Mobile Edge Computing(MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy requirements.In this paper,we propose a flexible MECbased re...Mobile Edge Computing(MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy requirements.In this paper,we propose a flexible MECbased requirement-adaptive partial offloading model to accommodate each user's specific preference regarding delay and energy consumption.To address the dimensional differences between time and energy,we introduce two normalized parameters and then derive the computational overhead of processing tasks.Different from existing works,this paper considers practical variations in the user request patterns,and exploits a flexible partial offloading mode to minimize computation overheads subject to tolerable delay,task workload and power constraints.Since the resulting problem is non-convex,we decouple it into two convex subproblems and present an iterative algorithm to obtain a feasible offloading solution.Numerical experiments show that our proposed scheme achieves a significant improvement in computation overheads compared with existing schemes.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
Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment.Designing the energy-efficient data collection methods in...Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment.Designing the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the research.Sensor node clustering is a popular approach for WSN.Moreover,the sensor nodes are grouped to form clusters in a cluster-based WSN environment.The battery performance of the sensor nodes is likewise constrained.As a result,the energy efficiency of WSNs is critical.In specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in WSN.In the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was used.The selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed method.It provides the best routing path and increases the lifetime and energy efficiency of the network.End-to-end delay and packet loss rate have also been improved.The proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor nodes.Compared to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.展开更多
All EU countries have targets for increasing the use of renewable energy at a national level. However this effort should become concrete at regional and local levels where investments on bioenergy are made. This study...All EU countries have targets for increasing the use of renewable energy at a national level. However this effort should become concrete at regional and local levels where investments on bioenergy are made. This study introduces a systematical and universally applicable method for constructing regional energy balance. This study focuses on the method how to combine specific regional primary energy sources with their end uses. The primary energy sources include different fuels and the net import of electricity. The energy end uses are heat, electricity and losses. The concept of the regional energy balance was illustrated through a case of South Karelia. The total use of primary energy in South Karelia was 25.2 TWh (or 91 PJ) in 2010 and the share of renewable energy sources was 65%. The regional energy balance analysis can be utilized as a guideline for strategically planning and allocating regional energy sources for example, increasing the use of renewable energy sources. It can provide local decision makers and shareholders about the current status of energy supply, convincing them to take proper actions and consider producing energy at a local and regional level.展开更多
Facing the challenge of climate change, forecasts of energy demand and carbon emissions demand are a key requirement for India to ensure energy security and the balance economic growth. The authors calculate the optim...Facing the challenge of climate change, forecasts of energy demand and carbon emissions demand are a key requirement for India to ensure energy security and the balance economic growth. The authors calculate the optimal economic growth under the balance economic growth path from 2009 to 2050 in India based on the economy-carbon dynamic model. Combination of Intergovernmental Panel on Climate Change (IPCC) 2006 edition of the formula of carbon emissions, energy intensity model, and population model, it gets the carbon emissions demand caused by energy consumption for time span 1980-2008. Then, it estimates the energy consumption demand and carbon emissions demand under the balance economic growth path from 2009 to 2050. The results show that the cumulative amount of energy demand and carbon emissions demand in India for the time span 2009 to 2050, are 44.65 Gtoe and 36.16 Gt C, separately. The annual demand of energy consumption and carbon emissions for India show an inverted U curve from 2009 to 2050. The demand of energy consumption and carbon emissions will peak in 2045, and the peak values are 1290.74 Mtoe and 1045.98 Mt C. Furthermore, India’s per capita energy consumption demand and carbon emissions demand also appear maximum values, which are separately 0.81 toe and 0.65 t C.展开更多
针对水下传感器网络中节点能耗不均衡和能量有限的问题,提出一种能耗均衡与节能的自适应水下路由协议ECBES(energy consumption balanced and energy saving adaptive underwater routing protocol)。构建双区非均匀分层拓扑。基于能耗...针对水下传感器网络中节点能耗不均衡和能量有限的问题,提出一种能耗均衡与节能的自适应水下路由协议ECBES(energy consumption balanced and energy saving adaptive underwater routing protocol)。构建双区非均匀分层拓扑。基于能耗均衡因子,利用拓扑和节点剩余能量计算节点转发优先级,实现自适应转发节点选择,均衡网络能耗。与此同时,通过候选转发区域各分区域中节点参与转发数据包的比例确定次优候选转发区域,将次优候选转发区域作为初始策略,利用策略迭代思想确定最优候选转发区域,保证投递率的同时减少不同网络规模中重复数据包的转发,降低网络的整体能耗。仿真结果表明,ECBES相比VBF、ES-VBF和ALRP,在不同节点数量下,节点死亡率均最低,在保证数据包投递率的同时,能耗最少。展开更多
基金This work was supported in part by the National Natural Science Foundation of China under Grant 62171113 and 61941113in part by the Fundamental Research Funds for the Central Universities under Grant N2116003 and N2116011.
文摘Mobile Edge Computing(MEC)-based computation offloading is a promising application paradigm for serving large numbers of users with various delay and energy requirements.In this paper,we propose a flexible MECbased requirement-adaptive partial offloading model to accommodate each user's specific preference regarding delay and energy consumption.To address the dimensional differences between time and energy,we introduce two normalized parameters and then derive the computational overhead of processing tasks.Different from existing works,this paper considers practical variations in the user request patterns,and exploits a flexible partial offloading mode to minimize computation overheads subject to tolerable delay,task workload and power constraints.Since the resulting problem is non-convex,we decouple it into two convex subproblems and present an iterative algorithm to obtain a feasible offloading solution.Numerical experiments show that our proposed scheme achieves a significant improvement in computation overheads compared with existing schemes.
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.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Larg Groups project Under Grant Number(71/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R238)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR20.
文摘Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment.Designing the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the research.Sensor node clustering is a popular approach for WSN.Moreover,the sensor nodes are grouped to form clusters in a cluster-based WSN environment.The battery performance of the sensor nodes is likewise constrained.As a result,the energy efficiency of WSNs is critical.In specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in WSN.In the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was used.The selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed method.It provides the best routing path and increases the lifetime and energy efficiency of the network.End-to-end delay and packet loss rate have also been improved.The proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor nodes.Compared to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.
文摘All EU countries have targets for increasing the use of renewable energy at a national level. However this effort should become concrete at regional and local levels where investments on bioenergy are made. This study introduces a systematical and universally applicable method for constructing regional energy balance. This study focuses on the method how to combine specific regional primary energy sources with their end uses. The primary energy sources include different fuels and the net import of electricity. The energy end uses are heat, electricity and losses. The concept of the regional energy balance was illustrated through a case of South Karelia. The total use of primary energy in South Karelia was 25.2 TWh (or 91 PJ) in 2010 and the share of renewable energy sources was 65%. The regional energy balance analysis can be utilized as a guideline for strategically planning and allocating regional energy sources for example, increasing the use of renewable energy sources. It can provide local decision makers and shareholders about the current status of energy supply, convincing them to take proper actions and consider producing energy at a local and regional level.
文摘Facing the challenge of climate change, forecasts of energy demand and carbon emissions demand are a key requirement for India to ensure energy security and the balance economic growth. The authors calculate the optimal economic growth under the balance economic growth path from 2009 to 2050 in India based on the economy-carbon dynamic model. Combination of Intergovernmental Panel on Climate Change (IPCC) 2006 edition of the formula of carbon emissions, energy intensity model, and population model, it gets the carbon emissions demand caused by energy consumption for time span 1980-2008. Then, it estimates the energy consumption demand and carbon emissions demand under the balance economic growth path from 2009 to 2050. The results show that the cumulative amount of energy demand and carbon emissions demand in India for the time span 2009 to 2050, are 44.65 Gtoe and 36.16 Gt C, separately. The annual demand of energy consumption and carbon emissions for India show an inverted U curve from 2009 to 2050. The demand of energy consumption and carbon emissions will peak in 2045, and the peak values are 1290.74 Mtoe and 1045.98 Mt C. Furthermore, India’s per capita energy consumption demand and carbon emissions demand also appear maximum values, which are separately 0.81 toe and 0.65 t C.
文摘针对水下传感器网络中节点能耗不均衡和能量有限的问题,提出一种能耗均衡与节能的自适应水下路由协议ECBES(energy consumption balanced and energy saving adaptive underwater routing protocol)。构建双区非均匀分层拓扑。基于能耗均衡因子,利用拓扑和节点剩余能量计算节点转发优先级,实现自适应转发节点选择,均衡网络能耗。与此同时,通过候选转发区域各分区域中节点参与转发数据包的比例确定次优候选转发区域,将次优候选转发区域作为初始策略,利用策略迭代思想确定最优候选转发区域,保证投递率的同时减少不同网络规模中重复数据包的转发,降低网络的整体能耗。仿真结果表明,ECBES相比VBF、ES-VBF和ALRP,在不同节点数量下,节点死亡率均最低,在保证数据包投递率的同时,能耗最少。
