01572nas a2200193   4500008004100000245010200041210006900143260000900212300001400221490000600235520091700241653001901158653002001177653001601197653001401213100001501227700001901242856011701261       2010                        eng d00aFault-tolerant meta-scheduler for price-based job scheduling by applying multi-reservation method0 aFaulttolerant metascheduler for pricebased job scheduling by app  c2010  a213 - 2180 v83 aIn market-like grids, applying an economical method for providing fault-tolerant job scheduling is necessary. Since we have to pay cost for job execution in economic grids, consumers tend to execute their jobs on a grid with minimum cost and acceptable completion time. To do this, many approaches have been proposed, but they unilaterally consider either time/cost or consumer/provider profit. Based on current research, a new approach has been proposed; the approach is an optimized, fault-tolerant method for meta-scheduler that considers bilateral satisfaction for consumer/provider and a tolerable completion time. We suppose that, if one of the provider nodes fails, there would not be enough time to start a task on a new node from the beginning. The experimental results show a promising improvement in job scheduling with less computation cost, better fault-tolerance, and an acceptable completion time.10aCheck-pointing10aFault tolerance10aReplication10aRough set1 aBouyer, A.1 aAbdullah, A.H.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960679148&partnerID=40&md5=e30a655c66545df2023a714a92a03da802066nas a2200229   4500008004100000245007200041210006900113260000900182300001200191490000600203520131500209653002101524653002301545653003901568653002001607653002001627653001301647100002001660700001701680700002201697856011701719       2007                        eng d00aA robust outlier detection scheme for collaborative sensor networks0 arobust outlier detection scheme for collaborative sensor network  c2007  a12 - 180 v53 aIn-networks, Data Aggregation is usually warranted for distributed wireless sensor networks, owing to reliability and energy efficiency reasons. Sensor nodes are usually deployed in unattended and unsafe environments and hence are vulnerable to intentional or unintentional damages. Individual nodes are prone to different type of faults such as hardware faults, crash faults etc and other security vulnerabilities wherein one or more nodes are compromised to produce bogus data so as to confuse the rest of the network in collaborative sensing applications. The availability of constrained resources and the presence of faulty nodes make designing fault tolerant information aggregation mechanisms in large sensor networks particularly challenging. In our work, we consider Byzantine type of faults, which encompasses most of the common sensor node faults [9]. Faulty nodes are assumed to send inconsistent and arbitrary values to other nodes during information exchange process. These values are termed as outliers and we use a statistical test called Modified Z-score method to reliably detect and remove outliers. We show by simulation that the proposed strategy works well for 2 major classes of collaborative sensor network applications viz. (i) Target/Event detection and (ii) Continuous data gathering.10aData aggregation10aDetection accuracy10aDistributed information processing10aFalse positives10aFault tolerance10aOutliers1 aJayashree, L.S.1 aArumugam, S.1 aVijayalakshmi, K.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-33947305265&partnerID=40&md5=2fae284d218d7852052fabf8a0ef68ca