In large wireless sensor networks (WSNs), each hop might incur varying delays due to medium access contention, transmission and computation delays. Fast and efficient query responses are essential to network performance and maintenance. To save energy in battery-powered sensors, it is desirable that data be aggregated or compressed along the way toward the base-station (BS). The common method to aggregate data from network edge to the BS uses a hard-line precomputed timer that requires sensors near the network edge to respond to a query earlier than sensors in the vicinity of the BS [1], [2]. Such rigid scheduling ignores the WSNs's topology and stability. Aggregation opportunities are wasted if the query response timer is set incorrectly. Estimating and allocating precise per- hop communication timers for each node in a large WSN is difficult because timing depends on the network dynamics. We develop a novel, generic and scalable method, which we call soft-line recursive response (SRR), that bases response-wait on actual response times to previous queries using a history buffer, and therefore, is tolerant of network faults or temporal delays. Our simulations show that SRR can improve aggregation opportunities up to 120% over the hard-line approach, while increasing delay less than 5%. SRR reduces query response traffic and data redundancy in both homogeneous and heterogeneous static and mobile WSNs with a maximum O(N) transmission overhead in large WSNs of N nodes and O(logb) update cost where b is the history buffer size.

Association rule discovery in large data sets is vulnerable to producing excessive false positives, due to the multiple inference effect. Analytical results presented here indicate that Bonferonni-based solutions to this problem may have inherent limitations. Thus the paper proposes a new approach to this problem, based on simultaneous confidence intervals, computed via a novel use of the statistical bootstrap tool. The proposal here differs markedly from previous bootstrap/resampling approaches, not only in function but also in basic goal, which is to enable much more active participation by domain experts. The new method is computationally intensive, but another analytical result presented here has implications for reducing the amount of computation.

PVM, a message-passing software system for parallel processing, is used on a wide variety of processor platforms, but this portability restricts execution speed. The work here will address this problem mainly in the context of Ethernet-based systems, proposing two PVM enhancements for such systems. The first enhancement exploits the fact that an Ethernet has broadcast capability. Since unenhanced PVM must, to keep portability, avoid using broadcast, execution speed is sacrificed. In addition, the larger the system, the larger the sacrifice in speed. A solution to this problem is presented. The second enhancement is intended for use in applications in which many concurrent tasks finish at the same time, and thus simultaneously try to transmit to a master process. On an Ethernet, this produces excessively long random backoffs, reducing program speed. An enhancement, termed "programmed backoff," is proposed.

The random data perturbation (RDP) method of preserving the privacy of individual records in a statistical database is discussed. In particular, it is shown that if confidential attributes are allowed as query-defining variables, severe biases may result in responses to queries. It is also shown that even if query definition through confidential variables is not allowed, biases can still occur in responses to queries such as those involving proportions or counts. In either case, serious distortions may occur in user statistical analyses. A modified version of RDP is presented, in the form of a query adjustment procedure and specialized perturbation structure which will produce unbiased results.

Recently, there has been considerable interest in parallel disk drive systems, in which full or partial replication of the stored data is used for both fault tolerance and enhanced performance. The performance-enhancement derives both from the ability to do parallel reads, and from the reduction of seek time which results from being able to assign a read to whichever drive will produce the shortest seek. Although earlier work implied that for a k-drive system, mean seek distance for read converges to 0 as k to alpha , a refined analysis is presented which shows that this limit is actually nonzero. It is further shown that the system behaves probabilistically as if k were small, no matter how large the physical value of k is.>

The p/sub i/-persistent protocol is based on a probabilistic scheduling mechanism (see Mukherjee and Meditch, 1988). The authors further develop the protocol to make it easily implementable, by allowing it to be sensitive to changing load conditions. They study various properties of a simple algorithm which stations execute independently by using channel feedback information. This results in a fully distributed control mechanism that continuously adjusts the station probabilities p/sub i/ at their proper levels as governed by the offered traffic. An extensive simulation model has been developed to study properties of this control mechanism such as p/sub i/ settling time and accuracy, behavior under step changes in traffic load, effect of injection of additional packets, and effect of various parameters associated with the underlying algorithm. These experiments indicate that this algorithm is suitable for implementing the protocol.>

A new approach is presented for organizing a large collection of multidimensional data with an unknown distribution by partitioning the data such that the data are relatively homogeneously distributed in each block. A multidimensional tree is generated according to this partition. After the tree is generated, summary data estimation such as selectively estimation can be performed via a tree search. This approach is applicable to both ordered and categorial attributes. The merits of this method are verified theoretically and by simulation.>

There has been considerable interest in parallel disk drive systems, in which replication of the stored data is used for both fault tolerance and enhanced performance. It has been discovered that performance gains are limited by the fact that no matter how large the number of disk drives, the system still behaves probabilistically like a small system. These findings are summarized, and a greedy, that is, anticipatory, approach is proposed to deal with the problem. In this approach idle read/write heads are moved to positions which will minimize the expected seek time of the next disk access request. Substantial performance gains are found to accrue.>

The p/sub i/-persistent protocol is an excellent candidate for multiaccess communication over very long and very high-speed (unidirectional) fiber-optic bus networks because it does not suffer from the distance and bandwidth limitations of round-robin-type access mechanisms. The authors develop this protocol further to make it easily implementable, by allowing it to be sensitive to changing load conditions. In particular, they provide and study various properties of a simple algorithm which stations execute independently by using channel feedback information. This results in a fully distributed control mechanism that continuously adjusts the station probabilities p/sub i/ at their proper levels as governed by the ordered traffic, where the p/sub i/ are parameters of the p/sub i/-persistent protocol.>

An optical interconnect is proposed for multiprocessor systems, of both the tightly and loosely coupled types. This interconnect solves the problem of contention for memory and interconnect in the tightly coupled case, and the problem of network bottleneck in the loosely coupled case.

A number of mechanisms have been proposed for protecting the privacy of individual records in statistical databases. One such method is to perturb the data by adding random noise. It has been previously thought that this method, although increasing estimation variance, produces unbiased estimates. This paper demonstrates that in fact the addition of noise may introduce quite serious biases in the responses given to user queries.