13,409 research outputs found
An approach to rollback recovery of collaborating mobile agents
Fault-tolerance is one of the main problems that must be resolved to improve the adoption of the agents' computing paradigm. In this paper, we analyse the execution model of agent platforms and the significance of the faults affecting their constituent components on the reliable execution of agent-based applications, in order to develop a pragmatic framework for agent systems fault-tolerance. The developed framework deploys a communication-pairs independent check pointing strategy to offer a low-cost, application-transparent model for reliable agent- based computing that covers all possible faults that might invalidate reliable agent execution, migration and communication and maintains the exactly-one execution property
Investigation into Mobile Learning Framework in Cloud Computing Platform
Abstract—Cloud computing infrastructure is increasingly
used for distributed applications. Mobile learning
applications deployed in the cloud are a new research
direction. The applications require specific development
approaches for effective and reliable communication. This
paper proposes an interdisciplinary approach for design and
development of mobile applications in the cloud. The
approach includes front service toolkit and backend service
toolkit. The front service toolkit packages data and sends it
to a backend deployed in a cloud computing platform. The
backend service toolkit manages rules and workflow, and
then transmits required results to the front service toolkit.
To further show feasibility of the approach, the paper
introduces a case study and shows its performance
Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges
This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented
Reliability of Mobile Agents for Reliable Service Discovery Protocol in MANET
Recently mobile agents are used to discover services in mobile ad-hoc network
(MANET) where agents travel through the network, collecting and sometimes
spreading the dynamically changing service information. But it is important to
investigate how reliable the agents are for this application as the
dependability issues(reliability and availability) of MANET are highly affected
by its dynamic nature.The complexity of underlying MANET makes it hard to
obtain the route reliability of the mobile agent systems (MAS); instead we
estimate it using Monte Carlo simulation. Thus an algorithm for estimating the
task route reliability of MAS (deployed for discovering services) is proposed,
that takes into account the effect of node mobility in MANET. That mobility
pattern of the nodes affects the MAS performance is also shown by considering
different mobility models. Multipath propagation effect of radio signal is
considered to decide link existence. Transient link errors are also considered.
Finally we propose a metric to calculate the reliability of service discovery
protocol and see how MAS performance affects the protocol reliability. The
experimental results show the robustness of the proposed algorithm. Here the
optimum value of network bandwidth (needed to support the agents) is calculated
for our application. However the reliability of MAS is highly dependent on link
failure probability
Automating Fault Tolerance in High-Performance Computational Biological Jobs Using Multi-Agent Approaches
Background: Large-scale biological jobs on high-performance computing systems
require manual intervention if one or more computing cores on which they
execute fail. This places not only a cost on the maintenance of the job, but
also a cost on the time taken for reinstating the job and the risk of losing
data and execution accomplished by the job before it failed. Approaches which
can proactively detect computing core failures and take action to relocate the
computing core's job onto reliable cores can make a significant step towards
automating fault tolerance.
Method: This paper describes an experimental investigation into the use of
multi-agent approaches for fault tolerance. Two approaches are studied, the
first at the job level and the second at the core level. The approaches are
investigated for single core failure scenarios that can occur in the execution
of parallel reduction algorithms on computer clusters. A third approach is
proposed that incorporates multi-agent technology both at the job and core
level. Experiments are pursued in the context of genome searching, a popular
computational biology application.
Result: The key conclusion is that the approaches proposed are feasible for
automating fault tolerance in high-performance computing systems with minimal
human intervention. In a typical experiment in which the fault tolerance is
studied, centralised and decentralised checkpointing approaches on an average
add 90% to the actual time for executing the job. On the other hand, in the
same experiment the multi-agent approaches add only 10% to the overall
execution time.Comment: Computers in Biology and Medicin
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