Cluster of small unmanned aerial vehicles (SUAVs) has become a subject of significant interest as a hopefully low-cost solution for the high-threat environment during modern warfare. Therein, the most fundamental issu...
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Cluster of small unmanned aerial vehicles (SUAVs) has become a subject of significant interest as a hopefully low-cost solution for the high-threat environment during modern warfare. Therein, the most fundamental issue is the cooperation control problem of these SUAVs. Moreover, it is still an open problem that how to control such a complex system flying as a flock while following an expected trajectory. In addition, how to organize the individuals belonging to one system is really a great challenge for large-scale systems. Since leader-follower structures widely exist in nature among the social animals, one leader-follower structure is introduced for effective organization of the large-scale cluster. A distributed and simplified flocking algorithm is proposed to enable the followers to fly in a cohesive configuration under the guidance of the leader and avoid collision with each other. The distributed protocol of the follower is proposed by just relying on the position-related measurement and the attitude-angle measurement in favor of the convenient engineering application. Numerical simulations are provided to illustrate the effectiveness of the cooperation approach for large-scale clusters of the SUAVs.
This paper describes a novel uplink scheduling (ULSC) algorithm for the Galileo system. The algorithm is designed to meet the stringent dissemination requirements that are currently foreseen for the provision of the G...
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This paper describes a novel uplink scheduling (ULSC) algorithm for the Galileo system. The algorithm is designed to meet the stringent dissemination requirements that are currently foreseen for the provision of the Galileo Commercial Service (CS). In particular, these include "link availability" (LA) requirements that call for a minimum percentage of time ("availability") when a minimum number of satellites ("space vehicles," SVs), connected with an uplink station antenna, shall be in view with a generic user at a minimum elevation angle. LA requirements for CS were not fully considered in the design phase of the ULSC algorithm, which is currently implemented at the Mission and Uplink Control Facility (MUCF) of the Galileo Ground Segment. Similarly, this type of requirements is not considered in the ULSC algorithms available in the scientific literature. In particular, current solutions take into account only specifications about 1) the maximum "gap" duration between two subsequent contacts and 2) the minimum contact duration (MCD). In the new ULSC algorithm, LA specifications are effectively dealt with by a proper selection of the subset of the SVs to be allocated. In particular, the proposed selection scheme takes into account the specifications about both maximum gap duration and MCD while maximizing the "spatial diversity" of the solution. Such a diversity is defined as the union of the coverage areas of the allocated satellites. The performance of the new ULSC algorithm is evaluated based on the final deployment stage (full operational capability) of the Galileo system. The performance is also compared with that of the ULSC algorithm currently implemented at the Galileo MUCF ("reference" algorithm). Numerical results show that, compared to the reference algorithm, the average disconnection duration is reduced by more than 50%. In addition, the availability of the links needed for the provision of CS is significantly improved (up to 7%). As a result, preliminar
NOVEMBER 1958, AT A SIX-DAY INTERNATIONAL CONFERence devoted to scientific information, the inventor Hans Peter Luhn demonstrated a series of his electromechanical machines. They looked rather ordinary. Much like othe...
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NOVEMBER 1958, AT A SIX-DAY INTERNATIONAL CONFERence devoted to scientific information, the inventor Hans Peter Luhn demonstrated a series of his electromechanical machines. They looked rather ordinary. Much like other computing devices of the day, they were boxy and utilitarian, designed to scoop and sort tall stacks of punch cards into slots and bins.
Recently, rapid growth in data services has ushered in the so-called big data era, and data mining and analysis techniques have been widely adopted to extract value from data for different applications. Channel modeli...
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Recently, rapid growth in data services has ushered in the so-called big data era, and data mining and analysis techniques have been widely adopted to extract value from data for different applications. Channel modeling also benefits in this era, in particular by exploiting algorithmic techniques developed for big data applications. In this article, the challenges and opportunities in clustering-enabled wireless channel modeling are discussed in this context. First, some well known clustering techniques, which are potentially capable of enabling clustered channel modeling, are presented. Next, the motivation of cluster-based channel modeling is presented. The typical concepts of clusters used in channel models are summarized, and the state-of-the-art clustering and tracking algorithms are reviewed and compared. Finally, several promising research problems for channel clustering are highlighted.
Data comparison is one of the core tasks in exploratory analysis, which combines algorithmic analysis and interactive visualization in a visual data comparison process. Comparison of large and complex datasets require...
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Data comparison is one of the core tasks in exploratory analysis, which combines algorithmic analysis and interactive visualization in a visual data comparison process. Comparison of large and complex datasets requires several steps-i.e., a workflow. This article discusses the comparison process, its research challenges, and examples of solutions.
Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems, there are several types of noise that can affect the performance of distributed machine learning algori...
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Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems, there are several types of noise that can affect the performance of distributed machine learning algorithms-straggler nodes, system failures, or communication bottlenecks-but there has been little interaction cutting across codes, machine learning, and distributed systems. In this paper, we provide theoretical insights on how coded solutions can achieve significant gains compared with uncoded ones. We focus on two of the most basic building blocks of distributed learning algorithms: matrix multiplication and data shuffling. For matrix multiplication, we use codes to alleviate the effect of stragglers and show that if the number of homogeneous workers is n, and the runtime of each subtask has an exponential tail, coded computation can speed up distributed matrix multiplication by a factor of log n. For data shuffling, we use codes to reduce communication bottlenecks, exploiting the excess in storage. We show that when a constant fraction a of the data matrix can be cached at each worker, and n is the number of workers, coded shuffling reduces the communication cost by a factor of (alpha + 1/n)gamma(n) compared with uncoded shuffling, where gamma(n) is the ratio of the cost of unicasting n messages to n users to multicasting a common message (of the same size) to n users. For instance, gamma(n) similar or equal to n if multicasting a message to n users is as cheap as unicasting a message to one user. We also provide experimental results, corroborating our theoretical gains of the coded algorithms.
In this article, we have undertaken a performance comparison of different variants and hybridized schemes of differential evolution (DE) algorithms with respect to several antenna and array designs. These include DE/r...
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In this article, we have undertaken a performance comparison of different variants and hybridized schemes of differential evolution (DE) algorithms with respect to several antenna and array designs. These include DE/rand/1, self-adaptive DE (SADE), DE with global and local neighborhood search (DEGL), biogeography-based optimization with DE (BBODE), modified DE (MDE), MDE with p-best crossover strategy (MDE-pBX), improved DE (IDE), harmonic search DE (HSDE), DE with an individual dependent mechanism (DE-IDP-IDM), and adaptive DE with optimization-state estimation (ADE).
In this paper, a novel distributed algorithm for asynchronous blind macro-calibration in sensor networks with noisy measurements is proposed. The algorithm is formulated as a set of instrumental variable type recursio...
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In this paper, a novel distributed algorithm for asynchronous blind macro-calibration in sensor networks with noisy measurements is proposed. The algorithm is formulated as a set of instrumental variable type recursions for estimating parameters of sensor calibration functions. It is proved using asynchronous stochastic approximation arguments and properties of block-diagonally dominant matrices that the algorithm achieves asymptotic consensus for sensor gains and offsets in the mean square sense and with probability one. Recommendations for system design in terms of the choice of a priori tunable weights are provided. Special attention is paid to the situation when a subset of sensors in the network (reference sensors) remains with fixed characteristics. In the case of only one reference sensor, convergence of the remaining sensors to its characteristics is proved. In the case of more than one reference sensor, it is proved that the calibration parameters converge to points that depend only on the characteristics of the reference sensors and the network properties.
As concerns about discrimination in black box machine learning systems rise, a legal "right to an explanation" has emerged as an attractive approach for governance. Meaningful information about algorithmic l...
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As concerns about discrimination in black box machine learning systems rise, a legal "right to an explanation" has emerged as an attractive approach for governance. Meaningful information about algorithmic logics is more technically possible than commonly thought, but this risks a new "transparency fallacy"-an illusion of remedy over a substantive provision.
State-of-the-art microservices have been attracting more attention in recent years. A broad spectrum of online interactive applications are now programmed to service chains on the cloud, seeking better system scalabil...
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State-of-the-art microservices have been attracting more attention in recent years. A broad spectrum of online interactive applications are now programmed to service chains on the cloud, seeking better system scalability and lower operating costs. Different from the conventional batch jobs, most of these applications consist of multiple stand-alone services that communicate with each other. These step-by-step operations unavoidably introduce higher latency to the delay-sensitive chained services. In this article, we aim at designing an optimization approach for reducing the latency of chained services. Specifically, presenting the measurement and analysis of chained services on Baidu's cloud platform, our real-world trace indicates that these chained services are suffering from significantly high latency because they are mostly handled by different queues on cloud servers for multiple times. However, such a unique feature introduces significant challenges to optimize a microservice's overall queueing delay. To address this problem, we propose a delay-guaranteed approach to accelerate the overall queueing of chained services while obtaining fairness across all the workloads. Our evaluations on Baidu servers shows that the proposed design can successfully reduce the latency of chained services by 35 percent with minimal impact on other workloads.
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