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.
19601656
A mutation-sensitive approach for locating conserved gene pairs between related species
This paper proposes a new approach for solving the whole genome alignment problem. Our approach is based on a new structural optimization problem (called the MUM selection problem) related to mutations via reversals and transpositions. We have devised a practical algorithm for this optimization problem and have evaluated the algorithm using 15 pairs of human and mouse chromosomes. The results show that our algorithm is both effective and efficient. More specifically, our algorithm can reveal 91% of the conserved gene pairs that have been reported in the literature. When compared to existing software MUMmer and MaxMinCluster , our algorithm uncovers 15% and 7% more genes on average, respectively. The sensitivity of our algorithm is also slightly higher. The paper concludes with a remark on the computational hardness of the MUM selection problem.
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.
18442431
Understanding the Balanced Effects of Belief and Feeling on Information Systems Continuance
There are innumerable studies on technology adoption as well as continuance of usage. A review of previous research shows that cognitive factors are considered prominently in information technology adoption and continuance while the affective feelings of users are not. Although attitude and user satisfaction are common factors considered in information systems research, these factors only involve partial aspects of feelings. Researchers in the marketing areas, as well as the psychology area, begin to note the importance of feelings in understanding and predicting human and customer behavior. In many modern applications, such as mobile Internet services, user feelings are expected to be important, since users are not just technology users but also service consumers. Drawing upon the support of consumer research, social psychology, and computer science, this study proposes a balanced belief–feeling model of IS continuance. In the process of developing this model, the concepts of attitude, belief, and feelings are further articulated, defined, and distinguished. The balanced model is tested in a survey of mobile Internet users. The results established the validity of the model. A comparison with the IS continuance model shows that the new model can explain significantly more variance in continuance intention, taking into account that the new model has more factors. We offer theoretical reasoning for the balanced effects of belief and feeling on IS continuance and discuss the theoretical and practical implications of this study.
5337517
Throughput Optimized SHA-1 Architecture Using Unfolding Transformation
In this paper, the authors analyze the theoretical delay bound of the SHA-1 algorithm and propose architectures to achieve high throughput hardware implementations which approach this bound. According to the results of FPGA implementations, 3,541 Mbps with a pipeline and 893 Mbps without a pipeline were achieved. Moreover, synthesis results using 0.18mum CMOS technology showed that 10.4 Gbps with a pipeline and 3.1 Gbps without a pipeline can be achieved. These results are much faster than previously published results. The high throughputs are due to the unfolding transformation, which reduces the number of required cycles for one block hash. The authors reduced the required number of cycles to 12 cycles for a 512 bit block and showed that 12 cycles is the optimal in our design
11373384
Joint Call Admission Control for Next Generation Wireless Network
Next generation wireless network (NGWN) will be heterogeneous in nature where different radio access technologies (RATs) such as UMTS, WiMax, WLAN, etc, coexist. This coexistence necessitates joint radio resource management (JRRM). This paper focuses on joint call admission control (JCAC) for NGWN. Factors that determine a user's preference for a particular RAT are discussed. We propose a JCAC algorithm which considers the user's preference in making admission decision. A specific case where the user prefers to be served by the RAT which has the least service cost is modeled and evaluated using Markov decision process. The results obtained shows that overall service cost in heterogeneous network can be significantly reduced by using the proposed joint call admission control
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.
239370
SIA: secure information aggregation in sensor networks
Sensor networks promise viable solutions to many monitoring problems. However, the practical deployment of sensor networks faces many challenges imposed by real-world demands. Sensor nodes often have limited computation and communication resources and battery power. Moreover, in many applications sensors are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the sensor's cryptographic keys.One of the basic and indispensable functionalities of sensor networks is the ability to answer queries over the data acquired by the sensors. The resource constraints and security issues make designing mechanisms for information aggregation in large sensor networks particularly challenging.In this paper, we propose a novel framework for secure information aggregation in large sensor networks. In our framework certain nodes in the sensor network, called aggregators, help aggregating information requested by a query, which substantially reduces the communication overhead. By constructing efficient random sampling mechanisms and interactive proofs, we enable the user to verify that the answer given by the aggregator is a good approximation of the true value even when the aggregator and a fraction of the sensor nodes are corrupted. In particular, we present efficient protocols for secure computation of the median and the average of the measurements, for the estimation of the network size, and for finding the minimum and maximum sensor reading. Our protocols require only sublinear communication between the aggregator and the user. To the best of our knowledge, this paper is the first on secure information aggregation in sensor networks that can handle a malicious aggregator and sensor nodes.