Data center resilience assessment : storage, networking and security.

Data centers (DC) are the core of the national cyber infrastructure. With the incredible growth of critical data volumes in financial institutions, government organizations, and global companies, data centers are becoming larger and more distributed posing more challenges for operational continuity in the presence of experienced cyber attackers and occasional natural disasters. The main objective of this research work is to present a new methodology for data center resilience assessment, this methodology consists of: • Define Data center resilience requirements. • Devise a high level metric for data center resilience. • Design and develop a tool to validate and the metric. Since computer networks are an important component in the data center architecture, this research work was extended to investigate computer network resilience enhancement opportunities within the area of routing protocols, redundancy, and server load to minimize the network down time and increase the time period of resisting attacks. Data center resilience assessment is a complex process as it involves several aspects such as: policies for emergencies, recovery plans, variation in data center operational roles, hosted/processed data types and data center architectures. However, in this dissertation, storage, networking and security are emphasized. The need for resilience assessment emerged due to the gap in existing reliability, availability, and serviceability (RAS) measures. Resilience as an evaluation metric leads to better proactive perspective in system design and management. The proposed Data center resilience assessment portal (DC-RAP) is designed to easily integrate various operational scenarios. DC-RAP features a user friendly interface to assess the resilience in terms of performance analysis and speed recovery by collecting the following information: time to detect attacks, time to resist, time to fail and recovery time. Several set of experiments were performed, results obtained from investigating the impact of routing protocols, server load balancing algorithms on network resilience, showed that using particular routing protocol or server load balancing algorithm can enhance network resilience level in terms of minimizing the downtime and ensure speed recovery. Also experimental results for investigating the use social network analysis (SNA) for identifying important router in computer network showed that the SNA was successful in identifying important routers. This important router list can be used to redundant those routers to ensure high level of resilience. Finally, experimental results for testing and validating the data center resilience assessment methodology using the DC-RAP showed the ability of the methodology quantify data center resilience in terms of providing steady performance, minimal recovery time and maximum resistance-attacks time. The main contributions of this work can be summarized as follows: • A methodology for evaluation data center resilience has been developed. • Implemented a Data Center Resilience Assessment Portal (D$-RAP) for resilience evaluations. • Investigated the usage of Social Network Analysis to Improve the computer network resilience

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Ontology Network for Social Network Analysis in a Knowledge Management Context

Organizational knowledge is one of the most valuable assets that companies own today. For several decades organizations have been developing strategies to manage knowledge with particular emphasis on tacit knowledge discovery. The particular dynamic that presents the evolution and transfer of tacit knowledge is closely tied to the relations between people. For this reason, Social Network Analysis (SNA) can be a powerful tool to support a Knowledge Management (KM) initiative. Despite usefulness recognition of SNA techniques within KM processes, there is still remains the initial problem of data collection and representation (problem shared by both initiatives). The aim of this paper is to analyze an ontology network usefulness to obtain the necessary knowledge structure to feed the SNA-KM integration architecture proposed.Sociedad Argentina de Informática e Investigación Operativa (SADIO

A comparison of integration architectures

This paper presents GenSIF, a Generic Systems Integration Framework. GenSIF features a pre-planned development process on a domain-wide basis and facilitates system integration and project coordination for very large, complex and distributed systems. Domain analysis, integration architecture design and infrastructure design are identified as the three main components of GenSIF. In the next step we map Beilcore\u27s OSCA interoperability architecture, ANSA, IBM\u27s SAA and Bull\u27s DCM into GenSIF. Using the GenSIF concepts we compare each of these architectures. GenSIF serves as a general framework to evaluate and position specific architecture. The OSCA architecture is used to discuss the impact of vendor architectures on application development. All opinions expressed in this paper, especially with regard to the OSCA architecture, are the opinions of the author and do not necessarily reflect the point of view of any of the mentioned companies

ERP Conceptual Ecology

The technological evolution of recent years has made that information systems frequently adapt to the market realities to fulfill the improvements of the company’s organizational processes. In this context, new paradigms, approaches, and concepts were disseminated through the new realities of information systems. This study aims to verify how ERP (Enterprise Resource Planning) has been related to other information systems within its ecosystem. For this purpose, we have reviewed the literature based on 650 publications whose central theme was the ERP. The data were treated through a graphical analysis, inspired by SNA (Social Network Analysis), represented by related ERP concepts. The study results, determine the connection degree between the concepts that emerged with the technological evolution and the ERP, thus representing the ERP interoperability tendencies, over the last years. The study concludes that ERPs have been improving and substantially increasing the conditions of nteroperability with other information systems and with new organizational concepts that have emerged through the technological availability. This fact led to a better organizational process’s adoption and more organizational performance.info:eu-repo/semantics/publishedVersio

Business Process Management, Social Network Analysis and Knowledge Management: A Triangulation of Sorts?

As its name suggests, Business Process Management seeks to manage the processes companies typically undertake on a day to day basis. In line with many management techniques, improvements can made through analysing at varying granularity how processes are actually undertaken compared to how management may consider they are being accomplished and vice versa. One innovative way Business Process Management may be improved is through the use of Social Network Analysis to observe actual working relationships among employees. This latter technique permits the workflow manager specifically to consider how well matched employees are to their workflow and as a result of this, we have a means of either reconstructing workflows or alternatively employee practices. A small research-in-progress case study is presented illustrating how these principles may be applied in practice. Overall one may consider such improvements as aiding in the knowledge management of the organization as a whole

Review and Comparative Analysis of Distributed Knowledge Management Systems

Distributed technologies attract researchers interest as they propose many technological, but as well organizational and end-user benefits. With development of Web 2.0 and Cloud computing, distributed networks are considered as new source of business opportunities. The present research will identify advantages and limitations of distributed knowledge management systems (DKMS). Thus technologies and models of distrubuted KMS will be assessed as an alternative approach to centralized KMS. A review of several theoretical DKMS model will be made in order to outline the common characteristics and alternative approaches to DKMS architecture. At the end will be summarised conclusions for development of new theoretical model of user-centered DKMS

Social Collaboration Analytics for Enterprise Collaboration Systems: Providing Business Intelligence on Collaboration Activities

The success of public Social Media has led to the emergence of Enterprise Social Software (ESS), a new type of collaboration software for organizations that incorporates “social features”. Surveys show that many companies are trying to implement ESS but that adoption is slower than expected. We believe that in order to understand the issues with its implementation we need to first examine and understand the “social” interactions that are taking place in this new kind of collaboration software. We propose Social Collaboration Analytics (SCA), a specialized form of examination of log files and content data, to gain a better understanding of the actual usage of ESS. Our research was guided by the CRISP-DM approach. We first analyzed the data available in a leading ESS. Together with leading user companies of this ESS, we then developed a framework for Social Collaboration Analysis, which we present in this paper