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Although network management tasks are highly automated using big data and artificial intelligence technologies, when an unforeseen cybersecurity problem or fault scenario occurs, administrators sometimes directly analyze system data to make a heuristic decision. However, a wide variety of information is required to address complex cybersecurity risks, whereas current systems are focused on narrowing the candidates of information. In this study, we propose a multiagent-based data presentation mechanism (MADPM) that consists of agents operating data-processing tools that store and analyze network data. Agents in MADPM interact with other agents to form data-processing sequences. In this process, we design not only the composition of the sequence according to requirements, but also a mechanism to expand it to enable multifaceted analysis that supports heuristic reasoning. We tested five case studies in the prototype system implemented in an experimental network. The results indicated that the multifaceted presentation of data can support administrators more than the selected single-faceted optimal presentation. The final outcome of our proposed approach is the provision of a multifaceted and cross-system data presentation for heuristic inference in network management tasks.

Multiagent application systems must deal with various changes in both the system and the system environment at runtime. Generally, such changes have undesirable negative effects on the system. To manage and control the system, it is important to observe and detect negative effects using an appropriate observation function of the system’s behavior. This paper focuses on the design of this function and proposes a new macroscopic measure with which to observe behavioral characteristics of a runtime multiagent system. The proposed measure is designed as the variance of fluctuation of a macroscopic activity factor of the whole system, based on theoretical analysis of the macroscopic behavioral model of a multiagent system. Experiments are conducted to investigate basic characteristics of the proposed measure, using a test bed system. The results of experiments show that the proposed measure reacts quickly and increases drastically in response to abnormal changes in the system. Hence, the proposed measure is considered a measure that can be used to detect undesirable changes in a multiagent system.

Electricity consumption in the world is constantly increasing, making our lives become more and more dependent on electricity. There are several new paradigms proposed in the field of power grids. In Japan, especially after the Great East Japan Earthquake in March 2011, the new power grid paradigms are expected to be more resilient to survive several difficulties during disasters. In this paper, we focus on microgrids and propose priority-based hierarchical operational management for multiagent-based microgrids. The proposed management is a new multiagent-based load shedding scheme and multiagent-based hierarchical architecture to realize such resilient microgrids. We developed a prototype system and performed an evaluation of the proposed management using the developed system. The result of the evaluation shows the effectiveness of our proposal in power shortage situations, such as disasters.

A microgrid is an eco-friendly power system because renewable sources are used as main power sources. In the islanded operation mode of a microgrid, maintaining the balance between power supply and power demand is a very important problem. In the case of surplus supply, decreased generation output and/or charge of distributed storages can be applied to solve the imbalance between power supply and demand. In the case of supply shortages, increased generation output and/or discharge of distributed storages can be applied. Especially in the case of critical supply shortages, load shedding should be applied. In a distributed load-shedding approach, microgrid components need to make decisions autonomously. For autonomous microgrid operation, a multi-agent system has been investigated. In this paper, a distributed load-shedding system for agent-based autonomous operation of a microgrid is designed. The designed system is implemented and tested to show the functionality and feasibility of the proposed system.

A microgrid is an eco-friendly power system because renewable sources such as solar and wind power are used as the main power sources. For this reason, much research, development, and demonstration projects have recently taken place in many countries. Operation is one of the important research topics for microgrids. For efficient and economical microgrid operation, a human operator is required as in other power systems, but it is difficult because there are some restrictions related to operation costs and privacy issues. To overcome the restriction, autonomous operation for microgrids is required. Recently, an intelligent agent system for autonomous microgrid operation has been studied as a potential solution. This paper proposes a multiagent system for autonomous microgrid operation. To build the multiagent system, the functionalities of agents, interactions among agents, and an effective agent protocol have been designed. The proposed system has been implemented by using an ADIPS/DASH framework as an agent platform. The intelligent multiagent system for microgrid operation based on the proposed scheme is tested to show the functionality and feasibility on a distributed environment through the Internet.

One of the most important requirements of microgrid operation is to maintain a constant frequency such as 50 Hz or 60 Hz, which is closely related to a power balance between supply and demand. In general, microgrids are connected to power grids and surplus/shortage power of microgrids is traded with power grids. Since islanded microgrids are isolated from any power grids, the decrease in generation or load-shedding can be used to maintain the frequency when a power imbalance between supply and demand occurs. The power imbalance restricts the electricity use of consumers in the case of supply shortage and the power supply of suppliers in the case of supply surplus. Therefore, the islanded microgrid should be operated to reduce power imbalance conditions. Meanwhile, the microgrid is a small-scale power system and the employment of skillful operators for effective operation of its components requires high costs. Therefore, automatic operation of the components is effective realistically. In addition, the components are distributed in the microgrid and their operation should consider their owners’ profits. For these reasons, a multiagent system application can be a good alternative for microgrid operation. In this paper, we present a multiagent system for autonomous operation of the islanded microgrid on a power market environment. The proposed multiagent system is designed based on a cooperative operation scheme. We show the functionality and the feasibility of the proposed multiagent system through several tests.

A microgrid is composed of distributed power generation systems (DGs), distributed energy storage devices (DSs), and loads. To maintain a specific frequency in the islanded mode as an important requirement, the control of DGs’ output and charge action of DSs are used in supply surplus conditions and load-shedding and discharge action of DSs are used in supply shortage conditions. Recently, multiagent systems for autonomous microgrid operation have been studied. Especially, load-shedding, which is intentional reduction of electricity use, is a critical problem in islanded microgrid operation based on the multiagent system. Therefore, effective schemes for load-shedding are required. Meanwhile, the bankruptcy problem deals with dividing short resources among multiple agents. In order to solve the bankruptcy problem, division rules, such as the constrained equal awards rule (CEA), the constrained equal losses rule (CEL), and the random arrival rule (RA), have been used. In this paper, we approach load-shedding as a bankruptcy problem. We compare load-shedding results by above-mentioned rules in islanded microgrid operation based on wireless sensor network (WSN) as the communication link for an agent’s interactions.

With the widespread use of wearable sensors, cloud services, social networking services (SNS), etc., there are various applications and systems that record information on users’ daily activities and support recalling these activities. In various situations in everyday life, it is useful to recall and refer to past events by utilizing such information; therefore, there are increasing expectations surrounding a memory recall system that supports users’ activities. In this research, we aim to realize a system that acquires records of users’ experiences, transforms these records as Active Information Resources, autonomously manages the accumulated records based on the record’s metadata, and supports users’ human memory recall. In this paper, we describe the design and implementation of a basic framework for accumulating records on daily activities and providing information related to past experiences according to the user’s request. We also present evaluation experiments using the implemented system.

Elasticity is one of the key features of cloud-hosted services built on virtualization technology. To utilize the elasticity of cloud environments, administrators should accurately capture the operational status of server systems, which changes constantly according to service requests incoming irregularly. However, it is difficult to detect and avoid in advance that operating services are falling into an undesirable state. In this paper, we focus on the management of server systems that include cloud systems, and propose a new method for detecting the sign of undesirable scenarios before the system becomes overloaded as a result of various causes. In this method, a measure that utilizes the fluctuation of the macroscopic operational state observed in the server system is introduced. The proposed measure has the property of drastically increasing before the server system is in an undesirable state. Using the proposed measure, we realize a function to detect that the server system is falling into an overload scenario, and we demonstrate its effectiveness through experiments.

In a microgrid as an energy infrastructure, the vulnerability against jamming attacks is fatal. Thus, the ability to deal with jamming attacks and maintain an acceptable level of service degradation in presence of the attacks is needed. To solve the problem, we propose a traffic rerouting scheme in wireless communication infrastructure for islanded microgrid. We determine disjoint multiple paths as candidates of a detour path and then select the detour path among the candidates in order to reduce the effect of jamming attack and distribute traffic flows on different detour paths. Through performance comparison, we show that our scheme outperforms a conventional scheme in terms of packet delivery ratio and end-to-end delay.