We explore the performance of different resource allocation schemes for transferring elastic traffic in a cellular network that is either overlaid or underlaid with D2D traffic. To this end, we model a single cell during uplink transmissions and jointly consider the presence of a randomly varying number of D2D and cellular users in the system. We use different processor sharing queueing models to characterize the performance of the overlaying and underlaying schemes and measure the performance as the mean flow level delay. In the overlaying approach, depending on the load a certain fraction of the radio resources is reserved for the D2D traffic and the cellular traffic, and hence there is no interference between the D2D and cellular users. In the underlaying approach, the D2D users are allowed to opportunistically transmit unless being interfered by a cellular user nearby. Our numerical studies reveal that the underlaying D2D traffic scheme provides a good performance compared to other methods, especially if the interference range of a cellular user is small compared with the cell dimensions. Moreover, the so-called dynamic overlay method we propose appears to perform better than the static overlay scheme.
{"title":"Performance of D2D Underlay and Overlay for Elastic Traffic","authors":"Prajwal Osti, P. Lassila, S. Aalto","doi":"10.1145/2988287.2989157","DOIUrl":"https://doi.org/10.1145/2988287.2989157","url":null,"abstract":"We explore the performance of different resource allocation schemes for transferring elastic traffic in a cellular network that is either overlaid or underlaid with D2D traffic. To this end, we model a single cell during uplink transmissions and jointly consider the presence of a randomly varying number of D2D and cellular users in the system. We use different processor sharing queueing models to characterize the performance of the overlaying and underlaying schemes and measure the performance as the mean flow level delay. In the overlaying approach, depending on the load a certain fraction of the radio resources is reserved for the D2D traffic and the cellular traffic, and hence there is no interference between the D2D and cellular users. In the underlaying approach, the D2D users are allowed to opportunistically transmit unless being interfered by a cellular user nearby. Our numerical studies reveal that the underlaying D2D traffic scheme provides a good performance compared to other methods, especially if the interference range of a cellular user is small compared with the cell dimensions. Moreover, the so-called dynamic overlay method we propose appears to perform better than the static overlay scheme.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122999396","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}
In this paper, we describe the design, implementation and evaluation of a new framework for the trace-based evaluation of 802.11n networks, which we call T-SIMn. We first develop novel techniques for collecting and processing traces for 802.11n networks that incorporate Frame Aggregation (FA). We then demonstrate that the simulator portion of our framework (SIMn) accurately simulates throughput for one, two and three-antenna Physical Layer Data Rates in 802.11n with FA. Finally, we evaluate the T-SIMn framework (including trace collection) by collecting traces using an iPhone which is representative of a wide variety of one antenna devices. We show that our framework can be used to accurately simulate these scenarios and we demonstrate the fidelity of SIMn by uncovering problems with our initial evaluation methodology. We expect that the T-SIMn framework will be suitable for easily and fairly comparing algorithms that must be optimized for different and varying 802.11n channel conditions which are challenging to evaluate experimentally. These include rate adaptation, frame aggregation and channel bandwidth adaptation algorithms. git
{"title":"T-SIMn: Towards the High Fidelity Trace-Based Simulation of 802.11n Networks","authors":"A. Abedi, Andrew Heard, Tim Brecht","doi":"10.1145/2988287.2989160","DOIUrl":"https://doi.org/10.1145/2988287.2989160","url":null,"abstract":"In this paper, we describe the design, implementation and evaluation of a new framework for the trace-based evaluation of 802.11n networks, which we call T-SIMn. We first develop novel techniques for collecting and processing traces for 802.11n networks that incorporate Frame Aggregation (FA). We then demonstrate that the simulator portion of our framework (SIMn) accurately simulates throughput for one, two and three-antenna Physical Layer Data Rates in 802.11n with FA. Finally, we evaluate the T-SIMn framework (including trace collection) by collecting traces using an iPhone which is representative of a wide variety of one antenna devices. We show that our framework can be used to accurately simulate these scenarios and we demonstrate the fidelity of SIMn by uncovering problems with our initial evaluation methodology. We expect that the T-SIMn framework will be suitable for easily and fairly comparing algorithms that must be optimized for different and varying 802.11n channel conditions which are challenging to evaluate experimentally. These include rate adaptation, frame aggregation and channel bandwidth adaptation algorithms. git","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128064155","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}
We propose a method for classifying Wi-Fi enabled mobile handheld devices (smartphones) and non-handheld devices (laptops) in a completely passive way, that is resorting neither to traffic probes on network edge devices nor to deep packet inspection techniques to read application layer information. Instead, classification is performed starting from probe requests Wi-Fi frames, which can be sniffed with inexpensive commercial hardware. We extract distinctive features from probe request frames (how many probe requests are transmitted by each device, how frequently, etc.) and take a machine learning approach, training four different classifiers to recognize the two types of devices. We compare the performance of the different classifiers and identify a solution based on a Random Decision Forest that correctly classify devices 95% of the times. The classification method is then used as a pre-processing stage to analyze network traffic traces from the wireless network of a university building, with interesting considerations on the way different types of devices uses the network (amount of data exchanged, duration of connections, etc.). The proposed methodology finds application in many scenarios related to Wi-Fi network management/optimization and Wi-Fi based services.
{"title":"Passive Classification of Wi-Fi Enabled Devices","authors":"A. Redondi, D. Sanvito, M. Cesana","doi":"10.1145/2988287.2989161","DOIUrl":"https://doi.org/10.1145/2988287.2989161","url":null,"abstract":"We propose a method for classifying Wi-Fi enabled mobile handheld devices (smartphones) and non-handheld devices (laptops) in a completely passive way, that is resorting neither to traffic probes on network edge devices nor to deep packet inspection techniques to read application layer information. Instead, classification is performed starting from probe requests Wi-Fi frames, which can be sniffed with inexpensive commercial hardware. We extract distinctive features from probe request frames (how many probe requests are transmitted by each device, how frequently, etc.) and take a machine learning approach, training four different classifiers to recognize the two types of devices. We compare the performance of the different classifiers and identify a solution based on a Random Decision Forest that correctly classify devices 95% of the times. The classification method is then used as a pre-processing stage to analyze network traffic traces from the wireless network of a university building, with interesting considerations on the way different types of devices uses the network (amount of data exchanged, duration of connections, etc.). The proposed methodology finds application in many scenarios related to Wi-Fi network management/optimization and Wi-Fi based services.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132505096","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}
Martin C. Bor, U. Roedig, T. Voigt, Juan M. Alonso
New Internet of Things (IoT) technologies such as Long Range (LoRa) are emerging which enable power efficient wireless communication over very long distances. Devices typically communicate directly to a sink node which removes the need of constructing and maintaining a complex multi-hop network. Given the fact that a wide area is covered and that all devices communicate directly to a few sink nodes a large number of nodes have to share the communication medium. LoRa provides for this reason a range of communication options (centre frequency, spreading factor, bandwidth, coding rates) from which a transmitter can choose. Many combination settings are orthogonal and provide simultaneous collision free communications. Nevertheless, there is a limit regarding the number of transmitters a LoRa system can support. In this paper we investigate the capacity limits of LoRa networks. Using experiments we develop models describing LoRa communication behaviour. We use these models to parameterise a LoRa simulation to study scalability. Our experiments show that a typical smart city deployment can support 120 nodes per 3.8 ha, which is not sufficient for future IoT deployments. LoRa networks can scale quite well, however, if they use dynamic communication parameter selection and/or multiple sinks.
新的物联网(IoT)技术，如远程(LoRa)正在出现，可以实现长距离的节能无线通信。设备通常直接与汇聚节点通信，这样就不需要构建和维护复杂的多跳网络。由于覆盖范围很广，而且所有设备都直接与几个汇聚节点通信，因此大量节点必须共享通信媒介。因此，LoRa提供了一系列通信选项(中心频率、扩频系数、带宽、编码速率)，发射机可以从中选择。许多组合设置是正交的，并提供同时无碰撞的通信。然而，LoRa系统所能支持的发射机数量是有限的。本文主要研究LoRa网络的容量限制问题。通过实验，我们开发了描述LoRa通信行为的模型。我们使用这些模型来参数化LoRa仿真以研究可扩展性。我们的实验表明，典型的智慧城市部署可以支持每3.8 ha 120个节点，这对于未来的物联网部署是不够的。但是，如果使用动态通信参数选择和/或多个接收器，LoRa网络可以很好地扩展。
{"title":"Do LoRa Low-Power Wide-Area Networks Scale?","authors":"Martin C. Bor, U. Roedig, T. Voigt, Juan M. Alonso","doi":"10.1145/2988287.2989163","DOIUrl":"https://doi.org/10.1145/2988287.2989163","url":null,"abstract":"New Internet of Things (IoT) technologies such as Long Range (LoRa) are emerging which enable power efficient wireless communication over very long distances. Devices typically communicate directly to a sink node which removes the need of constructing and maintaining a complex multi-hop network. Given the fact that a wide area is covered and that all devices communicate directly to a few sink nodes a large number of nodes have to share the communication medium. LoRa provides for this reason a range of communication options (centre frequency, spreading factor, bandwidth, coding rates) from which a transmitter can choose. Many combination settings are orthogonal and provide simultaneous collision free communications. Nevertheless, there is a limit regarding the number of transmitters a LoRa system can support. In this paper we investigate the capacity limits of LoRa networks. Using experiments we develop models describing LoRa communication behaviour. We use these models to parameterise a LoRa simulation to study scalability. Our experiments show that a typical smart city deployment can support 120 nodes per 3.8 ha, which is not sufficient for future IoT deployments. LoRa networks can scale quite well, however, if they use dynamic communication parameter selection and/or multiple sinks.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115311359","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}
Iñaki Ucar, Carlos Donato, P. Serrano, Andres Garcia-Saavedra, A. Azcorra, A. Banchs
Rate adaptation in 802.11 WLANs has received a lot of attention from the research community, with most of the proposals aiming at maximising throughput based on network conditions. Considering energy consumption, an implicit assumption is that optimality in throughput implies optimality in energy efficiency, but this assumption has been recently put into question. In this paper, we address via analysis and experimentation the relation between throughput performance and energy efficiency in multi-rate 802.11 scenarios. We demonstrate the trade-off between these performance figures, confirming that they may not be simultaneously optimised, and analyse their sensitivity towards the energy consumption parameters of the device. Our results provide the means to design novel rate adaptation schemes that takes energy consumption into account.
{"title":"Revisiting 802.11 Rate Adaptation from Energy Consumption's Perspective","authors":"Iñaki Ucar, Carlos Donato, P. Serrano, Andres Garcia-Saavedra, A. Azcorra, A. Banchs","doi":"10.1145/2988287.2989149","DOIUrl":"https://doi.org/10.1145/2988287.2989149","url":null,"abstract":"Rate adaptation in 802.11 WLANs has received a lot of attention from the research community, with most of the proposals aiming at maximising throughput based on network conditions. Considering energy consumption, an implicit assumption is that optimality in throughput implies optimality in energy efficiency, but this assumption has been recently put into question. In this paper, we address via analysis and experimentation the relation between throughput performance and energy efficiency in multi-rate 802.11 scenarios. We demonstrate the trade-off between these performance figures, confirming that they may not be simultaneously optimised, and analyse their sensitivity towards the energy consumption parameters of the device. Our results provide the means to design novel rate adaptation schemes that takes energy consumption into account.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133706213","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}
In theory, on-demand routing is very attractive for mobile ad hoc networks (MANET), because it induces signaling only for those destinations for which there is data traffic. However, in practice, the signaling overhead of existing on-demand routing protocols becomes excessive as the rate of topology changes increases due to mobility or other causes. We introduce the first on-demand routing approach that eliminates the main limitation of on-demand routing by aggregating route requests (RREQ) for the same destinations. The approach can be applied to any existing on-demand routing protocol, and we introduce the Ad-hoc Demand-Aggregated Routing with Adaptation (ADARA) as an example of how RREQ aggregation can be used. ADARA is compared to AODV and OLSR using discrete-event simulations, and the results show that aggregating RREQs can make on-demand routing more efficient than existing proactive or on-demand routing protocols.
{"title":"Making On-Demand Routing Efficient with Route-Request Aggregation","authors":"Maziar Mirzazad Barijough, J. Garcia-Luna-Aceves","doi":"10.1145/2988287.2989155","DOIUrl":"https://doi.org/10.1145/2988287.2989155","url":null,"abstract":"In theory, on-demand routing is very attractive for mobile ad hoc networks (MANET), because it induces signaling only for those destinations for which there is data traffic. However, in practice, the signaling overhead of existing on-demand routing protocols becomes excessive as the rate of topology changes increases due to mobility or other causes. We introduce the first on-demand routing approach that eliminates the main limitation of on-demand routing by aggregating route requests (RREQ) for the same destinations. The approach can be applied to any existing on-demand routing protocol, and we introduce the Ad-hoc Demand-Aggregated Routing with Adaptation (ADARA) as an example of how RREQ aggregation can be used. ADARA is compared to AODV and OLSR using discrete-event simulations, and the results show that aggregating RREQs can make on-demand routing more efficient than existing proactive or on-demand routing protocols.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115671168","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}
Sahar Imtiaz, H. Ghauch, Muhammad Mahboob Ur Rahman, G. Koudouridis, J. Gross
Provision of high data rates with always-on connectivity to high mobility users is one of the motivations for design of fifth generation (5G) systems. High system capacity can be achieved by coordination between large number of antennas, which is done using the cloud radio access network (CRAN) design in 5G systems. In terms of baseband processing, allocation of appropriate resources to the users is necessary to achieve high system capacity, for which the state of the art uses the users' channel state information (CSI); however, they do not take into account the associated overhead, which poses a major bottleneck for the effective system performance. In contrast to this approach, this paper proposes the use of machine learning for allocating resources to high mobility users using only their position estimates. Specifically, the `random forest' algorithm, a supervised machine learning technique, is used to design a learning-based resource allocation scheme by exploiting the relationships between the system parameters and the users' position estimates. In this way, the overhead for CSI acquisition is avoided by using the position estimates instead, with better spectrum utilization. While the initial numerical investigations, with minimum number of users in the system, show that the proposed learning-based scheme achieves 86% of the efficiency achieved by the perfect CSI-based scheme, if the effect of overhead is factored in, the proposed scheme performs better than the CSI-based approach. In a realistic scenario, with multiple users in the system, the significant increase in overhead for the CSI-based scheme leads to a performance gain of 100%, or more, by using the proposed scheme, and thus proving the proposed scheme to be more efficient in terms of system performance.
{"title":"Learning-Based Resource Allocation Scheme for TDD-Based 5G CRAN System","authors":"Sahar Imtiaz, H. Ghauch, Muhammad Mahboob Ur Rahman, G. Koudouridis, J. Gross","doi":"10.1145/2988287.2989158","DOIUrl":"https://doi.org/10.1145/2988287.2989158","url":null,"abstract":"Provision of high data rates with always-on connectivity to high mobility users is one of the motivations for design of fifth generation (5G) systems. High system capacity can be achieved by coordination between large number of antennas, which is done using the cloud radio access network (CRAN) design in 5G systems. In terms of baseband processing, allocation of appropriate resources to the users is necessary to achieve high system capacity, for which the state of the art uses the users' channel state information (CSI); however, they do not take into account the associated overhead, which poses a major bottleneck for the effective system performance. In contrast to this approach, this paper proposes the use of machine learning for allocating resources to high mobility users using only their position estimates. Specifically, the `random forest' algorithm, a supervised machine learning technique, is used to design a learning-based resource allocation scheme by exploiting the relationships between the system parameters and the users' position estimates. In this way, the overhead for CSI acquisition is avoided by using the position estimates instead, with better spectrum utilization. While the initial numerical investigations, with minimum number of users in the system, show that the proposed learning-based scheme achieves 86% of the efficiency achieved by the perfect CSI-based scheme, if the effect of overhead is factored in, the proposed scheme performs better than the CSI-based approach. In a realistic scenario, with multiple users in the system, the significant increase in overhead for the CSI-based scheme leads to a performance gain of 100%, or more, by using the proposed scheme, and thus proving the proposed scheme to be more efficient in terms of system performance.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129462654","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}
Due to the dramatic growth in mobile data traffic on one hand and the scarcity of the licensed spectrum on the other hand, mobile operators are considering the use of unlicensed bands (especially those in 5 GHz) as complementary spectrum for providing higher system capacity and better user experience. This approach is currently being standardized by 3GPP under the name of LTE Licensed-Assisted Access (LTE-LAA). In this paper, we take a holistic approach for LTE-LAA small cell traffic balancing by jointly optimizing the use of the licensed and unlicensed bands. We pose this traffic balancing as an optimization problem that seeks proportional fair coexistence of WiFi, small cell and macro cell users by adapting the transmission probability of the LTE-LAA small cell in the licensed and unlicensed bands. The motivation for this formulation is for the LTE-LAA small cell to switch between or aggregate licensed and unlicensed bands depending on the interference/traffic level and the number of active users in each band. We derive a closed form solution for this optimization problem and additionally propose a transmission mechanism for the operation of the LTE-LAA small cell on both bands. Through numerical and simulation results, we show that our proposed traffic balancing scheme, besides enabling better LTE-WiFi coexistence and efficient utilization of the radio resources relative to the existing traffic balancing scheme, also provides a better tradeoff between maximizing the total network throughput and achieving fairness among all network flows compared to alternative approaches.
{"title":"Holistic Small Cell Traffic Balancing across Licensed and Unlicensed Bands","authors":"Ursula Challita, M. Marina","doi":"10.1145/2988287.2989143","DOIUrl":"https://doi.org/10.1145/2988287.2989143","url":null,"abstract":"Due to the dramatic growth in mobile data traffic on one hand and the scarcity of the licensed spectrum on the other hand, mobile operators are considering the use of unlicensed bands (especially those in 5 GHz) as complementary spectrum for providing higher system capacity and better user experience. This approach is currently being standardized by 3GPP under the name of LTE Licensed-Assisted Access (LTE-LAA). In this paper, we take a holistic approach for LTE-LAA small cell traffic balancing by jointly optimizing the use of the licensed and unlicensed bands. We pose this traffic balancing as an optimization problem that seeks proportional fair coexistence of WiFi, small cell and macro cell users by adapting the transmission probability of the LTE-LAA small cell in the licensed and unlicensed bands. The motivation for this formulation is for the LTE-LAA small cell to switch between or aggregate licensed and unlicensed bands depending on the interference/traffic level and the number of active users in each band. We derive a closed form solution for this optimization problem and additionally propose a transmission mechanism for the operation of the LTE-LAA small cell on both bands. Through numerical and simulation results, we show that our proposed traffic balancing scheme, besides enabling better LTE-WiFi coexistence and efficient utilization of the radio resources relative to the existing traffic balancing scheme, also provides a better tradeoff between maximizing the total network throughput and achieving fairness among all network flows compared to alternative approaches.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122557599","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}
{"title":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","authors":"","doi":"10.1145/2988287","DOIUrl":"https://doi.org/10.1145/2988287","url":null,"abstract":"","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128986925","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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