The convergence of computation and communication at network edges plays a significant role in coping with computation-intensive and delay-critical tasks.During the stage of network planning,the resource provisioning p...The convergence of computation and communication at network edges plays a significant role in coping with computation-intensive and delay-critical tasks.During the stage of network planning,the resource provisioning problem for edge nodes has to be investigated to provide prior information for future system configurations.This work focuses on how to quantify the computation capabilities of access points at network edges when provisioning resources of computation and communication in multi-cell wireless networks.The problem is formulated as a discrete and non-convex minimization problem,where practical constraints including delay requirements,the inter-cell interference,and resource allocation strategies are considered.An iterative algorithm is also developed based on decomposition theory and fractional programming to solve this problem.The analysis shows that the necessary computation capability needed for certain delay guarantee depends on resource allocation strategies for delay-critical tasks.For delay-tolerant tasks,it can be approximately estimated by a derived lower bound which ignores the scheduling strategy.The efficiency of the proposed algorithm is demonstrated using numerical results.展开更多
A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobilit...A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobility brings significant challenges to the service provisioning for mobile users,especially to delay-sensitive mobile applications.With the objective to maximize a profit,which positively associates with the overall admitted traffic served by the local edge cloud,and negatively associates with the access delay as well as virtual machine migration delay,we study a fundamental problem in this paper:how to update the service provisioning solution for a given group of mobile users.Such a profit-maximization problem is formulated as a nonlinear integer linear programming and linearized by absolute value manipulation techniques.Then,we propose a framework of heuristic algorithms to solve this Nondeterministic Polynomial(NP)-hard problem.The numerical simulation results demonstrate the efficiency of the devised algorithms.Some useful summaries are concluded via the analysis of evaluation results.展开更多
基金Supported by the Shanghai Sailing Program(No.18YF1427900)the National Natural Science Foundation of China(No.61471347)the Shanghai Pujiang Program(No.2020PJD081).
文摘The convergence of computation and communication at network edges plays a significant role in coping with computation-intensive and delay-critical tasks.During the stage of network planning,the resource provisioning problem for edge nodes has to be investigated to provide prior information for future system configurations.This work focuses on how to quantify the computation capabilities of access points at network edges when provisioning resources of computation and communication in multi-cell wireless networks.The problem is formulated as a discrete and non-convex minimization problem,where practical constraints including delay requirements,the inter-cell interference,and resource allocation strategies are considered.An iterative algorithm is also developed based on decomposition theory and fractional programming to solve this problem.The analysis shows that the necessary computation capability needed for certain delay guarantee depends on resource allocation strategies for delay-critical tasks.For delay-tolerant tasks,it can be approximately estimated by a derived lower bound which ignores the scheduling strategy.The efficiency of the proposed algorithm is demonstrated using numerical results.
基金partially supported by JSPS KAKENHI under Grant Number JP16J07062
文摘A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobility brings significant challenges to the service provisioning for mobile users,especially to delay-sensitive mobile applications.With the objective to maximize a profit,which positively associates with the overall admitted traffic served by the local edge cloud,and negatively associates with the access delay as well as virtual machine migration delay,we study a fundamental problem in this paper:how to update the service provisioning solution for a given group of mobile users.Such a profit-maximization problem is formulated as a nonlinear integer linear programming and linearized by absolute value manipulation techniques.Then,we propose a framework of heuristic algorithms to solve this Nondeterministic Polynomial(NP)-hard problem.The numerical simulation results demonstrate the efficiency of the devised algorithms.Some useful summaries are concluded via the analysis of evaluation results.
