With the emergence of various forms of smart devices and new paradigms such as the Internet of Things (IoT) concept, the IT (Information Technology) service areas are expanding explosively compared to the provision of services by single systems. A new system operation concept that has emerged in accordance with such technical trends is the IT ecosystem. The IT ecosystem can be considered a special type of system of systems in which multiple systems with various degrees of autonomy achieve common goals while adapting to the given environment. The single systems that participate in the IT ecosystem adapt autonomously to the current situation based on collected data from sensors. Furthermore, to maintain the services supported by the whole IT ecosystem sustainably, the configuration of single systems that participate in the IT ecosystem also changes appropriately in accordance with the changed situation. In order to support the IT ecosystem, this paper proposes an architecture framework that supports dynamic configuration changes to achieve the goal of the whole IT ecosystem, while ensuring the autonomy of single systems through the collection of data from sensors so as to recognize the situational context of individual participating systems. For the feasibility evaluation of the proposed framework, a simulated example of an IT ecosystem for unmanned forest management was constructed, and the quantitative evaluation results are discussed in terms of the extent to which the proposed architecture framework can continuously provide sustainable services in response to diverse environmental context changes.

The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers to take considerable time and effort. Furthermore, the developed IoT collaboration services are often dependent on a particular domain, which cannot easily be referenced in other domains. This paper proposes a cloud-based middleware framework that provides a set of cloud services for self-adaptive IoT collaboration services. The proposed middleware framework is generic in the sense that it clearly separates domain-dependent components from the layers that leverage existing middleware frameworks. In addition, the proposed framework allows developers to upload domain-dependent components onto the cloud, search for registered components, and launch Virtual Machine (VM) running a new MAPE cycle via a convenient web-based interface. The feasibility of the proposed framework has been shown with a simulation of an IoT collaboration service that traces a criminal suspect. The performance evaluation shows that the proposed middleware framework runs with an overhead of only 6% compared to pure Java-based middleware and is scalable as the number of VMs increases up to 16.

This study examined the security of SCADA system and its protocols, more specifically, SCADA/DNP3 protocol security. To achieve the study goals, a SCADA simulation environment is designed for water pumping process through connectivity of intelligent sensors, the payload is constructed, and security is deployed inside DNP3 protocol stack and then bytes are multicast to subcontrollers.

Cloud computing has emerged as more than just a piece of technology, it is rather a new IT paradigm. The philosophy behind cloud computing shares its view with green computing where computing environments and resources are not as subjects to own but as subjects of sustained use. However, converting currently used IT services to Software as a Service (SaaS) cloud computing environments introduces several new risks. To mitigate such risks, existing software development processes must undergo significant remodeling. This study analyzes actual cases of SaaS cloud computing environment adoption as a way to derive four new best practices for software development and incorporates the identified best practices for currently-in-use processes. Furthermore, this study presents a design for generic software development processes that implement the proposed best practices. The design for the generic process has been applied to reinforce the weak points found in SaaS cloud service development practices used by eight enterprises currently developing or operating actual SaaS cloud computing services. Lastly, this study evaluates the applicability of the proposed SaaS cloud oriented development process through analyzing the feedback data collected from actual application to the development of a SaaS cloud service Astation.

Starting with the Internet of Things (IoT), new forms of system operation concepts have emerged to provide creative services through collaborations among autonomic devices. Following these paradigmatic changes, the ability of each participating system to automatically diagnose the degree of quality it is providing is inevitable. This paper proposed a method to automatically detect symptoms that hinder certain quality attributes. The method consisted of three steps: (1) extracting information from real usage logs and automatically generating an activity model from the captured information; (2) merging multiple user activity models into a single, representative model; and (3) detecting differences between the representative user activity model, and an expected activity model. The proposed method was implemented in a domain-independent framework, workable on the Android platform. Unlike other related works, we used quantitative evaluation results to show the benefits of applying the proposed method to five Android-based, open-source mobile applications. The evaluation results showed that the average precision rate for the automatic detection of symptoms was 70%, and the success rate for user implementation of usage scenarios demonstrated an improvement of around 21%, when the automatically detected symptoms were resolved.

One of the most widely used models for specifying functional requirements is a use case model. The viewpoint of the use case model that views a system as a black box focuses on descriptions of external interactions between the system and related environments. However, for embedded systems that do not disclose most implementation logics outside the system, black box-based use case models may experience the drawback that considerable information that must be defined for system developments is omitted. To solve this shortcoming, several studies have been proposed on the use of kind of white box technique in which the dynamic behaviors of embedded systems are defined first using a state diagram and the results are reflected in the requirement specifications. However, white box-based modeling has not been widely adopted by developers due to tasks that require a lot of time in the requirement analysis phase in the initial phase of the software development life cycle. This study proposes a gray box-based requirement specification method as a trade-off between two contradictory elements (the amount of information required to develop an embedded system and the cost of the effort required during the requirement analysis phase) in terms of the two approaches, the black and the white box-based models. The proposed method suggests that an appropriate depth level of embedded system modeling is required to define the requirements. This study also proposes a mechanism that automatically generates an application programming interface for each component based on the created model. The proposed method was applied to the development of a camera sensor controller in a mobile phone, and the case results proved the feasibility of the method through discussion of the application results.