When multiple companies in different industries collaborate to provide ICT services, the systems used by each company differ and the format in which information is expressed differs from system to system. Therefore, information cannot be distributed without manual information conversion. To promote provision of services through the cooperation of multiple companies, the distribution of information among them needs to be automated. In this case, information content needs to be automatically identified to determine the distribution destination. In this paper, we propose a method that can automatically identify information by using a combination of distributed representations and a synonym conversion. The evaluation results show that the method can identify information with an existing type with a 100% accuracy, but needs to be improved regarding identification of whether information is a new type.

The orchestration and management of 5G network slicing (NS) requires cross-domain orchestration across 5G radio access network (RAN), 5G core network (CN), and transport network and also coordination of closed loops of each 5G network segment. We propose a resource orchestration and management architecture for end-to-end (E2E) 5G network slices to automate the flexible and high-performance NS’s management and orchestration. Through developing a prototype of the proposed architecture on an experimental 5G network, the effectiveness of our architecture is proven through prominent use cases certified by ETSI ZSM.

In recent years, microservices architectures have become widespread, where services are divided into smaller pieces, communicate with each other, and operate in chains. Distributed tracing, which tracks the processing of user requests, is used to analyze and visualize microservices. In this paper, the trace data obtained from the distributed tracing is divided based on the parent-child relationship and converted into an event log. In addition, process discovery is performed on each of the split event logs to estimate the relationships between microservice processes. Then, generate a normal Petri net model that can reproduce each event log. Finally, the test trace data is used to verify the suitability of the Petri net model. We constructed a service model for two sample microservices with different scales and distributed tracing implementations and demonstrated the proposed method's feasibility through conformance checking using test trace data.

In the Business-to-Business-to-X (B2B2X) business model, the importance of an API orchestrator for constructing and operating services by combining multiple firstB services is increasing. In the development of RESTful API-based services, service providers are required to keep up with changes in specifications of new firstB services and existing services in a short period of time and at low cost. To do so, they need to quickly and inexpensively develop API adapters that can absorb API differences with various services. In this paper, we proposed a method for automating the test code generation while considering the API execution order, input parameter combination, test type (Normal/Semi-Normal), and state transition pattern. We implemented our method using open source software (OSS) and evaluated it from qualitative and quantitative viewpoints. The results show its effectiveness in tests with an actual software development project.

With the popularization of B2B2X (Business to Business to X, where “X” represents any end user) business, the software for supporting both deployment and maintenance of collaborative services, which combine multiple services, is required. We previously investigated technology for enabling both deployment and maintenance of collaborative services in one stop and achieved automation in every process such as deployment and maintenance. However, to complete a series of processes in one stop without operators, it is necessary to automatically distribute service information (configuration of systems that provide collaborative services) between processes. In this study, we developed a method for automatically distributing service information between a deployment system and a maintenance system, and we evaluated its feasibility. For the evaluation, we implemented the proposed method with current technologies and applied it to the service-maintenance process in a virtual environment.

Microservice architectures, in which services are divided into small pieces, communicate with each other, and operate in a chain, have been spreading. Distributed tracing, which tracks the processing of user requests, has been used to analyze microservices. To extract the service structure, we previously proposed a method of estimating the dependency between services and expressing it as a Petri net model. In this paper, we propose an extension of this method for the Petri net model to handle the non-deterministic processes of services. We evaluated the applicability of modeling to services with nondeterministic behaviors and confirmed that various nondeterministic processes can be modeled with our method.

In this paper, we propose a management method of API request execution history for service restoration. With this method, when an application that can be set on demand via REST API is constructed in a redundant configuration when a failure occurs in the application or the base on which the application runs, it is possible to restore the application while ensuring consistency the service state. In this method, the Bitemporal data model combines two types of time information, such as the time when the API is requested and the time set in the application, and information representing the redundant configuration, and manages them as history information. By combining the redundant configuration information and the current time from this history, it is possible to acquire the information necessary for recovering the application. Our experimental results showed that this method can correctly acquire the API information required for service recovery when a failure occurs.

The Business-to-Business-to-X (B2B2X) model has increased the importance of orchestrators that build and operate services that consists of various wholesale services. To develop RESTful API-based services, service providers need to catch up on the specifications of new wholesale services and specification changes of existing services quickly and inexpensively. Therefore, it is important to develop software called an API adapter that absorbs API differences from various services quickly and inexpensively. In this paper, we propose a method for comprehensively automating testing of not only C-Plane signals such as service provisioning/change/abolishment but also U-Plane signals such as communication between user devices and servers. We implemented our proposal using open source software and found that it improved test efficiency in an actual software development project.

The increasing complexity of services of telecommunications carriers has increased the burden of operators monitoring these services and the load on the system monitoring the target devices. Operators need to choose appropriate monitoring settings for each component of the services, considering the properties of each component. In addition, whenever a component is added or changed, its monitoring settings need to be reconfigured. Furthermore, if operators configure incorrect monitoring settings, service anomalies may not be detected, or quality of service may be damaged. Therefore, the monitoring system needs to automatically input and change the monitoring settings in accordance with the service. In this paper, we propose a method to dynamically adjust the monitoring interval for a monitoring system. Finally, evaluation results show the proposed method can reduce the monitoring overhead more effectively than the previous method and can also ensure the accuracy of monitoring when a service abnormality occurs.

In this paper, a workflow-less system architecture adopting Choreography architecture is proposed that can flexibly and quickly respond to changes in demand on a system. This approach makes each maintenance function into a microservice and enables each microservice to operate autonomously in an event-driven manner. In addition, a label assignment method is proposed in the communication control between the maintenance functions. With the proposed method, a series of operations can be automated without defining a workflow. Experiments were carried out using the proposed method, and results show that a workflow with synchronous control could be achieved without a workflow definition.

We proposed an orchestrator in which service providers construct multiple services by cooperating with each other at one stop without being conscious of individual services in order to respond to the B2B2X (Business to Business to X) business model which provides services service providers by flexibly and easily combining services of each field. The advantage of this orchestrator is that a Catalog-Driven Architecture which operates by defining service specifications, resource specifications, and collaboration methods in its catalog. This feature provides flexibility for adding new services and APIs. However, as the service specifications become more complicated, the contents of catalogs tend to become more complicated, and there is a problem that knowledge is required to generate catalogs. In this paper, we propose a method to automatically generate a GUI and a catalog output function for supporting catalog creation used in orchestrators based on catalog definition templates. And then, we evaluate and confirm the feasibility of the proposed method through experiments.

This paper describes methods for controlling routing points of VLAN domains using binary particle swarm optimization (BPSO) and angle modulated particle swarm optimization (AMPSO). Virtual LAN (VLAN) is a technique for virtualizing data link layer (or L2) and can construct arbitrary logical networks on top of a physical network. However, VLAN often causes much redundant traffic due to inappropriate deployments of network-layer (L3) routing capabilities in VLAN networks. We propose two methods using BPSO and AMPSO, and show that they can adaptively select the routing points dynamically in accordance with the observed traffic patterns and thus reduce the redundant traffic. The convergence features are compared with those of the conventional method on the basis of a statistical method. Then we also show that the scalability of the algorithm using AMPOS is high and thus we can expect that it is applicable to practical large VLAN environments.

We propose a method for estimating sensor network topology from only with time-series sensor data and without prior knowledge about the locations of sensors. The proposed method is based on ant colony optimization (ACO) but is further improved, compared with previous work[s], to construct a more accurate topology through an examination of the reliability of the acquired sensor data for the adjacency estimation. This reliability value is used to control the amount of pheromones deposited. We evaluate our method using actual sensor data and show that it can estimate adjacencies, in which the error rate is approximately 87% less than that of the previous method.