1,569 research outputs found
A Self-adaptive Agent-based System for Cloud Platforms
Cloud computing is a model for enabling on-demand network access to a shared
pool of computing resources, that can be dynamically allocated and released
with minimal effort. However, this task can be complex in highly dynamic
environments with various resources to allocate for an increasing number of
different users requirements. In this work, we propose a Cloud architecture
based on a multi-agent system exhibiting a self-adaptive behavior to address
the dynamic resource allocation. This self-adaptive system follows a MAPE-K
approach to reason and act, according to QoS, Cloud service information, and
propagated run-time information, to detect QoS degradation and make better
resource allocation decisions. We validate our proposed Cloud architecture by
simulation. Results show that it can properly allocate resources to reduce
energy consumption, while satisfying the users demanded QoS
Middleware-based Database Replication: The Gaps between Theory and Practice
The need for high availability and performance in data management systems has
been fueling a long running interest in database replication from both academia
and industry. However, academic groups often attack replication problems in
isolation, overlooking the need for completeness in their solutions, while
commercial teams take a holistic approach that often misses opportunities for
fundamental innovation. This has created over time a gap between academic
research and industrial practice.
This paper aims to characterize the gap along three axes: performance,
availability, and administration. We build on our own experience developing and
deploying replication systems in commercial and academic settings, as well as
on a large body of prior related work. We sift through representative examples
from the last decade of open-source, academic, and commercial database
replication systems and combine this material with case studies from real
systems deployed at Fortune 500 customers. We propose two agendas, one for
academic research and one for industrial R&D, which we believe can bridge the
gap within 5-10 years. This way, we hope to both motivate and help researchers
in making the theory and practice of middleware-based database replication more
relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on
Management of Data, Vancouver, Canada, June 200
A Uniform Programming Abstraction for Effecting Autonomic Adaptations onto Software Systems
Most general-purpose work towards autonomic or self-managing systems has emphasized the front end of the feedback control loop, with some also concerned with controlling the back end enactment of runtime adaptations but usually employing an effector technology peculiar to one type of target system. While completely generic 'one size fits all' effector technologies seem implausible, we propose a general-purpose programming model and interaction layer that abstracts away from the peculiarities of target-specific effectors, enabling a uniform approach to controlling and coordinating the low-level execution of reconfigurations, repairs, micro-reboots, etc
The Architecture of an Autonomic, Resource-Aware, Workstation-Based Distributed Database System
Distributed software systems that are designed to run over workstation
machines within organisations are termed workstation-based. Workstation-based
systems are characterised by dynamically changing sets of machines that are
used primarily for other, user-centric tasks. They must be able to adapt to and
utilize spare capacity when and where it is available, and ensure that the
non-availability of an individual machine does not affect the availability of
the system. This thesis focuses on the requirements and design of a
workstation-based database system, which is motivated by an analysis of
existing database architectures that are typically run over static, specially
provisioned sets of machines. A typical clustered database system -- one that
is run over a number of specially provisioned machines -- executes queries
interactively, returning a synchronous response to applications, with its data
made durable and resilient to the failure of machines. There are no existing
workstation-based databases. Furthermore, other workstation-based systems do
not attempt to achieve the requirements of interactivity and durability,
because they are typically used to execute asynchronous batch processing jobs
that tolerate data loss -- results can be re-computed. These systems use
external servers to store the final results of computations rather than
workstation machines. This thesis describes the design and implementation of a
workstation-based database system and investigates its viability by evaluating
its performance against existing clustered database systems and testing its
availability during machine failures.Comment: Ph.D. Thesi
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