Abstract-We present a framework and a set of algorithms for determining faults in networks when large scale outages occur. The design principles of our algorithm, netCSI, are motivated by the fact that failures are geographically clustered in such cases. We address the challenge of determining faults with incomplete symptom information due to a limited number of reporting nodes. netCSI consists of two parts: a hypotheses generation algorithm, and a ranking algorithm. When constructing the hypothesis list of potential causes, we make novel use of positive and negative symptoms to improve the precision of the results. In addition, we propose pruning and thresholding along with a dynamic threshold value selector, to reduce the complexity of our algorithm. The ranking algorithm is based on conditional failure probability models that account for the geographic correlation of the network objects in clustered failures. We evaluate the performance of netCSI for networks with both random and realistic topologies. We compare the performance of netCSI with an existing fault diagnosis algorithm, MAX-COVERAGE, and demonstrate an average gain of 128 percent in accuracy for realistic topologies. [7]. Massive outages tend to create faults at multiple components that are geographically close to each other. We call these failures clustered failures. Until now, the prior work in the area of fault diagnosis has focused on independent failures [1], [3], [7]. The performance of these algorithms degrades when applied to clustered failures. In this paper, we propose netCSI, a new algorithm that is designed to effectively identify faulty network components under clustered failures. To show the benefits of our algorithm, we compare it with an existing algorithm that is proposed for independent failures. netCSI determines possible causes of large-scale failures using a knowledge base and end-to-end symptom information. The knowledge base contains information about possible paths between different source-destination pairs and the inferred topology of the network. The end-to-end symptoms reflect end-to-end connectivity or disconnectivity in the network and are observed when a failure occurs. These symptoms include both negative information, such as which source-destination pairs are disconnected, as well as positive information, such as which source-destination pairs can still communicate. Keywords-Fault diagnosis, large-scale network failures, incomplete information, clustered failures. I. INTRODUCTIONOnce a clustered failure occurs, netCSI uses the knowledge base and symptoms to generate a list of possible causes of the outage, called the hypothesis list. Then, a ranking algorithm is applied to the hypothesis list to rate the possible causes.The main assumption in the existing fault diagnosis algorithms [1], [2], [7] is that complete and accurate information is available at the network manager. However, during large-scale failures, it is very unlikely that complete end-toend symptom information will be available, because reporting nodes ...

Transactions are vital for database management systems (DBMSs) because they provide transparency to concurrency and failure. Concurrent execution of transactions may lead to contention for access to data, which in a multilevel secure DBMS (MLSIDBMS) may lead to insecurity. In this paper we examine security issues involved in database concurrency control for MLS/DBMSs and show how a scheduler can affect security. We introduce Data Conflict Security; (DC-Security) a property that implies a system is free of convert channels due to contention for access to data. We present a definition of DC Security based on noninterference. Two properties that constitute a necessary condition for DC-Security are introduced along with two other simpler necessary conditions. We have identified a class of schedulers we call Output-State-Equivalent for which another criterion implies DC-Security. The criterion considers separately the behavior of the scheduler in response to those inputs that cause rollback and those that do not. We characterize the security properties of several existing scheduling protocols and find many to be insecure

The food basket of the world is diversifying toward high-value crops. A diversified cropping system offers multifaceted opportunities for farmers. The nature of diversification in developing countries is significantly different at both farming and cropping levels; thus, it is felt important to investigate such a study at different land size holding. This study is conducted to examine the spatiotemporal pattern of crop diversification under different land size classes in the state of West Bengal, which assumes as a representative image of India. The study uses secondary data obtained from the Agriculture Census for the years 1995–1996 and 2015–2016. Gibbs-Martin’s diversification technique is employed for the calculation of the diversification index. Overall analyses reveal that the stunting change in diversification is noted in marginal, small, large, and all land classes. The implication of such growth pushes the rural economy in a skewed direction. For de-stunting growth in diversification index, short- and long-term policy push from public and private agencies is the need of the hour.

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