also limits spacial reutilization and complexifies channel assignment. In this paper, we present a fast and efficient solution for channel width selection and channel assignment in 802.11 WLANs using channel bonding. The proposed algorithm uses a novel, graph-centric metric to propose a single channel width for all the APs of the WLAN aiming at avoiding starvation in any of the network's APs. Decoupling the choice of channel width and channel assignment results in a scalable approach that bypasses the usual complexity issues of classic channel assignment schemes. We test the solution's precision in choosing a suited channel width and assignment by comparing its results with those delivered by the ns-3 network simulator. We obtain that, in the large majority of the cases, the choice made by our solution matches the simulation results.
{"title":"Towards a Fast and Efficient Strategy to Assign Channels in WLANs with Channel Bonding","authors":"Amel Chadda, Marija Stojanova, Thomas Begin, A. Busson, I. G. Lassous","doi":"10.1145/3416011.3424755","DOIUrl":"https://doi.org/10.1145/3416011.3424755","url":null,"abstract":"With the aim of increasing wireless data rates, IEEE 802.11n introduced the possibility for WLAN nodes to bond two channels into a single channel. However, channel bonding also limits spacial reutilization and complexifies channel assignment. In this paper, we present a fast and efficient solution for channel width selection and channel assignment in 802.11 WLANs using channel bonding. The proposed algorithm uses a novel, graph-centric metric to propose a single channel width for all the APs of the WLAN aiming at avoiding starvation in any of the network's APs. Decoupling the choice of channel width and channel assignment results in a scalable approach that bypasses the usual complexity issues of classic channel assignment schemes. We test the solution's precision in choosing a suited channel width and assignment by comparing its results with those delivered by the ns-3 network simulator. We obtain that, in the large majority of the cases, the choice made by our solution matches the simulation results.","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75821666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Session details: Session 2: Wireless Sensor Networks and Internet of Things","authors":"M. A. Igartua","doi":"10.1145/3436346","DOIUrl":"https://doi.org/10.1145/3436346","url":null,"abstract":"","PeriodicalId":55557,"journal":{"name":"Ad Hoc & Sensor Wireless Networks","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78868239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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