34728545
Data dissemination with ring-based index for wireless sensor networks
In current sensor networks, sensor nodes are capable of not only measuring real world phenomena, but also storing, processing and transferring these measurements. Many data dissemination techniques have been proposed for sensor networks. However, these techniques may not work well in a large scale sensor network where a huge amount of sensing data are generated, but only a small portion of them are queried. In this paper, we propose an index-based data dissemination scheme to address the problem. This scheme is based on the idea that sensing data are collected, processed and stored at the nodes close to the detecting nodes, and the location information of these storing nodes is pushed to some index nodes, which act as the rendezvous points for sinks and sources. We further extend the scheme with an adaptive ring-based index (ARI) technique, in which the index nodes for one event type form a ring surrounding the location which is determined by the event type, and the ring can be dynamically reconfigured for fault tolerance and load balance. Analysis and simulations are conducted to evaluate the performance of the proposed index-based scheme. The results show that the index-based scheme outperforms the external storage-based scheme, the DCS scheme, and the local storage-based schemes with flood-response style. The results also show that using ARI can tolerate clustering failures and achieve load balance.
16468092
Group rekeying for filtering false data in sensor networks: a predistribution and local collaboration-based approach
When a sensor network is deployed in hostile environments, the adversary may compromise some sensor nodes, and use the compromised nodes to inject false sensing reports or modify the reports sent by other nodes. In order to defend against the attacks with low cost, researchers have proposed symmetric group key-based en-route filtering schemes, such as SEF [F. Ye et al., March 2004] and I-LHAP [S. Zhu et al., 2004]. However, if the adversary has compromised a large number of nodes, many group keys can be captured, and the filtering schemes may become ineffective or even useless. To deal with node compromise, the compromised nodes should be identified and the innocent nodes should update their group keys. Some existing intruder identification schemes can be used to identify the compromised nodes, but most existing group rekeying schemes are not suitable for sensor networks since they have large overhead and are not scalable. To address the problem, we propose a family of predistribution and local collaboration-based group rekeying (PCGR) schemes. These schemes are designed based on the ideas that future group keys can be preloaded to the sensor nodes before deployment, and neighbors can collaborate to protect and appropriately use the preloaded keys. Extensive analyses and simulations are conducted to evaluate the proposed schemes, and the results show that the proposed schemes can achieve a good level of security, outperform most previous group rekeying schemes, and significantly improve the effectiveness of filtering false data.
60809080
Phase Transitions of the Asymmetric Traveling Salesman
We empirically study phase transitions of the asymmetric Traveling Salesman. Using random instances of up to 1,500 cities, we show that many properties of the problem, including the backbone and optimal tour cost, experience sharp transitions as the precision of intercity distances increases across a critical value. We also show that the average computational cost of the well-known branch-and-bound subtour elimination algorithm for the problem also exhibits a threshold behavior, transitioning from easy to difficult as the distance precision increases. These results provide strong positive evidences to a decade-long open question regarding the existence of phase transitions of the Traveling Salesman.
28591822
Multicast Routing with Minimum Energy Cost and Minimum Delay in Wireless Sensor Networks
In this paper, we consider the multicast routing with minimum energy cost and minimum delay (MEMD) in wireless sensor networks under the access control scheme of Spatial Time Division Multiple Access (STDMA). We formulate and explore both MEMD multicast and ME multicast, and show that the latter is just the Maximum Leaf Spanning Tree (MLST) problem, which is NP-complete. A 2-approximation algorithm is proposed for the MLST problem through improving a known one. Based on this algorithm, an approximation algorithm is obtained for the MEMD multicast problem. To further improve the delay result, we provide another approximation algorithm for our main problem using a different approach. These algorithms are all near linear in the size of the network graph, and also are shown to have good performance by simulation results.
7100298
ILM: a web server for predicting RNA secondary structures with pseudoknots
The ILM web server provides a web interface to two algorithms, iterated loop matching and maximum weighted matching, for efficiently predicting RNA secondary structures with pseudoknots. The algorithms can utilize either thermodynamic or comparative information or both, and thus can work on both aligned and individual sequences. Predicted secondary structures are presented in several formats compatible with a variety of existing visualization tools. The service can be accessed at http://cic.cs.wustl.edu/RNA/.
8235488
Enhancing data cache reliability by the addition of a small fully-associative replication cache
Soft error conscious cache design is a necessity for reliable computing. ECC or parity-based integrity checking technique in use today either compromises performance for reliability or vice versa, and the N modular redundancy (NMR) scheme is too costly for microprocessors and applications with stringent cost constraint. This paper proposes a novel and cost-effective solution to enhance data reliability with minimum impact on performance. The idea is to add a small fully-associative cache to store the replica(s) of every write to the L1 data cache. The replicas can be used to detect and correct soft errors. The replication cache can also be used to increase performance by reducing the L1 data cache miss rate. Our experiments show that more than 97% read hits of the L1 data cache can find replicas available in a replication cache of 8 blocks.
12047559
Binary analysis and optimization-based normalization of gene expression data
MOTIVATION
Most approaches to gene expression analysis use real-valued expression data, produced by high-throughput screening technologies, such as microarrays. Often, some measure of similarity must be computed in order to extract meaningful information from the observed data. The choice of this similarity measure frequently has a profound effect on the results of the analysis, yet no standards exist to guide the researcher.


RESULTS
To address this issue, we propose to analyse gene expression data entirely in the binary domain. The natural measure of similarity becomes the Hamming distance and reflects the notion of similarity used by biologists. We also develop a novel data-dependent optimization-based method, based on Genetic Algorithms (GAs), for normalizing gene expression data. This is a necessary step before quantizing gene expression data into the binary domain and generally, for comparing data between different arrays. We then present an algorithm for binarizing gene expression data and illustrate the use of the above methods on two different sets of data. Using Multidimensional Scaling, we show that a reasonable degree of separation between different tumor types in each data set can be achieved by working solely in the binary domain. The binary approach offers several advantages, such as noise resilience and computational efficiency, making it a viable approach to extracting meaningful biological information from gene expression data.