04286nam 22006015 450 991025424250332120250609110101.03-319-32721-610.1007/978-3-319-32721-1(CKB)3710000000718291(EBL)4537348(DE-He213)978-3-319-32721-1(MiAaPQ)EBC4571510(PPN)19438134X(MiAaPQ)EBC4537348(EXLCZ)99371000000071829120160601d2016 u| 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierWireless Traffic Steering For Green Cellular Networks /by Shan Zhang, Ning Zhang, Sheng Zhou, Zhisheng Niu, Xuemin (Sherman) Shen1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (136 p.)Description based upon print version of record.3-319-32719-4 Includes bibliographical references at the end of each chapters.Introduction -- Literature Review on Green Communications -- Dynamic Network Planning with Intra-Tier Traffic Steering -- Dynamic Network Planning with Inter-Tier Traffic Steering -- Inter-Tier Traffic Steering with Renewable Energy Harvesting -- Concluding Remarks.This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking.Electrical engineeringRenewable energy sourcesComputer networksCommunications Engineering, Networkshttps://scigraph.springernature.com/ontologies/product-market-codes/T24035Renewable and Green Energyhttps://scigraph.springernature.com/ontologies/product-market-codes/111000Computer Communication Networkshttps://scigraph.springernature.com/ontologies/product-market-codes/I13022Electrical engineering.Renewable energy sources.Computer networks.Communications Engineering, Networks.Renewable and Green Energy.Computer Communication Networks.620Zhang Shanauthttp://id.loc.gov/vocabulary/relators/aut1062324Zhang Ningauthttp://id.loc.gov/vocabulary/relators/autZhou Shengauthttp://id.loc.gov/vocabulary/relators/autNiu Zhishengauthttp://id.loc.gov/vocabulary/relators/autShen Xuemin (Sherman)authttp://id.loc.gov/vocabulary/relators/autBOOK9910254242503321Wireless Traffic Steering For Green Cellular Networks2524393UNINA