Virtualization of network/service functions means time sharing network/service（and affiliated）resources in a hyper speed manner.The concept of time sharing was popularized in the 1970s with mainframe computing.The s...Virtualization of network/service functions means time sharing network/service（and affiliated）resources in a hyper speed manner.The concept of time sharing was popularized in the 1970s with mainframe computing.The same concept has recently resurfaced under the guise of cloud computing and virtualized computing.Although cloud computing was originally used in IT for server virtualization,the ICT industry is taking a new look at virtualization.This paradigm shift is shaking up the computing,storage,networking,and ser vice industries.The hope is that virtualizing and automating configuration and service management/orchestration will save both capes and opex for network transformation.A complimentary trend is the separation（over an open interface）of control and transmission.This is commonly referred to as software defined networking（SDN）.This paper reviews trends in network/service functions,efforts to standardize these functions,and required management and orchestration.展开更多
With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)sat...With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.展开更多
Service function chains(SFC)mapping takes the responsibility for managing virtual network functions(VNFs).In SFC mapping,existing solutions duplicate VNFs with redundant instances to provide high availability in respo...Service function chains(SFC)mapping takes the responsibility for managing virtual network functions(VNFs).In SFC mapping,existing solutions duplicate VNFs with redundant instances to provide high availability in response to failures.However,as a compromise,these solutions result in high resource consumption due to device maintenance.In this paper,we propose a novel method named dynamic backup sharing(DBS)that allows SFCs to dynamically share backups to reduce resource consumption.DBS formulates the problem of sharing backups among different VNFs as an integer linear programming(ILP).Thereafter,we design a novel online algorithm based on dynamic programming to solve the problem.The experimental results indicate that DBS outperforms state-ofthe-art works by reducing resource consumption and improving the number of accepted requests.展开更多
Software Defined Satellite Networks(SDSN) are proposed to solve the problems in traditional satellite networks, such as time-consuming configuration and inflexible traffic scheduling. The emerging application of small...Software Defined Satellite Networks(SDSN) are proposed to solve the problems in traditional satellite networks, such as time-consuming configuration and inflexible traffic scheduling. The emerging application of small satellite and research of SDSN make it possible for satellite networks to provide flexible network services. Service Function Chain(SFC) can satisfy this need. In this paper, we are motivated to investigate applying SFC in the small satellite-based SDSN for service delivery. We introduce the structure of the multi-layer constellation-based SDSN. Then, we describe two deployment patterns of SFC in SDSN, the Multi-Domain(MD) pattern and the Satellite Formation(SF) pattern. We propose two algorithms, SFP-MD, and SFP-SF, to calculate the Service Function Path(SFP). We implement the algorithms and conduct contrast experiments in our prototype. Finally, we summarize the applicable conditions of two deployment patterns according to the experimental results in terms of hops, delay, and packet loss rate.展开更多
Network function virtualization is a new network concept that moves network functions from dedicated hardware to software-defined applications running on standard high volume severs. In order to accomplish network ser...Network function virtualization is a new network concept that moves network functions from dedicated hardware to software-defined applications running on standard high volume severs. In order to accomplish network services, traffic flows are usually processed by a list of network functions in sequence which is defined by service function chain. By incorporating network function virtualization in inter-data center(DC) network, we can use the network resources intelligently and deploy network services faster. However, orchestrating service function chains across multiple data centers will incur high deployment cost, including the inter-data center bandwidth cost, virtual network function cost and the intra-data center bandwidth cost. In this paper, we orchestrate SFCs across multiple data centers, with a goal to minimize the overall cost. An integer linear programming(ILP) model is formulated and we provide a meta-heuristic algorithm named GBAO which contains three modules to solve it. We implemented our algorithm in Python and performed side-by-side comparison with prior algorithms. Simulation results show that our proposed algorithm reduces the overall cost by at least 21.4% over the existing algorithms for accommodating the same service function chain requests.展开更多
Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not be...Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.展开更多
It is foreseen that the Internet of Things (IoT) will comprise billions of connected devices, and this will make the provi?sioning and operation of some IoT connectivity services more challenging. Indeed, IoT services...It is foreseen that the Internet of Things (IoT) will comprise billions of connected devices, and this will make the provi?sioning and operation of some IoT connectivity services more challenging. Indeed, IoT services are very different from lega?cy Internet services because of their dimensioning figures and also because IoT services differ dramatically in terms of na?ture and constraints. For example, IoT services often rely on energy and CPU?constrained sensor technologies, regardless of whether the service is for home automation, smart building, e?health, or power or water metering on a regional or national scale. Also, some IoT services, such as dynamic monitoring of biometric data, manipulation of sensitive information, and pri?vacy needs to be safeguarded whenever this information is for?warded over the underlying IoT network infrastructure. This paper discusses how software?defined networking (SDN) can facilitate the deployment and operation of some advanced IoT services regardless of their nature or scope. SDN introduces a high degree of automation in service delivery and operation-from dynamic IoT service parameter exposure and negotiation to resource allocation, service fulfillment, and assurance. This paper does not argue that all IoT services must adopt SDN. Rather, it is left to the discretion of operators to decide which IoT services can best leverage SDN capabilities. This paper only discusses managed IoT services, i.e., services that are op?erated by a service provider.展开更多
Due to the development of network technology,the number of users is increasing rapidly,and the demand for emerging multicast services is becoming more and more abundant,traffic data is increasing day by day,network no...Due to the development of network technology,the number of users is increasing rapidly,and the demand for emerging multicast services is becoming more and more abundant,traffic data is increasing day by day,network nodes are becoming denser,network topology is becoming more complex,and operators’equipment operation and maintenance costs are increasing.Network functions virtualization multicast issues include building a traffic forwarding topology,deploying the required functions,and directing traffic.Combining the two is still a problem to be studied in depth at present,and this paper proposes a two-stage solution where the decisions of these two stages are interdependent.Specifically,this paper decouples multicast traffic forwarding and function delivery.The minimum spanning tree of traffic forwarding is constructed by Steiner tree,and the traffic forwarding is realized by Viterbi-algorithm.Use a general topology network to examine network cost and service performance.Simulation results show that this method can reduce overhead and delay and optimize user experience.展开更多
文摘Virtualization of network/service functions means time sharing network/service（and affiliated）resources in a hyper speed manner.The concept of time sharing was popularized in the 1970s with mainframe computing.The same concept has recently resurfaced under the guise of cloud computing and virtualized computing.Although cloud computing was originally used in IT for server virtualization,the ICT industry is taking a new look at virtualization.This paradigm shift is shaking up the computing,storage,networking,and ser vice industries.The hope is that virtualizing and automating configuration and service management/orchestration will save both capes and opex for network transformation.A complimentary trend is the separation（over an open interface）of control and transmission.This is commonly referred to as software defined networking（SDN）.This paper reviews trends in network/service functions,efforts to standardize these functions,and required management and orchestration.
基金supported in part by the National Natural Science Foundation of China(NSFC)under grant numbers U22A2007 and 62171010the Open project of Satellite Internet Key Laboratory in 2022(Project 3:Research on Spaceborne Lightweight Core Network and Intelligent Collaboration)the Beijing Natural Science Foundation under grant number L212003.
文摘With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.
基金This work is supported by the National Key R&D Program of China(2018YFB1800601)the Key R&D Program of Zhejiang Province(2021C01036,2020C01021)the Fundamental Research Funds for the Central Universities(Zhejiang University NGICS Platform:ZJUNGICS2021021).
文摘Service function chains(SFC)mapping takes the responsibility for managing virtual network functions(VNFs).In SFC mapping,existing solutions duplicate VNFs with redundant instances to provide high availability in response to failures.However,as a compromise,these solutions result in high resource consumption due to device maintenance.In this paper,we propose a novel method named dynamic backup sharing(DBS)that allows SFCs to dynamically share backups to reduce resource consumption.DBS formulates the problem of sharing backups among different VNFs as an integer linear programming(ILP).Thereafter,we design a novel online algorithm based on dynamic programming to solve the problem.The experimental results indicate that DBS outperforms state-ofthe-art works by reducing resource consumption and improving the number of accepted requests.
基金supported in part by NSFC of China under Grant No.61232017National Basic Research Program of China(“973 program”)under Grant No.2013CB329101+1 种基金Fundamental Research Funds for the Central Universities under Grant No.2016YJS026NSAF of China under Grant No.U1530118
文摘Software Defined Satellite Networks(SDSN) are proposed to solve the problems in traditional satellite networks, such as time-consuming configuration and inflexible traffic scheduling. The emerging application of small satellite and research of SDSN make it possible for satellite networks to provide flexible network services. Service Function Chain(SFC) can satisfy this need. In this paper, we are motivated to investigate applying SFC in the small satellite-based SDSN for service delivery. We introduce the structure of the multi-layer constellation-based SDSN. Then, we describe two deployment patterns of SFC in SDSN, the Multi-Domain(MD) pattern and the Satellite Formation(SF) pattern. We propose two algorithms, SFP-MD, and SFP-SF, to calculate the Service Function Path(SFP). We implement the algorithms and conduct contrast experiments in our prototype. Finally, we summarize the applicable conditions of two deployment patterns according to the experimental results in terms of hops, delay, and packet loss rate.
基金supported by the National Natural Science Foundation of China(61501044)
文摘Network function virtualization is a new network concept that moves network functions from dedicated hardware to software-defined applications running on standard high volume severs. In order to accomplish network services, traffic flows are usually processed by a list of network functions in sequence which is defined by service function chain. By incorporating network function virtualization in inter-data center(DC) network, we can use the network resources intelligently and deploy network services faster. However, orchestrating service function chains across multiple data centers will incur high deployment cost, including the inter-data center bandwidth cost, virtual network function cost and the intra-data center bandwidth cost. In this paper, we orchestrate SFCs across multiple data centers, with a goal to minimize the overall cost. An integer linear programming(ILP) model is formulated and we provide a meta-heuristic algorithm named GBAO which contains three modules to solve it. We implemented our algorithm in Python and performed side-by-side comparison with prior algorithms. Simulation results show that our proposed algorithm reduces the overall cost by at least 21.4% over the existing algorithms for accommodating the same service function chain requests.
基金supported by the National Natural Science Foundation of China under Grant 62171465。
文摘Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.
文摘It is foreseen that the Internet of Things (IoT) will comprise billions of connected devices, and this will make the provi?sioning and operation of some IoT connectivity services more challenging. Indeed, IoT services are very different from lega?cy Internet services because of their dimensioning figures and also because IoT services differ dramatically in terms of na?ture and constraints. For example, IoT services often rely on energy and CPU?constrained sensor technologies, regardless of whether the service is for home automation, smart building, e?health, or power or water metering on a regional or national scale. Also, some IoT services, such as dynamic monitoring of biometric data, manipulation of sensitive information, and pri?vacy needs to be safeguarded whenever this information is for?warded over the underlying IoT network infrastructure. This paper discusses how software?defined networking (SDN) can facilitate the deployment and operation of some advanced IoT services regardless of their nature or scope. SDN introduces a high degree of automation in service delivery and operation-from dynamic IoT service parameter exposure and negotiation to resource allocation, service fulfillment, and assurance. This paper does not argue that all IoT services must adopt SDN. Rather, it is left to the discretion of operators to decide which IoT services can best leverage SDN capabilities. This paper only discusses managed IoT services, i.e., services that are op?erated by a service provider.
基金supported by the R&D Program of Beijing Municipal Education Commission(Nos.KM202110858003 and2022X003-KXD)。
文摘Due to the development of network technology,the number of users is increasing rapidly,and the demand for emerging multicast services is becoming more and more abundant,traffic data is increasing day by day,network nodes are becoming denser,network topology is becoming more complex,and operators’equipment operation and maintenance costs are increasing.Network functions virtualization multicast issues include building a traffic forwarding topology,deploying the required functions,and directing traffic.Combining the two is still a problem to be studied in depth at present,and this paper proposes a two-stage solution where the decisions of these two stages are interdependent.Specifically,this paper decouples multicast traffic forwarding and function delivery.The minimum spanning tree of traffic forwarding is constructed by Steiner tree,and the traffic forwarding is realized by Viterbi-algorithm.Use a general topology network to examine network cost and service performance.Simulation results show that this method can reduce overhead and delay and optimize user experience.
