Load Balance Strategy of Data Routing Algorithm Using Semantics for Deduplication Clusters

The backup requirement of data centres is tremendous as the size of data created by human is massive and is increasing exponentially.Single node deduplication cannot meet the increasing backup requirement of data centres.A feasible way is the deduplication cluster,which can meet it by adding storage nodes.The data routing strategy is the key of the deduplication cluster.DRSS（data routing strategy using semantics） improves the storage utilization of MCS（minimum chunk signature） data routing strategy a lot.However,for the large deduplication cluster,the load balance of DRSS is worse than MCS.To improve the load balance of DRSS,we propose a load balance strategy used for DRSS,namely DRSSLB.When a node is overloaded,DRSSLB iteratively migrates the current smallest container of the node to the smallest node in the deduplication cluster until this overloaded node becomes non-overloaded.A container is the minimum unit of data migration.Similar files sharing the same features or file names are stored in the same container.This ensures the similar data groups are still in the same node after rebalancing the nodes.We use the dataset from the real world to evaluate DRSSLB.Experimental results show that,for various numbers of nodes of the deduplication cluster,the data skews of DRSSLB are under predefined value while the storage utilizations of DRSSLB do not nearly increase compared with DRSS,with the low penalty（the data migration rate is only6.5% when the number of nodes is 64）.

Evaluation of global navigation satellite system spoofing efficacy

The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.

Index Conditions of Resolution

In this paper, the following results are proved: (1) Using both deletion strategy and lock strategy, resolution is complete for a clause set where literals with the same predicate or proposition symbol have the same index. (2) Using deletion strategy, both positive unit lock resolution and input lock resolution are complete for a Horn set where the indexes of positive literals are greater than those of negative literals. (3) Using deletion strategy, input half-lock resolution is complete for a Horn set. Keywords Resolution - index strategy - deletion strategy - unit resolution - input resolution Xiaochun Cheng had his Ph.D in 1996. He has been working as a lecturer at The University of Reading since 2000. He is a guest professor at North East Normal University and at Beijing Normal University. His research interests include theoretical and applied aspects on decision support systems, knowledge-based systems, intelligent systems.