The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networ...The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networking services,the IoV still suffers with high processing latency,less mobility support and location awareness.In this paper,we integrate fog computing and software defined networking(SDN) to address those problems.Fog computing extends computing and storing to the edge of the network,which could decrease latency remarkably in addition to enable mobility support and location awareness.Meanwhile,SDN provides flexible centralized control and global knowledge to the network.In order to apply the software defined cloud/fog networking(SDCFN) architecture in the IoV effectively,we propose a novel SDN-based modified constrained optimization particle swarm optimization(MPSO-CO) algorithm which uses the reverse of the flight of mutation particles and linear decrease inertia weight to enhance the performance of constrained optimization particle swarm optimization(PSO-CO).The simulation results indicate that the SDN-based MPSO-CO algorithm could effectively decrease the latency and improve the quality of service(QoS) in the SDCFN architecture.展开更多
To deal with the dynamic and imbalanced traffic requirements in Low Earth Orbit satellite networks, several distributed load balancing routing schemes have been proposed. However, because of the lack of global view, t...To deal with the dynamic and imbalanced traffic requirements in Low Earth Orbit satellite networks, several distributed load balancing routing schemes have been proposed. However, because of the lack of global view, these schemes may lead to cascading congestion in regions with high volume of traffic. To solve this problem, a Hybrid-Traffic-Detour based Load Balancing Routing(HLBR) scheme is proposed, where a Long-Distance Traffic Detour(LTD) method is devised and coordinates with distributed traffic detour method to perform self-adaptive load balancing. The forwarding path of LTD is acquired by the Circuitous Multipath Calculation(CMC) based on prior geographical information, and activated by the LTDShift-Trigger(LST) through real-time congestion perception. Simulation results show that the HLBR can mitigate cascading congestion and achieve efficient traffic distribution.展开更多
In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route...In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.展开更多
As an important part of satellite communication network,LEO satellite constellation network is one of the hot research directions.Since the nonuniform distribution of terrestrial services may cause inter-satellite lin...As an important part of satellite communication network,LEO satellite constellation network is one of the hot research directions.Since the nonuniform distribution of terrestrial services may cause inter-satellite link congestion,improving network load balancing performance has become one of the key issues that need to be solved for routing algorithms in LEO network.Therefore,by expanding the range of available paths and combining the congestion avoidance mechanism,a load balancing routing algorithm based on extended link states in LEO constellation network is proposed.Simulation results show that the algorithm achieves a balanced distribution of traffic load,reduces link congestion and packet loss rate,and improves throughput of LEO satellite network.展开更多
In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The appro...In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When the load of system is imbalanced, the controller can allocate globally network resources. What＇s more, by using dynamic correction, the load of the system is not obvious tilt in the long run. The results of simulation show that this approach can realize and ensure that the load will not tilt over a long period of time, and improve the system throughput.展开更多
Software Defined Networking(SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane,...Software Defined Networking(SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane, which could divide the network into several subdomains with separate controllers. However, such deployment introduces a new problem of controller load imbalance due to the dynamic traffic and the static configuration between switches and controllers. To address this issue, this paper proposes a Distribution Decision Mechanism(DDM) based on switch migration in the multiple subdomains SDN network. Firstly, through collecting network information, it constructs distributed migration decision fields based on the controller load condition. Then we choose the migrating switches according to the selection probability, and the target controllers are determined by integrating three network costs, including data collection, switch migration and controller state synchronization. Finally, we set the migrating countdown to achieve the ordered switch migration. Through verifying several evaluation indexes, results show that the proposed mechanism can achieve controller load balancing with better performance.展开更多
Internet of Vehicles(IoV)is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles’sensors through the internet.These sensors generate diff...Internet of Vehicles(IoV)is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles’sensors through the internet.These sensors generate different tasks that should be analyzed and processed in some given period of time.They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency.Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities.In some situations,fog computing cannot execute some tasks due to lack of resources.Thus,in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again.Moreover,several fog servers may be fuelled while other servers are empty.This implies an unfair distribution of jobs.In this research study,we shall merge the software defined network(SDN)with IoV and fog computing and use the parked vehicle as assistant fog computing node.This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers.This increases the ratio of time sensitive tasks that meet the deadline.In addition,a new load balancing strategy is proposed.It works proactively to balance the load locally and globally by the local fog managers and SDN controller,respectively.The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption,meeting the deadline,and resource utilization.展开更多
Because of cloud computing's high degree of polymerization calculation mode, it can't give full play to the resources of the edge device such as computing, storage, etc. Fog computing can improve the resource ...Because of cloud computing's high degree of polymerization calculation mode, it can't give full play to the resources of the edge device such as computing, storage, etc. Fog computing can improve the resource utilization efficiency of the edge device, and solve the problem about service computing of the delay-sensitive applications. This paper researches on the framework of the fog computing, and adopts Cloud Atomization Technology to turn physical nodes in different levels into virtual machine nodes. On this basis, this paper uses the graph partitioning theory to build the fog computing's load balancing algorithm based on dynamic graph partitioning. The simulation results show that the framework of the fog computing after Cloud Atomization can build the system network flexibly, and dynamic load balancing mechanism can effectively configure system resources as well as reducing the consumption of node migration brought by system changes.展开更多
To decrease the cost of exchanging load information among processors, a dynamic load-balancing （DLB） algorithm which adopts multieast tree technology is proposed. The muhieast tree construction rules are also propos...To decrease the cost of exchanging load information among processors, a dynamic load-balancing （DLB） algorithm which adopts multieast tree technology is proposed. The muhieast tree construction rules are also proposed to avoid wrongly transferred or redundant DLB messages due to the overlapping of multicast trees. The proposed DLB algorithm is distributed controlled, sender initiated and can help heavily loaded processors with complete distribution of redundant loads with minimum number of executions. Experiments were executed to compare the effects of the proposed DLB algorithm and other three ones, the results prove the effectivity and practicability of the proposed algorithm in dealing with great scale compute-intensive tasks.展开更多
Integrating the blockchain technology into mobile-edge computing(MEC)networks with multiple cooperative MEC servers(MECS)providing a promising solution to improving resource utilization,and helping establish a secure ...Integrating the blockchain technology into mobile-edge computing(MEC)networks with multiple cooperative MEC servers(MECS)providing a promising solution to improving resource utilization,and helping establish a secure reward mechanism that can facilitate load balancing among MECS.In addition,intelligent management of service caching and load balancing can improve the network utility in MEC blockchain networks with multiple types of workloads.In this paper,we investigate a learningbased joint service caching and load balancing policy for optimizing the communication and computation resources allocation,so as to improve the resource utilization of MEC blockchain networks.We formulate the problem as a challenging long-term network revenue maximization Markov decision process(MDP)problem.To address the highly dynamic and high dimension of system states,we design a joint service caching and load balancing algorithm based on the double-dueling Deep Q network(DQN)approach.The simulation results validate the feasibility and superior performance of our proposed algorithm over several baseline schemes.展开更多
Large-scale parallelization of molecular dynamics simulations is facing challenges which seriously affect the simula- tion efficiency, among which the load imbalance problem is the most critical. In this paper, we pro...Large-scale parallelization of molecular dynamics simulations is facing challenges which seriously affect the simula- tion efficiency, among which the load imbalance problem is the most critical. In this paper, we propose, a new molecular dynamics static load balancing method （MDSLB）. By analyzing the characteristics of the short-range force of molecular dynamics programs running in parallel, we divide the short-range force into three kinds of force models, and then pack- age the computations of each force model into many tiny computational units called ＂cell loads＂, which provide the basic data structures for our load balancing method. In MDSLB, the spatial region is separated into sub-regions called ＂local domains＂, and the cell loads of each local domain are allocated to every processor in turn. Compared with the dynamic load balancing method, MDSLB can guarantee load balance by executing the algorithm only once at program startup without migrating the loads dynamically. We implement MDSLB in OpenFOAM software and test it on TianHe-lA supercomputer with 16 to 512 processors. Experimental results show that MDSLB can save 34%-64% time for the load imbalanced cases.展开更多
Cloud providers(e.g.,Google,Alibaba,Amazon)own large-scale datacenter networks that comprise thousands of switches and links.A loadbalancing mechanism is supposed to effectively utilize the bisection bandwidth.Both Eq...Cloud providers(e.g.,Google,Alibaba,Amazon)own large-scale datacenter networks that comprise thousands of switches and links.A loadbalancing mechanism is supposed to effectively utilize the bisection bandwidth.Both Equal-Cost Multi-Path(ECMP),the canonical solution in practice,and alternatives come with performance limitations or significant deployment challenges.In this work,we propose Closer,a scalable load balancing mechanism for cloud datacenters.Closer complies with the evaluation of technology including the deployment of Clos-based topologies,overlays for network virtualization,and virtual machine(VM)clusters.We decouple the system into centralized route calculation and distributed route decision to guarantee its flexibility and stability in large-scale networks.Leveraging In-band Network Telemetry(INT)to obtain precise link state information,a simple but efficient algorithm implements a weighted ECMP at the edge of fabric,which enables Closer to proactively map the flows to the appropriate path and avoid the excessive congestion of a single link.Closer achieves 2 to 7 times better flow completion time(FCT)at 70%network load than existing schemes that work with same hardware environment.展开更多
Load balancing is typically used in the frequency domain of cellular wireless networks to balance paging, access, and traffic load across the available bandwidth. In this paper, we extend load balancing into the spati...Load balancing is typically used in the frequency domain of cellular wireless networks to balance paging, access, and traffic load across the available bandwidth. In this paper, we extend load balancing into the spatial domain, and we develop two approaches--network load balancing and single-carrier multilink--for spatial load balancing. Although these techniques are mostly applied to cellular wireless networks and Wi-Fi networks, we show how they can be applied to EV-DO, a 3G cellular data network. When a device has more than one candidate server, these techniques can be used to determine the quality of the channel between a server and the device and to determine the Ipad on each server. The proposed techniques leverage the advantages of existing EV-DO network architecture and are fully backward compatible. Network operators can substantially increase network capacity and improve user experience by using these techniques. Combining load balancing in the frequency and spatial domains improves connectivity within a network and allows resources to be optimally allocated according to the p-fair criterion. Combined load balancing further improves performance.展开更多
In a data center network （DCN）, load balancing is required when servers transfer data on the same path. This is necessary to avoid congestion. Load balancing is challenged by the dynamic transferral of demands and c...In a data center network （DCN）, load balancing is required when servers transfer data on the same path. This is necessary to avoid congestion. Load balancing is challenged by the dynamic transferral of demands and complex routing control. Because of the distributed nature of a traditional network, previous research on load balancing has mostly focused on improving the performance of the local network; thus, the load has not been optimally balanced across the entire network. In this paper, we propose a novel dynamic load-balancing algorithm for fat-tree. This algorithm avoids congestions to the great possible extent by searching for non-conflicting paths in a centralized way. We implement the algorithm in the popular software-defined networking architecture and evaluate the algorithm＇ s performance on the Mininet platform. The results show that our algorithm has higher bisection band- width than the traditional equal-cost multi-path load-balancing algorithm and thus more effectively avoids congestion.展开更多
Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue wit...Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.展开更多
At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,wh...At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,which is far less than the number of traffic,so it is prone to overflow problem,and leads to network paralysis.That has become a bottleneck in restricting the processing capacity of the data center,and will become a weak point focused by attackers.In this paper,we propose an algorithm for the Alarm Switch Remove(ASR)that fully loads the flow table space in SDN,and further put forward an integrated load balancing scheme in SDN.Finally,we use Mininet to verify that the scheme can ease the SDN switch flow table overflow problem and increase network throughput.展开更多
By the load definition of cluster, the request is regarded as granularity to compute load and implement the load balancing in cache cluster. First, the processing power of cache-node is studied from four aspects: netw...By the load definition of cluster, the request is regarded as granularity to compute load and implement the load balancing in cache cluster. First, the processing power of cache-node is studied from four aspects: network bandwidth, memory capacity, disk access rate and CPU usage. Then, the weighted load of cache-node is customized. Based on this, a load-balancing algorithm that can be applied to the cache cluster is proposed. Finally, Polygraph is used as a benchmarking tool to test the cache cluster possessing the load-balancing algorithm and the cache cluster with cache array routing protocol respectively. The results show the load-balancing algorithm can improve the performance of the cache cluster.展开更多
As one of the key technologies of cloud computing,the virtualization technology can virtualize all kinds of resources and integrate them into the unified planning of the cloud computing management platform.The migrati...As one of the key technologies of cloud computing,the virtualization technology can virtualize all kinds of resources and integrate them into the unified planning of the cloud computing management platform.The migration of virtual machines is one of the important technologies of virtual machine applications.However,there are still many deficiencies in the implementation of load balancing by virtual machine dynamic migration in cloud computing.Traditional triggering strategy thresholds are mostly fixed.If there is an instantaneous peak,it will cause migration,which will cause a waste of resources.In order to solve this problem,based on improving the dynamic migration framework,this paper proposes node selection optimization algorithm and node load balancing strategy and designs a prediction module,which uses a one-time smooth prediction to avoid the shortcoming of peak load moment.The simulation experiments and conclusions analysis results show that the fusion algorithm has performance advantages obvious.展开更多
Load balancing plays a critical role in a cellular network. As one kind of cellular network, Radio-over-Fibre （RoF） system can provide ubiquitous high data-rate transmissions, which has attracted many attentions, bu...Load balancing plays a critical role in a cellular network. As one kind of cellular network, Radio-over-Fibre （RoF） system can provide ubiquitous high data-rate transmissions, which has attracted many attentions, but it also suffer load unbalancing problem. In order to improve the system performance, in this paper, we propose a novel loading balance scheme in RoF system based on differential game theory. The scheme formulates the load allocated to each RAP （Radio Access Point） as a Nasb Equilibrium, using non-cooperative differential game to obtain the optical load allocation of each RAP. The simulations performed show that the non-cooperative differential game algorithm is applicable and the optimal load solution can be achieved.展开更多
One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consider...One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.展开更多
基金supported in part by National Natural Science Foundation of China (No.61401331,No.61401328)111 Project in Xidian University of China(B08038)+2 种基金Hong Kong,Macao and Taiwan Science and Technology Cooperation Special Project (2014DFT10320,2015DFT10160)The National Science and Technology Major Project of the Ministry of Science and Technology of China(2015zx03002006-003)FundamentalResearch Funds for the Central Universities (20101155739)
文摘The Internet of Vehicles(IoV)has been widely researched in recent years,and cloud computing has been one of the key technologies in the IoV.Although cloud computing provides high performance compute,storage and networking services,the IoV still suffers with high processing latency,less mobility support and location awareness.In this paper,we integrate fog computing and software defined networking(SDN) to address those problems.Fog computing extends computing and storing to the edge of the network,which could decrease latency remarkably in addition to enable mobility support and location awareness.Meanwhile,SDN provides flexible centralized control and global knowledge to the network.In order to apply the software defined cloud/fog networking(SDCFN) architecture in the IoV effectively,we propose a novel SDN-based modified constrained optimization particle swarm optimization(MPSO-CO) algorithm which uses the reverse of the flight of mutation particles and linear decrease inertia weight to enhance the performance of constrained optimization particle swarm optimization(PSO-CO).The simulation results indicate that the SDN-based MPSO-CO algorithm could effectively decrease the latency and improve the quality of service(QoS) in the SDCFN architecture.
基金supported by the National Science Foundation of China(No.61472189)Zhejiang Provincial Natural Science Foundation of China(No.LY18F030015)Wenzhou Public Welfare Science and Technology Project of China(No.G20150015)
文摘To deal with the dynamic and imbalanced traffic requirements in Low Earth Orbit satellite networks, several distributed load balancing routing schemes have been proposed. However, because of the lack of global view, these schemes may lead to cascading congestion in regions with high volume of traffic. To solve this problem, a Hybrid-Traffic-Detour based Load Balancing Routing(HLBR) scheme is proposed, where a Long-Distance Traffic Detour(LTD) method is devised and coordinates with distributed traffic detour method to perform self-adaptive load balancing. The forwarding path of LTD is acquired by the Circuitous Multipath Calculation(CMC) based on prior geographical information, and activated by the LTDShift-Trigger(LST) through real-time congestion perception. Simulation results show that the HLBR can mitigate cascading congestion and achieve efficient traffic distribution.
基金supported by the State Grid project which names the simulation and service quality evaluation technology research of power communication network(No.XX71-14-046)
文摘In power communication networks, it is a challenge to decrease the risk of different services efficiently to improve operation reliability. One of the important factor in reflecting communication risk is service route distribution. However, existing routing algorithms do not take into account the degree of importance of services, thereby leading to load unbalancing and increasing the risks of services and networks. A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems. First, the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices, service load, and service characteristics. Second, service weights are determined with modified relative entropy TOPSIS method, and a balanced service routing determination algorithm is proposed. Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.
基金supported by the National Natural Science Foundation of China(No.6217011238 and No.61931011).
文摘As an important part of satellite communication network,LEO satellite constellation network is one of the hot research directions.Since the nonuniform distribution of terrestrial services may cause inter-satellite link congestion,improving network load balancing performance has become one of the key issues that need to be solved for routing algorithms in LEO network.Therefore,by expanding the range of available paths and combining the congestion avoidance mechanism,a load balancing routing algorithm based on extended link states in LEO constellation network is proposed.Simulation results show that the algorithm achieves a balanced distribution of traffic load,reduces link congestion and packet loss rate,and improves throughput of LEO satellite network.
基金supported by the National Natural Science Foundation of China(No.61163058No.61201250 and No.61363006)Guangxi Key Laboratory of Trusted Software(No.KX201306)
文摘In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When the load of system is imbalanced, the controller can allocate globally network resources. What＇s more, by using dynamic correction, the load of the system is not obvious tilt in the long run. The results of simulation show that this approach can realize and ensure that the load will not tilt over a long period of time, and improve the system throughput.
基金supported in part by This work is supported by the Project of National Network Cyberspace Security(Grant No.2017YFB0803204)the National High-Tech Research and Development Program of China(863 Program)(Grant No.2015AA016102)+1 种基金Foundation for Innovative Research Group of the National Natural Science Foundation of China(Grant No.61521003)Foundation for the National Natural Science Foundation of China(Grant No.61502530)
文摘Software Defined Networking(SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane, which could divide the network into several subdomains with separate controllers. However, such deployment introduces a new problem of controller load imbalance due to the dynamic traffic and the static configuration between switches and controllers. To address this issue, this paper proposes a Distribution Decision Mechanism(DDM) based on switch migration in the multiple subdomains SDN network. Firstly, through collecting network information, it constructs distributed migration decision fields based on the controller load condition. Then we choose the migrating switches according to the selection probability, and the target controllers are determined by integrating three network costs, including data collection, switch migration and controller state synchronization. Finally, we set the migrating countdown to achieve the ordered switch migration. Through verifying several evaluation indexes, results show that the proposed mechanism can achieve controller load balancing with better performance.
文摘Internet of Vehicles(IoV)is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles’sensors through the internet.These sensors generate different tasks that should be analyzed and processed in some given period of time.They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency.Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities.In some situations,fog computing cannot execute some tasks due to lack of resources.Thus,in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again.Moreover,several fog servers may be fuelled while other servers are empty.This implies an unfair distribution of jobs.In this research study,we shall merge the software defined network(SDN)with IoV and fog computing and use the parked vehicle as assistant fog computing node.This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers.This increases the ratio of time sensitive tasks that meet the deadline.In addition,a new load balancing strategy is proposed.It works proactively to balance the load locally and globally by the local fog managers and SDN controller,respectively.The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption,meeting the deadline,and resource utilization.
基金supported in part by the National Science and technology support program of P.R.China(No.2014BAH29F05)
文摘Because of cloud computing's high degree of polymerization calculation mode, it can't give full play to the resources of the edge device such as computing, storage, etc. Fog computing can improve the resource utilization efficiency of the edge device, and solve the problem about service computing of the delay-sensitive applications. This paper researches on the framework of the fog computing, and adopts Cloud Atomization Technology to turn physical nodes in different levels into virtual machine nodes. On this basis, this paper uses the graph partitioning theory to build the fog computing's load balancing algorithm based on dynamic graph partitioning. The simulation results show that the framework of the fog computing after Cloud Atomization can build the system network flexibly, and dynamic load balancing mechanism can effectively configure system resources as well as reducing the consumption of node migration brought by system changes.
基金the National Natural Science Foundation of China(69973007)
文摘To decrease the cost of exchanging load information among processors, a dynamic load-balancing （DLB） algorithm which adopts multieast tree technology is proposed. The muhieast tree construction rules are also proposed to avoid wrongly transferred or redundant DLB messages due to the overlapping of multicast trees. The proposed DLB algorithm is distributed controlled, sender initiated and can help heavily loaded processors with complete distribution of redundant loads with minimum number of executions. Experiments were executed to compare the effects of the proposed DLB algorithm and other three ones, the results prove the effectivity and practicability of the proposed algorithm in dealing with great scale compute-intensive tasks.
基金supported in part by the National Natural Science Foundation of China 62072096the Fundamental Research Funds for the Central Universities under Grant 2232020A-12+4 种基金the International S&T Cooperation Program of Shanghai Science and Technology Commission under Grant 20220713000the Young Top-notch Talent Program in Shanghaithe"Shuguang Program"of Shanghai Education Development Foundation and Shanghai Municipal Education Commissionthe Fundamental Research Funds for the Central Universities and Graduate Student Innovation Fund of Donghua University CUSF-DH-D-2019093supported in part by the NSF under grants CNS-2107190 and ECCS-1923717。
文摘Integrating the blockchain technology into mobile-edge computing(MEC)networks with multiple cooperative MEC servers(MECS)providing a promising solution to improving resource utilization,and helping establish a secure reward mechanism that can facilitate load balancing among MECS.In addition,intelligent management of service caching and load balancing can improve the network utility in MEC blockchain networks with multiple types of workloads.In this paper,we investigate a learningbased joint service caching and load balancing policy for optimizing the communication and computation resources allocation,so as to improve the resource utilization of MEC blockchain networks.We formulate the problem as a challenging long-term network revenue maximization Markov decision process(MDP)problem.To address the highly dynamic and high dimension of system states,we design a joint service caching and load balancing algorithm based on the double-dueling Deep Q network(DQN)approach.The simulation results validate the feasibility and superior performance of our proposed algorithm over several baseline schemes.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.61303071 and 61120106005)the Natural Science Fund from the Guangzhou Science and Information Technology Bureau (Grant No.134200026)
文摘Large-scale parallelization of molecular dynamics simulations is facing challenges which seriously affect the simula- tion efficiency, among which the load imbalance problem is the most critical. In this paper, we propose, a new molecular dynamics static load balancing method （MDSLB）. By analyzing the characteristics of the short-range force of molecular dynamics programs running in parallel, we divide the short-range force into three kinds of force models, and then pack- age the computations of each force model into many tiny computational units called ＂cell loads＂, which provide the basic data structures for our load balancing method. In MDSLB, the spatial region is separated into sub-regions called ＂local domains＂, and the cell loads of each local domain are allocated to every processor in turn. Compared with the dynamic load balancing method, MDSLB can guarantee load balance by executing the algorithm only once at program startup without migrating the loads dynamically. We implement MDSLB in OpenFOAM software and test it on TianHe-lA supercomputer with 16 to 512 processors. Experimental results show that MDSLB can save 34%-64% time for the load imbalanced cases.
基金supported by National Key Research and Development Project of China(2019YFB1802501)Research and Development Program in Key Areas of Guangdong Province(2018B010113001)Open Foundation of Science and Technology on Communication Networks Laboratory(No.6142104180106)。
文摘Cloud providers(e.g.,Google,Alibaba,Amazon)own large-scale datacenter networks that comprise thousands of switches and links.A loadbalancing mechanism is supposed to effectively utilize the bisection bandwidth.Both Equal-Cost Multi-Path(ECMP),the canonical solution in practice,and alternatives come with performance limitations or significant deployment challenges.In this work,we propose Closer,a scalable load balancing mechanism for cloud datacenters.Closer complies with the evaluation of technology including the deployment of Clos-based topologies,overlays for network virtualization,and virtual machine(VM)clusters.We decouple the system into centralized route calculation and distributed route decision to guarantee its flexibility and stability in large-scale networks.Leveraging In-band Network Telemetry(INT)to obtain precise link state information,a simple but efficient algorithm implements a weighted ECMP at the edge of fabric,which enables Closer to proactively map the flows to the appropriate path and avoid the excessive congestion of a single link.Closer achieves 2 to 7 times better flow completion time(FCT)at 70%network load than existing schemes that work with same hardware environment.
文摘Load balancing is typically used in the frequency domain of cellular wireless networks to balance paging, access, and traffic load across the available bandwidth. In this paper, we extend load balancing into the spatial domain, and we develop two approaches--network load balancing and single-carrier multilink--for spatial load balancing. Although these techniques are mostly applied to cellular wireless networks and Wi-Fi networks, we show how they can be applied to EV-DO, a 3G cellular data network. When a device has more than one candidate server, these techniques can be used to determine the quality of the channel between a server and the device and to determine the Ipad on each server. The proposed techniques leverage the advantages of existing EV-DO network architecture and are fully backward compatible. Network operators can substantially increase network capacity and improve user experience by using these techniques. Combining load balancing in the frequency and spatial domains improves connectivity within a network and allows resources to be optimally allocated according to the p-fair criterion. Combined load balancing further improves performance.
基金supported by the National Basic Research Program of China(973 Program)(2012CB315903)the Key Science and Technology Innovation Team Project of Zhejiang Province(2011R50010-05)+3 种基金the National Science and Technology Support Program(2014BAH24F01)863 Program of China(2012AA01A507)the National Natural Science Foundation of China(61379118 and 61103200)sponsored by the Research Fund of ZTE Corporation
文摘In a data center network （DCN）, load balancing is required when servers transfer data on the same path. This is necessary to avoid congestion. Load balancing is challenged by the dynamic transferral of demands and complex routing control. Because of the distributed nature of a traditional network, previous research on load balancing has mostly focused on improving the performance of the local network; thus, the load has not been optimally balanced across the entire network. In this paper, we propose a novel dynamic load-balancing algorithm for fat-tree. This algorithm avoids congestions to the great possible extent by searching for non-conflicting paths in a centralized way. We implement the algorithm in the popular software-defined networking architecture and evaluate the algorithm＇ s performance on the Mininet platform. The results show that our algorithm has higher bisection band- width than the traditional equal-cost multi-path load-balancing algorithm and thus more effectively avoids congestion.
基金supported by a grant from the National Basic Research Development Program of China(973 Program)(No.2012CB315901,2012CB315906)the National High Technology Research and Development Program of China(863 Program)(No.2011AA01A103)
文摘Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.
基金supported supported by the National Key Research and Development Program of China(No.2020YFE0200500)CERNET Innovation Project(NGII20190806)。
文摘At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,which is far less than the number of traffic,so it is prone to overflow problem,and leads to network paralysis.That has become a bottleneck in restricting the processing capacity of the data center,and will become a weak point focused by attackers.In this paper,we propose an algorithm for the Alarm Switch Remove(ASR)that fully loads the flow table space in SDN,and further put forward an integrated load balancing scheme in SDN.Finally,we use Mininet to verify that the scheme can ease the SDN switch flow table overflow problem and increase network throughput.
文摘By the load definition of cluster, the request is regarded as granularity to compute load and implement the load balancing in cache cluster. First, the processing power of cache-node is studied from four aspects: network bandwidth, memory capacity, disk access rate and CPU usage. Then, the weighted load of cache-node is customized. Based on this, a load-balancing algorithm that can be applied to the cache cluster is proposed. Finally, Polygraph is used as a benchmarking tool to test the cache cluster possessing the load-balancing algorithm and the cache cluster with cache array routing protocol respectively. The results show the load-balancing algorithm can improve the performance of the cache cluster.
基金supported by the National Natural Science Foundation of China(61772196,61472136)the Hunan Provincial Focus Social Science Fund(2016ZDB006)+2 种基金Hunan Provincial Social Science Achievement Review Committee results in appraisal identification project(Xiang social assessment 2016JD05)Key Project of Hunan Provincial Social Science Achievement Review Committee(XSP 19ZD1005)The authors gratefully acknowledge the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology(2017TP1026).
文摘As one of the key technologies of cloud computing,the virtualization technology can virtualize all kinds of resources and integrate them into the unified planning of the cloud computing management platform.The migration of virtual machines is one of the important technologies of virtual machine applications.However,there are still many deficiencies in the implementation of load balancing by virtual machine dynamic migration in cloud computing.Traditional triggering strategy thresholds are mostly fixed.If there is an instantaneous peak,it will cause migration,which will cause a waste of resources.In order to solve this problem,based on improving the dynamic migration framework,this paper proposes node selection optimization algorithm and node load balancing strategy and designs a prediction module,which uses a one-time smooth prediction to avoid the shortcoming of peak load moment.The simulation experiments and conclusions analysis results show that the fusion algorithm has performance advantages obvious.
基金This research was supported by the Fundamental Research Funds for the Central Universities，also supported by the National Natural Science Foundation of P.R.China
文摘Load balancing plays a critical role in a cellular network. As one kind of cellular network, Radio-over-Fibre （RoF） system can provide ubiquitous high data-rate transmissions, which has attracted many attentions, but it also suffer load unbalancing problem. In order to improve the system performance, in this paper, we propose a novel loading balance scheme in RoF system based on differential game theory. The scheme formulates the load allocated to each RAP （Radio Access Point） as a Nasb Equilibrium, using non-cooperative differential game to obtain the optical load allocation of each RAP. The simulations performed show that the non-cooperative differential game algorithm is applicable and the optimal load solution can be achieved.
基金supported by Scientific Research Foundation for the Returned Overseas Chinese ScholarsState Education Ministry under Grant No.2010-2011 and Chinese Post-doctoral Research Foundation
文摘One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines as well as the integrated features of hosting physical machines into consideration. We introduce a Dynamic and Integrated Resource Scheduling algorithm (DAIRS) for Cloud data centers. Unlike traditional load-balance scheduling algorithms which often consider only one factor such as the CPU load in physical servers, DAIRS treats CPU, memory and network bandwidth integrated for both physical machines and virtual machines. We develop integrated measurement for the total imbalance level of a Cloud datacenter as well as the average imbalance level of each server. Simulation results show that DAIRS has good performance with regard to total imbalance level, average imbalance level of each server, as well as overall running time.
