The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We pro...The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.展开更多
1|Background The innovation of triboelectric nanogenerators and their application in self‐powered sensors[1-3]provides a new strat-egy for sensor development.Such a development is becoming an important part of IoT as...1|Background The innovation of triboelectric nanogenerators and their application in self‐powered sensors[1-3]provides a new strat-egy for sensor development.Such a development is becoming an important part of IoT as a large number of sensors are needed to sense different things and communicate over net-works.Among the sensors,triboelectric nanogenerator(TENG)based sensors are attracting rising attention during the last 10 years.A unique feature of the TENG sensors is the self‐powering,which eliminates the need for batteries that are normally required of other types of sensors.In the early years of TENG sensors,researchers focused on the sensors'feasibility,flexibility,and sensitivity[4-7].Lately,TENG sensing systems[8,9]have been developed to obtain information from different places and times,which provides more data to be analyzed to describe a specific scenario.Moreover,the data could be communicated over a cloud.展开更多
In this paper, we present a novel, dynamic collaboration cloud platform in which a Combinatorial Auction（CA）-based market model enables the platform to run effectively. The platform can facilitate expense reduction ...In this paper, we present a novel, dynamic collaboration cloud platform in which a Combinatorial Auction（CA）-based market model enables the platform to run effectively. The platform can facilitate expense reduction and improve the scalability of the cloud, which is divided into three layers： The user-layer receives requests from end-users, the auction-layer matches the requests with the cloud services provided by the Cloud Service Provider（CSP）, and the CSP-layer forms a coalition to improve serving ability to satisfy complex requirements of users.In fact, the aim of the coalition formation is to find suitable partners for a particular CSP. However, identifying a suitable combination of partners to form the coalition is an NP-hard problem. Hence, we propose approximation algorithms for the coalition formation. The Breadth Traversal Algorithm（BTA） and Revised Ant Colony Algorithm（RACA） are proposed to form a coalition when bidding for a single cloud service in the auction. The experimental results show that RACA outperforms the BTA in bid price. Other experiments were conducted to evaluate the impact of the communication cost on coalition formation and to assess the impact of iteration times for the optimal bidding price. In addition, the performance of the market model was compared to the existing CA-based model in terms of economic efficiency.展开更多
基金This research was supported by Science and Technology Research Project of Education Department of Jiangxi Province,China(Nos.GJJ2206701,GJJ2206717).
文摘The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.
基金supported by the Swedish Research Council,Stiftelsen Promobilia and the Knowledge Foundation of Sweden.
文摘1|Background The innovation of triboelectric nanogenerators and their application in self‐powered sensors[1-3]provides a new strat-egy for sensor development.Such a development is becoming an important part of IoT as a large number of sensors are needed to sense different things and communicate over net-works.Among the sensors,triboelectric nanogenerator(TENG)based sensors are attracting rising attention during the last 10 years.A unique feature of the TENG sensors is the self‐powering,which eliminates the need for batteries that are normally required of other types of sensors.In the early years of TENG sensors,researchers focused on the sensors'feasibility,flexibility,and sensitivity[4-7].Lately,TENG sensing systems[8,9]have been developed to obtain information from different places and times,which provides more data to be analyzed to describe a specific scenario.Moreover,the data could be communicated over a cloud.
基金supported by the National Natural Science Foundation of China (Nos. 61070133, 61170201, and 61472344)the Collegiate Natural Science Foundation of Jiangsu Province (Grant No. 11KJD520011)+1 种基金Six talent peaks project in Jiangsu Province (No. 2011-DZXX-032)the Scientific Research Foundation of Graduate School of Jiangsu Province (No. CXZZ13 0901)
文摘In this paper, we present a novel, dynamic collaboration cloud platform in which a Combinatorial Auction（CA）-based market model enables the platform to run effectively. The platform can facilitate expense reduction and improve the scalability of the cloud, which is divided into three layers： The user-layer receives requests from end-users, the auction-layer matches the requests with the cloud services provided by the Cloud Service Provider（CSP）, and the CSP-layer forms a coalition to improve serving ability to satisfy complex requirements of users.In fact, the aim of the coalition formation is to find suitable partners for a particular CSP. However, identifying a suitable combination of partners to form the coalition is an NP-hard problem. Hence, we propose approximation algorithms for the coalition formation. The Breadth Traversal Algorithm（BTA） and Revised Ant Colony Algorithm（RACA） are proposed to form a coalition when bidding for a single cloud service in the auction. The experimental results show that RACA outperforms the BTA in bid price. Other experiments were conducted to evaluate the impact of the communication cost on coalition formation and to assess the impact of iteration times for the optimal bidding price. In addition, the performance of the market model was compared to the existing CA-based model in terms of economic efficiency.
