BiDAl: Big Data Analyzer for Cluster Traces

Modern data centers that provide Internet-scale services are stadium-size structures housing tens of thousands of heterogeneous devices (server clusters, networking equipment, power and cooling infrastructures) that must operate continuously and reliably. As part of their operation, these devices produce large amounts of data in the form of event and error logs that are essential not only for identifying problems but also for improving data center efficiency and management. These activities employ data analytics and often exploit hidden statistical patterns and correlations among different factors present in the data. Uncovering these patterns and correlations is challenging due to the sheer volume of data to be analyzed. This paper presents BiDAl, a prototype “log-data analysis framework” that incorporates various Big Data technologies to simplify the analysis of data traces from large clusters. BiDAl is written in Java with a modular and extensible architecture so that different storage backends (currently, HDFS and SQLite are supported), as well as different analysis languages (current implementation supports SQL, R and Hadoop MapReduce) can be easily selected as appropriate. We present the design of BiDAl and describe our experience using it to analyze several public traces of Google data clusters for building a simulation model capable of reproducing observed behavior

Firefly-inspired Heartbeat Synchronization in Overlay Networks

Heartbeat synchronization strives to have nodes in a distributed system generate periodic, local “heartbeat” events approximately at the same time. Many useful distributed protocols rely on the existence of such heart-beats for driving their cycle-based execution. Yet, solving the problem in environments where nodes are unreliable and messages are subject to delays and failures is non-trivial. We present a heartbeat synchronization protocol for overlay networks inspired by mathematical models of flash synchronization in certain species of fireflies. In our protocol, nodes send flash messages to their neighbors when a local heartbeat triggers. They adjust the phase of their next heartbeat based on incoming flash messages using an algorithm inspired by mathematical models of firefly synchronization. We report simulation results of the protocol in various realistic failure scenarios typical in overlay networks and show that synchronization emerges even when messages can have significant delay subject to large jitter

A remark on an overdetermined problem in Riemannian Geometry

Let $(M,g)$ be a Riemannian manifold with a distinguished point $O$ and assume that the geodesic distance $d$ from $O$ is an isoparametric function. Let $\Omega\subset M$ be a bounded domain, with $O \in \Omega$, and consider the problem $\Delta_p u = -1$ in $\Omega$ with $u=0$ on $\partial \Omega$, where $\Delta_p$ is the $p$-Laplacian of $g$. We prove that if the normal derivative $\partial_{\nu}u$ of $u$ along the boundary of $\Omega$ is a function of $d$ satisfying suitable conditions, then $\Omega$ must be a geodesic ball. In particular, our result applies to open balls of $\mathbb{R}^n$ equipped with a rotationally symmetric metric of the form $g=dt^2+\rho^2(t)\,g_S$, where $g_S$ is the standard metric of the sphere.Comment: 8 pages. This paper has been written for possible publication in a special volume dedicated to the conference "Geometric Properties for Parabolic and Elliptic PDE's. 4th Italian-Japanese Workshop", organized in Palinuro in May 201

Microcities: A Platform Based on Microclouds for Neighborhood Services

International audienceThe current datacenter-centralized architecture limits the cloud to the location of the datacenters, generally far from the user. This architecture collides with the latest trend of ubiquity of Cloud computing. Distance leads to increased utilization of the broadband Wide Area Network and poor user experience, especially for interactive applications. A semi-decentralized approach can provide a better Quality of Experience (QoE) in large urban populations in mobile cloud networks, by confining local traffic near the user while maintaining centralized characteristics, running on the users and network devices. In this paper, we propose a novel semi-decentralized cloud architecture based on microclouds. Microclouds are dynamically created and allow users to contribute resources from their computers, mobile and network devices to the cloud. Microclouds provide a dynamic and scalable system without an extra investment in infrastructure. We also provide a description of a realistic mobile cloud use case, and its adaptation to microclouds

Structure-Based Discovery of A2A Adenosine Receptor Ligands

The recent determination of X-ray structures of pharmacologically relevant GPCRs has made these targets accessible to structure-based ligand discovery. Here we explore whether novel chemotypes may be discovered for the A(2A) adenosine receptor, based on complementarity to its recently determined structure. The A(2A) adenosine receptor signals in the periphery and the CNS, with agonists explored as anti-inflammatory drugs and antagonists explored for neurodegenerative diseases. We used molecular docking to screen a 1.4 million compound database against the X-ray structure computationally and tested 20 high-ranking, previously unknown molecules experimentally. Of these 35% showed substantial activity with affinities between 200 nM and 9 microM. For the most potent of these new inhibitors, over 50-fold specificity was observed for the A(2A) versus the related A(1) and A(3) subtypes. These high hit rates and affinities at least partly reflect the bias of commercial libraries toward GPCR-like chemotypes, an issue that we attempt to investigate quantitatively. Despite this bias, many of the most potent new ligands were novel, dissimilar from known ligands, providing new lead structures for modulation of this medically important target

One Scaffold, Three Binding Modes: Novel and Selective Pteridine Reductase 1 Inhibitors Derived from Fragment Hits Discovered by Virtual Screening†

The enzyme pteridine reductase 1 (PTR1) is a potential target for new compounds to treat human African trypanosomiasis. A virtual screening campaign for fragments inhibiting PTR1 was carried out. Two novel chemical series were identified containing aminobenzothiazole and aminobenzimidazole scaffolds, respectively. One of the hits (2-amino-6-chloro-benzimidazole) was subjected to crystal structure analysis and a high resolution crystal structure in complex with PTR1 was obtained, confirming the predicted binding mode. However, the crystal structures of two analogues (2-amino-benzimidazole and 1-(3,4-dichloro-benzyl)-2-amino-benzimidazole) in complex with PTR1 revealed two alternative binding modes. In these complexes, previously unobserved protein movements and water-mediated protein-ligand contacts occurred, which prohibited a correct prediction of the binding modes. On the basis of the alternative bindingmode of 1-(3,4-dichloro-benzyl)-2-amino-benzimidazole, derivatives were designed and selective PTR1 inhibitors with low nanomolar potency and favorable physicochemical properties were obtained

Automated Docking Screens: A Feasibility Study

Molecular docking is themost practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCKBlaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCKBlaster recapitulates the crystal ligand pose within 2 A ̊ rmsd 50-60 % of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5 % of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5 % of 100 property-matched decoys while also posing within 2 A ̊ rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available a