12,000 research outputs found
A cooperative approach for distributed task execution in autonomic clouds
Virtualization and distributed computing are two key pillars that guarantee scalability of applications deployed in the Cloud. In Autonomous Cooperative Cloud-based Platforms, autonomous computing nodes cooperate to offer a PaaS Cloud for the deployment of user applications. Each node must allocate the necessary resources for customer applications to be executed with certain QoS guarantees. If the QoS of an application cannot be guaranteed a node has mainly two options: to allocate more resources (if it is possible) or to rely on the collaboration of other nodes. Making a decision is not trivial since it involves many factors (e.g. the cost of setting up virtual machines, migrating applications, discovering collaborators). In this paper we present a model of such scenarios and experimental results validating the convenience of cooperative strategies over selfish ones, where nodes do not help each other. We describe the architecture of the platform of autonomous clouds and the main features of the model, which has been implemented and evaluated in the DEUS discrete-event simulator. From the experimental evaluation, based on workload data from the Google Cloud Backend, we can conclude that (modulo our assumptions and simplifications) the performance of a volunteer cloud can be compared to that of a Google Cluster
Asynchronous Partial Overlay: A New Algorithm for Solving Distributed Constraint Satisfaction Problems
Distributed Constraint Satisfaction (DCSP) has long been considered an
important problem in multi-agent systems research. This is because many
real-world problems can be represented as constraint satisfaction and these
problems often present themselves in a distributed form. In this article, we
present a new complete, distributed algorithm called Asynchronous Partial
Overlay (APO) for solving DCSPs that is based on a cooperative mediation
process. The primary ideas behind this algorithm are that agents, when acting
as a mediator, centralize small, relevant portions of the DCSP, that these
centralized subproblems overlap, and that agents increase the size of their
subproblems along critical paths within the DCSP as the problem solving
unfolds. We present empirical evidence that shows that APO outperforms other
known, complete DCSP techniques
Design choices for agent-based control of AGVs in the dough making process
In this paper we consider a multi-agent system (MAS) for the logistics control of Automatic Guided Vehicles (AGVs) that are used in the dough making process at an industrial bakery. Here, logistics control refers to constructing robust schedules for all transportation jobs. The paper discusses how alternative MAS designs can be developed and compared using cost, frequency of messages between agents, and computation time for evaluating control rules as performance indicators. Qualitative design guidelines turn out to be insufficient to select the best agent architecture. Therefore, we also use simulation to support decision making, where we use real-life data from the bakery to evaluate several alternative designs. We find that architectures in which line agents initiate allocation of transportation jobs, and AGV agents schedule multiple jobs in advance, perform best. We conclude by discussing the benefits of our MAS systems design approach for real-life applications
Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments
The scarcity and diversity of resources among the devices of heterogeneous computing
environments may affect their ability to perform services with specific Quality
of Service constraints, particularly in dynamic distributed environments where the
characteristics of the computational load cannot always be predicted in advance.
Our work addresses this problem by allowing resource constrained devices to cooperate
with more powerful neighbour nodes, opportunistically taking advantage
of global distributed resources and processing power. Rather than assuming that
the dynamic configuration of this cooperative service executes until it computes
its optimal output, the paper proposes an anytime approach that has the ability
to tradeoff deliberation time for the quality of the solution. Extensive simulations
demonstrate that the proposed anytime algorithms are able to quickly find a good
initial solution and effectively optimise the rate at which the quality of the current
solution improves at each iteration, with an overhead that can be considered
negligible
A Centralized Model for Establishing End-to-End Communication Services via Management Agents
This paper presents a centralized approach for establishing end-to-end communication services via management agents. The main proposal is the modular architecture of the third-party based Service Establishment Agent (SEA). The SEA manages inter-provider service negotiation process with per-domain management agents through an appropriate signaling agent. It also receives and interprets end-toend service requests, selects inter-domain paths, performs mapping of service classes among domains on the path, and evaluates conformance of the offered service level with the required one. It allows implementation of different algorithms for the aforementioned functions as well as their selection and combination according to the predefined management policies. Simulation results show that the proposed model significantly outperforms the distributed model in terms of service negotiation times. In the prototype development process, a policy-based solution for mapping of service classes was implemented. The performance evaluation shows that processing requirements for handling multiple service requests are modest, while benefit of the SEA approach is the lack of need to build long-term consensus among providers about technical choices for achieving network interconnection. The SEA architecture is completely independent of the quality of service mechanisms available in particular domains.</p
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