We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures.In this mechanism,each item represents a computing task and is replicated intoξ+1 servers for some int...We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures.In this mechanism,each item represents a computing task and is replicated intoξ+1 servers for some integerξ≥1,with workloads specified by the amount of required resources.If one or more servers fail,the affected workloads can be redirected to other servers that host replicas associated with the same item,such that the service is not interrupted by the failure of up toξservers.This requires that any feasible assignment algorithm must reserve some capacity in each server to accommodate the workload redirected from potential failed servers without overloading,and determining the optimal method for reserving capacity becomes a key issue.Unlike existing algorithms that assume that no two servers share replicas of more than one item,we first formulate capacity reservation for a general arbitrary scenario.Due to the combinatorial nature of this problem,finding the optimal solution is difficult.To this end,we propose a Generalized and Simple Calculating Reserved Capacity(GSCRC)algorithm,with a time complexity only related to the number of items packed in the server.In conjunction with GSCRC,we propose a robust replica packing algorithm with capacity optimization(RobustPack),which aims to minimize the number of servers hosting replicas and tolerate multiple server failures.Through theoretical analysis and experimental evaluations,we show that the RobustPack algorithm can achieve better performance.展开更多
The Internet of Things(IoT)and allied applications have made real-time responsiveness for massive devices over the Internet essential.Cloud-edge/fog ensembles handle such applications'computations.For Beyond 5 th ...The Internet of Things(IoT)and allied applications have made real-time responsiveness for massive devices over the Internet essential.Cloud-edge/fog ensembles handle such applications'computations.For Beyond 5 th Generation(B5G)communication paradigms,Edge Servers(ESs)must be placed within Information Communication Technology infrastructures to meet Quality of Service requirements like response time and resource utilisation.Due to the large number of Base Stations(BSs)and ESs and the possibility of significant variations in placing the ESs within the IoTs geographical expanse for optimising multiple objectives,the Edge Server Placement Problem(ESPP)is NP-hard.Thus,stochastic evolutionary metaheuristics are natural.This work addresses the ESPP using a Particle Swarm Optimization that initialises particles as BS positions within the geography to maintain the workload while scanning through all feasible sets of BSs as an encoded sequence.The Workload-Threshold Aware Sequence Encoding(WTASE)Scheme for ESPP provides the number of ESs to be deployed,similar to existing methodologies and exact locations for their placements without the overhead of maintaining a prohibitively large distance matrix.Simulation tests using open-source datasets show that the suggested technique improves ESs utilisation rate,workload balance,and average energy consumption by 36%,17%,and 32%,respectively,compared to prior works.展开更多
本文在AJAX理念的指导下,针对WebGIS的不足之处,设计与实现了城市交通矢量WebGIS原型系统。原型系统以ArcGIS Server WebADF框架为核心构建地图引擎,以AJAX开源引擎ExtJS作为前端辅助工具实现查询以及统计分析功能。试验表明,基于AJAX...本文在AJAX理念的指导下,针对WebGIS的不足之处,设计与实现了城市交通矢量WebGIS原型系统。原型系统以ArcGIS Server WebADF框架为核心构建地图引擎,以AJAX开源引擎ExtJS作为前端辅助工具实现查询以及统计分析功能。试验表明,基于AJAX的富客户端WebGIS架构减轻了服务器端的负载,提升了客户端的运行效率,更加高效地提供了Web地理信息服务。展开更多
ArcGIS Server是ESRI公司基于IT工业标准推出的企业级WebGIS应用平台,它支持GIS功能集中管理和多用户负载均衡。ArcGIS Server GIS服务器运行机制复杂,部署基于ArcGIS Server API开发的Web应用程序或Web服务程序,需要考虑Web服务器、GI...ArcGIS Server是ESRI公司基于IT工业标准推出的企业级WebGIS应用平台,它支持GIS功能集中管理和多用户负载均衡。ArcGIS Server GIS服务器运行机制复杂,部署基于ArcGIS Server API开发的Web应用程序或Web服务程序,需要考虑Web服务器、GIS服务器和数据库服务器的配置和部署。本文通过研究ArcGIS Server的分布式体系结构和GIS服务器的运行机制,同时根据可用的硬件和软件资源,采取合理的服务器配置策略,以达到合理利用资源和有效发挥系统性能的目的。展开更多
基金supported in part by the National Key R&D Program of China under No.2023YFB2703800the National Science Foundation of China under Grants U22B2027,62172297,62102262,61902276 and 62272311+3 种基金Tianjin Intelligent Manufacturing Special Fund Project under Grants 20211097the China Guangxi Science and Technology Plan Project(Guangxi Science and Technology Base and Talent Special Project)under Grant AD23026096(Application Number 2022AC20001)Henan Provincial Natural Science Foundation of China under Grant 622RC616CCF-Nsfocus Kunpeng Fund Project under Grants CCF-NSFOCUS202207。
文摘We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures.In this mechanism,each item represents a computing task and is replicated intoξ+1 servers for some integerξ≥1,with workloads specified by the amount of required resources.If one or more servers fail,the affected workloads can be redirected to other servers that host replicas associated with the same item,such that the service is not interrupted by the failure of up toξservers.This requires that any feasible assignment algorithm must reserve some capacity in each server to accommodate the workload redirected from potential failed servers without overloading,and determining the optimal method for reserving capacity becomes a key issue.Unlike existing algorithms that assume that no two servers share replicas of more than one item,we first formulate capacity reservation for a general arbitrary scenario.Due to the combinatorial nature of this problem,finding the optimal solution is difficult.To this end,we propose a Generalized and Simple Calculating Reserved Capacity(GSCRC)algorithm,with a time complexity only related to the number of items packed in the server.In conjunction with GSCRC,we propose a robust replica packing algorithm with capacity optimization(RobustPack),which aims to minimize the number of servers hosting replicas and tolerate multiple server failures.Through theoretical analysis and experimental evaluations,we show that the RobustPack algorithm can achieve better performance.
基金the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project under grant number RGP2/603/46。
文摘The Internet of Things(IoT)and allied applications have made real-time responsiveness for massive devices over the Internet essential.Cloud-edge/fog ensembles handle such applications'computations.For Beyond 5 th Generation(B5G)communication paradigms,Edge Servers(ESs)must be placed within Information Communication Technology infrastructures to meet Quality of Service requirements like response time and resource utilisation.Due to the large number of Base Stations(BSs)and ESs and the possibility of significant variations in placing the ESs within the IoTs geographical expanse for optimising multiple objectives,the Edge Server Placement Problem(ESPP)is NP-hard.Thus,stochastic evolutionary metaheuristics are natural.This work addresses the ESPP using a Particle Swarm Optimization that initialises particles as BS positions within the geography to maintain the workload while scanning through all feasible sets of BSs as an encoded sequence.The Workload-Threshold Aware Sequence Encoding(WTASE)Scheme for ESPP provides the number of ESs to be deployed,similar to existing methodologies and exact locations for their placements without the overhead of maintaining a prohibitively large distance matrix.Simulation tests using open-source datasets show that the suggested technique improves ESs utilisation rate,workload balance,and average energy consumption by 36%,17%,and 32%,respectively,compared to prior works.
文摘本文在AJAX理念的指导下,针对WebGIS的不足之处,设计与实现了城市交通矢量WebGIS原型系统。原型系统以ArcGIS Server WebADF框架为核心构建地图引擎,以AJAX开源引擎ExtJS作为前端辅助工具实现查询以及统计分析功能。试验表明,基于AJAX的富客户端WebGIS架构减轻了服务器端的负载,提升了客户端的运行效率,更加高效地提供了Web地理信息服务。
文摘ArcGIS Server是ESRI公司基于IT工业标准推出的企业级WebGIS应用平台,它支持GIS功能集中管理和多用户负载均衡。ArcGIS Server GIS服务器运行机制复杂,部署基于ArcGIS Server API开发的Web应用程序或Web服务程序,需要考虑Web服务器、GIS服务器和数据库服务器的配置和部署。本文通过研究ArcGIS Server的分布式体系结构和GIS服务器的运行机制,同时根据可用的硬件和软件资源,采取合理的服务器配置策略,以达到合理利用资源和有效发挥系统性能的目的。
