scholarly journals Latency optimization for D2D-enabled parallel mobile edge computing in cellular networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yan Cai ◽  
Liang Ran ◽  
Jun Zhang ◽  
Hongbo Zhu
Keyword(s):  
Cellular Networks ◽  
Optimal Solution ◽  
Vital Role ◽  
Base Stations ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
System Delay ◽  
Simulation Results ◽  
And Task ◽  
Parallel Communication

AbstractEdge offloading, including offloading to edge base stations (BS) via cellular links and to idle mobile users (MUs) via device-to-device (D2D) links, has played a vital role in achieving ultra-low latency characteristics in 5G wireless networks. This paper studies an offloading method of parallel communication and computation to minimize the delay in multi-user systems. Three different scenarios are explored, i.e., full offloading, partial offloading, and D2D-enabled partial offloading. In the full offloading scenario, we find a serving order for the MUs. Then, we jointly optimize the serving order and task segment in the partial offloading scenario. For the D2D-enabled partial offloading scenario, we decompose the problem into two subproblems and then find the sub-optimal solution based on the results of the two subproblems. Finally, the simulation results demonstrate that the offloading method of parallel communication and computing can significantly reduce the system delay, and the D2D-enabled partial offloading can further reduce the latency.

scholarly journals Latency Optimization for D2D-Enabled Parallel Mobile Edge Computing in Cellular Networks

2020 ◽  
Author(s):  
Liang Ran ◽  
Yan Cai ◽  
Jun Zhang ◽  
Hongbo Zhu
Keyword(s):  
Cellular Networks ◽  
Optimal Solution ◽  
Vital Role ◽  
Base Stations ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
System Delay ◽  
Simulation Results ◽  
And Task ◽  
Parallel Communication

Abstract Edge offloading, including offloading to edge base stations (BS) via cellular links and to idle mobile users (MUs) via device-to-device (D2D) links, has played a vital role in achieving ultra-low latency characteristics in 5G wireless networks. This paper studies an offloading method of parallel communication and computation to minimize the delay in multi-user systems. Three different scenarios are explored, i.e., full offloading, partial offloading, and D2D-enabled partial offloading. In the full offloading scenario, we find a serving order for the MUs. Then, we jointly optimize the serving order and task segment in the partial offloading scenario. For the D2D-enabled partial offloading scenario, we decompose the problem into two subproblems and then find the optimal solution based on the results of the two subproblems. Finally, the simulation results demonstrate that the offloading method of parallel communication and computing can significantly reduce the system delay, and the D2D-enabled partial offloading can further reduce the latency.

scholarly journals Latency Optimization for D2D-Enabled Parallel Mobile Edge Computing in Cellular Networks

2021 ◽  
Author(s):  
Yan Cai ◽  
Liang Ran ◽  
Jun Zhang ◽  
Hongbo Zhu
Keyword(s):  
Cellular Networks ◽  
Optimal Solution ◽  
Vital Role ◽  
Base Stations ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
System Delay ◽  
Simulation Results ◽  
And Task ◽  
Parallel Communication

Abstract Edge offloading, including offloading to edge base stations (BS) via cellular links and to idle mobile users (MUs) via device-to-device (D2D) links, has played a vital role in achieving ultra-low latency characteristics in 5G wireless networks. This paper studies an offloading method of parallel communication and computation to minimize the delay in multi-user systems. Three different scenarios are explored, i.e., full offloading, partial offloading, and D2D-enabled partial offloading. In the full offloading scenario, we find a serving order for the MUs. Then, we jointly optimize the serving order and task segment in the partial offloading scenario. For the D2D-enabled partial offloading scenario, we decompose the problem into two subproblems and then find the optimal solution based on the results of the two subproblems. Finally, the simulation results demonstrate that the offloading method of parallel communication and computing can significantly reduce the system delay, and the D2D-enabled partial offloading can further reduce the latency.

scholarly journals Adaptive offloading in mobile-edge computing for ultra-dense cellular networks based on genetic algorithm

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhuofan Liao ◽  
Jingsheng Peng ◽  
Bing Xiong ◽  
Jiawei Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Cellular Networks ◽  
Physical Distance ◽  
Edge Computing ◽  
Base Stations ◽  
Mobile Edge Computing ◽  
Total Energy Consumption ◽  
Average Delay ◽  
Server Selection

AbstractWith the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

scholarly journals Optimal Topology Formation and Adaptation of Integrated Access and Backhaul Networks

2021 ◽  
Vol 1 ◽  
Author(s):  
Meryem Simsek ◽  
Murali Narasimha ◽  
Oner Orhan ◽  
Hosein Nikopour ◽  
Wei Mao ◽  
...  
Keyword(s):  
Cellular Networks ◽  
High Speed ◽  
Random Sequence ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Network Capacity ◽  
Base Stations ◽  
Optimal Topology ◽  
Wireless Backhaul ◽  
Topology Formation

With the increasing densification of cellular networks, it has become exceedingly difficult to provide traditional fiber backhaul access to each cell site, which is especially true for small cell base stations (SBSs). The increasing maturity of millimeter wave (mmWave) communication coupled with multiple-input-multiple-output (MIMO) and beamforming technologies has opened up the possibility of providing high-speed wireless backhaul to such cell sites. The third-generation partnership project (3GPP) is defining an integrated access and backhaul (IAB) architecture for the fifth-generation (5G) cellular networks, in which the same infrastructure and spectral resources are used for both the access and the backhaul. In IAB networks, SBSs, so-called IAB nodes, act either as relay nodes carrying the traffic through multiple hops from a macrocell to an end user and vice versa or as access points to serve user equipments (UEs) in their proximity. To this end, the topology of such IAB networks is essential to enable efficient traffic flow and minimize congestion or increase robustness to backhaul link failure. In this paper, we propose a topology formation algorithm together with methodologies to implement it in real networks and compare it with a standard random sequence approach as well as with an optimal topology obtained using dynamic programming. Our simulation results demonstrate that the proposed algorithm outperforms the random sequence approach by 26% on average in terms of lower bound of the network capacity and is up to 99.7% close to the optimal solution, while being significantly less complex.

scholarly journals Optimization Strategy of Task Offloading with Wireless and Computing Resource Management in Mobile Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xintao Wu ◽  
Jie Gan ◽  
Shiyong Chen ◽  
Xu Zhao ◽  
Yucheng Wu
Keyword(s):  
Resource Management ◽  
Optimal Solution ◽  
Edge Computing ◽  
Base Stations ◽  
Mobile Edge Computing ◽  
Optimization Strategy ◽  
Resource Allocation Algorithm ◽  
Computing Resource ◽  
Task Offloading

Mobile edge computing (MEC) provides user equipment (UE) with computing capability through wireless networks to improve the quality of experience (QoE). The scenario with multiple base stations and multiple mobile users is modeled and analyzed. The optimization strategy of task offloading with wireless and computing resource management (TOWCRM) in mobile edge computing is considered. A resource allocation algorithm based on an improved graph coloring method is used to allocate wireless resource blocks (RBs). The optimal solution of computing resource is obtained by using KKT conditions. To improve the system utility, a semi-distributed TOWCRM strategy is proposed to obtain the task offloading decision. Theoretical simulations under different system parameters are executed, and the proposed semi-distributed TOWCRM strategy can be completed with finite iterations. Simulation results have verified the effectiveness of the proposed algorithm.

scholarly journals Distributed energy-efficient and secure offloading in air-to-ground MEC networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wanning Liu ◽  
Yitao Xu ◽  
Ducheng Wu ◽  
Haichao Wang ◽  
Xueqiang Zheng ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Mobile Edge Computing ◽  
Distributed Energy ◽  
Integer Nonlinear Programming ◽  
Minlp Problem ◽  
System Energy ◽  
Simulation Results

AbstractThis paper mainly investigates the energy-efficient and secure offloading problem in air-to-ground Mobile Edge Computing (MEC) networks. The proposed efficient offloading mechanism is as per the requirements of the heterogeneous tasks of ground users. Further, the optimizing offloading rate, offloading object, and channel access jointly formulate system energy consumption and eavesdropping rate minimization. A distributed two-stage offloading scheme is proposed for achieving the sub-optimal solution for the Mixed-integer Nonlinear Programming (MINLP) problem. Finally, simulation results demonstrate that the proposed scheme is superior to several benchmark schemes.

QoS aware Multi-Path Routing using Link Scheduling Algorithm

2019 ◽  
Vol 09 ◽  
Author(s):  
Satyasrikanth Palle ◽  
Shivashankar
Keyword(s):  
Cellular Networks ◽  
Scheduling Algorithm ◽  
Research Work ◽  
Scheduling Algorithms ◽  
Turnaround Time ◽  
Link Scheduling ◽  
Spatial Reuse ◽  
Mobile Cellular ◽  
Simulation Results ◽  
End To End

Objective: The demand for Cellular based multimedia services is growing day by day, in order to fulfill such demand the present day cellular networks needs to be upgraded to support excessive capacity calls along with high data accessibility. Analysis of traffic and huge network size could become very challenging issue for the network operators for scheduling the available bandwidth between different users. In the proposed work a novel QoS Aware Multi Path scheduling algorithm for smooth CAC in wireless mobile networks. The performance of the proposed algorithm is assessed and compared with existing scheduling algorithms. The simulation results show that the proposed algorithm outperforms existing CAC algorithms in terms of throughput and delay. The CAC algorithm with scheduling increases end-to-end throughput and decreases end-to-end delay. Methods: The key idea to implement the proposed research work is to adopt spatial reuse concept of wireless sensor networks to mobile cellular networks. Spatial reusability enhances channel reuse when the node pairs are far away and distant. When Src and node b are communicating with each other, the other nodes in the discovered path should be idle without utilizing the channel. Instead the other nodes are able to communicate parallelly the end-to-end throughput can be improved with acceptable delay. Incorporating link scheduling algorithms to this key concept further enhances the end-to-end throughput with in the turnaround time. So, in this research work we have applied spatial reuse concept along with link scheduling algorithm to enhance end-to-end throughput with in turnaround time. The proposed algorithm not only ensures that a connection gets the required bandwidth at each mobile node on its way by scheduling required slots to meet the QoS requirements. By considering the bandwidth requirement of the mobile connections, the CAC module at the BS not only considers the bandwidth requirement but also conforming the constrains of system dealy and jitter are met. Result: To verify the feasibility and effectiveness of our proposed work, with respect to scheduling the simulation results clearly shows the throughput improvement with Call Admission Control. The number of dropped calls is significantly less and successful calls are more with CAC. The percentage of dropped calls is reduced by 9 % and successful calls are improved by 91%. The simulation is also conducted on time constraint and ratio of dropped calls are shown. The total time taken to forward the packets and the ration of dropped calls is less when compared to non CAC. On a whole the CAC with scheduling algorithms out performs existing scheduling algorithms. Conclusion: In this research work we have proposed a novel QoS aware scheduling algorithm that provides QoS in Wireless Cellular Networks using Call Admission Control (CAC). The simulation results show that the end-to-end throughput has been increased by 91% when CAC is used. The proposed algorithm is also compared with existing link scheduling algorithms. The results reveal that CAC with scheduling algorithm can be used in Mobile Cellular Networks in order to reduce packet drop ratio. The algorithm is also used to send the packets within acceptable delay.

scholarly journals Machine Learning for the Dynamic Positioning of UAVs for Extended Connectivity

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4618
Author(s):  
Francisco Oliveira ◽  
Miguel Luís ◽  
Susana Sargento
Keyword(s):  
Machine Learning ◽  
Cellular Networks ◽  
Real Data ◽  
Emerging Technology ◽  
Machine Learning Algorithms ◽  
Base Stations ◽  
Aerial Vehicle ◽  
Positioning Algorithm ◽  
The Military ◽  
Better Than

Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV positioning algorithm responsible for determining suitable positions for the UAVs, with the objective of a more balanced redistribution of traffic, to avoid saturated base stations and decrease the number of users without a connection. The tests performed with real data of user connections through base stations show that, in less restrictive network conditions, the algorithm to dynamically place the UAVs performs significantly better than in more restrictive conditions, reducing significantly the number of users without a connection. We also conclude that the accuracy of the prediction is a very important factor, not only in the reduction of users without a connection, but also on the number of UAVs deployed.

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