Mobile object location discovery in unpredictable environments

Emerging mobile and ubiquitous computing environments present hard challenges to software engineering. The use of mobile code has been suggested as a natural fit for simplifing software development for these environments. However, the task of discovering mobile code location becomes a problem in unpredictable environments when using existing strategies, designed with fixed and relatively stable networks in mind. This paper introduces AMOS, a mobile code platform augmented with a structured overlay network. We demonstrate how the location discovery strategy of AMOS has better reliability and scalability properties than existing approaches, with minimal communication overhead. Finally, we demonstrate how AMOS can provide autonomous distribution of effort fairly throughout a network using probabilistic methods that requires no global knowledge of host capabilities

An instance of the MIKADO migration model

In this document, we briefly describe the main contribution to the deliverable on experimenting with the implementation of most of the calculi considered in the project. First, we describe how two well known calculi for mobile processes KLAIM and Dπ have been implemented on the top of IMC. We then describe the implementation of the MiKO programming language, an instance of the parametric calculus introduced in the WP1 with the TyCO calculus as the content of the membrane itself. After this, we outline the description of the implementation of the abstract machine for an instance of the Kell Calculus that dedicates particular attention to the proof of its correctness. Our presentation ends with a discussion of the problem of implementing security membranes on the top of an execution platform

Process Management in Distributed Operating Systems

As part of designing and building the Amoeba distributed operating system, we have come up with a simple set of mechanisms for process management that allows downloading process migration, checkpointing, remote debugging and emulation of alien operating system interfaces.\ud The basic process management facilities are realized by the Amoeba Kernel and can be augmented by user-space services: Debug Service, Load-Balancing Service, Unix-Emulation Service, Checkpoint Service, etc.\ud The Amoeba Kernel can produce a representation of the state of a process which can be given to another Kernel where it is accepted for continued execution. This state consists of the memory contents in the form of a collection of segments, and a Process Descriptor which contains the additional state, program counters, stack pointers, system call state, etc.\ud Careful separation of mechanism and policy has resulted in a compact set of Kernel operations for process creation and management. A collection of user-space services provides process management policies and a simple interface for application programs.\ud In this paper we shall describe the mechanisms as they are being implemented in the Amoeba Distributed System at the Centre for Mathematics and Computer Science in Amsterdam. We believe that the mechanisms described here can also apply to other distributed systems

RAFDA: A Policy-Aware Middleware Supporting the Flexible Separation of Application Logic from Distribution

Middleware technologies often limit the way in which object classes may be used in distributed applications due to the fixed distribution policies that they impose. These policies permeate applications developed using existing middleware systems and force an unnatural encoding of application level semantics. For example, the application programmer has no direct control over inter-address-space parameter passing semantics. Semantics are fixed by the distribution topology of the application, which is dictated early in the design cycle. This creates applications that are brittle with respect to changes in distribution. This paper explores technology that provides control over the extent to which inter-address-space communication is exposed to programmers, in order to aid the creation, maintenance and evolution of distributed applications. The described system permits arbitrary objects in an application to be dynamically exposed for remote access, allowing applications to be written without concern for distribution. Programmers can conceal or expose the distributed nature of applications as required, permitting object placement and distribution boundaries to be decided late in the design cycle and even dynamically. Inter-address-space parameter passing semantics may also be decided independently of object implementation and at varying times in the design cycle, again possibly as late as run-time. Furthermore, transmission policy may be defined on a per-class, per-method or per-parameter basis, maximizing plasticity. This flexibility is of utility in the development of new distributed applications, and the creation of management and monitoring infrastructures for existing applications.Comment: Submitted to EuroSys 200

Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models

Given large amount of real photos for training, Convolutional neural network shows excellent performance on object recognition tasks. However, the process of collecting data is so tedious and the background are also limited which makes it hard to establish a perfect database. In this paper, our generative model trained with synthetic images rendered from 3D models reduces the workload of data collection and limitation of conditions. Our structure is composed of two sub-networks: semantic foreground object reconstruction network based on Bayesian inference and classification network based on multi-triplet cost function for avoiding over-fitting problem on monotone surface and fully utilizing pose information by establishing sphere-like distribution of descriptors in each category which is helpful for recognition on regular photos according to poses, lighting condition, background and category information of rendered images. Firstly, our conjugate structure called generative model with metric learning utilizing additional foreground object channels generated from Bayesian rendering as the joint of two sub-networks. Multi-triplet cost function based on poses for object recognition are used for metric learning which makes it possible training a category classifier purely based on synthetic data. Secondly, we design a coordinate training strategy with the help of adaptive noises acting as corruption on input images to help both sub-networks benefit from each other and avoid inharmonious parameter tuning due to different convergence speed of two sub-networks. Our structure achieves the state of the art accuracy of over 50\% on ShapeNet database with data migration obstacle from synthetic images to real photos. This pipeline makes it applicable to do recognition on real images only based on 3D models.Comment: 14 page

On the orbital evolution and growth of protoplanets embedded in a gaseous disc

We present a new computation of the linear tidal interaction of a protoplanetary core with a thin gaseous disc in which it is fully embedded. For the first time a discussion of the orbital evolution of cores with eccentricity (e) significantly larger than the gas-disc scale height to radius ratio (H/r) is given. We find that the direction of orbital migration reverses for e>1.1H/r. This occurs as a result of the orbital crossing of resonances in the disc that do not overlap the orbit when the eccentricity is very small. Simple expressions giving approximate fits to the eccentricity damping rate and the orbital migration rate are presented. We go on to calculate the rate of increase of the mean eccentricity for a system of protoplanetary cores due to dynamical relaxation. By equating the eccentricity damping time-scale with the dynamical relaxation time-scale we deduce that an equilibrium between eccentricity damping and excitation through scattering is attained on a 10^3 to 10^4 yr time-scale, at 1au. The equilibrium thickness of the protoplanet distribution is such that it is generally well confined within the gas disc. By use of a three dimensional N-body code we simulate the evolution of a system of protoplanetary cores, incorporating our eccentricity damping and migration rates. Assuming that collisions lead to agglomeration, we find that the vertical confinement of the protoplanet distribution permits cores to build up from 0.1 to 1 earth mass in only ~10^4 yr, within 1au. The time-scale required to achieve this is comparable to the migration time-scale. We deduce that it is not possible to build up a massive enough core to form a gas giant planet before orbital migration ultimately results in the preferential delivery of all such bodies to the neighbourhood of the central star. [Abridged]Comment: Latex in MNRAS style, 13 pages with 6 figures, also available from http://www.maths.qmw.ac.uk/~jdl

Survey of partitioning techniques in silicon compilation

In the silicon compilation design process, partitioning is usually the first problem to be investigated because partitioning algorithms form the backbone of many algorithms including: system synthesis, processor synthesis, floorplanning, and placement. In this survey, several partitioning techniques will be examined. In addition, this paper will review the partitioning algorithms used by synthesis systems at different design levels