scholarly journals Decentralized Probabilistic Frequency-Block Activation Control Method of Base Stations for Inter-cell Interference Coordination and Traffic Load Balancing

2020 ◽  
Vol E103.B (10) ◽  
pp. 1172-1181
Author(s):  
Fumiya ISHIKAWA ◽  
Keiki SHIMADA ◽  
Yoshihisa KISHIYAMA ◽  
Kenichi HIGUCHI
Keyword(s):  
Load Balancing ◽  
Control Method ◽  
Base Stations ◽  
Traffic Load ◽  
Interference Coordination ◽  
Inter Cell Interference ◽  
Traffic Load Balancing

scholarly journals Traffic Load Balancing Using Software Defined Networking (SDN) Controller as Virtualized Network Function

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 46646-46658 ◽  
Author(s):  
Sikandar Ejaz ◽  
Zeshan Iqbal ◽  
Peer Azmat Shah ◽  
Bilal Haider Bukhari ◽  
Armughan Ali ◽  
...  
Keyword(s):  
Load Balancing ◽  
Software Defined Networking ◽  
Traffic Load ◽  
Network Function ◽  
Sdn Controller ◽  
Traffic Load Balancing

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 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 Novel Multi-Level Dynamic Traffic Load-Balancing Protocol for Data Center

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 145 ◽  
Author(s):  
Sheeba Memon ◽  
Jiawei Huang ◽  
Hussain Saajid ◽  
Naadiya Khuda Bux ◽  
Arshad Saleem ◽  
...  
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
State Of The Art ◽  
Traffic Load ◽  
Parameter Setting ◽  
Dynamic Traffic ◽  
Typical Data ◽  
Fixed Parameter ◽  
Multi Level ◽  
Traffic Load Balancing

Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstances as well as the reduction of failures. However, under dynamic traffic, current load-balancing schemes use the fixed parameter setting, resulting in suboptimal performances. Therefore, we propose a multi-level dynamic traffic load-balancing (MDTLB) protocol, which uses an adaptive approach of parameter setting. The simulation results show that the MDTLB outperforms the state-of-the-art schemes in terms of both the flow completion time and throughput in typical data center applications.

scholarly journals Mobility Load Balancing in Cellular System with Multicriteria Handoff Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Solomon T. Girma ◽  
Abinet G. Abebe
Keyword(s):  
Load Balancing ◽  
Propagation Model ◽  
Traffic Load ◽  
Call Blocking ◽  
Coverage Area ◽  
Low Load ◽  
Load Balancing Algorithm ◽  
Cover Up ◽  
Highly Loaded ◽  
Traffic Load Balancing

Efficient traffic load balancing algorithm is very important to serve more mobile users in the cellular networks. This paper is based on mobility load balancing handoff algorithm using fuzzy logic. The rank of the serving and the neighboring Base Transceiver Stations (BTSs) are calculated every half second with the help of measurement report from the two-ray propagation model. This algorithm is able to balance load of the BTS by handing off some ongoing calls on BTS’s edge of highly loaded BTS to move to overlapping underloaded BTS, such that the coverage area of loaded BTS virtually shrunk towards BTS center of a loaded sector. In case of low load scenarios, the coverage area of a BTS is presumed to be virtually widened to cover up to the partial serving area of neighboring BTS. This helps a highly loaded neighboring BTS or failed BTS due to power or transmission. Simulation shows that new call blocking and handoff blocking using the proposed algorithm are enhanced notably.

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