In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management...In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is proposed.Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is given.The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the host.Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.展开更多
This paper analyzes the reasons for the formation of security problems in mobile agent systems, and analyzes and compares the security mechanisms and security technologies of existing mobile agent systems from the per...This paper analyzes the reasons for the formation of security problems in mobile agent systems, and analyzes and compares the security mechanisms and security technologies of existing mobile agent systems from the perspective of blocking attacks. On this basis, the host protection mobile agent protection technology is selected, and a method to enhance the security protection of mobile agents (referred to as IEOP method) is proposed. The method first encrypts the mobile agent code using the encryption function, and then encapsulates the encrypted mobile agent with the improved EOP protocol IEOP, and then traces the suspicious execution result. Experiments show that using this method can block most malicious attacks on mobile agents, and can protect the integrity and confidentiality of mobile agents, but the increment of mobile agent tour time is not large.展开更多
Mobile agents is becoming a prosperous research field due to recent prevalence of Internet andJava. Although it brings great challenges to traditional distributed processing technologies, its attractive advantages sti...Mobile agents is becoming a prosperous research field due to recent prevalence of Internet andJava. Although it brings great challenges to traditional distributed processing technologies, its attractive advantages stimulate us to further the work on it with great ardor. This paper presents the basic concepts aboutthe Inchoate technique and describes current research status on it. Major obstacles and their possible solutions are discussed.展开更多
Software coordination is central to the construction of large-scale high-performance distributed applications with software services scattered over the decentralized Internet. In this paper, a new mobile-agent-based a...Software coordination is central to the construction of large-scale high-performance distributed applications with software services scattered over the decentralized Internet. In this paper, a new mobile-agent-based architecture is proposed for the utilization and coordination of geographically distributed computing resources. Under this architecture, a user application is built with a set of software agents that can travel across the network autonomously. These agents utilize the distributed resources and coordinate with each other to complete their task. This approach' s advantages include the natural expression and flexible deployment of the coordination logic, the dynamic adaptation to the network environment and the potential of better application performance. This coordination architecture, together with an object-oriented hierarchical parallel application framework and a graphical application construction tool, is implemented in the HOOPE environment, which provides a systematic support for the development and execution of Internet-based distributed and parallel applications in the petroleum exploration industry.展开更多
Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and...Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and improve the performance of certain classes of distributed applications, especially for those running on a wide-area, heterogeneous, and dynamic networking environment like the Internet. In our previous work, we extended the application of MA to the design of distributed control functions, which require the maintenance of logical relationship among and/or coordination of processing entities in a distributed system. A novel framework is presented for structuring and building distributed systems, which use cooperating mobile agents as an aid to carry out coordination and cooperation tasks in distributed systems. The framework has been used for designing various distributed control functions such as load balancing and mutual ex- clusion in our previous work. In this paper, we use the framework to propose a novel approach to detecting deadlocks in distributed system by using mobile agents, which demonstrates the advantage of being adaptive and flexible of mobile agents. We first describe the MAEDD （Mobile Agent Enabled Deadlock Detection） scheme, in which mobile agents are dispatched to collect and analyze deadlock information distributed across the network sites and, based on the analysis, to detect and resolve deadlocks. Then the design of an adaptive hybrid algorithm derived from the framework is presented. The algorithm can dynamically adapt itself to the changes in system state by using different deadlock detection strategies. The performance of the proposed algorithm has been evaluated using simulations. The results show that the algorithm can outperform existing algorithms that use a fixed deadlock detection strategy.展开更多
Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the applicat...Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still exist.Due to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of terminals.Considering the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption.However,the resulting optimization problem is originally nonconvex and thus,difficult to solve optimally.To tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex subproblems.Furthermore,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser terminals.Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.展开更多
Heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for b...Heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for both control plane(CP)and data plane(DP).Likewise,the heterogeneous 5th generation(5G)communication applications,including Mobile Broadband Communications(MBBC),massive Machine-Type Commutation(mMTC),and ultra-reliable low latency communications(URLLC),obligate to perform intelligent Quality-of-Service(QoS)Class Identifier(QCI),while the CP entities will be suffered from the complicated massive HIOT applications.Moreover,the existing management and orchestration(MANO)models are inappropriate for resource utilization and allocation in large-scale and complicated network environments.To cope with the issues mentioned above,this paper presents an adopted software-defined mobile edge computing(SDMEC)with a lightweight machine learning(ML)algorithm,namely support vector machine(SVM),to enable intelligent MANO for real-time and resource-constraints IoT applications which require lightweight computation models.Furthermore,the SVM algorithm plays an essential role in performing QCI classification.Moreover,the software-defined networking(SDN)controller allocates and configures priority resources according to the SVM classification outcomes.Thus,the complementary of SVM and SDMEC conducts intelligent resource MANO for massive QCI environments and meets the perspectives of mission-critical communication with resource constraint applications.Based on the E2E experimentation metrics,the proposed scheme shows remarkable outperformance in key performance indicator(KPI)QoS,including communication reliability,latency,and communication throughput over the various powerful reference methods.展开更多
基金This work was supported by the National Natural Science Foundation of China(61772196,61472136)the Hunan Provincial Focus Social Science Fund(2016ZDB006)+2 种基金Hunan Provincial Social Science Achievement Review Committee results appraisal identification project(Xiang social assessment 2016JD05)Key Project of Hunan Provincial Social Science Achievement Review Committee(XSP 19ZD1005)The authors gratefully acknowledge the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology(2017TP1026).
文摘In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is proposed.Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is given.The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the host.Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.
基金supported by the National Natural Science Foundation of China (61772196 61472136)+3 种基金the Hunan Provincial Focus Social Science Fund (2016ZDB006)Hunan Provincial Social Science Achievement Review Committee results appraisal identification project (Xiang social assessment 2016JD05)Key Project of Hunan Provincial Social Science Achievement Review Committee (XSP 19ZD1005)the financial support provided by the Key Laboratory of Hunan Province for New Retail Virtual Reality Technology (2017TP1026)
文摘This paper analyzes the reasons for the formation of security problems in mobile agent systems, and analyzes and compares the security mechanisms and security technologies of existing mobile agent systems from the perspective of blocking attacks. On this basis, the host protection mobile agent protection technology is selected, and a method to enhance the security protection of mobile agents (referred to as IEOP method) is proposed. The method first encrypts the mobile agent code using the encryption function, and then encapsulates the encrypted mobile agent with the improved EOP protocol IEOP, and then traces the suspicious execution result. Experiments show that using this method can block most malicious attacks on mobile agents, and can protect the integrity and confidentiality of mobile agents, but the increment of mobile agent tour time is not large.
文摘Mobile agents is becoming a prosperous research field due to recent prevalence of Internet andJava. Although it brings great challenges to traditional distributed processing technologies, its attractive advantages stimulate us to further the work on it with great ardor. This paper presents the basic concepts aboutthe Inchoate technique and describes current research status on it. Major obstacles and their possible solutions are discussed.
基金This work was supported by the National Natural Science Foundation for Excellent Young Scientists of China the National 863 High-Technology Program and Beijing Global Software Corporation.
文摘Software coordination is central to the construction of large-scale high-performance distributed applications with software services scattered over the decentralized Internet. In this paper, a new mobile-agent-based architecture is proposed for the utilization and coordination of geographically distributed computing resources. Under this architecture, a user application is built with a set of software agents that can travel across the network autonomously. These agents utilize the distributed resources and coordinate with each other to complete their task. This approach' s advantages include the natural expression and flexible deployment of the coordination logic, the dynamic adaptation to the network environment and the potential of better application performance. This coordination architecture, together with an object-oriented hierarchical parallel application framework and a graphical application construction tool, is implemented in the HOOPE environment, which provides a systematic support for the development and execution of Internet-based distributed and parallel applications in the petroleum exploration industry.
文摘Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and improve the performance of certain classes of distributed applications, especially for those running on a wide-area, heterogeneous, and dynamic networking environment like the Internet. In our previous work, we extended the application of MA to the design of distributed control functions, which require the maintenance of logical relationship among and/or coordination of processing entities in a distributed system. A novel framework is presented for structuring and building distributed systems, which use cooperating mobile agents as an aid to carry out coordination and cooperation tasks in distributed systems. The framework has been used for designing various distributed control functions such as load balancing and mutual ex- clusion in our previous work. In this paper, we use the framework to propose a novel approach to detecting deadlocks in distributed system by using mobile agents, which demonstrates the advantage of being adaptive and flexible of mobile agents. We first describe the MAEDD （Mobile Agent Enabled Deadlock Detection） scheme, in which mobile agents are dispatched to collect and analyze deadlock information distributed across the network sites and, based on the analysis, to detect and resolve deadlocks. Then the design of an adaptive hybrid algorithm derived from the framework is presented. The algorithm can dynamically adapt itself to the changes in system state by using different deadlock detection strategies. The performance of the proposed algorithm has been evaluated using simulations. The results show that the algorithm can outperform existing algorithms that use a fixed deadlock detection strategy.
基金supported by the Jiangsu Provincial Key Research and Development Program(No.BE2020084-4)the National Natural Science Foundation of China(No.92067201)+2 种基金the National Natural Science Foundation of China(61871446)the Open Research Fund of Jiangsu Key Laboratory of Wireless Communications(710020017002)the Natural Science Foundation of Nanjing University of Posts and telecommunications(NY220047).
文摘Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground infrastructure.Mitigating this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still exist.Due to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of terminals.Considering the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy consumption.However,the resulting optimization problem is originally nonconvex and thus,difficult to solve optimally.To tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex subproblems.Furthermore,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser terminals.Simulation results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.
基金This work was funded by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2020R1I1A3066543)this research was supported by the Bio and Medical Technology Development Program of the National Research Foundation(NRF)funded by the Korean government(MSIT)(No.NRF-2019M3E5D1A02069073)In addition,this work was supported by the Soonchunhyang University Research Fund.
文摘Heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for both control plane(CP)and data plane(DP).Likewise,the heterogeneous 5th generation(5G)communication applications,including Mobile Broadband Communications(MBBC),massive Machine-Type Commutation(mMTC),and ultra-reliable low latency communications(URLLC),obligate to perform intelligent Quality-of-Service(QoS)Class Identifier(QCI),while the CP entities will be suffered from the complicated massive HIOT applications.Moreover,the existing management and orchestration(MANO)models are inappropriate for resource utilization and allocation in large-scale and complicated network environments.To cope with the issues mentioned above,this paper presents an adopted software-defined mobile edge computing(SDMEC)with a lightweight machine learning(ML)algorithm,namely support vector machine(SVM),to enable intelligent MANO for real-time and resource-constraints IoT applications which require lightweight computation models.Furthermore,the SVM algorithm plays an essential role in performing QCI classification.Moreover,the software-defined networking(SDN)controller allocates and configures priority resources according to the SVM classification outcomes.Thus,the complementary of SVM and SDMEC conducts intelligent resource MANO for massive QCI environments and meets the perspectives of mission-critical communication with resource constraint applications.Based on the E2E experimentation metrics,the proposed scheme shows remarkable outperformance in key performance indicator(KPI)QoS,including communication reliability,latency,and communication throughput over the various powerful reference methods.
