Providing workflow function is one of the most important research issues in the next generation Internet services such as Web Service and Grid Computing. Scalability for Internet scale services, reliability for unstable Internet resources, and management functions of workflow systems are the essential requirements in these environments. However, existing workflow enactment models for enterprises could not meet these requirements. This paper proposes the PeerFlow that is a P2P based workflow enactment model, to provide workflow functions for the next generation Internet services. To apply P2P model to the workflow enactment model, we introduce the concept of the instance buddy and the index data of workflow instances, then propose the principle architecture of the PeerFlow. The instance buddy enables the autonomous processing of peers, and it is used for recovery and monitoring functions. This paper also presents the recovery capabilities of PeerFlow with formal proofs for the reliability issues and a performance evaluation with SimPy, the Python simulation package.

This letter proposes a comprehensive assessment of the mission-level damage caused by cyberattacks on an entire defense mission system. We experimentally prove that our method produces swift and accurate assessment results and that it can be applied to actual defense applications. This study contributes to the enhancement of cyber damage assessment with a faster and more accurate method.

By using distributed database systems, many advantages can be obtained such as database management cost, efficiency, and high integrity of systems through allocating fragments to many distributed sites with horizontal/vertical fragmentation of global database schema. To minimize costs, distributed algorithms must be applied so that database fragments are allocated to optimal sites. It is useful to replicate fragments, such as allocating many copies in many sites including load balancing. But there are too many possible combinations of each site and fragment, making it impossible to find a solution in real time, i.e., it is an NP-complete problem. This paper proposes near optimal heuristic algorithms for minimizing cost by defining a cost model based on read and update queries that are requested in many sites. Various factors are applied to the proposed algorithms for sizing efficient network resources that compute database transactions as remote query or update requests for consistency in replicated database systems. For network load balancing, incoming network traffic table is defined in each site. A request transaction from unallocated sites to allocated sites can be accessed properly at any other replicated sites by using the network traffic table. Finally, some experimental results verified the proposed algorithms by comparing actual cases of database allocation.

This paper proposes a feature-based service identification method to improve productivity using a feature relationship; where a feature can express service properties. We define the distance measured between features by considering their selective (node) and relational (edge) attributes and present the service boundary concept. The result of an evaluation of the proposed method shows that it has higher productivity than existing methods.

The TMN that appears to operate the various communication networks generally and efficiently is developed under the different platform environment such as the different hardware and the different operating system. One of the main problems is that all the agents of the TMN system must be duplicated and maintain the software and the data blocks that perform the identical function. Therefore, the standard of the Q3 interface development cannot be defined and the multi-platform cannot be supported in the development of the TMN agent. In order to overcome these problems, the Farming methodology that is based on the Farmer model has been suggested. The main concept of the Farming methodology is that the software and the data components that are duplicated and stored in each distributed object are saved in the Platform Independent Class Repository (PICR) by converting into the format of the independent componentware in the platform, so that the componentwares that are essential for the execution can be loaded and used statically or dynamically from PICR as described in the framework of each distributed object. The distributed TMN agent of the personal communication network is designed and developed by using the Farmer model.

The Semantic Web uses RDF/RDFS, which can enable a machine to understand web data without human interference. But most web data is not available in RDF/RDFS documents because most web data is still stored in databases. It is much more favorable to use stored data in a database to build the Semantic Web. This paper proposes an enhanced relational RDF/RDFS interoperable data model (ER2iDM) and a transformation procedure from relational data model (RDM) to RDF/RDFS based on ER2iDM. The ER2iDM is a data model that plays the role of an inter-mediator between RDM and RDF/RDFS during a transformation procedure. The data and schema information in the database are migrated to the ER2iDM according to the proposed translation procedures without incurring loss of meaning of the entities, relationships, and data. The RDF/RDFS generation tool makes a RDF/RDFS XML document automatically from the ER2iDM. The proposed ER2iDM and transformation procedure provides detailed guidelines for transformation from RDM to RDF/RDFS unlike existing studies; therefore, we can more efficiently build up the Semantic Web using database stored data.

We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.

Metadata registry (MDR) is based on the international standard ISO/IEC 11179. The committee of ISO/IEC JTC 1/SC 32, which had standardized the MDR, has started to improvise the MDR, and the improvised version is named extended MDR (XMDR). However, the XMDR does not fully support the ontology concept, and no method is available for mapping ontology registrations onto registries. To overcome the limitations of the outdated XMDR, this paper proposes an extended XMDR (XMDR+) framework. The XMDR+ framework provides a method for mapping of ontology registrations between the metadata registry and ontologies. To improve the functions of the XMDR, we have proposed herein a framework that is capable of defining a model that manages the relations not only among ontological concepts but also among instances, and guarantees the management and storage of their relationships for supporting valid relations of the ontologies.

In this letter, a new received power pairing scheduling (PPS) algorithm is proposed for Multi User Multiple Input and Multiple Output (MU-MIMO) systems. In contrast to existing algorithms that manage complex orthogonal factors, the PPS algorithm simply utilizes CINR to determine a MU-MIMO pair. Simulation results show that the PPS algorithm achieves up to 77% of MU-MIMO gain of determinant pairing scheduling (DPS) with low complexity.