As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and el...As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.展开更多
The advancement of flexible memristors has significantly promoted the development of wearable electronic for emerging neuromorphic computing applications.Inspired by in-memory computing architecture of human brain,fle...The advancement of flexible memristors has significantly promoted the development of wearable electronic for emerging neuromorphic computing applications.Inspired by in-memory computing architecture of human brain,flexible memristors exhibit great application potential in emulating artificial synapses for highefficiency and low power consumption neuromorphic computing.This paper provides comprehensive overview of flexible memristors from perspectives of development history,material system,device structure,mechanical deformation method,device performance analysis,stress simulation during deformation,and neuromorphic computing applications.The recent advances in flexible electronics are summarized,including single device,device array and integration.The challenges and future perspectives of flexible memristor for neuromorphic computing are discussed deeply,paving the way for constructing wearable smart electronics and applications in large-scale neuromorphic computing and high-order intelligent robotics.展开更多
High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic f...High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic features enable forming-free resistive switching,multilevel conductance modulation,and synaptic plasticity,making HEOs attractive for neuromorphic computing.This review outlines recent progress in HEO-based memristors across materials engineering,switching mechanisms,and synaptic emulation.Particular attention is given to vacancy migration,phase transitions,and valence-state dynamics—mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems.Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined.While encouraging results have been achieved at the device level,challenges remain in conductance precision,variability control,and scalable integration.Addressing these demands a concerted effort across materials design,interface optimization,and task-aware modeling.With such integration,HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.展开更多
A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communic...A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.展开更多
Pervasive computing environment is a distributed and mobile space. Trust relationship must be established and ensured between devices and the systems in the pervasive computing environment. The trusted computing （TC...Pervasive computing environment is a distributed and mobile space. Trust relationship must be established and ensured between devices and the systems in the pervasive computing environment. The trusted computing （TC） technology introduced by trusted computing group is a distributed-system-wide approach to the provisions of integrity protection of resources. The TC＇s notion of trust and security can be described as conformed system behaviors of a platform environment such that the conformation can be attested to a remote challenger. In this paper the trust requirements in a pervasive/ubiquitous environment are analyzed. Then security schemes for the pervasive computing are proposed using primitives offered by TC technology.展开更多
Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications ...Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications of pervasive computing that addresses the road safety challenges.Vehicles participating within the IoV are embedded with a wide range of sensors which operate in a real time environment to improve the road safety issues.Various mechanisms have been proposed which allow automatic actions based on uncertainty of sensory and managed data.Due to the lack of existing transportation integration schemes,IoV has not been completely explored by business organizations.In order to tackle this problem,we have proposed a novel trusted mechanism in IoV during communication,sensing,and record storing.Our proposed method uses trust based analysis and subjective logic functions with the aim of creating a trust environment for vehicles to communicate.In addition,the subjective logic function is integrated with multi-attribute SAW scheme to improve the decision metrics of authenticating nodes.The trust analysis depends on a variety of metrics to ensure an accurate identification of legitimate vehicles embedded with IoT devices ecosystem.The proposed scheme is determined and verified rigorously through various IoT devices and decision making metrics against a baseline solution.The simulation results show that the proposed scheme leads to 88%improvement in terms of better identification of legitimate nodes,road accidents and message alteration records during data transmission among vehicles as compared to the baseline approach.展开更多
In pervasive computing environments,users can get services anytime and anywhere,but the ubiquity and mobility of the environments bring new security challenges.The user and the service provider do not know each other ...In pervasive computing environments,users can get services anytime and anywhere,but the ubiquity and mobility of the environments bring new security challenges.The user and the service provider do not know each other in advance,they should mutually authenticate each other.The service provider prefers to authenticate the user based on his identity while the user tends to stay anonymous.Privacy and security are two important but seemingly contradictory objectives.As a result,a user prefers not to expose any sensitive information to the service provider such as his physical location,ID and so on when being authenticated.In this paper,a highly flexible mutual authentication and key establishment protocol scheme based on biometric encryption and Diffie-Hellman key exchange to secure interactions between a user and a service provider is proposed.Not only can a user's anonymous authentication be achieved,but also the public key cryptography operations can be reduced by adopting this scheme.Different access control policies for different services are enabled by using biometric encryption technique.The correctness of the proposed authentication and key establishment protocol is formally verified based on SVO logic.展开更多
Lots of pervasive computing researchers are working on how to realize the user-centered intelligent pervasive computing environment as Mark Weiser figured out.Task abstraction is the fundamentation of configuration fo...Lots of pervasive computing researchers are working on how to realize the user-centered intelligent pervasive computing environment as Mark Weiser figured out.Task abstraction is the fundamentation of configuration for pervasive application.Based on task-oriented and descriptive properties of scenario,a scenario-based participatory design model was proposed to realize the task abstraction.The design model provided users and domain experts a useful mechanism to build the customized applications by separating system model into domain model and design model.In this design model,domain experts,together with users,stakeholders focus on the logic rules(domain model)and programmers work on the implementation(design model).In order to formalize the model description,a human-agent interaction language to transform users' goals and domain rules into executable scenarios was also discussed.An agent platform-describer used to link design and implementation of scenarios was developed to realize the configuration of applications according to different requirements.The demand bus application showed the design process and the usability of this model.展开更多
This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment ...This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment is apt to result in notable service isomorphs. And moreover, as the environment cannot assure the stability of network communication and device services, the situation gets worse. Therefore, it becomes urgent to simplify user operations and let them take full and highly efficient advantage of the environments. Super-Service-Odented Architecture （SSOA） is an Serrice-Otiented Architecture （SOA）-based architecture for service management and organization in peryasive environments. With combining one kind of isomorphic services into a super service, SSOA provides better scalability and quick, convenient service invocations. Also, the complexity and instability of services, and network types are transparent, and system performance is highly promoted under the architecture.展开更多
In order to integrate heterogeneous location-aware systems into pervasive computing environment,a novel pervasive computing location-aware model based on ontology is presented.A location-aware model ontology(LMO)is co...In order to integrate heterogeneous location-aware systems into pervasive computing environment,a novel pervasive computing location-aware model based on ontology is presented.A location-aware model ontology(LMO)is constructed.The location-aware model has the capabilities of sharing knowledge,reasoning and adjusting the usage policies of services dynamically through a unified semantic location manner.At last,the work process of our proposed location-aware model is explained by an application scenario.展开更多
Modern research emphasizes Pervasive Computing change faces, learning cultures, structures, communications, intellectual properties, information securities, data presentations and web dis-plays to make attraction for ...Modern research emphasizes Pervasive Computing change faces, learning cultures, structures, communications, intellectual properties, information securities, data presentations and web dis-plays to make attraction for human interaction. Pervasive systems have a broad range of applica-tions but it is relatively challenging for pervasive applications to meet emergence into existing physical environment and newly built structure requirements. Due to their interaction to gather information and change the environment via activating devices independently is highlighted. Se-curity of the pervasive devices and applications which control our activities has primary importance and will be destroyed, if the pervasive system operations are not secure. There is a need to improve the security measures for data to travel rapidly, unbroken, unchanged and invisible by deceptive recipients. Pervasive Computing allows users to get information and services access anytime and anywhere but need to discuss issues and solutions to deliver secure information with privacy and trust. Possible solutions for these challenges of Pervasive Computing interaction between human are emphasized. A collection of papers and articles have been collected in order to investigate the previous study of Pervasive Computing interaction and its challenges. Is it possible for us to understand what the scientific world will be close to generate new avenues? Expectations of future bring new openings for user interaction with systems, data, information and the environments in which they live, work and play.展开更多
Nowadays, application systems in pervasive computing have to be self-adaptive, which means adapting themselves to dynamic environments. Our aim is to enable systematic development of self-adaptive compo-nent-based app...Nowadays, application systems in pervasive computing have to be self-adaptive, which means adapting themselves to dynamic environments. Our aim is to enable systematic development of self-adaptive compo-nent-based applications. The paper first introduces a novel policy based framework for self-adaptive scheme in pervasive computing. Then the proposed policy ontology and policy language are well expressive and eas-ily extensible to support the design of policy which is based on the Separation of Concerns principle. Fur-thermore, the context-driven event channel decouples the communication between the suppliers and con-sumers for asynchronous communication. The proposed framework can provide both a domain-independent and a flexible self-adaptation solution.展开更多
Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in us...Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user experience.In this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their priority.Subsequently,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN framework.Next,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of sub-tasks.Simulation results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.展开更多
Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic ...Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic functions,i.e.,excita-tory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations.More importantly,the device exhibited distinguishable response currents by adjusting 4-bit input electrical/opti-cal signals.A multi-mode reservoir computing(RC)system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7%is achieved.The optoelectronic memristor provides potential for developing multi-mode RC system.展开更多
As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the...As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective optimization problem aimed at minimizing both delay and energy consumption. We model the task offloading strategy using a directed acyclic graph (DAG). Furthermore, we propose a distributed edge computing adaptive task offloading algorithm rooted in MRL. This algorithm integrates multiple Markov decision processes (MDP) with a sequence-to-sequence (seq2seq) network, enabling it to learn and adapt task offloading strategies responsively across diverse network environments. To achieve joint optimization of delay and energy consumption, we incorporate the non-dominated sorting genetic algorithm II (NSGA-II) into our framework. Simulation results demonstrate the superiority of our proposed solution, achieving a 21% reduction in time delay and a 19% decrease in energy consumption compared to alternative task offloading schemes. Moreover, our scheme exhibits remarkable adaptability, responding swiftly to changes in various network environments.展开更多
The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language proc...The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.展开更多
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051,ZR2025QB50)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2025A1515011191)the Shanghai Sailing Program(23YF1402200,23YF1402400)funded by Basic Research Program of Jiangsu(BK20240424)Open Research Fund of State Key Laboratory of Crystal Materials(KF2406)Taishan Scholar Foundation of Shandong Province(tsqn202408006,tsqn202507058)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University。
文摘As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051)+5 种基金Open Research Fund of State Key Laboratory of Materials for Integrated Circuits(SKLJC-K2024-12)the Shanghai Sailing Program(23YF1402200,23YF1402400)Natural Science Foundation of Jiangsu Province(BK20240424)Taishan Scholar Foundation of Shandong Province(tsqn202408006)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University.
文摘The advancement of flexible memristors has significantly promoted the development of wearable electronic for emerging neuromorphic computing applications.Inspired by in-memory computing architecture of human brain,flexible memristors exhibit great application potential in emulating artificial synapses for highefficiency and low power consumption neuromorphic computing.This paper provides comprehensive overview of flexible memristors from perspectives of development history,material system,device structure,mechanical deformation method,device performance analysis,stress simulation during deformation,and neuromorphic computing applications.The recent advances in flexible electronics are summarized,including single device,device array and integration.The challenges and future perspectives of flexible memristor for neuromorphic computing are discussed deeply,paving the way for constructing wearable smart electronics and applications in large-scale neuromorphic computing and high-order intelligent robotics.
基金financially supported by the National Natural Science Foundation of China(Grant No.12172093)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515012607)。
文摘High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic features enable forming-free resistive switching,multilevel conductance modulation,and synaptic plasticity,making HEOs attractive for neuromorphic computing.This review outlines recent progress in HEO-based memristors across materials engineering,switching mechanisms,and synaptic emulation.Particular attention is given to vacancy migration,phase transitions,and valence-state dynamics—mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems.Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined.While encouraging results have been achieved at the device level,challenges remain in conductance precision,variability control,and scalable integration.Addressing these demands a concerted effort across materials design,interface optimization,and task-aware modeling.With such integration,HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.
基金The National Natural Science Foundation of China(No60503041)the Science and Technology Commission of ShanghaiInternational Cooperation Project (No05SN07114)
文摘A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.
基金Supported by the National Natural Science Foun-dation of China (60573030 ,60303026 ,60473020) the Institutefor Infocomm Research 21 Heng Mui Keng Terrace ,Singapore .
文摘Pervasive computing environment is a distributed and mobile space. Trust relationship must be established and ensured between devices and the systems in the pervasive computing environment. The trusted computing （TC） technology introduced by trusted computing group is a distributed-system-wide approach to the provisions of integrity protection of resources. The TC＇s notion of trust and security can be described as conformed system behaviors of a platform environment such that the conformation can be attested to a remote challenger. In this paper the trust requirements in a pervasive/ubiquitous environment are analyzed. Then security schemes for the pervasive computing are proposed using primitives offered by TC technology.
基金funded by the Abu Dhabi University,Faculty Research Incentive Grant(19300483–Adel Khelifi),United Arab Emirates.Link to Sponsor website:https://www.adu.ac.ae/research/research-at-adu/overview.
文摘Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications of pervasive computing that addresses the road safety challenges.Vehicles participating within the IoV are embedded with a wide range of sensors which operate in a real time environment to improve the road safety issues.Various mechanisms have been proposed which allow automatic actions based on uncertainty of sensory and managed data.Due to the lack of existing transportation integration schemes,IoV has not been completely explored by business organizations.In order to tackle this problem,we have proposed a novel trusted mechanism in IoV during communication,sensing,and record storing.Our proposed method uses trust based analysis and subjective logic functions with the aim of creating a trust environment for vehicles to communicate.In addition,the subjective logic function is integrated with multi-attribute SAW scheme to improve the decision metrics of authenticating nodes.The trust analysis depends on a variety of metrics to ensure an accurate identification of legitimate vehicles embedded with IoT devices ecosystem.The proposed scheme is determined and verified rigorously through various IoT devices and decision making metrics against a baseline solution.The simulation results show that the proposed scheme leads to 88%improvement in terms of better identification of legitimate nodes,road accidents and message alteration records during data transmission among vehicles as compared to the baseline approach.
基金Supported by the National Natural Science Foundation of China (No.60703101)
文摘In pervasive computing environments,users can get services anytime and anywhere,but the ubiquity and mobility of the environments bring new security challenges.The user and the service provider do not know each other in advance,they should mutually authenticate each other.The service provider prefers to authenticate the user based on his identity while the user tends to stay anonymous.Privacy and security are two important but seemingly contradictory objectives.As a result,a user prefers not to expose any sensitive information to the service provider such as his physical location,ID and so on when being authenticated.In this paper,a highly flexible mutual authentication and key establishment protocol scheme based on biometric encryption and Diffie-Hellman key exchange to secure interactions between a user and a service provider is proposed.Not only can a user's anonymous authentication be achieved,but also the public key cryptography operations can be reduced by adopting this scheme.Different access control policies for different services are enabled by using biometric encryption technique.The correctness of the proposed authentication and key establishment protocol is formally verified based on SVO logic.
文摘Lots of pervasive computing researchers are working on how to realize the user-centered intelligent pervasive computing environment as Mark Weiser figured out.Task abstraction is the fundamentation of configuration for pervasive application.Based on task-oriented and descriptive properties of scenario,a scenario-based participatory design model was proposed to realize the task abstraction.The design model provided users and domain experts a useful mechanism to build the customized applications by separating system model into domain model and design model.In this design model,domain experts,together with users,stakeholders focus on the logic rules(domain model)and programmers work on the implementation(design model).In order to formalize the model description,a human-agent interaction language to transform users' goals and domain rules into executable scenarios was also discussed.An agent platform-describer used to link design and implementation of scenarios was developed to realize the configuration of applications according to different requirements.The demand bus application showed the design process and the usability of this model.
文摘This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment is apt to result in notable service isomorphs. And moreover, as the environment cannot assure the stability of network communication and device services, the situation gets worse. Therefore, it becomes urgent to simplify user operations and let them take full and highly efficient advantage of the environments. Super-Service-Odented Architecture （SSOA） is an Serrice-Otiented Architecture （SOA）-based architecture for service management and organization in peryasive environments. With combining one kind of isomorphic services into a super service, SSOA provides better scalability and quick, convenient service invocations. Also, the complexity and instability of services, and network types are transparent, and system performance is highly promoted under the architecture.
基金The Key Project of Chinese Ministry of Education(No.104086)
文摘In order to integrate heterogeneous location-aware systems into pervasive computing environment,a novel pervasive computing location-aware model based on ontology is presented.A location-aware model ontology(LMO)is constructed.The location-aware model has the capabilities of sharing knowledge,reasoning and adjusting the usage policies of services dynamically through a unified semantic location manner.At last,the work process of our proposed location-aware model is explained by an application scenario.
文摘Modern research emphasizes Pervasive Computing change faces, learning cultures, structures, communications, intellectual properties, information securities, data presentations and web dis-plays to make attraction for human interaction. Pervasive systems have a broad range of applica-tions but it is relatively challenging for pervasive applications to meet emergence into existing physical environment and newly built structure requirements. Due to their interaction to gather information and change the environment via activating devices independently is highlighted. Se-curity of the pervasive devices and applications which control our activities has primary importance and will be destroyed, if the pervasive system operations are not secure. There is a need to improve the security measures for data to travel rapidly, unbroken, unchanged and invisible by deceptive recipients. Pervasive Computing allows users to get information and services access anytime and anywhere but need to discuss issues and solutions to deliver secure information with privacy and trust. Possible solutions for these challenges of Pervasive Computing interaction between human are emphasized. A collection of papers and articles have been collected in order to investigate the previous study of Pervasive Computing interaction and its challenges. Is it possible for us to understand what the scientific world will be close to generate new avenues? Expectations of future bring new openings for user interaction with systems, data, information and the environments in which they live, work and play.
文摘Nowadays, application systems in pervasive computing have to be self-adaptive, which means adapting themselves to dynamic environments. Our aim is to enable systematic development of self-adaptive compo-nent-based applications. The paper first introduces a novel policy based framework for self-adaptive scheme in pervasive computing. Then the proposed policy ontology and policy language are well expressive and eas-ily extensible to support the design of policy which is based on the Separation of Concerns principle. Fur-thermore, the context-driven event channel decouples the communication between the suppliers and con-sumers for asynchronous communication. The proposed framework can provide both a domain-independent and a flexible self-adaptation solution.
文摘Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable challenges.The sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user experience.In this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their priority.Subsequently,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN framework.Next,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of sub-tasks.Simulation results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.
基金Acknowledgements： This work is supported by National Natural Science Foundation of China （No. 60773118）, National High Tech. Development Plan （No. 2006AA01A109）, and Program for Changjiang Scholars and Innovative Research Team in University.
基金supported by the"Science and Technology Development Plan Project of Jilin Province,China"(Grant No.20240101018JJ)the Fundamental Research Funds for the Central Universities(Grant No.2412023YQ004)the National Natural Science Foundation of China(Grant Nos.52072065,52272140,52372137,and U23A20568).
文摘Optoelectronic memristor is generating growing research interest for high efficient computing and sensing-memory applications.In this work,an optoelectronic memristor with Au/a-C:Te/Pt structure is developed.Synaptic functions,i.e.,excita-tory post-synaptic current and pair-pulse facilitation are successfully mimicked with the memristor under electrical and optical stimulations.More importantly,the device exhibited distinguishable response currents by adjusting 4-bit input electrical/opti-cal signals.A multi-mode reservoir computing(RC)system is constructed with the optoelectronic memristors to emulate human tactile-visual fusion recognition and an accuracy of 98.7%is achieved.The optoelectronic memristor provides potential for developing multi-mode RC system.
基金funded by the Fundamental Research Funds for the Central Universities(J2023-024,J2023-027).
文摘As an important complement to cloud computing, edge computing can effectively reduce the workload of the backbone network. To reduce latency and energy consumption of edge computing, deep learning is used to learn the task offloading strategies by interacting with the entities. In actual application scenarios, users of edge computing are always changing dynamically. However, the existing task offloading strategies cannot be applied to such dynamic scenarios. To solve this problem, we propose a novel dynamic task offloading framework for distributed edge computing, leveraging the potential of meta-reinforcement learning (MRL). Our approach formulates a multi-objective optimization problem aimed at minimizing both delay and energy consumption. We model the task offloading strategy using a directed acyclic graph (DAG). Furthermore, we propose a distributed edge computing adaptive task offloading algorithm rooted in MRL. This algorithm integrates multiple Markov decision processes (MDP) with a sequence-to-sequence (seq2seq) network, enabling it to learn and adapt task offloading strategies responsively across diverse network environments. To achieve joint optimization of delay and energy consumption, we incorporate the non-dominated sorting genetic algorithm II (NSGA-II) into our framework. Simulation results demonstrate the superiority of our proposed solution, achieving a 21% reduction in time delay and a 19% decrease in energy consumption compared to alternative task offloading schemes. Moreover, our scheme exhibits remarkable adaptability, responding swiftly to changes in various network environments.
基金the National Research Foundation(NRF)Singapore mid-sized center grant(NRF-MSG-2023-0002)FrontierCRP grant(NRF-F-CRP-2024-0006)+2 种基金A*STAR Singapore MTC RIE2025 project(M24W1NS005)IAF-PP project(M23M5a0069)Ministry of Education(MOE)Singapore Tier 2 project(MOE-T2EP50220-0014).
文摘The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.
