This work presents a comprehensive sustainable sentiment analysis system utilizing textual data,designed within a structured client-server architecture for real-time deployment.The system integrates dual feature repre...This work presents a comprehensive sustainable sentiment analysis system utilizing textual data,designed within a structured client-server architecture for real-time deployment.The system integrates dual feature representations Bag-of-Words(BoW)and Term Frequency-Inverse Document Frequency(TF-IDF)whose prediction scores are combined through a parameter-free score-level fusion strategy.The implementation of the proposed system consists of five major components.The first component involves the acquisition of textual data from various sources,followed by rigorous text preprocessing to eliminate noise and enhance data quality.The second component focuses on feature extraction,ensuring that the extracted features not only reduce computational overhead but also retain high discriminative capability to effectively represent sentiments.The third component involves the development of sentiment classification models to categorize textual data based on sentiment polarity.The framework is evaluated across binary(2-class),ternary(3-class),and fine-grained(13-class)sentiment and emotion datasets.To address class imbalance in the 13-class setting,LLM-based data augmentation is incorporated during training.Following model development,the fourth component involves performance optimization,where the best-performing feature models are selected,and classifier parameters are fine-tuned to maximize accuracy and efficiency.Finally,in the fifth component,the optimized and scalable sentiment analysis models for both three-class and thirteen-class sentiment categories are deployed to a server environment for sustainable real-time sentiment classification tasks.Experimental results demonstrate that the proposed architecture maintains stable predictive performance while supporting controlled vocabulary sizes for efficient deployment.The system design emphasizes thin-client interaction,stateless REST-based inference,and centralized model management,ensuring practical applicability in real-world environments,making the system suitable for large-scale implementation in various domains such as customer feedback analysis,social media monitoring,and opinion mining.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
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
WebGIS是GIS的一个重要的发展方向.本文主要研究基于ArcGIS Server Java ADF和JSF框架的Web-GIS产品开发的关键性技术。文章首先介绍了JSF和ArcGIS Server Java ADF的基本知识,然后对ArcGIS Server Ja-va ADF基本开发技术进行了深入分析...WebGIS是GIS的一个重要的发展方向.本文主要研究基于ArcGIS Server Java ADF和JSF框架的Web-GIS产品开发的关键性技术。文章首先介绍了JSF和ArcGIS Server Java ADF的基本知识,然后对ArcGIS Server Ja-va ADF基本开发技术进行了深入分析,最后以村镇民俗旅游资源空间化分析系统为例,总结了开发此类程序的基本框架。展开更多
During the past decade,rapid advances in wireless communication technologies have made it possible for users to access desired services using hand-held devices.Service providers have hosted multiple servers to ensure ...During the past decade,rapid advances in wireless communication technologies have made it possible for users to access desired services using hand-held devices.Service providers have hosted multiple servers to ensure seamless online services to end-users.To ensure the security of this online communication,researchers have proposed several multi-server authentication schemes incorporating various cryptographic primitives.Due to the low power and computational capacities of mobile devices,the hash-based multi-server authenticated key agreement schemes with offline Registration Server(RS)are the most efficient choice.Recently,Kumar-Om presented such a scheme and proved its security against all renowned attacks.However,we find that their scheme bears an incorrect login phase,and is unsafe to the trace attack,the Session-Specific Temporary Information Attack(SSTIA),and the Key Compromise Impersonation Attack(KCIA).In fact,all of the existing multi-server authentication schemes(hash-based with offline RS)do not withstand KCLA.To deal with this situation,we propose an improved hash-based multi-server authentication scheme(with offline RS).We analyze the security of the proposed scheme under the random oracle model and use the t4Automated Validation of Internet Security Protocols and Applications''(AVISPA)tool.The comparative analysis of communication overhead and computational complexity metrics shows the efficiency of the proposed scheme.展开更多
The problem of state space explosion is still ran outstanding challenge in Markovian performance analysis for multiserver multiqueue (MSMQ) systems. The system behavior of a MSMQ system is described using stochastic h...The problem of state space explosion is still ran outstanding challenge in Markovian performance analysis for multiserver multiqueue (MSMQ) systems. The system behavior of a MSMQ system is described using stochastic high-level Petri net (SHLPN) models, and an approximate performance analysis technique is proposed based on decomposition and refinement methods as well as iteration technique. A real MSMQ system, Web-server cluster, is investigated. The performance of an integrated scheme of request dispatching and scheduling is analyzed with both Poisson and self-similar request arrivals. The study shows that the approximate analysis technique significantly reduces the complexity of the model solution and is also efficient for accuracy of numerical results.展开更多
摘要This work presents a comprehensive sustainable sentiment analysis system utilizing textual data,designed within a structured client-server architecture for real-time deployment.The system integrates dual feature representations Bag-of-Words(BoW)and Term Frequency-Inverse Document Frequency(TF-IDF)whose prediction scores are combined through a parameter-free score-level fusion strategy.The implementation of the proposed system consists of five major components.The first component involves the acquisition of textual data from various sources,followed by rigorous text preprocessing to eliminate noise and enhance data quality.The second component focuses on feature extraction,ensuring that the extracted features not only reduce computational overhead but also retain high discriminative capability to effectively represent sentiments.The third component involves the development of sentiment classification models to categorize textual data based on sentiment polarity.The framework is evaluated across binary(2-class),ternary(3-class),and fine-grained(13-class)sentiment and emotion datasets.To address class imbalance in the 13-class setting,LLM-based data augmentation is incorporated during training.Following model development,the fourth component involves performance optimization,where the best-performing feature models are selected,and classifier parameters are fine-tuned to maximize accuracy and efficiency.Finally,in the fifth component,the optimized and scalable sentiment analysis models for both three-class and thirteen-class sentiment categories are deployed to a server environment for sustainable real-time sentiment classification tasks.Experimental results demonstrate that the proposed architecture maintains stable predictive performance while supporting controlled vocabulary sizes for efficient deployment.The system design emphasizes thin-client interaction,stateless REST-based inference,and centralized model management,ensuring practical applicability in real-world environments,making the system suitable for large-scale implementation in various domains such as customer feedback analysis,social media monitoring,and opinion mining.
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。
摘要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.
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。
摘要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.
摘要WebGIS是GIS的一个重要的发展方向.本文主要研究基于ArcGIS Server Java ADF和JSF框架的Web-GIS产品开发的关键性技术。文章首先介绍了JSF和ArcGIS Server Java ADF的基本知识,然后对ArcGIS Server Ja-va ADF基本开发技术进行了深入分析,最后以村镇民俗旅游资源空间化分析系统为例,总结了开发此类程序的基本框架。
摘要During the past decade,rapid advances in wireless communication technologies have made it possible for users to access desired services using hand-held devices.Service providers have hosted multiple servers to ensure seamless online services to end-users.To ensure the security of this online communication,researchers have proposed several multi-server authentication schemes incorporating various cryptographic primitives.Due to the low power and computational capacities of mobile devices,the hash-based multi-server authenticated key agreement schemes with offline Registration Server(RS)are the most efficient choice.Recently,Kumar-Om presented such a scheme and proved its security against all renowned attacks.However,we find that their scheme bears an incorrect login phase,and is unsafe to the trace attack,the Session-Specific Temporary Information Attack(SSTIA),and the Key Compromise Impersonation Attack(KCIA).In fact,all of the existing multi-server authentication schemes(hash-based with offline RS)do not withstand KCLA.To deal with this situation,we propose an improved hash-based multi-server authentication scheme(with offline RS).We analyze the security of the proposed scheme under the random oracle model and use the t4Automated Validation of Internet Security Protocols and Applications''(AVISPA)tool.The comparative analysis of communication overhead and computational complexity metrics shows the efficiency of the proposed scheme.
摘要The problem of state space explosion is still ran outstanding challenge in Markovian performance analysis for multiserver multiqueue (MSMQ) systems. The system behavior of a MSMQ system is described using stochastic high-level Petri net (SHLPN) models, and an approximate performance analysis technique is proposed based on decomposition and refinement methods as well as iteration technique. A real MSMQ system, Web-server cluster, is investigated. The performance of an integrated scheme of request dispatching and scheduling is analyzed with both Poisson and self-similar request arrivals. The study shows that the approximate analysis technique significantly reduces the complexity of the model solution and is also efficient for accuracy of numerical results.