Takanori Iwai

An Autonomous and Distributed Mobility Management Scheme in Mobile Core Networks

The 5th generation mobile and wireless communication systems are expected to accommodate exploding traffic, increasing number of devices, and heterogeneous applications driven by proliferation of IoT and M2M technologies. The centralized mobility management architecture in a current mobile core network cannot satisfy these emerging requirements. In this paper, we introduce novel architecture of distributed mobility management and an autonomous and adaptive mobility management scheme which distributes mobility management function on nodes in a mobile core network in accordance with mobility characteristics of UEs and a management policy. We adopt a biologically-inspired adaptation algorithm, called attractor selection, to accomplish adaptive selection taking into account multiple objectives. Through simulation experiments, we conrmed that our proposal could accomplish lower delay, higher load balancing, and lower C-plane overhead comparing to other methods including the current standard.

Performance evaluation of a tunnel sharing method for accommodating M2M communication to mobile cellular networks

Machine-to-Machine (M2M) communication has attracted considerable attention as a new communication paradigm that increases wireless network traffic. Since existing mobile cellular networks need to persistently maintain a tunnel for each mobile terminal in their core system, the number of concurrent tunnels increases dramatically when a large number of M2M devices are handled in mobile cellular networks large popularity. The small Average Revenue Per User (ARPU) of M2M terminals also has a strong impact on network cost. In this paper, we propose a tunnel sharing method to reduce the cost of accommodating M2M terminals to mobile cellular networks. In the proposed method, multiple terminals are aggregated as a group and share a single tunnel in the mobile core network. We also propose introduction of temporary tunnels to avoid call blocking caused by competition for a single tunnel among simultaneous calls. We evaluate the performance of the proposed method by mathematical analysis to examine its basic characteristics. We also estimate the monetary cost to realize the proposed method and reveal that it can reduce at 80% compared with traditional mobile core networks, while keeping the call blocking rate less than 0.1%.

Temporal load balancing of time-driven machine type communications in mobile core networks

Machine Type Communications (MTC) has been paid much attention as a new communication paradigm to increase mobile network traffic. Most of MTC terminals are time-driven, that is, they send and receive data periodically. Therefore, network access requests on mobile core networks are concentrated at a specific timing, which results in instantaneous increase in network load. Considering the fact that such time-driven MTC would accept a certain amount of latency in their cyclic communication, in this paper, we propose a scheduling method of communication timings of time-driven MTC terminals to mitigate traffic concentration. We extend the standardized back-off mechanism of 3GPP to configure the back-off time length for each terminal to decrease the number of concurrent bearers in the network, while satisfying requirements on communication latency. We compare proposed methods by simulation experiments and reveal that we can achieve almost zero access rejections at reasonable communication quality by a simple timeslot selection algorithm when the core network maintain the timeslot assignment status for accommodated User Equipments. To the best of our knowledge, this is the first proposal to alleviate short-term congestion of mobile core networks by MTC with TDMA-like network control.

A Deadline-Aware Scheduling Scheme for Connected Car Services Using Mobile Networks with Quality Fluctuation

Traffic collision is an extremely serious issue in the world today. The World Health Organization (WHO) reported the number of road traffic deaths globally has plateaued at 1.25 million a year. In an attempt to decrease the occurrence of such traffic collisions, various driving systems for detecting pedestrians and vehicles have been proposed, but they are inadequate as they cannot detect vehicles and pedestrians in blind places such as sharp bends and blind intersections. Therefore, mobile networks such as long term evolution (LTE), LTE-Advanced, and 5G networks are attracting a great deal of attention as platforms for connected car services. Such platforms enable individual devices such as vehicles, drones, and sensors to exchange real-time information (e.g., location information) with each other. To guarantee effective connected car services, it is important to deliver a data block within a certain maximum tolerable delay (called a deadline in this work). The Third Generation Partnership Project (3GPP) stipulates that this deadline be 100 ms and that the arrival ratio within the deadline be 0.95. We investigated an intersection at which vehicle collisions often occur to evaluate a realistic environment and found that schedulers such as proportional fairness (PF) and payload-size and deadline-aware (PayDA) cannot satisfy the deadline and arrival ratio within the deadline, especially as network loads increase. They fail because they do not consider three key elements— radio quality, chunk size, and the deadline—when radio resources are allocated. In this paper, we propose a deadline-aware scheduling scheme that considers chunk size and the deadline in addition to radio quality and uses them to prioritize users in order to meet the deadline. The results of a simulation on ns-3 showed that the proposed method can achieve approximately four times the number of vehicles satisfying network requirements compared to PayDA. key words: IoT, resource control, 5G, LTE, connected car, V2X

Temporal traffic smoothing for IoT traffic in mobile networks

Abstract The proportion of mobile-device traffic relative to the total Internet traffic has been increasing as Internet of Things (IoT) devices have spread. Here, if a large number of IoT devices send communication requests to the same base station at the same time, those requests conflict with each other, which results in serious congestion in the cellular network. To solve this problem, researchers have discussed traffic smoothing techniques. However, their work has focused on either temporal offloading or spatial offloading only. When we consider moving IoT devices, delaying their communication requests for temporal offloading might also work as spatial offloading, because the devices might move to other neighboring cells while waiting for their transmission timing. That is, delaying requests contributes to not only temporal but also spatial traffic offloading.On the basis of this principle, we propose a communication timing control for temporal and spatial traffic offloading that works for moving IoT devices in cellular networks. By using our method, part of the excess traffic is moved to off-peak times and neighboring cells. A comparative evaluation proved that our method effectively reduces peak traffic while satisfying latency requirements of IoT applications.

A control method for autonomous mobility management systems toward 5G mobile networks

Fifth-generation mobile and wireless communication systems are actively being studied as a next-generation mobile communication network. People and devices will connect to the Internet via wireless networks in future communication networks, but many challenges must be solved to realize 5G networks. For example, it is difficult to manage connected user devices using centralized control in the control plane. We previously proposed an architecture for autonomous and distributed mobility management and a biology-inspired mobility management scheme that adaptively selects the location of management entities. However, this scheme has some problems from a network-wide perspective, due to entities autonomous decision-making. This paper introduces a control node for monitoring and managing the network to resolve the otherwise unsolvable problem of autonomous distributed control. We show that this control node can improve network stability without much loss of performance in the entire network.

Autonomous and distributed mobility management in mobile core networks

The 5th generation mobile and wireless communication systems are expected to accommodate exploding traffic, increasing number of devices, and heterogeneous applications driven by proliferation of IoT and M2M technologies. However, the centralized mobility management architecture in a current mobile core network would face critical problems such as excessive concentration of load on specific servers and considerable increase in C-plane overhead. To solve the problems we first consider a novel architecture of distributed mobility management in C-plane in the mobile core network, which employs virtualized mobility management entity called ADMMEs (Autonomous Distributed Mobility Management Entity) in this paper. In addition, to assign an appropriate ADMME to a UE in accordance with mobility characteristics of the UE and a management policy, we propose an autonomous and adaptive ADMME selection scheme. We adopt a biologically-inspired algorithm, called attractor selection, to accomplish adaptive selection taking into account multiple objectives. Through simulation experiments, we confirmed our proposal could accomplish more than 63xa0% performance improvement comparing to the current method from viewpoints of delay, load balancing, and C-plane overhead under a dynamic mobility scenario.

Real-Time Measurement of End-to-End Available Bandwidth: A Feasibility Study

We propose a real-time measurement method, DPDC (Detection of Packet-Delay Correlation), which models both available bandwidth and the averaging time scale. In this method, measurement periods are short and constant, while the theoretical measurement error is reduced. DPDC is established based on the discussion of the systematic error of the packet pair/train measurement. We evaluate through simulations its accuracy and robustness against the multihop effect. We also verify the feasibility of real-time measurements through testbed experiments using a tool called Linear that implements DPDC. Efficiency is demonstrated through simulations and testbed experiments by analyzing accidental and systematic errors. Finally, we discuss the available bandwidth variation in an Internet path using real-time data produced by Linear measurements and passive monitoring.