scholarly journals Optimal User Association Strategy for Large-Scale IoT Sensor Networks with Mobility on Cloud RANs

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4415 ◽  
Author(s):  
Taewoon Kim ◽  
Chanjun Chun ◽  
Wooyeol Choi
Keyword(s):  
Load Balancing ◽  
Large Scale ◽  
Mobile Internet ◽  
Base Stations ◽  
Traffic Load ◽  
User Association ◽  
Network Simulator ◽  
Traffic Loads ◽  
Association Strategy ◽  
Radio Access

In networking systems such as cloud radio access networks (C-RAN) where users receive the connection and data service from short-range, light-weight base stations (BSs), users’ mobility has a significant impact on their association with BSs. Although communicating with the closest BS may yield the most desirable channel conditions, such strategy can lead to certain BSs being over-populated while leaving remaining BSs under-utilized. In addition, mobile users may encounter frequent handovers, which imposes a non-negligible burden on BSs and users. To reduce the handover overhead while balancing the traffic loads between BSs, we propose an optimal user association strategy for a large-scale mobile Internet of Things (IoT) network operating on C-RAN. We begin with formulating an optimal user association scheme focusing only on the task of load balancing. Thereafter, we revise the formulation such that the number of handovers is minimized while keeping BSs well-balanced in terms of the traffic load. To evaluate the performance of the proposed scheme, we implement a discrete-time network simulator. The evaluation results show that the proposed optimal user association strategy can significantly reduce the number of handovers, while outperforming conventional association schemes in terms of load balancing.

scholarly journals Online Distributed User Association for Heterogeneous Radio Access Network

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1412 ◽  
Author(s):  
B. Bikram Kumar ◽  
Lokesh Sharma ◽  
Shih-Lin Wu
Keyword(s):  
Wireless Local Area Network ◽  
Local Area Network ◽  
Access Network ◽  
Future Generation ◽  
Visible Light Communication ◽  
Data Rate ◽  
Base Stations ◽  
User Association ◽  
Area Network ◽  
Radio Access

Future-generation radio access networks (RAN) are projected to fulfill the diverse requirements of user equipment (UE) by adopting a heterogeneous network (HetNet) environment. Necessary integration of different radio access technologies (RAT), such as 2G, 3G, 4G, wireless local area network (WLAN), and visible light communication (VLC) is inevitable. Moreover, UEs equipped with diverse requirements will be capable of accessing some or all the RATs. The complex HetNet environment with diverse requirements of UEs will present many challenges. The HetNet is likely to suffer severely from load imbalance among the base stations (BSs) from inheriting the traditional user association scheme such as max-SINR (signal-to-interference-plus-noise ratio)/max-RSSI (received signal strength indicator), unless some sophisticated schemes are invented. In this paper, a novel scheme is devised for a joint-user association for load balancing, where BSs are densely deployed and UEs typically have a certain degree of mobility. Unlike most of the present works, a dynamic network is considered where the position and channel condition of the UEs are not fixed. We develop two complex and distributed association schemes based on probability and d-choices, while carefully considering both loads of the BSs and SINR experienced by the UEs. Numerical results validate the efficiency of the proposed schemes by showing a received data-rate fairness among UEs and an improvement in the UE’s minimum received data rate.

scholarly journals LSTM-Based Traffic Load Balancing and Resource Allocation for an Edge System

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Thembelihle Dlamini ◽  
Sifiso Vilakati
Keyword(s):  
Resource Allocation ◽  
Load Balancing ◽  
Mobile Applications ◽  
Energy Savings ◽  
Tunable Laser ◽  
Green Energy ◽  
Base Stations ◽  
Traffic Load ◽  
Superior Performance ◽  
System Management

The massive deployment of small cell Base Stations (SBSs) empowered with computing capabilities presents one of the most ingenious solutions adopted for 5G cellular networks towards meeting the foreseen data explosion and the ultralow latency demanded by mobile applications. This empowerment of SBSs with Multi-access Edge Computing (MEC) has emerged as a tentative solution to overcome the latency demands and bandwidth consumption required by mobile applications at the network edge. The MEC paradigm offers a limited amount of resources to support computation, thus mandating the use of intelligence mechanisms for resource allocation. The use of green energy for powering the network apparatuses (e.g., Base Stations (BSs), MEC servers) has attracted attention towards minimizing the carbon footprint and network operational costs. However, due to their high intermittency and unpredictability, the adoption of learning methods is a requisite. Towards intelligent edge system management, this paper proposes a Green-based Edge Network Management (GENM) algorithm, which is an online edge system management algorithm for enabling green-based load balancing in BSs and energy savings within the MEC server. The main goal is to minimize the overall energy consumption and guarantee the Quality of Service (QoS) within the network. To achieve this, the GENM algorithm performs dynamic management of BSs, autoscaling and reconfiguration of the computing resources, and on/off switching of the fast tunable laser drivers coupled with location-aware traffic scheduling in the MEC server. The obtained simulation results validate our analysis and demonstrate the superior performance of GENM compared to a benchmark algorithm.

scholarly journals A Baseband Wireless Spectrum Hypervisor for Multiplexing Concurrent OFDM Signals

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1101
Author(s):  
Felipe A. P. de Figueiredo ◽  
Ruben Mennes ◽  
Irfan Jabandžić ◽  
Xianjun Jiao ◽  
Ingrid Moerman
Keyword(s):  
Radio Frequency ◽  
Mobile Networks ◽  
Spectral Efficiency ◽  
Base Stations ◽  
Traffic Load ◽  
Front End ◽  
Rf Front End ◽  
Radio Access ◽  
Wireless Spectrum ◽  
Arbitrary Frequency

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the current ones. This situation calls for novel ways to increase the spectral efficiency. Therefore, in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, i.e., the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The proposed architecture is a non-intrusive and highly optimized wireless hypervisor that multiplexes the signals of several different and concurrent multi-carrier-based radio access technologies with numerologies that are multiple integers of one another, which are also referred in our work as radio access technologies with correlated numerology. For example, the proposed architecture can multiplex the signals of several Wi-Fi access points, several LTE base stations, several WiMAX base stations, etc. As it able to multiplex the signals of radio access technologies with correlated numerology, it can, for instance, multiplex the signals of LTE, 5G-NR and NB-IoT base stations. It abstracts a radio frequency front-end into a configurable number of virtual RF front ends, making it possible for such different technologies to share the same RF front-end and consequently reduce the costs and increasing the spectral efficiency by employing densification, once several networks share the same infrastructure or by dynamically accessing free chunks of spectrum. Therefore, the main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

One QoS Routing Algorithm for Load Balancing in IP Backbone Networks: Design and Simulation

2013 ◽  
Vol 427-429 ◽  
pp. 2664-2667
Author(s):  
Zhi Qiang Cai ◽  
Rong Sheng Lv ◽  
Shi Wen Sun
Keyword(s):  
Load Balancing ◽  
Routing Algorithm ◽  
Qos Routing ◽  
Traffic Load ◽  
Network Simulator ◽  
Network Resources ◽  
Routing Problem ◽  
Backbone Networks ◽  
Qos Routing Algorithm

Quality of Service (QoS) routing is intent to find feasible routes according to QoS constraints and optimize utilization of whole network resources. In order to solve bandwidth-guaranteed QoS routing problem, a simple but effective routing algorithm based on precomputation scheme with load balancing consideration, is proposed. The algorithm is implemented and simulated using Network Simulator (NS2). Research results showed that the proposal can keep some links free from becoming bottlenecks earlier, avoid congestion caused by unbalanced traffic load distribution, and improve performance of IP backbone networks.

scholarly journals A Wireless Location System in LTE Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Qi Liu ◽  
Rongyi Hu ◽  
Shan Liu
Keyword(s):  
Rapid Development ◽  
Access Network ◽  
Mobile Internet ◽  
Base Stations ◽  
Lte Networks ◽  
Location Service ◽  
Location System ◽  
Radio Access ◽  
Processing Resources ◽  
Location Measurement

Personal location technologies are becoming important with the rapid development of Mobile Internet services. In traditional cellular networks, the key problems of user location technologies are high-precision synchronization among different base stations, inflexible processing resources, and low accuracy positioning, especially for indoor environment. In this paper, a new LTE location system in Centralized Radio Access Network (C-RAN) is proposed, which makes channel and location measurement more available, allocation of baseband processing resources more flexible, and location service capability opening. The location system contains more than two antenna clusters, and each of them gets time-difference-of-arrival (TDOA) of sounding reference signals (SRSs) from different antennas. Then, based on data provided by location measurement units (LMUs), the location information server calculates TDOAs and derives the users’ position. Furthermore, a new location algorithm is raised which can achieve distributed antennas collaboration and centralized location computing. And an improved optimized algorithm with the best TDOA selection is proposed. Finally, simulations are given out to verify the efficiency of the proposed algorithm in this LTE location system.

scholarly journals Load Balancing As A Service In Openstack-Liberty

2019 ◽  
Author(s):  
Girish L
Keyword(s):  
Load Balancing ◽  
Dynamic Load ◽  
Virtual Machines ◽  
Dynamic Load Balancing ◽  
Traffic Load ◽  
The Internet ◽  
Private Institution ◽  
On Demand ◽  
Traffic Loads ◽  
Traffic Load Balancing

Cloud computing is a technology which provides computing resource on demand over the internet as a service. To meet this, many opensource cloud operating system are provided for the tenants, in order to get useful services from the cloud. There are many opensource cloud OS like AWS, Open Shift, HP, OpenStack etc. Out of all these OpenStack comes with free of cost and it has got a huge community. It can be installed and deploy in private institution or company with free of cost. This paper provides a model and techniques for the dynamic load balancing in OpenStack for managing the traffic/loads among the Virtual Machines. The main purpose is to increase the utilization of computing resources and minimize the traffic. Load Balancing as a Service is one of the main service in OpenStack Networking. OpenStack is an opensource platform which provides Infrastructure as a Service. It allows users/tenants tocreate their own private clouds and to deploy Virtual Machines, which manages different workloads. In this paper, we provide an architecture of openstack LBaaS, for dynamic load balancing in open stack cloud deployment.

scholarly journals Joint Optical and Wireless Resource Allocation for Cooperative Transmission in C-RAN

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 217
Author(s):  
Peng Yang ◽  
Liao Chen ◽  
Hong Zhang ◽  
Jing Yang ◽  
Ruyan Wang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Wavelength Division Multiplexing ◽  
Optical Network ◽  
Cooperative Transmission ◽  
Passive Optical Network ◽  
Traffic Load ◽  
User Association ◽  
Wavelength Division ◽  
Redundant Data ◽  
Radio Access

Cooperative multipoint transmission (CoMP) is one of the most promising paradigms for mitigating interference in cloud radio access networks (C-RAN). It allows multiple remote radio units (RRUs) to transmit the same data flow to a user to further improve the signal quality. However, CoMP may incur redundant data transmission over fronthaul network in the C-RAN. In a C-RAN employing CoMP, a key problem is how to coordinate heterogeneous resource allocation to maximize the cooperation gain while reducing the fronthaul load. In this paper, the cooperation transmission based on a multi-dimensional resource schedule (MRSCT) scheme, jointly considering user association, spectrum resource allocation, and wavelength resource allocation, is firstly envisioned in the underlying C-RAN integrating time and wavelength division multiplexing passive optical network (TWDM-PON) to maximize fronthaul efficiency. Then a two-timescale resource allocation framework including two sub-approaches is established. More specially, the first sub-approach mainly focuses on exploiting reinforcement learning to obtain a wavelength resource allocation strategy to relieve fronthaul traffic load. Moreover, the second sub-approach adopts the overlapping coalition formation game to establish a user-centric cooperative set, where spectrum resources are dynamically allocated to further alleviate the interference issue. The theoretical analysis and simulation results validate the performance of MRSCT scheme on the fronthaul efficiency, user experience, and system service capability.

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