Multi-hop is the current communication architecture of wireless mesh and ad hoc networks. Information is relayed from each source to its destination in successive transmissions between intermediate nodes. A major problem regarding this architecture is its poor performance at large system size: as the number of users in a wireless network increases, the communication rate for each user rapidly decreases. Can we design new communication architectures that significantly increase the capacity of large wireless networks? In this monograph, we present a scaling law characterization of the information-theoretic capacity of wireless networks, which sheds some light on this question. We show that the answer depends on the parameter range in which a particular network lies, namely the operating regime of the network. There are operating regimes where the information-theoretic capacity of the network is drastically higher than the capacity of conventional multi-hop. New architectures can provide substantial capacity gains here. We determine what these regimes are and investigate the new architectures that are able to approach the information-theoretic capacity of the network. In some regimes, there is no way to outperform multi-hop. In other words, the conventional multi-hop architecture indeed achieves the information-theoretic capacity of the network. We discuss the fundamental factors limiting the capacity of the network in these regimes and provide an understanding of why conventional multi-hop indeed turns out to be the right architecture. The monograph is structured as follows: In Section 2, we discuss the role of interference in wireless networks. We show that while current communication architectures are fundamentally limited by interference, new architectures based on distributed MIMO communication can overcome this interference limitation, yielding drastic performance improvements. Section 3 discusses the impact of power. We show that in power-limited regimes, distributed MIMO-based techniques are important not only because they remove interference but also because they provide received power gain. We identify the power-limited operating regimes of wireless networks and define the engineering quantities that determine the operating regime of a given wireless network. We show that unless the wireless network operates in a severely power-limited regime, distributed MIMO communication provides significant capacity gain over current techniques. Finally, in Section 4, we study how the area of the network, i.e., space, impacts the capacity of the network. This study enriches the earlier picture by adding new operating regimes where wireless networks can be moderately or severely space-limited. We see that unless the network is severely limited in space, distributed-MIMO-based communication continues to provide drastic improvements over conventional multi-hop.
{"title":"Operating Regimes of Large Wireless Networks","authors":"Ayfer Özgür, O. Lévêque, David Tse","doi":"10.1561/1300000016","DOIUrl":"https://doi.org/10.1561/1300000016","url":null,"abstract":"Multi-hop is the current communication architecture of wireless mesh and ad hoc networks. Information is relayed from each source to its destination in successive transmissions between intermediate nodes. A major problem regarding this architecture is its poor performance at large system size: as the number of users in a wireless network increases, the communication rate for each user rapidly decreases. Can we design new communication architectures that significantly increase the capacity of large wireless networks? \u0000 \u0000In this monograph, we present a scaling law characterization of the information-theoretic capacity of wireless networks, which sheds some light on this question. We show that the answer depends on the parameter range in which a particular network lies, namely the operating regime of the network. There are operating regimes where the information-theoretic capacity of the network is drastically higher than the capacity of conventional multi-hop. New architectures can provide substantial capacity gains here. We determine what these regimes are and investigate the new architectures that are able to approach the information-theoretic capacity of the network. In some regimes, there is no way to outperform multi-hop. In other words, the conventional multi-hop architecture indeed achieves the information-theoretic capacity of the network. We discuss the fundamental factors limiting the capacity of the network in these regimes and provide an understanding of why conventional multi-hop indeed turns out to be the right architecture. \u0000 \u0000The monograph is structured as follows: In Section 2, we discuss the role of interference in wireless networks. We show that while current communication architectures are fundamentally limited by interference, new architectures based on distributed MIMO communication can overcome this interference limitation, yielding drastic performance improvements. Section 3 discusses the impact of power. We show that in power-limited regimes, distributed MIMO-based techniques are important not only because they remove interference but also because they provide received power gain. We identify the power-limited operating regimes of wireless networks and define the engineering quantities that determine the operating regime of a given wireless network. We show that unless the wireless network operates in a severely power-limited regime, distributed MIMO communication provides significant capacity gain over current techniques. Finally, in Section 4, we study how the area of the network, i.e., space, impacts the capacity of the network. This study enriches the earlier picture by adding new operating regimes where wireless networks can be moderately or severely space-limited. We see that unless the network is severely limited in space, distributed-MIMO-based communication continues to provide drastic improvements over conventional multi-hop.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125934460","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 present a review of the problem of scheduled channel access in wireless networks with emphasis on ad hoc and sensor networks as opposed to WiFi, cellular, and infrastructure-based networks. After a brief introduction and problem definition, we examine in detail specific instances of the scheduling problem. These instances differ from each other in a number of ways, including the detailed network model and the objective function or performance criteria. They all share the “layerless” viewpoint that connects the access problem with the physical layer and, occasionally, with the routing layer. This review is intended to provide a reference point for the rich set of problems that arise in the allocation of resources in modern and future networks.
{"title":"Scheduling in Wireless Networks","authors":"A. Pantelidou, A. Ephremides","doi":"10.1561/1300000030","DOIUrl":"https://doi.org/10.1561/1300000030","url":null,"abstract":"We present a review of the problem of scheduled channel access in wireless networks with emphasis on ad hoc and sensor networks as opposed to WiFi, cellular, and infrastructure-based networks. After a brief introduction and problem definition, we examine in detail specific instances of the scheduling problem. These instances differ from each other in a number of ways, including the detailed network model and the objective function or performance criteria. They all share the “layerless” viewpoint that connects the access problem with the physical layer and, occasionally, with the routing layer. This review is intended to provide a reference point for the rich set of problems that arise in the allocation of resources in modern and future networks.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130363263","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 monograph we survey results from a newly emerging line of research that targets algorithm analysis in the physical interference model. In the main part of our monograph we focus on wireless scheduling: given a set of communication requests, arbitrarily distributed in space, how can these requests be scheduled efficiently? We study the difficulty of this problem and we examine algorithms for wireless scheduling with provable performance guarantees. Moreover, we present a few results for related problems and give additional context.
{"title":"Efficiency of Wireless Networks: Approximation Algorithms for the Physical Interference Model","authors":"Olga Goussevskaia, Y. Pignolet, Roger Wattenhofer","doi":"10.1561/1300000019","DOIUrl":"https://doi.org/10.1561/1300000019","url":null,"abstract":"In this monograph we survey results from a newly emerging line of research that targets algorithm analysis in the physical interference model. In the main part of our monograph we focus on wireless scheduling: given a set of communication requests, arbitrarily distributed in space, how can these requests be scheduled efficiently? We study the difficulty of this problem and we examine algorithms for wireless scheduling with provable performance guarantees. Moreover, we present a few results for related problems and give additional context.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122910496","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}
Since interference is the main performance-limiting factor in most wireless networks, it is crucial to characterize the interference statistics. The two main determinants of the interference are the network geometry (spatial distribution of concurrently transmitting nodes) and the path loss law (signal attenuation with distance). For certain classes of node distributions, most notably Poisson point processes, and attenuation laws, closed-form results are available, for both the interference itself as well as the signal-to-interference ratios, which determine the network performance. This monograph presents an overview of these results and gives an introduction to the analytical techniques used in their derivation. The node distribution models range from lattices to homogeneous and clustered Poisson models to general motion-invariant ones. The analysis of the more general models requires the use of Palm theory, in particular conditional probability generating functionals, which are briefly introduced in the appendix.
{"title":"Interference in Large Wireless Networks","authors":"M. Haenggi, R. Ganti","doi":"10.1561/1300000015","DOIUrl":"https://doi.org/10.1561/1300000015","url":null,"abstract":"Since interference is the main performance-limiting factor in most wireless networks, it is crucial to characterize the interference statistics. The two main determinants of the interference are the network geometry (spatial distribution of concurrently transmitting nodes) and the path loss law (signal attenuation with distance). For certain classes of node distributions, most notably Poisson point processes, and attenuation laws, closed-form results are available, for both the interference itself as well as the signal-to-interference ratios, which determine the network performance. \u0000 \u0000This monograph presents an overview of these results and gives an introduction to the analytical techniques used in their derivation. The node distribution models range from lattices to homogeneous and clustered Poisson models to general motion-invariant ones. The analysis of the more general models requires the use of Palm theory, in particular conditional probability generating functionals, which are briefly introduced in the appendix.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124367394","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}
Volume I first provides a compact survey on classical stochastic geometry models, with a main focus on spatial shot-noise processes, coverage processes and random tessellations. It then focuses on signal to interference noise ratio (SINR) stochastic geometry, which is the basis for the modeling of wireless network protocols and architectures considered in Volume II. It also contains an appendix on mathematical tools used throughout Stochastic Geometry and Wireless Networks, Volumes I and II.
{"title":"Stochastic Geometry and Wireless Networks, Volume 1: Theory","authors":"F. Baccelli, B. Błaszczyszyn","doi":"10.1561/1300000006","DOIUrl":"https://doi.org/10.1561/1300000006","url":null,"abstract":"Volume I first provides a compact survey on classical stochastic geometry models, with a main focus on spatial shot-noise processes, coverage processes and random tessellations. It then focuses on signal to interference noise ratio (SINR) stochastic geometry, which is the basis for the modeling of wireless network protocols and architectures considered in Volume II. It also contains an appendix on mathematical tools used throughout Stochastic Geometry and Wireless Networks, Volumes I and II.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126950489","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}
Unlike the Telephone network or the Internet, many of the next generation networks are not engineered for the purpose of providing efficient communication between various networked entities. Examples abound: sensor networks, peer-to-peer networks, mobile networks of vehicles and social networks. Indeed, these emerging networks do require algorithms for communication, computation, or merely spreading information. For example, estimation algorithms in sensor networks, broadcasting news through a peer-to-peer network, or viral advertising in a social network. These networks lack infrastructure; they exhibit unpredictable dynamics and they face stringent resource constraints. Therefore, algorithms operating within them need to be extremely simple, distributed, robust against networks dynamics, and efficient in resource utilization. Gossip algorithms, as the name suggests, are built upon a gossip or rumor style unreliable, asynchronous information exchange protocol. Due to their immense simplicity and wide applicability, this class of algorithms has emerged as a canonical architectural solution for the next generation networks. This has led to exciting recent progress to understand the applicability as well as limitations of the Gossip algorithms. In this review, we provide a systematic survey of many of these recent results on Gossip network algorithms. The algorithmic results described here utilize interdisciplinary tools from Markov chain theory, Optimization, Percolation, Random graphs, Spectral graph theory, and Coding.
{"title":"Gossip Algorithms","authors":"D. Shah","doi":"10.1561/1300000014","DOIUrl":"https://doi.org/10.1561/1300000014","url":null,"abstract":"Unlike the Telephone network or the Internet, many of the next generation networks are not engineered for the purpose of providing efficient communication between various networked entities. Examples abound: sensor networks, peer-to-peer networks, mobile networks of vehicles and social networks. Indeed, these emerging networks do require algorithms for communication, computation, or merely spreading information. For example, estimation algorithms in sensor networks, broadcasting news through a peer-to-peer network, or viral advertising in a social network. These networks lack infrastructure; they exhibit unpredictable dynamics and they face stringent resource constraints. Therefore, algorithms operating within them need to be extremely simple, distributed, robust against networks dynamics, and efficient in resource utilization. \u0000 \u0000Gossip algorithms, as the name suggests, are built upon a gossip or rumor style unreliable, asynchronous information exchange protocol. Due to their immense simplicity and wide applicability, this class of algorithms has emerged as a canonical architectural solution for the next generation networks. This has led to exciting recent progress to understand the applicability as well as limitations of the Gossip algorithms. In this review, we provide a systematic survey of many of these recent results on Gossip network algorithms. The algorithmic results described here utilize interdisciplinary tools from Markov chain theory, Optimization, Percolation, Random graphs, Spectral graph theory, and Coding.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129310447","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}
Transmit power in wireless cellular networks is a key degree of freedom in the management of interference, energy, and connectivity. Power control in both the uplink and downlink of a cellular network has been extensively studied, especially over the last 15 years, and some of the results have enabled the continuous evolution and significant impact of the digital cellular technology. This survey provides a comprehensive discussion of the models, algorithms, analysis, and methodologies in this vast and growing literature. It starts with a taxonomy of the wide range of power control problem formulations, and progresses from the basic formulation to more sophisticated ones. When transmit power is the only set of optimization variables, algorithms for fixed SIR are presented first, before turning to their robust versions and joint SIR and power optimization. This is followed by opportunistic and non-cooperative power control. Then joint control of power together with beamforming pattern, base station assignment, spectrum allocation, and transmit schedule is surveyedbreak one-by-one. Throughout the survey, we highlight the use of mathematical language and tools in the study of power control, including optimization theory, control theory, game theory, and linear algebra. Practical implementations of some of the algorithms in operational networks are discussed in the concluding section. As illustrated by the open problems presented at the end of most chapters, in the area of power control in cellular networks, there are still many under-explored directions and unresolved issues that remain theoretically challenging and practically important..
{"title":"Power Control in Wireless Cellular Networks","authors":"M. Chiang, P. Hande, T. Lan, C. Tan","doi":"10.1561/1300000009","DOIUrl":"https://doi.org/10.1561/1300000009","url":null,"abstract":"Transmit power in wireless cellular networks is a key degree of freedom in the management of interference, energy, and connectivity. Power control in both the uplink and downlink of a cellular network has been extensively studied, especially over the last 15 years, and some of the results have enabled the continuous evolution and significant impact of the digital cellular technology. \u0000 \u0000This survey provides a comprehensive discussion of the models, algorithms, analysis, and methodologies in this vast and growing literature. It starts with a taxonomy of the wide range of power control problem formulations, and progresses from the basic formulation to more sophisticated ones. When transmit power is the only set of optimization variables, algorithms for fixed SIR are presented first, before turning to their robust versions and joint SIR and power optimization. This is followed by opportunistic and non-cooperative power control. Then joint control of power together with beamforming pattern, base station assignment, spectrum allocation, and transmit schedule is surveyedbreak one-by-one. \u0000 \u0000Throughout the survey, we highlight the use of mathematical language and tools in the study of power control, including optimization theory, control theory, game theory, and linear algebra. Practical implementations of some of the algorithms in operational networks are discussed in the concluding section. As illustrated by the open problems presented at the end of most chapters, in the area of power control in cellular networks, there are still many under-explored directions and unresolved issues that remain theoretically challenging and practically important..","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114515178","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 study how protocol design for various functionalities within a communication network architecture can be viewed as a distributed resource allocation problem. This involves understanding what resources are, how to allocate them fairly, and perhaps most importantly, how to achieve this goal in a distributed and stable fashion. We start with ideas of a centralized optimization framework and show how congestion control, routing and scheduling in wired and wireless networks can be thought of as fair resource allocation. We then move to the study of controllers that allow a decentralized solution of this problem. These controllers are the analytical equivalent of protocols in use on the Internet today, and we describe existing protocols as realizations of such controllers. The Internet is a dynamic system with feedback delays and flows that arrive and depart, which means that stability of the system cannot be taken for granted. We show how to incorporate stability into protocols, and thus, prevent undesirable network behavior. Finally, we consider a futuristic scenario where users are aware of the effects of their actions and try to game the system. We will see that the optimization framework is remarkably robust even to such gaming.
{"title":"Network Optimization and Control","authors":"S. Shakkottai, R. Srikant, A. Ephremides","doi":"10.1561/1300000007","DOIUrl":"https://doi.org/10.1561/1300000007","url":null,"abstract":"We study how protocol design for various functionalities within a communication network architecture can be viewed as a distributed resource allocation problem. This involves understanding what resources are, how to allocate them fairly, and perhaps most importantly, how to achieve this goal in a distributed and stable fashion. We start with ideas of a centralized optimization framework and show how congestion control, routing and scheduling in wired and wireless networks can be thought of as fair resource allocation. We then move to the study of controllers that allow a decentralized solution of this problem. These controllers are the analytical equivalent of protocols in use on the Internet today, and we describe existing protocols as realizations of such controllers. The Internet is a dynamic system with feedback delays and flows that arrive and depart, which means that stability of the system cannot be taken for granted. We show how to incorporate stability into protocols, and thus, prevent undesirable network behavior. Finally, we consider a futuristic scenario where users are aware of the effects of their actions and try to game the system. We will see that the optimization framework is remarkably robust even to such gaming.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125771379","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}
Network coding is an elegant and novel technique introduced at the turn of the millennium to improve network throughput and performance. It is expected to be a critical technology for networks of the future. This tutorial deals with wireless and content distribution networks, considered to be the most likely applications of network coding, and it also reviews emerging applications of network coding such as network monitoring and management. Multiple unicasts, security, networks with unreliable links, and quantum networks are also addressed. The preceding companion deals with theoretical foundations of network coding.
{"title":"Network Coding Applications","authors":"C. Fragouli, E. Soljanin","doi":"10.1561/1300000013","DOIUrl":"https://doi.org/10.1561/1300000013","url":null,"abstract":"Network coding is an elegant and novel technique introduced at the turn of the millennium to improve network throughput and performance. It is expected to be a critical technology for networks of the future. This tutorial deals with wireless and content distribution networks, considered to be the most likely applications of network coding, and it also reviews emerging applications of network coding such as network monitoring and management. Multiple unicasts, security, networks with unreliable links, and quantum networks are also addressed. The preceding companion deals with theoretical foundations of network coding.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131009219","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}
Network coding is an elegant and novel technique introduced at the turn of the millennium to improve network throughput and performance. It is expected to be a critical technology for networks of the future. This tutorial addresses the first most natural questions one would ask about this new technique: how network coding works and what are its benefits, how network codes are designed and how much it costs to deploy networks implementing such codes, and finally, whether there are methods to deal with cycles and delay that are present in all real networks. A companion issue deals primarily with applications of network coding.
{"title":"Network Coding Fundamentals","authors":"C. Fragouli, E. Soljanin","doi":"10.1561/1300000003","DOIUrl":"https://doi.org/10.1561/1300000003","url":null,"abstract":"Network coding is an elegant and novel technique introduced at the turn of the millennium to improve network throughput and performance. It is expected to be a critical technology for networks of the future. This tutorial addresses the first most natural questions one would ask about this new technique: how network coding works and what are its benefits, how network codes are designed and how much it costs to deploy networks implementing such codes, and finally, whether there are methods to deal with cycles and delay that are present in all real networks. A companion issue deals primarily with applications of network coding.","PeriodicalId":188056,"journal":{"name":"Found. Trends Netw.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134131648","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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