COSMOS: Multi-Layered Network Survivability Project

We consider the load balancing problem in large-scale heterogeneous systems with multiple dispatchers. We introduce a general framework called Local-Estimation-Driven (LED). Under this framework, each dispatcher keeps local (possibly outdated) estimates of the queue lengths for all the servers, and the dispatching decision is made purely based on these local estimates. The local estimates are updated via infrequent communications between dispatchers and servers. We derive sufficient conditions for LED policies to achieve throughput optimality and delay optimality in heavy-traffic, respectively. These conditions directly imply delay optimality for many previous local-memory based policies in heavy traffic. Moreover, the results enable us to design new delay optimal policies for heterogeneous systems with multiple dispatchers. Finally, the heavy-traffic delay optimality of the LED framework also sheds light on a recent open question on how to design optimal load balancing schemes using delayed information.

This paper has proposed a classification rule base mining algorithm combining the genetic algorithm and intuitionistic fuzzy-rough set for large-scale intuitionistic fuzzy information system. The algorithm has proposed innovatively the definitions and measurement metrics of completeness, interaction and compatibility describing the whole rule base, and constructed a multi-objective optimization model to optimize the population size of data sample, and used the intuitionistic fuzzy-rough set to reduce the attribute set of fuzzy information system, and used intuitionistic fuzzy similar class to extract large-scale intuitionistic fuzzy information system rules, and obtained an optimal rule base with the minimal size, configuration, generation time and storage space. A threshold control mechanism is used to evaluate the completeness, interaction and correlation of rule population and improves the robustness and flexibility of sample population optimization and rule base generation. The algorithm is verified by the real aircraft health data sets. The algorithm is validated by similar mature and effective algorithms in accuracy, time complexity using real data and has good robustness and adaptability to different size large-scale fuzzy information system.

After analyzing the requirements of large-scale management system on genetic log service modules, a flexible, reliable and convenient solution, Log Service, is presented based on struts frame in order to solve the drawbacks of existing log management middleware in using or migration? The JDBC Appender is used to store the log records, parsed by the record parser, into the database. So it is convenient for audit module to view and maintain the log records. It’s shown that Log Service provides an all-sided mechanism to satisfy the logging requirement from development stage to implement stage in a large—scale system. And it also provides an effective and flexible manipulating method for the audit management information in running stage.

Traditionally measurements of service quality have followed the expectation-disconfirmation approach. Further, previous studies have shown that negative disconfirmation is more influential than positive disconfirmation. In this research, we hypothesized information systems(IS) service quality scales based on the dimensionality of the expectation-disconfirmation (ED) and desire-disconfirmation (DD) approach. Using the SERVQUAL+ instrument and data collected from 321 IS users, we developed ED and DD based IS service quality scales using contemporary methods, such as LISREL-based CFA. We have proposed and empirically validated the following two new IS service quality constructs: Service Adequacy (difference of expected service and perceived service) and Service Superiority (difference of desired service and perceived service). Our results indicate that both measures have shown better predictive power than earlier scales like SERVQUAL+ and the IS ZOT scales. We have outlined several implications of ED and DD scales to practice and research.

Nowadays, the efficiency and even the feasibility of traditional load-balancing policies are challenged by the rapid growth of cloud infrastructure and the increasing levels of server heterogeneity. In such heterogeneous systems with many load-balancers, traditional solutions, such as $JSQ$ , incur a prohibitively large communication overhead and detrimental incast effects due to herd behavior. Alternative low-communication policies, such as $JSQ(d)$ and the recently proposed $JIQ$ , are either unstable or provide poor performance. We introduce the Local Shortest Queue ( $LSQ$ ) family of load balancing algorithms. In these algorithms, each dispatcher maintains its own, local, and possibly outdated view of the server queue lengths, and keeps using $JSQ$ on its local view. A small communication overhead is used infrequently to update this local view. We formally prove that as long as the error in these local estimates of the server queue lengths is bounded in expectation , the entire system is strongly stable. Finally, in simulations, we show how simple and stable $LSQ$ policies exhibit appealing performance and significantly outperform existing low-communication policies, while using an equivalent communication budget. In particular, our simple policies often outperform even $JSQ$ due to their reduction of herd behavior. We further show how, by relying on smart servers ( i.e., advanced pull-based communication), we can further improve performance and lower communication overhead.

Air Traffic Control System (ATCS) is a large-scale information system that spreads all over the world and is widely used (Zhang et al., Modern Air Traffic Management (in Chinese). Beijing University of Aeronautics and Astronautics Press, Beijing, 2005). Although it cannot represent the entire information system, its structure, functional composition and application methods can already reflect many basic characteristics of today’s information systems, especially large-scale information systems. In this chapter, OIT is applied to explain the behavior of ATCS for demonstrating the feasibility and practicality to investigate information systems.

This paper presents an exploratory case study to examine information systems development (ISD) processes in a low methodology maturity environment, and to understand the role of control mechanisms in project success. The case involves the development of a large scale information system, which progressed without a fully-defined “master plan” or much reliance on formal methodologies, but was successfully launched nevertheless despite some delay. Data were analyzed from the lens of control theory. Results show that clan control emerged as a dominant form of informal control in a high complexity and low methodology maturity environment. Moreover, end-to-end user participation through collocation with the developers served as effective outcome control, which appeared to be a critical success factor. The reliance on behavior control was marginal, although the project manager’s effective leadership as a form of self-control also played a role in project success. This work contributes to ISD research in general and the development of a control perspective to user participation in ISD.

This paper presents a method and concepts of a supporting tool for rapid prototyping of large-scale business information systems. Our method is based on the following guidelines: (1) small team of highly skilled members with combined skills, (2) prototype-based development of subsystems and the system as a whole, (3) brainstorming sessions always involving system analysts database and application designers, and user representatives (if needed), and (4) application generator providing for efficient prototype development by maximum automation of all design phases. The also presented application generator (AppGen) is based on standardization of functional and visual characteristics of an application, a library of high-level, coarse grained components, and a set of rules for model-to-application mapping enabling automatic application reconfiguration in case of changes in the data model.

Audits are performed to ascertain the validity and reliability of information, also to provide an assessment of a system's internal control. Analyzed here is an incremental design of unified auditing and monitoring platform (UAM) in view point of business software. In fact, UAM is an integrated managing system of logs and running parameters. Database is the core of all kinds of management information system (MIS), and the more business logic implemented in database, the less coding work left to programmers. In this paper, complex network is introduced into the database table designing to visualization the internal associations which denotes the external business logic relationship. Though an example is discussed, but the approach can be widely used in various MIS system design, especially in large scale information system.

Lexical problems in large distributed information systems

It is generally acknowledged that integration of large-scale information systems is a challenging problem. A domain that particularly encounters this problem currently is healthcare, where information systems tend to be heterogeneous and in constant evolution. A particular need for health professionals is the ability to ask medical questions across a heterogeneous information system, then visualise and analyse the results in a synthetic and coherent manner. In this paper, we present a case study of a heterogeneous data source search meta-engine framework, based on category theory. This framework addresses the problem of cross-interrogation of heterogeneous data sources, such as relational database management systems, documentary database systems, or collections of documents. It additionally attempts to address the problem of constant evolution of such information systems. The framework has been successfully applied to the biomedical data of the medical information system at the Institut Curie, a major French cancer care centre. Different aspects of this work are illustrated, such as the mathematical foundations of the Prométhée framework, the methodology used for its implementation, and the impact that Prométhée has encountered since its deployment in a hospital environment.KeywordsCategory TheoryMedical Information SystemConstant EvolutionRelational Database Management SystemHeterogeneous Data SourceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The article considers general issues of managing access control to resources of large-scale information systems (LSIS) from the standpoint of formal mathematical models. The properties inherent in LSIS and the requirements imposed on its security policy implementing methods and rules of access control are analyzed. The task is set to develop new models, methods and algorithms for managing access control in LSIS.

This paper investigates the problem of distributed piecewise filtering for discrete-time large-scale nonlinear systems. The considered large-scale system is composed of a number of nonlinear subsystems and exchanges its information through communication network. Each nonlinear subsystem is described by a Takagi-Sugeno (T-S) model, and data-packet dropouts happen intermittently in communication network, and its stochastic variables are assumed to satisfy the Bernoulli random-binary distribution. Our objective is to design a distributed piecewise filter such that the filtering error system is stochastically stable with an performance. Based on a piecewise Lyapunov function and some convexifying techniques, less conservative results are developed for the distributed piecewise filtering design of the considered system in the form of linear matrix inequalities (LMIs). The effectiveness of the proposed method is validated by two examples.

In view of the characteristics with big data, high feature dimension, and dynamic for a large-scale intuitionistic fuzzy information systems, this paper integrates intuitionistic fuzzy rough sets and generalized dynamic sampling theory, proposes a generalized attribute reduction algorithm based on similarity relation of intuitionistic fuzzy rough sets and dynamic reduction. It uses dynamic reduction sampling theory to divide a big data set into small data sets and relative positive domain cardinality instead of dependency degree as decision-making condition, and obtains reduction attributes of big intuitionistic fuzzy decision information systems, and achieves the goal of extracting key features and fault diagnosis. The innovation of this paper is that it integrates generalized dynamic reduction and intuitionistic fuzzy rough set, and solves the problem of big data set which cannot be solved by intuitionistic fuzzy rough set. Taking an actual data as an example, the scientificity, rationality and effectiveness of the algorithm are verified from the aspects of stability, diagnostic accuracy, optimization ability and time complexity. Compared with similar algorithms, the advantages of the proposed algorithm for big data processing are confirmed.

To facilitate architecture development of largescale and complex systems, we have proposed an architecture engineering methodology and defined seven kernels of architecture engineering (i.e., opportunity, Stakeholder, Need, Architecture, Team, Work and Way-of-Working) which must be considered during the process of developing an architecture. Each kernel has five or six different states that can indicate the progress and health of architecture development. To further improve practicability of the defined seven kernels and their 36 states in architecture development, a reference guide is suggested based on our engineering experience in practice, which contains more than 100 items helping to check kernel states and move them forward. Using the reference guide, we conducted an application of architecture development of a complex business information system. Results show that the proposed guide can be effectively used to help architecture engineers to determine and push on the state of architecture development. Architecture development can be proceeded clearly, timely and smoothly. Moreover, all the team members can work well together.