24,258 research outputs found
Cloud computing resource scheduling and a survey of its evolutionary approaches
A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon
Reallocation Problems in Agent Societies: A Local Mechanism to Maximize Social Welfare
Resource reallocation problems are common in real life and therefore gain an increasing interest in Computer Science and Economics. Such problems consider agents living in a society and negotiating their resources with each other in order to improve the welfare of the population. In many studies however, the unrealistic context considered, where agents have a flawless knowledge and unlimited interaction abilities, impedes the application of these techniques in real life problematics. In this paper, we study how agents should behave in order to maximize the welfare of the society. We propose a multi-agent method based on autonomous agents endowed with a local knowledge and local interactions. Our approach features a more realistic environment based on social networks, inside which we provide the behavior for the agents and the negotiation settings required for them to lead the negotiation processes towards socially optimal allocations. We prove that bilateral transactions of restricted cardinality are sufficient in practice to converge towards an optimal solution for different social objectives. An experimental study supports our claims and highlights the impact of a realistic environment on the efficiency of the techniques utilized.Resource Allocation, Negotiation, Social Welfare, Agent Society, Behavior, Emergence
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
Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements
Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)
Metaphor-based negotiation and its application in AGV movement planning
The theme of this thesis is "metaphor-based negotiation". By metaphor-based negotiation I mean a category of approaches for problem-solving in Distributed Artificial
Intelligence (DAI) that mimic some aspects of human negotiation behaviour. The
research in this dissertation is divided into two closely related parts. Cooperative interaction among agents in a multiagent system (MAS) is discussed in general, and
the discussion leads to a formal definition of metaphor-based negotiation. Then, as
a specific application, a "spring-based" computational model for metaphor-based negotiation is developed as an approach to solving movement planning, specifically the
AGV scheduling problem (AGVSP) — determing the timings of AGVs' activities, of
automated guided vehicles (AGVs) in a factory.By formally addressing the multi-agent cooperative interaction problem and assuming
that agents in a MAS are rational, benevolent and fully informed, an initial strategy
set of cooperative interaction can be reduced to a strategy set by eliminating strategies
that are irrational in a group sense. However, it is proved in this dissertation that, in
the remaining strategy set, no unique strategy can be found that is acceptable to all
agents according their individual preferences. More specifically, in this smaller strategy
set, if one agent moves from one strategy to another in an attempt to better its individual goal achievement, then there is at least one agent whose goal achievement will
be negatively affected by such a move. So, the cooperative interaction problem can
only be partially solved if no further knowledge is given to those agents. The idea of a
common sense principle is introduced in this dissertation to overcome the deficiencies
of the assumptions of rationality, benevolence and full-informedness.In reality, the assumption of full-informedness of agents may not be practical. Communication is needed for agents to (1) exchange their local problem solving information,
and (2) exchange proposals for global problem solving, when their views are in conflict.
Based on the discussion of cooperative interaction, a formal definition of metaphorbased
negotiation is proposed to formally indicate what is a proposal and what is the
condition for accepting a proposal from another agent. In this definition, the common
sense principle is one of the most important features, not found in definitions of negotiation available so far in the literature, which guides agents to find an agreement
when negotiation is running into difficulties.The AGVSP involves timing activities for each AGV in a AGV-based factory. The
AGVSP is naturally distributed: the whole problem can be easily divided into several
subproblems each of which involves timing of activities of one AGV. Therefore, it is
intuitively straightforward for us to seek DAI approaches to solving the AGVSP. In
spired by Kwa's Iterative Negotiation Model [Kwa 88b] [Kwa 88a] for the AGVSP, we
developed a spring-based (metaphor-based) negotiation model for the AGVSP to overcome some vital problems in Kwa's model. The idea of the spring-based negotiation
model is described below:The AGVSP can be regarded as a Distributed Constraint Satisfaction Problem (DCSP)
and solved in a MAS. Each agent in the MAS is designed to solve a subproblem — a
local scheduling problem which is a small Constraint Satisfaction Problem (CSP). Conflicts exist when intra-agent constraints or inter-agent constraints are violated. These
constraints can be classified into hard constraints— those that can not be relaxed at
the agent level unless the system designer permits (e.g., by providing an arbitrator),
and soft constraints — those that can be relaxed at the agent level when necessary.
When agents are in conflict, i.e, when some inter-agent constraints are violated (or
say, when one agent's timings of its activities overlap those of some other agents),
these agents involved will resolve the conflicts through a (metaphor-based) negotiation
procedure in which conflicts will be gradually resolved by each agent's relaxation of
its intra-agent constraints, i.e, by yielding some amount of its initially allocated resources to other agents or by shifting its initially allocated resources. The negotiation
can be viewed as a process of exchanging proposals (of cooperative strategies) between
conflicting agents, where a cooperative strategy is a possible resolution to a conflict
according to the viewpoint of the proposing agent. However, since agents are designed
to be rational, each agent that is involved in the conflicts will try hard to relax its
intra-agent constraints as little as possible. Further, it is reasonably acceptable that
the more an intra-agent constraint has been relaxed the less the respective agent is
willing to relax it further. This feature can be modeled by a spring — the more it
has been compressed the harder it is to compress it further. Based on this inspiration,
a spring-based computational model of metaphor-based negotiation is proposed: each
agent's local schedule is represented by a local spring network in which each spring element represents a soft intra-agent constraint. Relaxation of an intra-agent constraint
is likened to a spring being compressed by external forces from other agents. As a
consequence, the compressed spring will also show a reacting force upon those compressing agents. An agreement will be reached when those forces and reacting forces
are balanced. This is the common sense principle in the spring-based negotiation. The
model solves some key issues, e.g., how to select negotiation techniques and skills during the process of negotiation, that have not been solved by Kwa's iterative negotiation
model. Some experimental evidence of the value of this model is presented
QoS-based surrogates selection and service proposal formulation in offloading environments
Resource constraints are becoming a problem as many of the wireless mobile devices have
increased generality. Our work tries to address this growing demand on resources and performance,
by proposing the dynamic selection of neighbor nodes for cooperative service execution.
This selection is in
uenced by user's quality of service requirements expressed in his request,
tailoring provided service to user's speci c needs. In this paper we improve our proposal's
formulation algorithm with the ability to trade o time for the quality of the solution. At any
given time, a complete solution for service execution exists, and the quality of that solution is
expected to improve overtime
Production/maintenance cooperative scheduling using multi-agents and fuzzy logic
Within companies, production is directly concerned with the manufacturing schedule, but other services like sales, maintenance, purchasing or workforce management should also have an influence on this schedule. These services often have together a hierarchical relationship, i.e. the leading function (most of the time sales or production) generates constraints defining the framework within which the other functions have to satisfy their own objectives. We show how the multi-agent paradigm, often used in scheduling for its ability to distribute decision-making, can also provide a framework for making several functions cooperate in the schedule performance. Production and maintenance have been chosen as an example: having common resources (the machines), their activities are actually often conflicting. We show how to use a fuzzy logic in order to model the temporal degrees of freedom of the two functions, and show that this approach may allow one to obtain a schedule that provides a better compromise between the satisfaction of the respective objectives of the two functions
Agent-based transportation planning compared with scheduling heuristics
Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. We use simulation to compare the on-time delivery percentage and the vehicle utilization of an agent-based planning system to a traditional system based on OR heuristics (look-ahead rules, serial scheduling). Numerical experiments show that a properly designed multi-agent system may perform as good as or even better than traditional methods
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