Energy aware optimal service control of base stations in wireless downlink systems

2015 ◽  
Author(s):  
Yuan Gao ◽  
Yi Li ◽  
Peng Xue ◽  
Quan Zhou ◽  
Bo Zhou ◽  
...  
Keyword(s):  
Base Stations ◽  
Energy Aware ◽  
Optimal Service ◽  
Service Control

scholarly journals Online Supervisory Control and Resource Management for Energy Harvesting BS Sites Empowered with Computation Capabilities

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Thembelihle Dlamini ◽  
Ángel Fernández Gambín ◽  
Daniele Munaretto ◽  
Michele Rossi
Keyword(s):  
Energy Harvesting ◽  
Energy Savings ◽  
Virtual Machines ◽  
Mobile Network ◽  
Base Stations ◽  
Traffic Load ◽  
Short Term ◽  
Energy Aware ◽  
Multi Access

The convergence of communication and computing has led to the emergence of multi-access edge computing (MEC), where computing resources (supported by virtual machines (VMs)) are distributed at the edge of the mobile network (MN), i.e., in base stations (BSs), with the aim of ensuring reliable and ultra-low latency services. Moreover, BSs equipped with energy harvesting (EH) systems can decrease the amount of energy drained from the power grid resulting into energetically self-sufficient MNs. The combination of these paradigms is considered here. Specifically, we propose an online optimization algorithm, called Energy Aware and Adaptive Management (ENAAM), based on foresighted control policies exploiting (short-term) traffic load and harvested energy forecasts, where BSs and VMs are dynamically switched on/off towards energy savings and Quality of Service (QoS) provisioning. Our numerical results reveal that ENAAM achieves energy savings with respect to the case where no energy management is applied, ranging from 57% to 69%. Moreover, the extension of ENAAM within a cluster of BSs provides a further gain ranging from 9% to 16% in energy savings with respect to the optimization performed in isolation for each BS.

Congestion Avoidance and Delay Minimization in Energy Aware Routing of Dynamic ieee 802.11s WMN

2020 ◽  
pp. 164-193
Author(s):  
S.P. Shiva Prakash ◽  
T.N. Nagabhushan ◽  
Kirill Krinkin
Keyword(s):  
Mesh Networks ◽  
Cluster Head ◽  
Base Stations ◽  
Cluster Head Selection ◽  
Slot Allocation ◽  
Energy Aware ◽  
Available Energy ◽  
Proposed Model ◽  
Slot Scheduling ◽  
Link Duration

Minimization of delay in collecting the data at any base stations is one of the major concerns in cluster based Wireless Mesh Networks. several researches have proposed algorithms to control congestion considering static nature of a node. Mobility of a node results in high congestion due to frequent link breakages and high energy consumption due to re-establishment of route during routing process. Hence, the authors consider dynamic nodes with single hop inside the static cluster. The proposed model includes four modules namely, Cluster head selection, slot allocation, slot scheduling and data collection process. the cluster head selection is based on the maximum energy, number of links and link duration. Slot allocation is based on the available energy () and the required energy (). Slot scheduling is carried out based on the link duration. Data at the base station will be collected as they are scheduled. Model is tested using Network Simulator-3 (NS3) and results indicate that the proposed model achieves least delay besides reducing the congestion compared to the existing methods.

Energy-Aware Dynamic Sectorization of Base Stations in Multi-Cell OFDMA Networks

2013 ◽  
Vol 2 (6) ◽  
pp. 587-590 ◽  
Author(s):  
Md. Farhad Hossain ◽  
Kumudu S. Munasinghe ◽  
Abbas Jamalipour
Keyword(s):  
Base Stations ◽  
Energy Aware ◽  
Ofdma Networks

Energy-Aware Network Control Approaches

2017 ◽  
pp. 148-170
Keyword(s):  
Cellular Networks ◽  
Network Control ◽  
Base Stations ◽  
Alternative Methods ◽  
Energy Aware ◽  
Carbon Footprints ◽  
Power Battery ◽  
Wireless Device ◽  
Harvesting Techniques ◽  
Key Techniques

Energy is considered as valuable resource for loT network, because the devices used for loT applications are low power-battery operated nodes. In some applications the devices are placed in remote area, when battery of the device would drain out its power, it is difficult to replace the battery. Radio Frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to overcome the barriers that prevent the real world wireless device deployment. Meanwhile, for cellular networks, the base stations (BSs) account for more than 50 percent of the energy consumption of the networks. Therefore, reducing the power consumption of BSs is crucial to energy efficient wireless networks. It can also subsequently reduce the carbon footprints. In this chapter, we focus our attention on the energy-aware IoT control algorithms. For the next-generation IoT systems, they will be key techniques.

Optimal service control of a station connected with two parallel substations

1993 ◽  
Vol 38 (10) ◽  
pp. 1567-1572 ◽  
Author(s):  
N. Miyoshi ◽  
M. Ohnishi ◽  
N. Okino
Keyword(s):  
Optimal Service ◽  
Service Control

Energy-constrained transmission on hybrid communication networks

2018 ◽  
Vol 29 (11) ◽  
pp. 1850114
Author(s):  
Xiaopeng Ji ◽  
Cunlai Pu ◽  
Jie Li
Keyword(s):  
Communication Networks ◽  
Network Lifetime ◽  
Traffic Congestion ◽  
Communication Systems ◽  
Base Stations ◽  
Selection Strategy ◽  
Energy Aware ◽  
Gateway Selection ◽  
Selection Parameter ◽  
Energy Constrained

The real communication systems usually consist of different types of agents, e.g. computers, routers, base stations and mobile phones, forming various hybrid communication networks. Furthermore, in many cases, those agents are energy-constrained resulting in a limited lifetime of the communication networks. We proposed a hybrid communication network model composed of energy-constrained base stations and mobile users, and further gave a novel energy-aware gateway selection strategy to balance the energy consumption of base stations. We developed a new metric of nodes, called node forwarding strength, which measures the intrinsic forwarding capability of nodes and is basically dependent on the network structure and routing protocol. Based on this metric, we further derived the critical packet generation rate of traffic congestion, average number of transmission hops, and network lifetime. By investigating the influence of factors on the network lifetime, we obtained the optimal user moving speed and gateway selection parameter corresponding to the maximum network lifetime. Our work may provide some clues for the designing and optimization of real hybrid communication systems.

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