8 research outputs found
On the Performance and Optimization for MEC Networks Using Uplink NOMA
In this paper, we investigate a non-orthogonal multiple access (NOMA) based
mobile edge computing (MEC) network, in which two users may partially offload
their respective tasks to a single MEC server through uplink NOMA. We propose a
new offloading scheme that can operate in three different modes, namely the
partial computation offloading, the complete local computation, and the
complete offloading. We further derive a closed-form expression of the
successful computation probability for the proposed scheme. As part of the
proposed offloading scheme, we formulate a problem to maximize the successful
computation probability by jointly optimizing the time for offloading, the
power allocation of the two users and the offloading ratios which decide how
many tasks should be offloaded to the MEC server. We obtain the optimal
solutions in the closed forms. Simulation results show that our proposed scheme
can achieve the highest successful computation probability than the existing
schemes.Comment: This paper has been accepted by IEEE ICC Workshop 201
Efficient Mobile Edge Computing for Mobile Internet of Thing in 5G Networks
We study the off-line efficient mobile edge computing (EMEC) problem for a joint computing to process a task both locally and remotely with the objective of minimizing the finishing time. When computing remotely, the time will include the communication and computing time. We first describe the time model, formulate EMEC, prove NP-completeness of EMEC, and show the lower bound. We then provide an integer linear programming (ILP) based algorithm to achieve the optimal solution and give results for small-scale cases. A fully polynomial-time approximation scheme (FPTAS), named Approximation Partition (AP), is provided through converting ILP to the subset sum problem. Numerical results show that both the total data length and the movement have great impact on the time for mobile edge computing. Numerical results also demonstrate that our AP algorithm obtain the finishing time, which is close to the optimal solution
Energy Efficient UAV Flight Path Model for Cluster Head Selection in Next‐Generation Wireless Sensor Networks
Abstract: Please refer to full text to view abstrac