Crime analysis has been widely studied, but problem of identifying conspirators through communication network analysis is still not well resolved. In this paper, we proposed a fuzzy clustering algorithm to detect hidd...
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ISBN:
(纸本)9781479958771
Crime analysis has been widely studied, but problem of identifying conspirators through communication network analysis is still not well resolved. In this paper, we proposed a fuzzy clustering algorithm to detect hidden criminals from topic network, which took no use of individuals' prior identity information. We first built up a local suspicion calculation from nodes' neighboring information (node and edge);and then with global information, we employed the fuzzy k-means clustering algorithm, and made the membership to suspicious group as the global suspicion degree. Experiments showed it works well on identification: known suspects gained relative high values and known innocents got relative low values.
Affinity is common among Virtual Machines (VMs) in cloud environments. If VMs collaborating on a job are split in geographically distributed clouds, the low bandwidth and high latency inter-cloud communication via a w...
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ISBN:
(纸本)9781479940875
Affinity is common among Virtual Machines (VMs) in cloud environments. If VMs collaborating on a job are split in geographically distributed clouds, the low bandwidth and high latency inter-cloud communication via a wide area network (WAN) will dramatically degrade the system performance. A potential solution is migrating all of the VMs collaborating on a job in parallel, so as to avoid wide area communication. However, if the job is too large, it becomes impractical to migrate all of the VMs simultaneously due to limited WAN bandwidth and high block dirty rate. We propose a migration optimization mechanism called Clique Migration to partition a large group of VMs into subgroups based on the traffic affinities among VMs. Then, subgroups are migrated one at a time. Based on Clique Migration, we propose and implement two algorithms called R-Min-Cut and Kmeans-SF. Analysis of the traffic trace of 68 VMs in an IBM production cluster shows that our algorithms can reduce inter-cloud traffic by 25% to 60%, when the degree of parallel migration is from 2 to 32. Tests of MPI multi-PingPing benchmark running on simulated inter-cloud environments, show that our algorithms can significantly shorten the period during which applications undergo performance degradation. Tests of MPI Reduce scatter benchmark show that R-Min-Cut can keep the performance during migration at 26% to 75% of the non-migration scenario.
Guided Local Search is a powerful meta-heuristic algorithm that has been applied to a successful Genetic Programming Financial Forecasting tool called EDDIE. Although previous research has shown that it has significan...
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ISBN:
(纸本)9781479923809
Guided Local Search is a powerful meta-heuristic algorithm that has been applied to a successful Genetic Programming Financial Forecasting tool called EDDIE. Although previous research has shown that it has significantly improved the performance of EDDIE, it also increased its computational cost to a high extent. This paper presents an attempt to deal with this issue by combining Guided Local Search with Fast Local Search, an algorithm that has shown in the past to be able to significantly reduce the computational cost of Guided Local Search. Results show that EDDIE's computational cost has been reduced by an impressive 77%, while at the same time there is no cost to the predictive performance of the algorithm.
Community detection and influence analysis are significant notions in social networks. We exploit the implicit knowledge of influence-based connectivity and proximity encoded in the network topology, and propose a nov...
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ISBN:
(纸本)9781479958771
Community detection and influence analysis are significant notions in social networks. We exploit the implicit knowledge of influence-based connectivity and proximity encoded in the network topology, and propose a novel algorithm for both community detection and influence ranking. Using a new influence cascade model, the algorithm generates an influence vector for each node, which captures in detail how the node's influence is distributed through the network. Similarity in this influence space defines a new, meaningful and refined connectivity measure for the closeness of any pair of nodes. Our approach not only differentiates the influence ranking but also effectively finds communities in both undirected and directed networks, and incorporates these two important tasks into one integrated framework. We demonstrate its superior performance with extensive tests on a set of real-world networks and synthetic benchmarks.
Over the few decades the characteristics of the magnetic disk based persistent primary storage system have remained essentially unchanged. Seek, read and write are the primitive operations that can be performed agains...
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ISBN:
(纸本)9781479949816
Over the few decades the characteristics of the magnetic disk based persistent primary storage system have remained essentially unchanged. Seek, read and write are the primitive operations that can be performed against these devices. These three operations have endured because the devices within storage subsystems have not fundamentally changed since the invention of magnetic disks. In many cases, the file systems for the existing storage arrays are custom and proprietary and tuned for the characteristics of magnetic disk. As the cost of flash memory continues to decrease, enterprises are attempting to deploy flash in primary network attached storage systems such as storage arrays. Flash memory poses unique characteristics, which requires sophisticated data structures and algorithms to exploit the performance benefits. When flash memory is used in primary storage arrays, the file systems face lot of design challenges for the optimal flash performance and device endurance. Replace the new flash arrays with existing enterprise disk based storage arrays that provide data management and protection features is a challenging task. We discussed various challenges in file system and the storage arrays for integrating flash memory arrays in the primary storage. Also we discussed the previously proposed solutions to overcome the discussed problems.
This paper introduces two distributed Bluetooth Scatternet Formation (BSF) algorithms, called BSFWAVVY (MSF) and BSFWAVVY (ODL). The first algorithm forms scatternets that contain no MS-bridges (MS-free scatternets), ...
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ISBN:
(纸本)9781479937806
This paper introduces two distributed Bluetooth Scatternet Formation (BSF) algorithms, called BSFWAVVY (MSF) and BSFWAVVY (ODL). The first algorithm forms scatternets that contain no MS-bridges (MS-free scatternets), while the second forms scatternets in which each piconet has at most k slaves (outdegree-limited scatternets). MS-freeness and outdegree-limitation are two properties that significantly improve the quality of the scatternets. Contrary to existing BSF algorithms, our algorithms consider these properties under pessimistic environments modeled as arbitrary networks (i.e. no assumptions are made on the underlying network topology). The optimality of our algorithms are proven. Future directions are proposed to further improve the empirical performance of the introduced algorithms.
Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first ...
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ISBN:
(纸本)9781479958771
Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We were able to detect significant differences in phone usage among different subgroups of the population. Our second contribution is to provide a novel methodology to predict demographic features (namely age and gender) of unlabeled users by leveraging individual calling patterns, as well as the structure of the communication graph. We provide details of the methodology and show experimental results on a real world dataset that involves millions of users.
The high performance Digital Signal Processors (DSPs) currently manufactured by Texas Instruments are heterogeneous multiprocessor architectures. Programming these architectures is a complex task often reserved to spe...
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ISBN:
(纸本)9781479968435
The high performance Digital Signal Processors (DSPs) currently manufactured by Texas Instruments are heterogeneous multiprocessor architectures. Programming these architectures is a complex task often reserved to specialized engineers because the bottlenecks of both the algorithm and the architecture need to be deeply understood in order to obtain a fairly parallel execution. The PREESM framework objective is to simplify the programming of multicore DSP systems by building on dataflow programming methods. The current functionalities of this scalable framework cover memory and time analysis, as well as automatic deadlock-free code generation. Several tutorials are provided with the tool for fast initiation of C programmers to multicore DSP programming. This paper demonstrates PREESM capabilities by comparing simulation and execution performances on a stereo matching algorithm prototyped on the TMS320C6678 8-core DSP device.
Studying price impact is important in finance and previous work examines the relationship between trade size and price impact on a number of equity markets. In this study, using recent order book data from the London ...
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ISBN:
(纸本)9781479923809
Studying price impact is important in finance and previous work examines the relationship between trade size and price impact on a number of equity markets. In this study, using recent order book data from the London Stock Exchange, we examine the price impact function for six highly-liquid stocks and novelly investigate whether the function displays time-of-day effects. The results show that price impact exhibits a power-law scaling, and that price impact is highest in the first hour of the trading day and lowest in the last ninety minutes of trading.
Bounded Model Checking (BMC) is a major verification technique for finding errors in sequential circuits by unfolding the design iteratively and converting the BMC instances into Boolean satisfiability (SAT) formulas....
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ISBN:
(纸本)9781479932467
Bounded Model Checking (BMC) is a major verification technique for finding errors in sequential circuits by unfolding the design iteratively and converting the BMC instances into Boolean satisfiability (SAT) formulas. Here, we consider incomplete designs (i.e. those containing so-called black boxes) where the verification task is to prove unrealizability of a property. A property is called unrealizable by an incomplete design, if there is an error which can not be compensated by any implementation of the black boxes. While 01X-modeling of the unknown behavior of the black boxes yields easy-to-solve SAT problems, the logic of quantified Boolean formulas (QBF) is needed for 01X-hard problems to obtain a more precise modeling. However, QBF-modeling does not guarantee success in proving unrealizability. To this purpose, we introduce the concept of QBF-hardness in this paper, a classification of problems for which the QBF-based modeling does not provide a result. Furthermore, we present an iterative method to prove the QBF-hardness. We provide a first practical example (a parameterized incomplete arbiter bus system) to demonstrate the concept.
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