This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocatio...This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.展开更多
Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmiss...Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks(EONs) with single mode fiber or single core fiber. In this paper, multicore virtual concatenation(MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation(SCVC) scheme, in terms of blocking probability and spectrum utilization.展开更多
Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients us...Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.展开更多
As a promising solution, virtualization is vigorously developed to eliminate the ossification of traditional Internet infrastructure and enhance the flexibility in sharing the substrate network (SN) resources includin...As a promising solution, virtualization is vigorously developed to eliminate the ossification of traditional Internet infrastructure and enhance the flexibility in sharing the substrate network (SN) resources including computing, storage, bandwidth, etc. With network virtualization, cloud service providers can utilize the shared substrate resources to provision virtual networks (VNs) and facilitate a wide and diverse range of applications. As more and more internet applications migrate to the cloud, the resource efficiency and the survivability of VNs, such as single link failure or large-scale disaster survivability, have become crucial issues. Elastic optical networks have emerged in recent years as a strategy for dealing with the divergence of network application bandwidth needs. The network capacity has been constrained due to the usage of only two multiplexing dimensions. As transmission rates rise, so does the demand for network failure protection. Due to their end-to-end solutions, those safe-guarding paths are of particular importance among the protection methods. Due to their end-to-end solutions, those safeguarding paths are of particular importance among the protection methods. This paper presents approaches that provide a failure-independent route-protecting p-cycle for path protection in space-division multiplexed elastic optical networks. This letter looks at two SDM network challenges and presents a heuristic technique (k-shortest path) for each. In the first approach, we study a virtual network embedding (SVNE) problem and propose an algorithm for EONs, which can combat against single-link failures. We evaluate the proposed POPETA algorithm and compare its performance with some counterpart algorithms. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance in terms of spectrum utilization and blocking ratio, even if with a higher backup redundancy ratio.展开更多
With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Thing...With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.展开更多
The major challenge in elastic optical networks is to determine the path of a connection and to allocate spectral resources on the links of this path. This problem consists of two sub-problems, routing and spectrum al...The major challenge in elastic optical networks is to determine the path of a connection and to allocate spectral resources on the links of this path. This problem consists of two sub-problems, routing and spectrum allocation. In the literature, these sub-problems are solved with a predefined order for all topology node pairs. Recent work proposes hybrid resolution algorithms based on connection demand and network state to provide a solution to these problems. However, the blocking rate of new connection requests has become problematic. In this work, we propose a hybrid routing and spectrum assignment policy to improve blocking rate of new connection requests. The proposed solution consists to change the routing policy of a pair node if the connection request is blocked. This algorithm improves the blocking rate of new connection requests.展开更多
As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model...As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.展开更多
In elastic networking,the WDM fixed frequency grid is replaced by a more flexible structure,in which the spectrum is organized in frequency slots,and each traffic flow is assigned to an appropriate set of contiguous s...In elastic networking,the WDM fixed frequency grid is replaced by a more flexible structure,in which the spectrum is organized in frequency slots,and each traffic flow is assigned to an appropriate set of contiguous slots.The classical RWA(routing and wavelength assignment)problem is then replaced by the RSA(routing and spectrum assignment)problem.In this paper,we discuss the SA(spectrum assignment)problem in a single link,where it is not coupled to the routing problem,thus allowing for a better understanding of its dynamics.The best SA algorithm,taken as anyone who minimizes the average time it takes to provide total exhaustion of the initial available spectrum under incremental traffic,is shown to be a function of the traffic profile.It is shown that the greedy algorithm,which is unaware of the traffic profile,may impose severe performance penalties if the request rates increase with the number of requested slots.However,no penalty is incurred by more friendly profiles,like the uniform one.展开更多
Currently, the elastic interconnection has realized the high-rate data transmission among data centers(DCs). Thus, the elastic data center network(EDCN) emerged. In EDCNs, it is essential to achieve the virtual networ...Currently, the elastic interconnection has realized the high-rate data transmission among data centers(DCs). Thus, the elastic data center network(EDCN) emerged. In EDCNs, it is essential to achieve the virtual network(VN) embedding, which includes two main components: VM(virtual machine) mapping and VL(virtual link) mapping. In VM mapping, we allocate appropriate servers to hold VMs. While for VL mapping,an optimal substrate path is determined for each virtual lightpath. For the VN embedding in EDCNs, the power efficiency is a significant concern, and some solutions were proposed through sleeping light-duty servers.However, the increasing communication traffic between VMs leads to a serious energy dissipation problem, since it also consumes a great amount of energy on switches even utilizing the energy-efficient optical transmission technique. In this paper, considering load balancing and power-efficient VN embedding, we formulate the problem and design a novel heuristic for EDCNs, with the objective to achieve the power savings of servers and switches. In our solution, VMs are mapped into a single DC or multiple DCs with the short distance between each other, and the servers in the same cluster or adjacent clusters are preferred to hold VMs. Such that, a large amount of servers and switches will become vacant and can go into sleep mode. Simulation results demonstrate that our method performs well in terms of power savings and load balancing. Compared with benchmarks, the improvement ratio of power efficiency is 5%–13%.展开更多
As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and...As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and hence has been applicated in edge computing scenarios. In this paper, we propose a reinforced virtual optical network embedding(R-VONE) algorithm based on deep reinforcement learning(DRL) to optimize network embedding policies automatically. The network resource attributes are extracted as the environment state for model training, based on which DRL agent can deduce the node embedding probability. Experimental results indicate that R-VONE presents a significant advantage with lower blocking probability and higher resource utilization.展开更多
This study focuses on the integrated energy production system in industrial parks, addressing the problem of stable load dispatch of equipment under demand fluctuations. A cross-level method for steam load smoothing a...This study focuses on the integrated energy production system in industrial parks, addressing the problem of stable load dispatch of equipment under demand fluctuations. A cross-level method for steam load smoothing and optimization is proposed, aiming to achieve stable production and optimal economic performance through three levels of integration: load forecasting, load dispatch, and load regulation. Unlike traditional methods that directly use load forecasting values, heat network elasticity is presented as a buffer between demand and supply. Constraints for minimal changes in equipment load and operational parameters are established for smooth regulation. Industrial cases demonstrate that the load forecasting model has mean absolute percentage errors of 2.44% and 1.68% for medium-pressure and low-pressure steam, respectively, meeting accuracy requirements. The modified supply-side load smoothness is effectively improved by considering heat network elasticity. The method increases boiler efficiency by 1.92%, reducing average coal consumption by 0.92 t/h. Compared to manual operation, the proposed model leads to an average increase of 5.69 MW in power generation and an average reduction of 10.81% in coal-to-electricity ratio. This study verifies the importance of smooth integration across different levels and analyzes the effective response of the proposed method to the uncertainty in load forecasting. The method demonstrates the enormous potential of data-driven methods in achieving safe, economical, and sustainable production in industrial parks.展开更多
Background:Blood glucose control is closely related to type 2 diabetes mellitus(T2DM)prognosis.This multicenter study aimed to investigate blood glucose control among patients with insulin-treated T2DM in North China ...Background:Blood glucose control is closely related to type 2 diabetes mellitus(T2DM)prognosis.This multicenter study aimed to investigate blood glucose control among patients with insulin-treated T2DM in North China and explore the application value of combining an elastic network(EN)with a machine-learning algorithm to predict glycemic control.Methods:Basic information,biochemical indices,and diabetes-related data were collected via questionnaire from 2787 consecutive participants recruited from 27 centers in six cities between January 2016 and December 2017.An EN regression was used to address variable collinearity.Then,three common machine learning algorithms(random forest[RF],support vector machine[SVM],and back propagation artificial neural network[BP-ANN])were used to simulate and predict blood glucose status.Additionally,a stepwise logistic regression was performed to compare the machine learning models.Results:The well-controlled blood glucose rate was 45.82%in North China.The multivariable analysis found that hypertension history,atherosclerotic cardiovascular disease history,exercise,and total cholesterol were protective factors in glycosylated hemoglobin(HbAlc)control,while central adiposity,family history,T2DM duration,complications,insulin dose,blood pressure,and hypertension were risk factors for elevated HbAlc.Before the dimensional reduction in the EN,the areas under the curve of RF,SVM,and BP were 0.73,0.61,and 0.70,respectively,while these figures increased to 0.75,0.72,and 0.72,respectively,after dimensional reduction.Moreover,the EN and machine learning models had higher sensitivity and accuracy than the logistic regression models(the sensitivity and accuracy of logistic were 0.52 and 0.56;RF:0.79,0.70;SVM:0.84,0.73;BP-ANN:0.78,0.73,respectively).Conclusions:More than half of T2DM patients in North China had poor glycemic control and were at a higher risk of developing diabetic complications.The EN and machine learning algorithms are alternative choices,in addition to the traditional logistic model,for building predictive models of blood glucose control in patients with T2DM.展开更多
文摘This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.
基金supported in part by NSFC project (61571058, 61601052)
文摘Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks(EONs) with single mode fiber or single core fiber. In this paper, multicore virtual concatenation(MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation(SCVC) scheme, in terms of blocking probability and spectrum utilization.
基金National Key R&D Program China under Grant 2018YFB1801701National Natural Science Foundation of China(NSFC)under Grant 61671313the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.
文摘As a promising solution, virtualization is vigorously developed to eliminate the ossification of traditional Internet infrastructure and enhance the flexibility in sharing the substrate network (SN) resources including computing, storage, bandwidth, etc. With network virtualization, cloud service providers can utilize the shared substrate resources to provision virtual networks (VNs) and facilitate a wide and diverse range of applications. As more and more internet applications migrate to the cloud, the resource efficiency and the survivability of VNs, such as single link failure or large-scale disaster survivability, have become crucial issues. Elastic optical networks have emerged in recent years as a strategy for dealing with the divergence of network application bandwidth needs. The network capacity has been constrained due to the usage of only two multiplexing dimensions. As transmission rates rise, so does the demand for network failure protection. Due to their end-to-end solutions, those safe-guarding paths are of particular importance among the protection methods. Due to their end-to-end solutions, those safeguarding paths are of particular importance among the protection methods. This paper presents approaches that provide a failure-independent route-protecting p-cycle for path protection in space-division multiplexed elastic optical networks. This letter looks at two SDM network challenges and presents a heuristic technique (k-shortest path) for each. In the first approach, we study a virtual network embedding (SVNE) problem and propose an algorithm for EONs, which can combat against single-link failures. We evaluate the proposed POPETA algorithm and compare its performance with some counterpart algorithms. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance in terms of spectrum utilization and blocking ratio, even if with a higher backup redundancy ratio.
文摘With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.
文摘The major challenge in elastic optical networks is to determine the path of a connection and to allocate spectral resources on the links of this path. This problem consists of two sub-problems, routing and spectrum allocation. In the literature, these sub-problems are solved with a predefined order for all topology node pairs. Recent work proposes hybrid resolution algorithms based on connection demand and network state to provide a solution to these problems. However, the blocking rate of new connection requests has become problematic. In this work, we propose a hybrid routing and spectrum assignment policy to improve blocking rate of new connection requests. The proposed solution consists to change the routing policy of a pair node if the connection request is blocked. This algorithm improves the blocking rate of new connection requests.
基金Supported by the National Key Research and Development Program of China(No.2021YFB2401204)。
文摘As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.
文摘In elastic networking,the WDM fixed frequency grid is replaced by a more flexible structure,in which the spectrum is organized in frequency slots,and each traffic flow is assigned to an appropriate set of contiguous slots.The classical RWA(routing and wavelength assignment)problem is then replaced by the RSA(routing and spectrum assignment)problem.In this paper,we discuss the SA(spectrum assignment)problem in a single link,where it is not coupled to the routing problem,thus allowing for a better understanding of its dynamics.The best SA algorithm,taken as anyone who minimizes the average time it takes to provide total exhaustion of the initial available spectrum under incremental traffic,is shown to be a function of the traffic profile.It is shown that the greedy algorithm,which is unaware of the traffic profile,may impose severe performance penalties if the request rates increase with the number of requested slots.However,no penalty is incurred by more friendly profiles,like the uniform one.
基金supported in part by Open Foundation of State Key Laboratory of Information Photonics and Optical Communications (Grant No. IPOC2014B009)Fundamental Research Funds for the Central Universities (Grant Nos. N130817002, N140405005, N150401002)+3 种基金Foundation of the Education Department of Liaoning Province (Grant No. L2014089)National Natural Science Foundation of China (Grant Nos. 61302070, 61401082, 61471109, 61502075)Liaoning Bai Qian Wan Talents ProgramNational High-Level Personnel Special Support Program for Youth Top-Notch Talent
文摘Currently, the elastic interconnection has realized the high-rate data transmission among data centers(DCs). Thus, the elastic data center network(EDCN) emerged. In EDCNs, it is essential to achieve the virtual network(VN) embedding, which includes two main components: VM(virtual machine) mapping and VL(virtual link) mapping. In VM mapping, we allocate appropriate servers to hold VMs. While for VL mapping,an optimal substrate path is determined for each virtual lightpath. For the VN embedding in EDCNs, the power efficiency is a significant concern, and some solutions were proposed through sleeping light-duty servers.However, the increasing communication traffic between VMs leads to a serious energy dissipation problem, since it also consumes a great amount of energy on switches even utilizing the energy-efficient optical transmission technique. In this paper, considering load balancing and power-efficient VN embedding, we formulate the problem and design a novel heuristic for EDCNs, with the objective to achieve the power savings of servers and switches. In our solution, VMs are mapped into a single DC or multiple DCs with the short distance between each other, and the servers in the same cluster or adjacent clusters are preferred to hold VMs. Such that, a large amount of servers and switches will become vacant and can go into sleep mode. Simulation results demonstrate that our method performs well in terms of power savings and load balancing. Compared with benchmarks, the improvement ratio of power efficiency is 5%–13%.
基金supported in part by the National Natural Science Foundation of China(62001422)Henan Scientific and Technology Innovation Talents(22HASTIT016).
文摘As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and hence has been applicated in edge computing scenarios. In this paper, we propose a reinforced virtual optical network embedding(R-VONE) algorithm based on deep reinforcement learning(DRL) to optimize network embedding policies automatically. The network resource attributes are extracted as the environment state for model training, based on which DRL agent can deduce the node embedding probability. Experimental results indicate that R-VONE presents a significant advantage with lower blocking probability and higher resource utilization.
基金supported by National Key R&D Program of China(Grant No.2022YFB3304502)National Natural Science Foundation of China(Grant No.51806190)+1 种基金National Key R&D Program of China(Grant No.2023YFE0108600)Self-directed project,State Key Laboratory of Clean Energy Utilization.
文摘This study focuses on the integrated energy production system in industrial parks, addressing the problem of stable load dispatch of equipment under demand fluctuations. A cross-level method for steam load smoothing and optimization is proposed, aiming to achieve stable production and optimal economic performance through three levels of integration: load forecasting, load dispatch, and load regulation. Unlike traditional methods that directly use load forecasting values, heat network elasticity is presented as a buffer between demand and supply. Constraints for minimal changes in equipment load and operational parameters are established for smooth regulation. Industrial cases demonstrate that the load forecasting model has mean absolute percentage errors of 2.44% and 1.68% for medium-pressure and low-pressure steam, respectively, meeting accuracy requirements. The modified supply-side load smoothness is effectively improved by considering heat network elasticity. The method increases boiler efficiency by 1.92%, reducing average coal consumption by 0.92 t/h. Compared to manual operation, the proposed model leads to an average increase of 5.69 MW in power generation and an average reduction of 10.81% in coal-to-electricity ratio. This study verifies the importance of smooth integration across different levels and analyzes the effective response of the proposed method to the uncertainty in load forecasting. The method demonstrates the enormous potential of data-driven methods in achieving safe, economical, and sustainable production in industrial parks.
基金This study was supported by grants from the Ministry of Education of the Humanities and Social Science Project(No.17YJAZH048)the National Natural Science Foundation of China(No.81803333).
文摘Background:Blood glucose control is closely related to type 2 diabetes mellitus(T2DM)prognosis.This multicenter study aimed to investigate blood glucose control among patients with insulin-treated T2DM in North China and explore the application value of combining an elastic network(EN)with a machine-learning algorithm to predict glycemic control.Methods:Basic information,biochemical indices,and diabetes-related data were collected via questionnaire from 2787 consecutive participants recruited from 27 centers in six cities between January 2016 and December 2017.An EN regression was used to address variable collinearity.Then,three common machine learning algorithms(random forest[RF],support vector machine[SVM],and back propagation artificial neural network[BP-ANN])were used to simulate and predict blood glucose status.Additionally,a stepwise logistic regression was performed to compare the machine learning models.Results:The well-controlled blood glucose rate was 45.82%in North China.The multivariable analysis found that hypertension history,atherosclerotic cardiovascular disease history,exercise,and total cholesterol were protective factors in glycosylated hemoglobin(HbAlc)control,while central adiposity,family history,T2DM duration,complications,insulin dose,blood pressure,and hypertension were risk factors for elevated HbAlc.Before the dimensional reduction in the EN,the areas under the curve of RF,SVM,and BP were 0.73,0.61,and 0.70,respectively,while these figures increased to 0.75,0.72,and 0.72,respectively,after dimensional reduction.Moreover,the EN and machine learning models had higher sensitivity and accuracy than the logistic regression models(the sensitivity and accuracy of logistic were 0.52 and 0.56;RF:0.79,0.70;SVM:0.84,0.73;BP-ANN:0.78,0.73,respectively).Conclusions:More than half of T2DM patients in North China had poor glycemic control and were at a higher risk of developing diabetic complications.The EN and machine learning algorithms are alternative choices,in addition to the traditional logistic model,for building predictive models of blood glucose control in patients with T2DM.
