413 research outputs found
Extensions to the self protecting object model to facilitate integrity in stationary and mobile hosts
M.Sc. (Computer Science)In this dissertation we propose extensions to the Self Protecting Object (SPO) model to facilitate the sharing of information in a more effective manner. We see the sharing ofinformation as the sharing of objects that provide services. Sharing objects effectively is allowing the objects to be used in a secure environment, independent of their location, in a manner usage was intended. The SPO model proposed by Olivier [32] allows for objects in a federated database to be moved from one site to another and ensures that the security policy of the object will always be respected and implemented, regardless of its location. Although the SPO model does indeed allow for objects (information) to be shared effectively, it fails to address issues of maintaining integrity within objects. We therefore define the notion of maintaining integrity within the spa model and propose a model to achieve it. We argue that ensuring an SPO is only used in a way usage was intended does not suffice to ensure integrity. The model we propose is based on ensuring that modifications to an SPO are only executed if the modification does not violate the constraints defined for the Sf'O, The model" allows for an spa to maintain its unique identity in addition to maintaining its integrity. The SPO model is designed to be used in a federated database on sites that are stationary. Therefore, having addressed the issue of maintaining integrity within SPOs on stationary sites in the federated database, we then introduce the notion of a mobile site: a site that will eventually disconnect from the federated database and become unreachable for some time. Introducing the mobile site into the federated database allows us to propose the Mobile Self Protecting Object (MSPO) and its associated architecture. Because of the nature of mobile sites, the original model for maintaining integrity can not be applied to the MSPO architecture. We therefore propose a mechanism (to be implemented in unison with the original model) to ensure the integrity of MSPOs on mobile sites. We then discuss the JASPO prototype. The aim of the prototype was to determine if the Self Protecting Object model was feasible using current development technologies. We examine the requirements identified in order for the prototype to be successful and discuss how these were satisfied. Several modifications were made to the original spa model, including the addition of a new module and the exclusion of others, we discuss these modifications and examine why they were necessary
Models of higher-order, type-safe, distributed computation over autonomous persistent object stores
A remote procedure call (RPC) mechanism permits the calling of procedures in another
address space. RPC is a simple but highly effective mechanism for interprocess communication
and enjoys nowadays a great popularity as a tool for building distributed applications.
This popularity is partly a result of their overall simplicity but also partly a consequence
of more than 20 years of research in transpaxent distribution that have failed to deliver
systems that meet the expectations of real-world application programmers.
During the same 20 years, persistent systems have proved their suitability for building
complex database applications by seamlessly integrating features traditionally found in
database management systems into the programming language itself. Some research. effort
has been invested on distributed persistent systems, but the outcomes commonly suffer
from the same problems found with transparent distribution.
In this thesis I claim that a higher-order persistent RPC is useful for building distributed
persistent applications. The proposed mechanism is: realistic in the sense that it uses
current technology and tolerates partial failures; understandable by application programmers;
and general to support the development of many classes of distributed persistent
applications.
In order to demonstrate the validity of these claims, I propose and have implemented three
models for distributed higher-order computation over autonomous persistent stores. Each
model has successively exposed new problems which have then been overcome by the next
model. Together, the three models provide a general yet simple higher-order persistent
RPC that is able to operate in realistic environments with partial failures.
The real strength of this thesis is the demonstration of realism and simplicity. A higherorder
persistent RPC was not only implemented but also used by programmers without
experience of programming distributed applications. Furthermore, a distributed persistent
application has been built using these models which would not have been feasible with a
traditional (non-persistent) programming language
LINC: A Compact Yet Powerful Coordination Environment
International audienceThis paper presents LINC, a coordination programming environment. It is an evolution of earlier middlewares (the Coordination Language Facility (CLF) and Stitch). The aim is to provide a more flexible and expressive language correcting several of their limitations and an improved run-time environment. LINC provides a compact yet powerful coordination language and an optimised run-time which executes rules. This paper describes the intrinsic properties brought by the LINC environment and how it helps the coordination aspects in a distributed system. This paper also emphasises on the reflexivity of LINC and its usage at system level. Finally, it illustrates through several case studies, how LINC can manage a wide range of application domains
Adaptive learning-based resource management strategy in fog-to-cloud
Technology in the twenty-first century is rapidly developing and driving us into a new smart computing world, and emerging lots
of new computing architectures. Fog-to-Cloud (F2C) is among one of them, which emerges to ensure the commitment for
bringing the higher computing facilities near to the edge of the network and also help the large-scale computing system to be
more intelligent. As the F2C is in its infantile state, therefore one of the biggest challenges for this computing paradigm is to
efficiently manage the computing resources. Mainly, to address this challenge, in this work, we have given our sole interest for
designing the initial architectural framework to build a proper, adaptive and efficient resource management mechanism in F2C.
F2C has been proposed as a combined, coordinated and hierarchical computing platform, where a vast number of
heterogeneous computing devices are participating. Notably, their versatility creates a massive challenge for effectively handling
them. Even following any large-scale smart computing system, it can easily recognize that various kind of services is served for
different purposes. Significantly, every service corresponds with the various tasks, which have different resource requirements.
So, knowing the characteristics of participating devices and system offered services is giving advantages to build effective and
resource management mechanism in F2C-enabled system. Considering these facts, initially, we have given our intense focus for
identifying and defining the taxonomic model for all the participating devices and system involved services-tasks.
In any F2C-enabled system consists of a large number of small Internet-of-Things (IoTs) and generating a continuous and
colossal amount of sensing-data by capturing various environmental events. Notably, this sensing-data is one of the key
ingredients for various smart services which have been offered by the F2C-enabled system. Besides that, resource statistical
information is also playing a crucial role, for efficiently providing the services among the system consumers. Continuous
monitoring of participating devices generates a massive amount of resource statistical information in the F2C-enabled system.
Notably, having this information, it becomes much easier to know the device's availability and suitability for executing some tasks
to offer some services. Therefore, ensuring better service facilities for any latency-sensitive services, it is essential to securely
distribute the sensing-data and resource statistical information over the network. Considering these matters, we also proposed
and designed a secure and distributed database framework for effectively and securely distribute the data over the network.
To build an advanced and smarter system is necessarily required an effective mechanism for the utilization of system resources.
Typically, the utilization and resource handling process mainly depend on the resource selection and allocation mechanism. The
prediction of resources (e.g., RAM, CPU, Disk, etc.) usage and performance (i.e., in terms of task execution time) helps the
selection and allocation process. Thus, adopting the machine learning (ML) techniques is much more useful for designing an
advanced and sophisticated resource allocation mechanism in the F2C-enabled system. Adopting and performing the ML
techniques in F2C-enabled system is a challenging task. Especially, the overall diversification and many other issues pose a
massive challenge for successfully performing the ML techniques in any F2C-enabled system. Therefore, we have proposed and
designed two different possible architectural schemas for performing the ML techniques in the F2C-enabled system to achieve
an adaptive, advance and sophisticated resource management mechanism in the F2C-enabled system. Our proposals are the
initial footmarks for designing the overall architectural framework for resource management mechanism in F2C-enabled system.La tecnologia del segle XXI avança rà pidament i ens condueix cap a un nou món intel·ligent, creant nous models d'arquitectures informà tiques. Fog-to-Cloud (F2C) és un d’ells, i sorgeix per garantir el compromÃs d’acostar les instal·lacions informà tiques a prop de la xarxa i també ajudar el sistema informà tic a gran escala a ser més intel·ligent. Com que el F2C es troba en un estat preliminar, un dels majors reptes d’aquest paradigma tecnològic és gestionar eficientment els recursos informà tics. Per fer front a aquest repte, en aquest treball hem centrat el nostre interès en dissenyar un marc arquitectònic per construir un mecanisme de gestió de recursos adequat, adaptatiu i eficient a F2C.F2C ha estat concebut com una plataforma informà tica combinada, coordinada i jerà rquica, on participen un gran nombre de dispositius heterogenis. La seva versatilitat planteja un gran repte per gestionar-los de manera eficaç. Els serveis que s'hi executen consten de diverses tasques, que tenen requisits de recursos diferents. Per tant, conèixer les caracterÃstiques dels dispositius participants i dels serveis que ofereix el sistema és un requisit per dissenyar mecanismes eficaços i de gestió de recursos en un sistema habilitat per F2C. Tenint en compte aquests fets, inicialment ens hem centrat en identificar i definir el model taxonòmic per a tots els dispositius i sistemes implicats en l'execució de tasques de serveis. Qualsevol sistema habilitat per F2C inclou en un gran nombre de dispositius petits i connectats (conegut com a Internet of Things, o IoT) que generen una quantitat contÃnua i colossal de dades de detecció capturant diversos events ambientals. Aquestes dades són un dels ingredients clau per a diversos serveis intel·ligents que ofereix F2C. A més, el seguiment continu dels dispositius participants genera igualment una gran quantitat d'informació estadÃstica. En particular, en tenir aquesta informació, es fa molt més fà cil conèixer la disponibilitat i la idoneïtat dels dispositius per executar algunes tasques i oferir alguns serveis. Per tant, per garantir millors serveis sensibles a la latència, és essencial distribuir de manera equilibrada i segura la informació estadÃstica per la xarxa. Tenint en compte aquests assumptes, també hem proposat i dissenyat un entorn de base de dades segura i distribuïda per gestionar de manera eficaç i segura les dades a la xarxa. Per construir un sistema avançat i intel·ligent es necessita un mecanisme eficaç per a la gestió de l'ús dels recursos del sistema. Normalment, el procés d’utilització i manipulació de recursos depèn principalment del mecanisme de selecció i assignació de recursos. La predicció de l’ús i el rendiment de recursos (per exemple, RAM, CPU, disc, etc.) en termes de temps d’execució de tasques ajuda al procés de selecció i assignació. Adoptar les tècniques d’aprenentatge automà tic (conegut com a Machine Learning, o ML) és molt útil per dissenyar un mecanisme d’assignació de recursos avançat i sofisticat en el sistema habilitat per F2C. L’adopció i la realització de tècniques de ML en un sistema F2C és una tasca complexa. Especialment, la diversificació general i molts altres problemes plantegen un gran repte per realitzar amb èxit les tècniques de ML. Per tant, en aquesta recerca hem proposat i dissenyat dos possibles esquemes arquitectònics diferents per realitzar tècniques de ML en el sistema habilitat per F2C per aconseguir un mecanisme de gestió de recursos adaptatiu, avançat i sofisticat en un sistema F2C. Les nostres propostes són els primers passos per dissenyar un marc arquitectònic general per al mecanisme de gestió de recursos en un sistema habilitat per F2C.Postprint (published version
SCFS: A Shared Cloud-backed File System
Despite of their rising popularity, current cloud storage services and cloud-backed storage systems still have some limitations related to reliability, durability assurances and inefficient file sharing. We present SCFS, a cloud-backed file system that addresses these issues and provides strong consistency and near-POSIX semantics on top of eventually-consistent cloud storage services. SCFS provides a pluggable backplane that allows it to work with various storage clouds or a cloud-of-clouds (for added dependability). It also exploits some design opportunities inherent in the current cloud services through a set of novel ideas for cloud-backed file systems: always write and avoid reading, modular coordination, private name spaces and consistency anchors.
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