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## Type of Work

Article (30) Book (0) Theses (0) Multimedia (0)

## Peer Review

Peer-reviewed only (30)

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UC Berkeley (3) UC Davis (4) UC Irvine (9) UCLA (2) UC Merced (0) UC Riverside (0) UC San Diego (3) UCSF (3) UC Santa Barbara (1) UC Santa Cruz (0) UC Office of the President (5) Lawrence Berkeley National Laboratory (6) UC Agriculture & Natural Resources (0)

## Department

Research Grants Program Office (RGPO) (4) University of California Research Initiatives (UCRI) (2) Multicampus Research Programs and Initiatives (MRPI); a funding opportunity through UC Research Initiatives (UCRI) (2)

Department of Earth, Planetary, and Space Sciences (1)

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## Discipline

Physical Sciences and Mathematics (2)

## Reuse License

BY - Attribution required (8) BY-NC - Attribution; NonCommercial use only (1) BY-NC-ND - Attribution; NonCommercial use; No derivatives (1) BY-SA - Attribution; Derivatives must use same license (1)

## Scholarly Works (30 results)

© 2015 IEEE. We revisit the problem of identifying link metrics from end- to-end path measurements in practical IP networks where shortest path routing is the norm. Previous solutions rely on explicit routing techniques (e.g., source routing or MPLS) to construct independent measurement paths for efficient link metric identification. However, most IP networks still adopt shortest path routing paradigm, while the explicit routing is not supported by most of the routers. Thus, this paper studies the link metric identification problem under shortest path routing constraints. To uniquely identify the link metrics, we need to place sufficient number of monitors into the network such that there exist m (the number of links) linear independent shortest paths between the monitors. In this paper, we first formulate the problem as a mixed integer linear programming problem, and then to make the problem tractable in large networks, we propose a Monitor Placement and Measurement Path Selection (MP-MPS) algorithm that adheres to shortest path routing constraints. Extensive simulations on random and real networks show that the MP- MPS gets near-optimal solutions in small networks, and MP- MPS significantly outperforms a baseline solution in large networks.

The authors demonstrate the detection of magnetic particles carried by water in a continuous flow using an atomic magnetic gradiometer. Studies on three types of magnetic particles are presented: a single cobalt particle (diameter similar to 150 mu m, multidomain), a suspension of superparamagnetic magnetite particles (diameter similar to 1 mu m), and ferromagnetic cobalt nanoparticles (diameter similar to 10 nm). Estimated detection limits are 20 mu m diameter for a single cobalt particle at a water flow rate of 30 ml/min, 5x10(3) magnetite particles at 160 ml/min, and 50 pl for the ferromagnetic fluid of cobalt nanoparticles at 130 ml/min. Possible applications of their method are discussed.

© 2016 American Physical Society. A detailed systematic derivation of a logarithmically discretized model for two-dimensional turbulence is given, starting from the basic fluid equations and proceeding with a particular form of discretization of the wave-number space. We show that it is possible to keep all or a subset of the interactions, either local or disparate scale, and recover various limiting forms of shell models used in plasma and geophysical turbulence studies. The method makes no use of the conservation laws even though it respects the underlying conservation properties of the fluid equations. It gives a family of models ranging from shell models with nonlocal interactions to anisotropic shell models depending on the way the shells are constructed. Numerical integration of the model shows that energy and enstrophy equipartition seem to dominate over the dual cascade, which is a common problem of two-dimensional shell models.

© 1993-2012 IEEE. In this paper, we propose the Programmable LInk Metric Identification (ProgLIMI) infrastructure for software-defined networking (SDN) networks. ProgLIMI identifies round-trip link metrics (RTLMs) from accumulated end-to-end metrics of selected measurement paths by leveraging the flexible routing control capability of SDN networks. ProgLIMI mainly solves three sub-problems: 1) monitor placement; 2) linearly independent measurement path construction; and 3) flow rule design. To reduce measurement cost, ProgLIMI tries to minimize the number of required monitors and flow rules. In this paper, we address the three sub-problems for both full and hybrid SDN networks. For full SDN networks, ProgLIMI can achieve full RTLM identification using only one monitor and two flow rules in each SDN switch. In contrast, the RTLM identification in hybrid SDN networks is more complicated due to the routing constraint of hybrid SDN networks. We first prove that the monitor placement problem in hybrid SDN networks is NP-hard. We then formulate the monitor placement and measurement path selection problem in hybrid SDN networks and propose a greedy heuristic algorithm to solve the problem efficiently. Our evaluations on both physical testbed and simulation platform reveal that ProgLIMI can accurately identify the RTLMs (delay and loss rate). Besides, ProgLIMI is also resource efficient, i.e., it only requires two flow rules in each SDN switch and a small number of monitors, and the extra probing traffic load incurred by ProgLIMI is also low.