In this paper, we employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices...In this paper, we employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices and the children number sequence of corresponding tree vertices. The proposed encoding scheme has the advantages of simplicity for encoding and decoding, ease for GA operations, and better equilibrium between exploration and exploitation. It is also adaptive in that, with few restrictions on the length of code, it can be freely lengthened or shortened according to the characteristics of the problem space. Furthermore, the encoding scheme is highly applicable to the degree-constrained minimum spanning tree problem because it also contains the degree information of each node. The simulation results demonstrate the higher performance of our algorithm, with fast convergence to the optima or sub-optima on various problem sizes. Comparing with the binary string encoding of vertices, when the problem size is large, our algorithm runs remarkably faster with comparable search capability. Key words distributed information retrieval - mobile agents - migration problem - genetic algorithms CLC number TP 301. 6 Foundation item: Supported by the National Natural Science Foundation of China (90104005), the Natural Science Foundation of Hubei Province and the Hong Kong Polytechnic University under the grant G-YD63Biography: He Yan-xiang (1952-), male, Professor, research direction: distributed and parallel processing, multi-agent systems, data mining and e-business.展开更多
Mobile agents are able to migrate among machines to achieve their tasks. This feature is attractive to design, implement, and maintain distributed systems because we can implement both client-side and server-side prog...Mobile agents are able to migrate among machines to achieve their tasks. This feature is attractive to design, implement, and maintain distributed systems because we can implement both client-side and server-side programming in one mobile agent. However, it involves the increase of data traffic for mobile agent migrations. In this paper, we propose program code caching to reduce the data traffic caused by mobile agent migrations. A mobile agent consists of many program codes that define a task executed in each machine they migrate; thus, the mobile agent migration involves the transfer of their program codes. Therefore, our method reduces the number of the transfer of program codes by using program code cache. We have implemented our method on a mobile agent framework called Maglog and conducted experiments on a meeting scheduling system.展开更多
Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability,availability,and ultra-low latency.The requirements of such ne...Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability,availability,and ultra-low latency.The requirements of such networks are the main challenges that can be handled using a range of recent technologies,including multi-access edge computing(MEC),artificial intelligence(AI),millimeterwave communications(mmWave),and software-defined networking.Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service(QoS).This article considers developing a complex MEC structure for fifth and sixth-generation(5G/6G)cellular networks.Furthermore,we propose a seamless migration technique for complex edge computing structures.The developed migration scheme enables services to adapt to the required load on the radio channels.The proposed algorithm is analyzed for various use cases,and a test bench has been developed to emulate the operator’s infrastructure.The obtained results are introduced and discussed.展开更多
Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy....Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.展开更多
Mobility is inherent in Internet,traditional message passing,RPC,or Remote Evaluation,can not meet more and more various mobility requirements. Mobile Agent implements computation migration,including data,code and con...Mobility is inherent in Internet,traditional message passing,RPC,or Remote Evaluation,can not meet more and more various mobility requirements. Mobile Agent implements computation migration,including data,code and control,is a good way to suit Internet. Migration mechanism is the key technology of mobile Agent. We discuss it from the perspective of both system programmer and application programmer and introduce migration mechanisms of some famous Java based mobile Agent system.At last,present the structured migration mechanism of self-designed mobile Agent system Mogent.展开更多
文摘In this paper, we employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices and the children number sequence of corresponding tree vertices. The proposed encoding scheme has the advantages of simplicity for encoding and decoding, ease for GA operations, and better equilibrium between exploration and exploitation. It is also adaptive in that, with few restrictions on the length of code, it can be freely lengthened or shortened according to the characteristics of the problem space. Furthermore, the encoding scheme is highly applicable to the degree-constrained minimum spanning tree problem because it also contains the degree information of each node. The simulation results demonstrate the higher performance of our algorithm, with fast convergence to the optima or sub-optima on various problem sizes. Comparing with the binary string encoding of vertices, when the problem size is large, our algorithm runs remarkably faster with comparable search capability. Key words distributed information retrieval - mobile agents - migration problem - genetic algorithms CLC number TP 301. 6 Foundation item: Supported by the National Natural Science Foundation of China (90104005), the Natural Science Foundation of Hubei Province and the Hong Kong Polytechnic University under the grant G-YD63Biography: He Yan-xiang (1952-), male, Professor, research direction: distributed and parallel processing, multi-agent systems, data mining and e-business.
文摘Mobile agents are able to migrate among machines to achieve their tasks. This feature is attractive to design, implement, and maintain distributed systems because we can implement both client-side and server-side programming in one mobile agent. However, it involves the increase of data traffic for mobile agent migrations. In this paper, we propose program code caching to reduce the data traffic caused by mobile agent migrations. A mobile agent consists of many program codes that define a task executed in each machine they migrate; thus, the mobile agent migration involves the transfer of their program codes. Therefore, our method reduces the number of the transfer of program codes by using program code cache. We have implemented our method on a mobile agent framework called Maglog and conducted experiments on a meeting scheduling system.
基金This work was supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R308),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability,availability,and ultra-low latency.The requirements of such networks are the main challenges that can be handled using a range of recent technologies,including multi-access edge computing(MEC),artificial intelligence(AI),millimeterwave communications(mmWave),and software-defined networking.Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service(QoS).This article considers developing a complex MEC structure for fifth and sixth-generation(5G/6G)cellular networks.Furthermore,we propose a seamless migration technique for complex edge computing structures.The developed migration scheme enables services to adapt to the required load on the radio channels.The proposed algorithm is analyzed for various use cases,and a test bench has been developed to emulate the operator’s infrastructure.The obtained results are introduced and discussed.
基金supported by Jilin Provincial Science and Technology Department Natural Science Foundation of China(20210101415JC)Jilin Provincial Science and Technology Department Free exploration research project of China(YDZJ202201ZYTS642).
文摘Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.
文摘Mobility is inherent in Internet,traditional message passing,RPC,or Remote Evaluation,can not meet more and more various mobility requirements. Mobile Agent implements computation migration,including data,code and control,is a good way to suit Internet. Migration mechanism is the key technology of mobile Agent. We discuss it from the perspective of both system programmer and application programmer and introduce migration mechanisms of some famous Java based mobile Agent system.At last,present the structured migration mechanism of self-designed mobile Agent system Mogent.
