Groundwater exploitation has been regarded as the main reason for land subsidence in China and thus receives considerable attention from the government and the academic community.Recently,building loads have been iden...Groundwater exploitation has been regarded as the main reason for land subsidence in China and thus receives considerable attention from the government and the academic community.Recently,building loads have been identified as another important factor of land subsidence,but researches in this sector have lagged.The effect of a single building load on land subsidence was neglected in many cases owing to the narrow scope and the limited depth of the additional stress in stratum.However,due to the superposition of stresses between buildings,the additional stress of cluster loads is greater than that of a single building load under the same condition,so that the land subsidence caused by cluster loads cannot be neglected.Taking Shamen village in the north of Zhengzhou,China,as an example,a finite-difference model based on the Biot consolidation theory to calculate the land subsidence caused by cluster loads was established in this paper.Cluster loads present the characteristics of large-area loads,and the land subsidence caused by cluster loads can have multiple primary consolidation processes due to the stress superposition of different buildings was shown by the simulation results.Pore water migration distances are longer when the cluster loads with high plot ratio are imposed,so that consolidation takes longer time.The higher the plot ratio is,the deeper the effective deformation is,and thus the greater the land subsidence is.A higher plot ratio also increases the contribution that the deeper stratigraphic layers make to land subsidence.Contrary to the calculated results of land subsidence caused by cluster loads and groundwater recession,the percentage of settlement caused by cluster loads in the total settlement was 49.43%and 55.06%at two simulated monitoring points,respectively.These data suggest that the cluster loads can be one of the main causes of land subsidence.展开更多
Aiming at the load imbalance and poor scalability in single-tier Web server clusters, an efficient load balancing ap- proach is proposed for constructing an N-hierarchical （multi-tier） Web server cluster. In each la...Aiming at the load imbalance and poor scalability in single-tier Web server clusters, an efficient load balancing ap- proach is proposed for constructing an N-hierarchical （multi-tier） Web server cluster. In each layer, multiple load balancers are set to receive the user requests simultaneously, and different load bal- ancing algorithms are used to construct the high-scalable Web cluster system. At the same time, an improved load balancing al- gorithm is proposed, which can dynamically calculate weights according to the utilization of the server resources, and reasonably distribute the loads for each server according to the load status of the servers. The experimental results show that the proposed ap- proach can greatly decrease the load imbalance among the Web servers and reduce the response time of the entire Web cluster system.展开更多
Ambient Assisted Living(AAL) is becoming an important research field. Many technologies have emerged related with pervasive computing vision, which can give support for AAL. One of the most reliable approaches is base...Ambient Assisted Living(AAL) is becoming an important research field. Many technologies have emerged related with pervasive computing vision, which can give support for AAL. One of the most reliable approaches is based on wireless sensor networks(WSNs). In this paper, we propose a coverage-aware unequal clustering protocol with load separation(CUCPLS) for data gathering of AAL applications based on WSNs. Firstly, the coverage overlap factor for nodes is introduced that accounts for the degree of target nodes covered. In addition, to balance the intra-cluster and inter-cluster energy consumptions, different competition radiuses of CHs are computed theoretically in different rings, and smaller clusters are formed near the sink. Moreover, two CHs are selected in each cluster for load separation to alleviate the substantial energy consumption difference between a single CH and its member nodes. Furthermore, a backoff waiting time is adopted during the selection of the two CHs to reduce the number of control messages employed. Simulation results demonstrate that the CUCPLS not only can achieve better coverage performance, but also balance the energy consumption of a network and prolong network lifetime.展开更多
Sensors are considered as important elements of electronic devices.In many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy ...Sensors are considered as important elements of electronic devices.In many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop communications.But,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much needed.However,reducing energy con-sumption can increase the network lifetime in effective manner.For that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor nodes.In that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member nodes.For providing equal rate of energy consumption among nodes,the dimensions of framed clusters are measured.Moreover,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base station.The evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head node.Additionally,the model also provides higher throughput and minimal delay in delivering data packets.展开更多
In order to solve the uneven node load in the tradition clustering routing protocols, a new clustering algorism based on SOM is proposed. Firstly, the network radio model and the energy consumption model are defined. ...In order to solve the uneven node load in the tradition clustering routing protocols, a new clustering algorism based on SOM is proposed. Firstly, the network radio model and the energy consumption model are defined. A new algorism using SOM to form the cluster and select the cluster head is defined. In the clustering node remain energy and the Euclidean distance from cluster head to the cluster member are considered. The experiment shows our method has the longer life cycle and less total energy consumption. It is an effective clustering protocol.展开更多
Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called ...Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.展开更多
Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the...Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.展开更多
In this paper, we explored a load-balancing algorithm in a cluster file system contains two levels of metadata-server, primary-level server quickly distributestasks to second-level servers depending on the closest loa...In this paper, we explored a load-balancing algorithm in a cluster file system contains two levels of metadata-server, primary-level server quickly distributestasks to second-level servers depending on the closest load-balancing information. At the same time, we explored a method which accurately reflect I/O traffic and storage of storage-node： computing the heat-value of file, according to which we realized a more logical storage allocation. According to the experiment result, we conclude that this new algorithm shortens the executing time of tasks and improves the system performance compared with other load algorithm.展开更多
This paper presented an idea to replace the traditionally expensive parallel machines by heterogeneous cluster of workstations. To emphasise the usability of cluster of workstations platform for parallel and distribut...This paper presented an idea to replace the traditionally expensive parallel machines by heterogeneous cluster of workstations. To emphasise the usability of cluster of workstations platform for parallel and distributed computing, also the paper presented the status report on the effort and experiences for the implementation of a dynamic load balancing for parallel tree computation depth first search(DFS) on the cluster of a workstations project. It compared the speedup performance obtained from our platform with that obtained from the traditional one. The speedup results show that cluster of workstations can be a serious alternative to the expensive parallel machines.展开更多
The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic l...The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.展开更多
The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection an...The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection and its convergence to local optimal solutions.To overcome these limitations,an improved KFCM algorithm with adaptive optimal clustering number selection is proposed in this paper.This algorithm optimizes the KFCM algorithm by combining the powerful global search ability of genetic algorithm and the robust local search ability of simulated annealing algorithm.The improved KFCM algorithm adaptively determines the ideal number of clusters using the clustering evaluation index ratio.Compared with the traditional KFCM algorithm,the enhanced KFCM algorithm has robust clustering and comprehensive abilities,enabling the efficient convergence to the global optimal solution.展开更多
基金National Key R&D Program of China:Effectively Utilized and Optimized Surface Water and Groundwater in the Fault Basin(2016YFC0502502)China Geology Survey(DD20190356&DD20189262)+1 种基金Chinese Academy of Geological Sciences(YKWF201628)National Natural Science Foundation of China(No.41272301)
文摘Groundwater exploitation has been regarded as the main reason for land subsidence in China and thus receives considerable attention from the government and the academic community.Recently,building loads have been identified as another important factor of land subsidence,but researches in this sector have lagged.The effect of a single building load on land subsidence was neglected in many cases owing to the narrow scope and the limited depth of the additional stress in stratum.However,due to the superposition of stresses between buildings,the additional stress of cluster loads is greater than that of a single building load under the same condition,so that the land subsidence caused by cluster loads cannot be neglected.Taking Shamen village in the north of Zhengzhou,China,as an example,a finite-difference model based on the Biot consolidation theory to calculate the land subsidence caused by cluster loads was established in this paper.Cluster loads present the characteristics of large-area loads,and the land subsidence caused by cluster loads can have multiple primary consolidation processes due to the stress superposition of different buildings was shown by the simulation results.Pore water migration distances are longer when the cluster loads with high plot ratio are imposed,so that consolidation takes longer time.The higher the plot ratio is,the deeper the effective deformation is,and thus the greater the land subsidence is.A higher plot ratio also increases the contribution that the deeper stratigraphic layers make to land subsidence.Contrary to the calculated results of land subsidence caused by cluster loads and groundwater recession,the percentage of settlement caused by cluster loads in the total settlement was 49.43%and 55.06%at two simulated monitoring points,respectively.These data suggest that the cluster loads can be one of the main causes of land subsidence.
基金Supported by the National Natural Science Foundation of China(61073063,61173029,61272182 and 61173030)the Ocean Public Welfare Scientific Research Project of State Oceanic Administration of China(201105033)National Digital Ocean Key Laboratory Open Fund Projects(KLDO201306)
文摘Aiming at the load imbalance and poor scalability in single-tier Web server clusters, an efficient load balancing ap- proach is proposed for constructing an N-hierarchical （multi-tier） Web server cluster. In each layer, multiple load balancers are set to receive the user requests simultaneously, and different load bal- ancing algorithms are used to construct the high-scalable Web cluster system. At the same time, an improved load balancing al- gorithm is proposed, which can dynamically calculate weights according to the utilization of the server resources, and reasonably distribute the loads for each server according to the load status of the servers. The experimental results show that the proposed ap- proach can greatly decrease the load imbalance among the Web servers and reduce the response time of the entire Web cluster system.
基金supported by the National Nature Science Foundation of China (61170169, 61170168)
文摘Ambient Assisted Living(AAL) is becoming an important research field. Many technologies have emerged related with pervasive computing vision, which can give support for AAL. One of the most reliable approaches is based on wireless sensor networks(WSNs). In this paper, we propose a coverage-aware unequal clustering protocol with load separation(CUCPLS) for data gathering of AAL applications based on WSNs. Firstly, the coverage overlap factor for nodes is introduced that accounts for the degree of target nodes covered. In addition, to balance the intra-cluster and inter-cluster energy consumptions, different competition radiuses of CHs are computed theoretically in different rings, and smaller clusters are formed near the sink. Moreover, two CHs are selected in each cluster for load separation to alleviate the substantial energy consumption difference between a single CH and its member nodes. Furthermore, a backoff waiting time is adopted during the selection of the two CHs to reduce the number of control messages employed. Simulation results demonstrate that the CUCPLS not only can achieve better coverage performance, but also balance the energy consumption of a network and prolong network lifetime.
文摘Sensors are considered as important elements of electronic devices.In many applications and service,Wireless Sensor Networks(WSNs)are involved in significant data sharing that are delivered to the sink node in energy efficient man-ner using multi-hop communications.But,the major challenge in WSN is the nodes are having limited battery resources,it is important to monitor the consumption rate of energy is very much needed.However,reducing energy con-sumption can increase the network lifetime in effective manner.For that,clustering methods are widely used for optimizing the rate of energy consumption among the sensor nodes.In that concern,this paper involves in deriving a novel model called Improved Load-Balanced Clustering for Energy-Aware Routing(ILBC-EAR),which mainly concentrates on optimal energy utilization with load-balanced process among cluster heads and member nodes.For providing equal rate of energy consumption among nodes,the dimensions of framed clusters are measured.Moreover,the model develops a Finest Routing Scheme based on Load-Balanced Clustering to transmit the sensed information to the sink or base station.The evaluation results depict that the derived energy aware model attains higher rate of life time than other works and also achieves balanced energy rate among head node.Additionally,the model also provides higher throughput and minimal delay in delivering data packets.
文摘In order to solve the uneven node load in the tradition clustering routing protocols, a new clustering algorism based on SOM is proposed. Firstly, the network radio model and the energy consumption model are defined. A new algorism using SOM to form the cluster and select the cluster head is defined. In the clustering node remain energy and the Euclidean distance from cluster head to the cluster member are considered. The experiment shows our method has the longer life cycle and less total energy consumption. It is an effective clustering protocol.
文摘Aiming at the problem that node load is rarely considered in existing clustering routing algorithm for Wireless Sensor Networks (WSNs), a dynamic clustering routing algorithm for WSN is presented in this paper called DCRCL (Dynamic Clustering Routing Considering Load). This algorithm is comprised of three phases including cluster head (CH) selection, cluster setup and inter-cluster routing. First, the CHs are selected based on residual energy and node load. Then the non-CH nodes choose a cluster by comparing the cost function of its neighbor CHs. At last, each CH communicates with base station by using multi-hop communication. The simulation results show that comparing with the existing one, the techniques life cycle and date volume of the network are increased by 30.7 percent and 29.8 percent respectively by using the proposed algorithm DCRCL.
基金supported by the Spanish Ministry of Science and Innovation under Projects PID2022-137680OB-C32 and PID2022-139187OB-I00.
文摘Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.
基金Supported by the Industrialized Foundation ofHebei Province(020501) the Natural Science Foundation of HebeiUniversity(2005Q04)
文摘In this paper, we explored a load-balancing algorithm in a cluster file system contains two levels of metadata-server, primary-level server quickly distributestasks to second-level servers depending on the closest load-balancing information. At the same time, we explored a method which accurately reflect I/O traffic and storage of storage-node： computing the heat-value of file, according to which we realized a more logical storage allocation. According to the experiment result, we conclude that this new algorithm shortens the executing time of tasks and improves the system performance compared with other load algorithm.
基金National Science Foundation of China(No.60 173 0 3 1)
文摘This paper presented an idea to replace the traditionally expensive parallel machines by heterogeneous cluster of workstations. To emphasise the usability of cluster of workstations platform for parallel and distributed computing, also the paper presented the status report on the effort and experiences for the implementation of a dynamic load balancing for parallel tree computation depth first search(DFS) on the cluster of a workstations project. It compared the speedup performance obtained from our platform with that obtained from the traditional one. The speedup results show that cluster of workstations can be a serious alternative to the expensive parallel machines.
基金Natural Science Foundation of China (No.60 173 0 3 1)
文摘The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.
基金supported by the Planning Special Project of Guangdong Power Grid Co.,Ltd.:“Study on load modeling based on total measurement and discrimination method suitable for system characteristic analysis and calculation during the implementation of target grid in Guangdong power grid”(0319002022030203JF00023).
文摘The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection and its convergence to local optimal solutions.To overcome these limitations,an improved KFCM algorithm with adaptive optimal clustering number selection is proposed in this paper.This algorithm optimizes the KFCM algorithm by combining the powerful global search ability of genetic algorithm and the robust local search ability of simulated annealing algorithm.The improved KFCM algorithm adaptively determines the ideal number of clusters using the clustering evaluation index ratio.Compared with the traditional KFCM algorithm,the enhanced KFCM algorithm has robust clustering and comprehensive abilities,enabling the efficient convergence to the global optimal solution.
