In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned...In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.展开更多
A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmissio...A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmission connections can switch smoothly among the multiple proxies by maint aining a coherent connection context.The mechanism is transparent to application programs and can support th e building of VPN.With the cooperation of some other security components,the mechanism guarantees the reso urce availability and reliability of the end system against some attacks to the specific ports or hosts.展开更多
Implementing cooperative scheduling of multi-home microgrid energy and reducing the dependence on the main grid have become the focus of microgrid energy management research.This paper proposes a new multi-agent adapt...Implementing cooperative scheduling of multi-home microgrid energy and reducing the dependence on the main grid have become the focus of microgrid energy management research.This paper proposes a new multi-agent adaptive dynamic programming(MAADP)method for the cooperative control of distributed home energy.Each home is defined as a learning agent that needs to reasonably schedule the energy storage system to meet the respective load demand while accomplishing cooperative scheduling among the individual homes.In addition,an energy clearing center(ECC)is introduced to complete the energy exchange between each microgrid to protect the benefits of all parties.The proposed method adopts the learning strategy of“centralized learning and decentralized execution”to avoid the leakage of private information.The experimental comparison with the benchmark method verifies that the method can realize the cooperative scheduling of each home and reduce the dependence on the main grid.展开更多
Proxy Mobile IPv6 (PMIPv6) is a network based mobility management protocol. It is proposed by the Internet Engineering Task Force. In PMIPv6 the Mobile Node (MN) need not participate in signalling of mobility. PMIPv6 ...Proxy Mobile IPv6 (PMIPv6) is a network based mobility management protocol. It is proposed by the Internet Engineering Task Force. In PMIPv6 the Mobile Node (MN) need not participate in signalling of mobility. PMIPv6 is a layer 3 protocol. In this paper the issue of layer 3 mobility is resolved by the Enhanced Open Flow Technique (EOFT). Generally, the open flow protocol makes functions on network devices, routers, switches. Open flow controller act as server for network devices to make communication between them. In the proposed EOFT-PMIPv6, the control signalling and mobility is managed by EOFT controller. In PMIPv6, the Mobility Access gateway (MAG) has the responsibility of the control signalling. But in the EOFT-PMIPv6, the responsibility of MAG is done by the EOFT-Controller. In the proposed technique, the mobility management function is isolated from PMIPv6 mechanisms. These isolated mechanisms are combined in the EOFT-Con- troller. This EOFT-Controller satisfies the responsibility of the mechanisms which are separated from PMIPv6. The eminent mobile environment must provide the efficient multi-homing protocols. The proposed technique overcomes the problem of multihoming in PMIPv6. The EOFT-Controller takeover the responsibility of Layer 3 functions. Also, the proposed technique combines with Modified Mobility Access Gateway (M_MAG) and it handles the handover session dynamically. This paper provides the extended architecture of EOFT-PMIPv6 and provide unbeaten handover scheme for multi-homing. The result is provided by systematic analysis based on comparison with PMIPv6 and EOFT-PMIPv6 is obtained.展开更多
文摘In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.
基金National Natural Science Foundation ofChina (No.90104029)
文摘A multi-homed VPN architecture based on extended SOCKSv5 and TLS was proposed. The architecture employs a dynamic connection mechanism for multiple proxies in the end system,i n which the security-demanded transmission connections can switch smoothly among the multiple proxies by maint aining a coherent connection context.The mechanism is transparent to application programs and can support th e building of VPN.With the cooperation of some other security components,the mechanism guarantees the reso urce availability and reliability of the end system against some attacks to the specific ports or hosts.
基金supported in part by the National Key R&D Program of China(Nos.2021YFE0206100 and 2018YFB1702300)the National Natural Science Foundation of China(No.62073321)+1 种基金the National Defense Basic Scientific Research Program(No.JCKY2019203C029)the Science and Technology Development Fund,Macao SAR(No.0015/2020/AMJ).
文摘Implementing cooperative scheduling of multi-home microgrid energy and reducing the dependence on the main grid have become the focus of microgrid energy management research.This paper proposes a new multi-agent adaptive dynamic programming(MAADP)method for the cooperative control of distributed home energy.Each home is defined as a learning agent that needs to reasonably schedule the energy storage system to meet the respective load demand while accomplishing cooperative scheduling among the individual homes.In addition,an energy clearing center(ECC)is introduced to complete the energy exchange between each microgrid to protect the benefits of all parties.The proposed method adopts the learning strategy of“centralized learning and decentralized execution”to avoid the leakage of private information.The experimental comparison with the benchmark method verifies that the method can realize the cooperative scheduling of each home and reduce the dependence on the main grid.
文摘Proxy Mobile IPv6 (PMIPv6) is a network based mobility management protocol. It is proposed by the Internet Engineering Task Force. In PMIPv6 the Mobile Node (MN) need not participate in signalling of mobility. PMIPv6 is a layer 3 protocol. In this paper the issue of layer 3 mobility is resolved by the Enhanced Open Flow Technique (EOFT). Generally, the open flow protocol makes functions on network devices, routers, switches. Open flow controller act as server for network devices to make communication between them. In the proposed EOFT-PMIPv6, the control signalling and mobility is managed by EOFT controller. In PMIPv6, the Mobility Access gateway (MAG) has the responsibility of the control signalling. But in the EOFT-PMIPv6, the responsibility of MAG is done by the EOFT-Controller. In the proposed technique, the mobility management function is isolated from PMIPv6 mechanisms. These isolated mechanisms are combined in the EOFT-Con- troller. This EOFT-Controller satisfies the responsibility of the mechanisms which are separated from PMIPv6. The eminent mobile environment must provide the efficient multi-homing protocols. The proposed technique overcomes the problem of multihoming in PMIPv6. The EOFT-Controller takeover the responsibility of Layer 3 functions. Also, the proposed technique combines with Modified Mobility Access Gateway (M_MAG) and it handles the handover session dynamically. This paper provides the extended architecture of EOFT-PMIPv6 and provide unbeaten handover scheme for multi-homing. The result is provided by systematic analysis based on comparison with PMIPv6 and EOFT-PMIPv6 is obtained.
