Izuru Sato

Improving Radio Resource Usage with Suitable Policy and Charging Control in LTE

The LTE (Long-Term Evolution) is a high-data rate open multimedia mobile system. In this paper, we consider the LTE QoS model framework and try to optimize the operator policy with regard to the radio use efficiency. Our objective is to propose a link between the PCRF (Policy Charging and Rules Function) decisions and the radio situation as an evolution for the LTE standard. We define a central database for the access network radio information that can be used for the operator policy choices. In this paper, we concentrate on the voice service, as a first step. Simple computations are provided. We show that our contribution can lead to a greater user average quality without loss of capacity. Other important openings are highlighted, promising interesting radio efficiency gains.

Applicability of a layered architecture adopting distributed data processing to M2M communications

We show that a layered architecture distributing M2M application to multiple processing entities in the M2M network is applicable for ubiquitous era. This paper firstly introduces a layered architecture of M2M system, where we put layers for the decomposition of application and the association of de-composited subroutines. Next, we categorize the association of subroutines into two patterns (sequential and random order), and model schemes on state managements (centralization and distribution). Then, we clarify the condition that the performance can be improved by distributed management in terms of processing time for two association patterns. Next, the deployment of de-composited subroutines on processing entities is discussed, where we show basic rules to reduce carried traffic. Finally, we address the requirements of messaging between two processing entities in M2M network to provide QoS such as time limitation.

An extension of Information-Centric Networking for IoT applications

Information-Centric Networking (ICN) is getting noticed as an emerging network technology. Due to its attractive features such as accessing content by its name, in-network caching, etc., it is expected to apply to Internet of Things (IoT). IoT applications typically collect a large amount of data widely distributed in various locations. In conventional ICN, it is not easy to access such data because each name for desired data needs to be specified beforehand and the number of requests for data becomes so large. In this paper, we propose a network architecture for IoT applications by an extension of ICN, namely Keyword-Based Content Retrieval (KBCR). When KBCR node receives a request with some keywords, it spreads multiple requests towards the data related to the keywords. When the node receives the multiple responses, it merges them into one response. This process is carried out on multiple nodes in tandem manner over the network. Hence, the requester can receive the aggregated data in one response and the number of request/response messages is reduced. This paper describes the concept of KBCR, a typical IoT application example, the detail of KBCR behavior for the application example, and finally shows the advantage of the proposal by numerical analysis.

Short Paper: Performance evaluation on distributed data process in M2M systems

We show that distributed data processing for M2M applications improves the performance of M2M systems. The important roles of the M2M systems are to associate an application with required data and to execute the application on suitable processing entities for coming ubiquitous environment. First, we show simple rules on deployment of data process to reduce load in underlying M2M network. Next, we clarify cases such that an application should be divided into subroutines for distributed executions. And so, we model centralized and distributed execution as multi-stage queuing system to show the improvement by the distributed execution.

A New LTE/EPC Control-Plane Based Transmission Procedure to Cope with Short Data Push Services

The architecture and the protocols of LTE/EPC were designed to deliver high transmission rates with QoS requirements. In order to be able to guarantee different levels of QoS, each transmission is based on a bearer, which needs to be set up within the network. It then requires to store contexts in the various entities of the network and to set up several tunnels or connections both in the user and the control planes. This approach is, however, inadequate when considering a class of value-added services obedient to a “Short Data push principle”. This category which contains, at least, very popular services like Short Message Service (SMS) and Twitter, or new ones like Machine-to-Machine communication services, represents on one hand a continuously growing part of the worldwide amount of data traffic exchanged and on the other hand is easily recognizable thanks to its specific traffic pattern. To allow LTE/EPC to conveniently cope with the sporadic nature of these services, we introduce a new procedure based on a set of simple messages to transport such isolated messages only in the control plane. We show that this procedure may generate additional signaling in some cases but is efficient as soon as the proportion of sporadic traffic is not negligible. We illustrate our approach in the case of the SMS which is emblematic of the targeted category of services. The proposed procedure is, however, generic and may be used for any type of sporadic traffic.

Traffic engineering for IoT

Considering IoT environment, where even network nodes are having not only data transfer function but also data processing function, we are studying which processing entity should execute an IoT application and how to connect the processing entity with terminals requesting the application. Then, we show 4 types of traffic engineering (TE) to minimize delay by the selection of processor and the rearrange of route. Next, we evaluate the complexity of algorithm for each TE type and clarify the effectiveness of each TE in term of the reduction of delay for delay relatively sensitive application. Finally we map IoT applications with adoptable TE types.