Software-Defined Mobility Management and Base Station Control for Green Cellular Networks

Abstract

Mobile communication systems have revolutionized in order to fulfill exponentially increasing data traffic volume due to the introduction of new devices such as smartphones and tablets and success of social networking services. Evolving cellular networks include emerging technologies such as Software-Defined Network (SDN) and Network Function Virtualization (NFV). SDN is an emerging network architecture that allows dynamic and flexible network operations with centralized controller. NFV addresses the problem of a large and increasing number of hardware appliances and focuses on optimizing the network services themselves. With SDN and NFV, cellular networks are able to provide more flexible and agile management that can better align and support the mobile users. In this dissertation, we address location management and handover to reduce data traffic toward the core network and to reduce energy consumption. Location management is a key control task in cellular network operations. We propose and develop an efficient group location management scheme as a virtualized network function for group cellular applications. The performance improvement is mainly achieved by the virtualized and separate group management architecture and an efficient dynamic group profiling algorithm. We conduct theoretical analyses of our scheme for signaling costs and performance gains under diverse traffic conditions. Furthermore, we carry out extensive evaluations using both real traces and synthetic human mobility data, and we validate the efficiency of the proposed scheme in both location updates and paging. Moreover, in order to tackle the issues of mounting deployments and large energy consumption of base stations, it is integral to devise schemes to improve energy efficiency in cellular networks. We propose a virtualized network function of cell management on an SDN architecture. We develop a cell management algorithm on the architecture that can effectively control the sleep and awake modes of base stations and perform handover operations in a cellular network. It provides significant benefits over current cellular networks that suffer from inflexible management and complex control. Our extensive trace-driven evaluation results show that the proposed control architecture and the cell management algorithm achieve significant energy savings, and incur less control message exchanges, more cells in a sleep mode for longer durations, and less cell status changes than existing energy saving approaches for cellular networks.