18562701
Compressed Index for a Dynamic Collection of Texts
Let T be a string with n characters over an alphabet of bounded size. The recent breakthrough on compressed indexing allows us to build an index for T in optimal space (i.e., O(n) bits), while supporting very efficient pattern matching [2,4]. This paper extends the work on optimal-space indexing to a dynamic collection of texts. Precisely, we give a compressed index using O(n) bits where n is the total length of texts, such that searching for a pattern P takes O(|P|log n + occ log2 n) time where occ is the number of occurrences, and inserting or deleting a text T takes O(|T|log n) time.
8031191
Dynamic dictionary matching and compressed suffix trees
Recent breakthrough in compressed indexing data structures has reduced the space for indexing a text (or a collection of texts) of length <i>n</i> from <i>O</i>(<i>n</i> log <i>n</i>) bits to <i>O</i>(<i>n</i>) bits, while allowing very efficient pattern matching [10, 13]. Yet the compressed nature of such indices also makes them difficult to update dynamically. This paper presents the first <i>O</i>(<i>n</i>)-bit representation of a suffix tree for a dynamic collection of texts whose total length is <i>n</i>, which supports insertion and deletion of a text <i>T</i> in <i>O</i>(|<i>T</i> | log<sup>2</sup> <i>n</i>) time, as well as all suffix tree traversal operations, including forward and backward suffix links. This work can be regarded as a generalization of the compressed representation of static texts. Our new suffix tree representation serves as a core part in a compact solution for the dynamic dictionary matching problem, i.e., providing an <i>O</i>(<i>d</i>)-bit data structure for a dynamic collection of patterns of total length <i>d</i> that can support the dictionary matching query efficiently. When compared with the <i>O</i>(<i>d</i> log <i>d</i>)-bit suffix tree based solution of Amir <i>et al.</i>, the compact solution increases the query time by roughly a factor of log <i>d</i> only. In the study of the above results, we also derive the first <i>O</i>(<i>n</i>)-bit representation for maintaining <i>n</i> pairs of balanced parentheses in <i>O</i>(log <i>n</i>/log log <i>n</i>) time per operation, matching the time complexity of the previous <i>O</i>(<i>n</i> log <i>n</i>)-bit solution.
17611435
Extra unit-speed machines are almost as powerful as speedy machines for competitive flow time scheduling
We study online scheduling of jobs to minimize the flow time and stretch on parallel machines. We consider algorithms that are given extra resources so as to compensate the lack of future information. Recent results show that a modest increase in machine speed can provide very competitive performance; in particular, using O(1) times faster machines, the algorithm SRPT (shortest remaining processing time) is 1-competitive for both flow time [23] and stretch [12], and HDF (highest density first) is O(1)-competitive for weighted flow time [6]. Using extra unit-speed machines instead of faster machines is more challenging. This paper gives a non-trivial relationship between the extra-speed and extra-machine analysis. It shows that competitive results via faster machines can be transformed to similar results via extra machines, and hence giving the first algorithms that, using O(1) times unit-speed machines, are 1-competitive for flow time and stretch and O(1)-competitive for weighted flow time, respectively.
15069863
Non-migratory online deadline scheduling on multiprocessors
In this paper we consider multiprocessor scheduling with hard deadlines and investigate the cost of eliminating migration in the online setting. Let I be any set of jobs that can be completed by some migratory offline schedule on m processors. We show that I can also be completed by a non-migratory online schedule using m speed-5.828 processors (i.e., processors of 5.828 times faster). This result supplements the previous results that I can also be completed by a non-migratory offline schedule using 6m unit-speed processors [8] or a migratory online schedule using m speed-2 processors [13]. Our result is based on a simple conservative scheduling algorithm called PARK which commits a processor to a job only when the processor has zero commitment before its deadline. A careful analysis of PARK further shows that the processor speed can be reduced arbitrarily close to 1 by exploiting more processors (say, using 16m speed-1.8 processors). PARK also finds application in overloaded systems; it gives the first online non-migratory algorithm that can exploit moderately faster processors to match the performance of any migratory offline algorithm.
34112863
Compressed Indexes for Approximate String Matching
We revisit the problem of indexing a string S[1..n] to support searching all substrings in S that match a given pattern P[1..m] with at most k errors. Previous solutions either require an index of size exponential in k or need Ω(mk) time for searching. Motivated by the indexing of DNA sequences, we investigate space efficient indexes that occupy only O(n) space. For k = 1, we give an index to support matching in O(m + occ + logn loglogn) time. The previously best solution achieving this time complexity requires an index of size O(n logn). This new index can be used to improve existing indexes for k ≥2 errors. Among others, it can support matching with k=2 errors in O(m logn loglogn + occ) time.
1880699
A distance measure for bounding probabilistic belief change
We propose a distance measure between two probability distributions, which allows one to bound the amount of belief change that occurs when moving from one distribution to another. We contrast the proposed measure with some well known measures, including KL-divergence, showing how they fail to be the basis for bounding belief change as is done using the proposed measure. We then present two practical applications of the proposed distance measure: sensitivity analysis in belief networks and probabilistic belief revision. We show how the distance measure can be easily computed in these applications, and then use it to bound global belief changes that result from either the perturbation of local conditional beliefs or the accommodation of soft evidence. Finally, we show that two well known techniques in sensitivity analysis and belief revision correspond to the minimization of our proposed distance measure and, hence, can be shown to be optimal from that viewpoint.
987821
Using Clustering Information for Sensor Network Localization
Sensor network localization continues to be an important research challenge. The goal of localization is to assign geographic coordinates to each node in the sensor network. Localization schemes for sensor network systems should work with inexpensive off-the-shelf hardware, scale to large networks, and also achieve good accuracy in the presence of irregularities and obstacles in the deployment area. 
 
We present a novel approach for localization that can satisfy all of these desired properties. Recent developments in sensor network clustering algorithms have resulted in distributed algorithms that produce highly regular clusters. We propose to make use of this regularity to inform our localization algorithm. The main advantages of our approach are that our protocol requires only three randomly-placed nodes that know their geographic coordinates, and does not require any ranging or positioning equipment (i.e., no signal strength measurement, ultrasound ranging, or directional antennas are needed). So far, only the DV-Hop localization mechanism worked with the same assumptions [1]. We show that our proposed approach may outperform DV-Hop in certain scenarios, in particular when there exist large obstacles in the deployment field, or when the deployment area is free of obstacles but the number of anchors is limited.
37565473
A Scalable QoS Guaranteeing Scheme for Scheduling IP Traffic
3557483
Streaming encryption for a secure wavelength and time domain hopped optical network
We describe a working implementation of a streaming encryption system for optical networks. The 10 Gbps data stream is encrypted on the physical level in both the wavelength and time domains. Security is obtained by applying a strong pseudo-random hopping pattern to both. The AES algorithm in counter mode is used to control the switches that implement the hopping permutations. Because of the high throughput requirements, aggressive parallelizing and pipelining techniques are used to achieve data rates of 10 Gbps. The core logic of the system was implemented on the Virtex2-XC2V1000 FPGA. Using four FPGA boards and four serializer and deserializer chips, a secure switch of 4 users over 4 wavelengths can be realized, resulting in a total throughput of 10 Gbps. This system is important as a platform for further research in the area of secure optical networks.
5935513
On Bayesian Network Approximation by Edge Deletion
We consider the problem of deleting edges from a Bayesian network for the purpose of simplifying models in probabilistic inference. In particular, we propose a new method for deleting network edges, which is based on the evidence at hand. We provide some interesting bounds on the KL-divergence between original and approximate networks, which highlight the impact of given evidence on the quality of approximation and shed some light on good and bad candidates for edge deletion. We finally demonstrate empirically the promise of the proposed edge deletion technique as a basis for approximate inference.