Characterizing and Modeling Control-Plane Traffic for Mobile Core Network

In this paper, we first carry out to our knowledge the first in-depth characterization of control-plane traffic, using a real-world control-plane trace for 37,325 UEs sampled at a real-world LTE Mobile Core Network (MCN). Our analysis shows that control events exhibit significant diversity in device types and time-of-day among UEs. Second, we study whether traditional probability distributions that have been widely adopted for modeling Internet traffic can model the control-plane traffic originated from individual UEs. Our analysis shows that the inter-arrival time of the control events as well as the sojourn time in the UE states of EMM and ECM for the cellular network cannot be modeled as Poisson processes or other traditional probability distributions. We further show that the reasons that these models fail to capture the control-plane traffic are due to its higher burstiness and longer tails in the cumulative distribution than the traditional models. Third, we propose a two-level hierarchical state-machine-based traffic model for UE clusters derived from our adaptive clustering scheme based on the Semi-Markov Model to capture key characteristics of mobile network control-plane traffic -- in particular, the dependence among events generated by each UE, and the diversity in device types and time-of-day among UEs. Finally, we show how our model can be easily adjusted from LTE to 5G to support modeling 5G control-plane traffic, when the sizable control-plane trace for 5G UEs becomes available to train the adjusted model. The developed control-plane traffic generator for LTE/5G networks is open-sourced to the research community to support high-performance MCN architecture design R&D

A Survey on Wireless Security: Technical Challenges, Recent Advances and Future Trends

This paper examines the security vulnerabilities and threats imposed by the inherent open nature of wireless communications and to devise efficient defense mechanisms for improving the wireless network security. We first summarize the security requirements of wireless networks, including their authenticity, confidentiality, integrity and availability issues. Next, a comprehensive overview of security attacks encountered in wireless networks is presented in view of the network protocol architecture, where the potential security threats are discussed at each protocol layer. We also provide a survey of the existing security protocols and algorithms that are adopted in the existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term evolution (LTE) systems. Then, we discuss the state-of-the-art in physical-layer security, which is an emerging technique of securing the open communications environment against eavesdropping attacks at the physical layer. We also introduce the family of various jamming attacks and their counter-measures, including the constant jammer, intermittent jammer, reactive jammer, adaptive jammer and intelligent jammer. Additionally, we discuss the integration of physical-layer security into existing authentication and cryptography mechanisms for further securing wireless networks. Finally, some technical challenges which remain unresolved at the time of writing are summarized and the future trends in wireless security are discussed.Comment: 36 pages. Accepted to Appear in Proceedings of the IEEE, 201

Understanding Mobile Data Demand regarding Mobility: The report for mid-term thesis evaluation

Smartphones are supposedly the fastest-spreading technology in human history. Global mobile data traffic has a growth of 74% in 2015, and is predicted to have an eightfold increase in 2020. Hence the understanding of subscriber’s mobile data demand is of great significance for solutions managing the increasing data traffic as well as improving quality of communication service. A core problem in understanding mobile data demand is to what degree is mobile data traffic predictable? We explore the predictability of data volume for individuals. Specifically, our goal is to determine the maximum probability of forecasting data volume for each subscriber. To this end, we mine a large-scale mobile dataset with both voice traffic and data traffic, construct a dataset of time series of data volume and explore the upper bound of predictability hidden in the time series. We find a overall > 90% of predictability hidden in individual’s time series of data volume

A Unified Mobility Management Architecture for Interworked Heterogeneous Mobile Networks

The buzzword of this decade has been convergence: the convergence of telecommunications, Internet, entertainment, and information technologies for the seamless provisioning of multimedia services across different network types. Thus the future Next Generation Mobile Network (NGMN) can be envisioned as a group of co-existing heterogeneous mobile data networking technologies sharing a common Internet Protocol (IP) based backbone. In such all-IP based heterogeneous networking environments, ongoing sessions from roaming users are subjected to frequent vertical handoffs across network boundaries. Therefore, ensuring uninterrupted service continuity during session handoffs requires successful mobility and session management mechanisms to be implemented in these participating access networks. Therefore, it is essential for a common interworking framework to be in place for ensuring seamless service continuity over dissimilar networks to enable a potential user to freely roam from one network to another. For the best of our knowledge, the need for a suitable unified mobility and session management framework for the NGMN has not been successfully addressed as yet. This can be seen as the primary motivation of this research. Therefore, the key objectives of this thesis can be stated as: To propose a mobility-aware novel architecture for interworking between heterogeneous mobile data networks To propose a framework for facilitating unified real-time session management (inclusive of session establishment and seamless session handoff) across these different networks. In order to achieve the above goals, an interworking architecture is designed by incorporating the IP Multimedia Subsystem (IMS) as the coupling mediator between dissipate mobile data networking technologies. Subsequently, two different mobility management frameworks are proposed and implemented over the initial interworking architectural design. The first mobility management framework is fully handled by the IMS at the Application Layer. This framework is primarily dependant on the IMS’s default session management protocol, which is the Session Initiation Protocol (SIP). The second framework is a combined method based on SIP and the Mobile IP (MIP) protocols, which is essentially operated at the Network Layer. An analytical model is derived for evaluating the proposed scheme for analyzing the network Quality of Service (QoS) metrics and measures involved in session mobility management for the proposed mobility management frameworks. More precisely, these analyzed QoS metrics include vertical handoff delay, transient packet loss, jitter, and signaling overhead/cost. The results of the QoS analysis indicates that a MIP-SIP based mobility management framework performs better than its predecessor, the Pure-SIP based mobility management method. Also, the analysis results indicate that the QoS performances for the investigated parameters are within acceptable levels for real-time VoIP conversations. An OPNET based simulation platform is also used for modeling the proposed mobility management frameworks. All simulated scenarios prove to be capable of performing successful VoIP session handoffs between dissimilar networks whilst maintaining acceptable QoS levels. Lastly, based on the findings, the contributions made by this thesis can be summarized as: The development of a novel framework for interworked heterogeneous mobile data networks in a NGMN environment. The final design conveniently enables 3G cellular technologies (such as the Universal Mobile Telecommunications Systems (UMTS) or Code Division Multiple Access 2000 (CDMA2000) type systems), Wireless Local Area Networking (WLAN) technologies, and Wireless Metropolitan Area Networking (WMAN) technologies (e.g., Broadband Wireless Access (BWA) systems such as WiMAX) to interwork under a common signaling platform. The introduction of a novel unified/centralized mobility and session management platform by exploiting the IMS as a universal coupling mediator for real-time session negotiation and management. This enables a roaming user to seamlessly handoff sessions between different heterogeneous networks. As secondary outcomes of this thesis, an analytical framework and an OPNET simulation framework are developed for analyzing vertical handoff performance. This OPNET simulation platform is suitable for commercial use

Self-Organizing Networks use cases in commercial deployments

These measurements can be obtained from different sources, but these sources are either expensive or not applicable to any network. To solve this problem, this thesis proposes a method that uses information available in any network so that the calibration of predictive maps is converted into universal without losing accuracy with respect to current methods. Furthermore, the complexity of today's networks makes them prone to failure. To save costs, operators employ network self-healing techniques so that networks are able to self-diagnose and even self-fix when possible. Among the various failures that can occur in mobile communication networks, a common case is the existence of sectors whose radiated signal has been exchanged. This issue appears during the network roll-out when engineers accidentally cross feeders of several antennas. Currently, manual methodology is used to identify this problem. Therefore, this thesis presents an automatic system to detect these cases. Finally, special attention has been paid to the computational efficiency of the algorithms developed in this thesis since they have finally been integrated into commercial tools.Ince their origins, mobile communication networks have undergone major changes imposed by the need for networks to adapt to user demand. To do this, networks have had to increase in complexity. In turn, complexity has made networks increasingly difficult to design and maintain. To mitigate the impact of network complexity, the concept of self-organizing networks (SON) emerged. Self-organized networks aim at reducing the complexity in the design and maintenance of mobile communication networks by automating processes. Thus, three major blocks in the automation of networks are identified: self-configuration, self-optimization and self-healing. This thesis contributes to the state of the art of self-organized networks through the identification and subsequent resolution of a problem in each of the three blocks into which they are divided. With the advent of 5G networks and the speeds they promise to deliver to users, new use cases have emerged. One of these use cases is known as Fixed Wireless Access. In this type of network, the last mile of fiber is replaced by broadband radio access of mobile technologies. Until now, regarding self-configuration, greenfield design methodologies for wireless networks based on mobile communication technologies are based on the premise that users have mobility characteristics. However, in fixed wireless access networks, the antennas of the users are in fixed locations. Therefore, this thesis proposes a novel methodology for finding the optimal locations were to deploy network equipment as well as the configuration of their radio parameters in Fixed Wireless Access networks. Regarding self-optimization of networks, current algorithms make use of signal maps of the cells in the network so that the changes that these maps would experience after modifying any network parameter can be estimated. In order to obtain these maps, operators use predictive models calibrated through real network measurements