dc.contributor |
Ph.D. Program in Computer Engineering. |
|
dc.contributor.advisor |
Ersoy, Cem. |
|
dc.contributor.advisor |
İncel, Özlem Durmaz. |
|
dc.contributor.author |
Yiğitel, M. Aykut. |
|
dc.date.accessioned |
2023-03-16T10:13:47Z |
|
dc.date.available |
2023-03-16T10:13:47Z |
|
dc.date.issued |
2016. |
|
dc.identifier.other |
CMPE 2016 Y54 PhD |
|
dc.identifier.uri |
http://digitalarchive.boun.edu.tr/handle/123456789/12611 |
|
dc.description.abstract |
Increasing energy costs drive the telecommunication service providers to become highly interested in energy efficient operations. The exponential growth in mobile data exchange which is further augmented by the rapid proliferation of smart phones increases the operational expenses of the cellular network operators significantly. Also, ecologists state that the primary triggering factor of the global warming is adding excessive amounts of greenhouse gases to the atmosphere and 72% of the totally emitted greenhouse gases is carbon dioxide (C02 ). Increasing environmental awareness combined with the high energy prices has driven the network operators to reduce their C02 footprint by adopting energy efficient green methods. In this thesis, our main focus is to save energy in three types of wireless cellular networks (i) Conventional Cellular Networks (ii) Packet-switched Cellular Networks and (iii) Next Generation Multi-tier Cellular Networks. \Ve formulate novel mathematical optimization problems for each of the listed cellular networks to find the best possible topology which minimizes the overall power consumption of the network while satisfying a certain quality of service level. Our decision variables in the optimization models are switching base stations on/off and adaptively adjusting their transmission power levels as well as deploying additional pico base stations as a remedy according to the present traffic conditions. Although the optimization tools provide the optimum solutions for smaller instances of the problem, we propose novel heuristics to solve large-scale realistic instances due to their prohibitive complexity. Results of extensive simulations, which are designed as close to real life conditions as possible, show that the proposed green methods help to maintain an energy-aware network and save significant amount of energy by adjusting the network topology to the current traffic conditions adaptively. |
|
dc.format.extent |
30 cm. |
|
dc.publisher |
Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016. |
|
dc.subject.lcsh |
Telecommunication -- Energy conservation. |
|
dc.subject.lcsh |
Computer networks -- Energy conservation. |
|
dc.subject.lcsh |
Green technology. |
|
dc.title |
Green networking: from conventional to next generation heterogeneous cellular networks |
|
dc.format.pages |
xx, 124 leaves ; |
|