A density-aware, energy- and spectrum efficient scheduling model for dynamic networks

Download

index.pdf

Date

2019

Author

Mollahasani, Shahra

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

137
views

66
downloads

Future mobile networks have to be densified by employing small cells to handle the upsurge in traffic load. Although the amount of energy each small cell consumes is low, the total energy consumption of a large-scale network may be enormous. To enhance the energy efficiency, we have to adapt the number of active base stations to the offered traffic load. Deactivating base stations may cause coverage holes, degrade the quality of service and throughput while redundant base stations waste energy. That is why we have to adapt the network to the effective density. In this thesis, we show that achieving an optimal solution for adapting density of base stations to the demand is NP-hard. We propose a solution that consists of two heuristic algorithms: a base station density adaptation algorithm and a cell-zooming algorithm that determines which base stations must be kept active and adapts transmit power of base stations to enhance throughput, energy and spectral efficiency. We employ multi-access edge clouds for taking a snapshot of the network state in nearly real-time and for collecting network telemetry over a large area. We show that the proposed algorithm conserves energy up to 12% while the spectral efficiency and network throughput can be enhanced up to 30% and 26% in comparison with recent works, respectively.

Subject Keywords

Mobile communication systems, Mobile communication systems Design., Keywords: 5G mobile networks, densification, density-aware networking, energyefficiency, green networks, multi-access edge cloud (MEC), self-organizing networks.

URI

http://etd.lib.metu.edu.tr/upload/12623580/index.pdf
https://hdl.handle.net/11511/43786

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Density-Aware, Energy- and Spectrum-Efficient Small Cell Scheduling Mollahasani, Shahram; Onur, Ertan (2019-01-01) Future mobile networks have to be densified by employing small cells to handle the upsurge in traffic load. Although the amount of energy each small cell consumes is low, the total energy consumption of a large-scale network may be enormous. To enhance energy efficiency, we have to adapt the number of active base stations to the offered traffic load. Deactivating base stations may cause coverage holes, degrade the quality of service and throughput while redundant base stations waste energy. That is why we h...
An Experimental Comparison of Messaging Protocols MQTT and COAP Çoban, Hasan Faruk; Betin Can, Aysu; Department of Information Systems (2017) As the attention towards to Internet of Things (IoT) increases recently, the need for the infrastructure that carries the communication between nodes, which have limited resources, also increases. The network beneath applications has direct effect on resilience of IoT environments. Due to the advances on mobile devices in terms of more powerful hardware, developers focused on mobile applications. However, solid network structures are needed for these applications. To match these needs several protocols are ...
Joint optimization of cell zooming, scheduling and user association Çalık, Mert; Onur, Ertan; Department of Computer Engineering (2018) Capacity can be increased by employing small cells in future mobile networks. When small cells are considered, a large number of base stations have to be deployed. This approach enlarges network infrastructures and increases the amount of energy consumption. Traffic demand in a mobile network is not fixed in time or space, and it cannot be accurately predicted in advance. Network functions such as base station scheduling, cell zooming or user-to-base-station association can be dynamically controlled to cons...
An Efficient graph-theoretical approach for interactive mobile image and video segmentation Şener, Ozan; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2013) Over the past few years, processing of visual information by mobile devices getting more affordable due to the advances in mobile technologies. Efficient and accurate segmentation of objects from an image or video leads many interesting multimedia applications. In this study, we address interactive image and video segmentation on mobile devices. We first propose a novel interaction methodology leading better satisfaction based on subjective user evaluation. Due to small screens of the mobile devices, error ...
A novel user activity prediction model for context aware computing systems Peker, Serhat; Koçyiğit, Altan; Department of Information Systems (2011) In the last decade, with the extensive use of mobile electronic and wireless communication devices, there is a growing need for context aware applications and many pervasive computing applications have become integral parts of our daily lives. Context aware recommender systems are one of the popular ones in this area. Such systems surround the users and integrate with the environment; hence, they are aware of the users' context and use that information to deliver personalized recommendations about everyday ...

Citation Formats

S. Mollahasani, “A density-aware, energy- and spectrum efficient scheduling model for dynamic networks,” Thesis (Ph.D.) -- Graduate School of Natural and Applied Sciences. Computer Engineering., Middle East Technical University, 2019.