A Fuzzy Load Balancing Service for Network Computing Based on Jini

Distributed object computing systems are widely envisioned to be the desired distributed software development paradigm due to the higher modularity and the capability of handling machine and operating system heterogeneity. As the system scales up (e.g., with larger number of server and client objects, and more machines), a judicious load balancing system is required to efficiently distributed the workload (e.g., the queries, messages/objects passing) among the different servers in the system. However, in existing distributed object middleware systems, such a load balancing facility is lacking. In this paper, we describe the design and implementation of a dynamic fuzzy-decision based load balancing system incorporated in a distributed object computing environment. The proposed approach works by using a fuzzy logic controller which informs a client object to use the most appropriate service such that load balancing among servers is achieved. We have chosen Jini to build our experimental middleware platform, on which our proposed approach as well as other approaches are implemented and compared. Extensive experiments are conducted to investigate the effectiveness of our fuzzy-decision based approach, which is found to be consistently better than other approaches

KFUPM: A CASE STUDY

ABSTRACT. The academic computing environment at King Fah

A new method to fuzzy modeling and its application in performance evaluation of tenants in incubators

As we know fuzzy modeling is one of the most powerful techniques to extract experts’ knowledge in the form of fuzzy if-then rules. In this research work, a new method to fuzzy modeling is proposed in which the main goal is to construct a fuzzy rule-base of the type of Mamdani. In the proposed method, fuzzy c-means (FCM) clustering is used for structure identification and two optimization problems are used for parameter identification. The proposed method is used to simulate experts’ knowledge for performance evaluation of tenants in incubators. The authors have implemented their proposed method in a real numerical example successfully

The importance of robust design methodology: case study of the infamous GM ignition switch recall

While a systematic quality strategy is of crucial importance for the success of manufacturing companies, the universal applicability and effectiveness of implemented quality management practices were called into question by a number of major product recalls in recent years. This article seeks to illustrate how already simple analyses and early stage design methods can help to better understand one of the potential reasons for these failures, namely the variation inherent in manufacturing, assembly, and use processes. Usually thoroughly controlled in production, it seems as if particularly the risk of unanticipated variation effects remain largely underestimated and thus unaccounted for in design practice, sometimes with disastrous consequences. To foster the awareness of this variation and to illustrate the benefits of its early consideration in product development, this paper reviews one of the most infamous recalls in automotive history, that of the GM ignition switch, from the perspective of Robust Design. It is investigated if available Robust Design methods such as sensitivity analysis, tolerance stack-ups, design clarity, etc. would have been suitable to account for the performance variation, which has led to a number of fatal product defects and the recall of 30 million vehicles. Furthermore, the disclosed legal case files were examined, offering a unique opportunity to examine how technical malfunctioning of the ignition switch could stay undetected long enough to result in fatalities