63,724 research outputs found
On Modelling and Analysis of Dynamic Reconfiguration of Dependable Real-Time Systems
This paper motivates the need for a formalism for the modelling and analysis
of dynamic reconfiguration of dependable real-time systems. We present
requirements that the formalism must meet, and use these to evaluate well
established formalisms and two process algebras that we have been developing,
namely, Webpi and CCSdp. A simple case study is developed to illustrate the
modelling power of these two formalisms. The paper shows how Webpi and CCSdp
represent a significant step forward in modelling adaptive and dependable
real-time systems.Comment: Presented and published at DEPEND 201
Reliable Provisioning of Spot Instances for Compute-intensive Applications
Cloud computing providers are now offering their unused resources for leasing
in the spot market, which has been considered the first step towards a
full-fledged market economy for computational resources. Spot instances are
virtual machines (VMs) available at lower prices than their standard on-demand
counterparts. These VMs will run for as long as the current price is lower than
the maximum bid price users are willing to pay per hour. Spot instances have
been increasingly used for executing compute-intensive applications. In spite
of an apparent economical advantage, due to an intermittent nature of biddable
resources, application execution times may be prolonged or they may not finish
at all. This paper proposes a resource allocation strategy that addresses the
problem of running compute-intensive jobs on a pool of intermittent virtual
machines, while also aiming to run applications in a fast and economical way.
To mitigate potential unavailability periods, a multifaceted fault-aware
resource provisioning policy is proposed. Our solution employs price and
runtime estimation mechanisms, as well as three fault tolerance techniques,
namely checkpointing, task duplication and migration. We evaluate our
strategies using trace-driven simulations, which take as input real price
variation traces, as well as an application trace from the Parallel Workload
Archive. Our results demonstrate the effectiveness of executing applications on
spot instances, respecting QoS constraints, despite occasional failures.Comment: 8 pages, 4 figure
Cloud engineering is search based software engineering too
Many of the problems posed by the migration of computation to cloud platforms can be formulated and solved using techniques associated with Search Based Software Engineering (SBSE). Much of cloud software engineering involves problems of optimisation: performance, allocation, assignment and the dynamic balancing of resources to achieve pragmatic trade-offs between many competing technical and business objectives. SBSE is concerned with the application of computational search and optimisation to solve precisely these kinds of software engineering challenges. Interest in both cloud computing and SBSE has grown rapidly in the past five years, yet there has been little work on SBSE as a means of addressing cloud computing challenges. Like many computationally demanding activities, SBSE has the potential to benefit from the cloud; ‘SBSE in the cloud’. However, this paper focuses, instead, of the ways in which SBSE can benefit cloud computing. It thus develops the theme of ‘SBSE for the cloud’, formulating cloud computing challenges in ways that can be addressed using SBSE
Encapsulation and Dynamic Modularity in the Pi-Calculus
We describe a process calculus featuring high level constructs for
component-oriented programming in a distributed setting. We propose an
extension of the higher-order pi-calculus intended to capture several important
mechanisms related to component-based programming, such as dynamic update,
reconfiguration and code migration. In this paper, we are primarily concerned
with the possibility to build a distributed implementation of our calculus.
Accordingly, we define a low-level calculus, that describes how the high-level
constructs are implemented, as well as details of the data structures
manipulated at runtime. We also discuss current and future directions of
research in relation to our analysis of component-based programming
An Efficient Thread Mapping Strategy for Multiprogramming on Manycore Processors
The emergence of multicore and manycore processors is set to change the
parallel computing world. Applications are shifting towards increased
parallelism in order to utilise these architectures efficiently. This leads to
a situation where every application creates its desirable number of threads,
based on its parallel nature and the system resources allowance. Task
scheduling in such a multithreaded multiprogramming environment is a
significant challenge. In task scheduling, not only the order of the execution,
but also the mapping of threads to the execution resources is of a great
importance. In this paper we state and discuss some fundamental rules based on
results obtained from selected applications of the BOTS benchmarks on the
64-core TILEPro64 processor. We demonstrate how previously efficient mapping
policies such as those of the SMP Linux scheduler become inefficient when the
number of threads and cores grows. We propose a novel, low-overhead technique,
a heuristic based on the amount of time spent by each CPU doing some useful
work, to fairly distribute the workloads amongst the cores in a
multiprogramming environment. Our novel approach could be implemented as a
pragma similar to those in the new task-based OpenMP versions, or can be
incorporated as a distributed thread mapping mechanism in future manycore
programming frameworks. We show that our thread mapping scheme can outperform
the native GNU/Linux thread scheduler in both single-programming and
multiprogramming environments.Comment: ParCo Conference, Munich, Germany, 201
Redundant movements in autonomous mobility: experimental and theoretical analysis
<p>Distributed load balancers exhibit thrashing where tasks are repeatedly moved between locations due to incomplete global load information. This paper shows that systems of autonomous mobile programs (AMPs) exhibit the same behaviour, and identifies two types of redundant movement (greedy effect). AMPs are unusual in that, in place of some external load management system, each AMP periodically recalculates network and program parameters and may independently move to a better execution environment. Load management emerges from the behaviour of collections of AMPs.</p>
<p>The paper explores the extent of greedy effects by simulating collections of AMPs and proposes negotiating AMPs (NAMPs) to ameliorate the problem. We present the design of AMPs with a competitive negotiation scheme (cNAMPs), and compare their performance with AMPs by simulation. We establish new properties of balanced networks of AMPs, and use these to provide a theoretical analysis of greedy effects.</p>
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