Improving the Scalability of Multi-agent Systems

Turner, Philip; Jennings, Nicholas R.

doi:10.1007/3-540-47772-1_25

Cited by 34 publications

(14 citation statements)

References 4 publications

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“…In some cases, thousands of agents are considered to be a large-scale agent system [7], [22], while in other cases hundreds compose such a system [3], [4], [23], [24] and there are even cases where only dozens of agents are considered to be a large-scale system [13].…”

Section: Related Workmentioning

confidence: 99%

Coverage Density as a Dominant Property of Large-Scale Sensor Networks

Yadgar

Kraus

2006

Cooperative Information Agents X

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Abstract. Large-scale sensor networks are becoming more present in our life then ever. Such an environment could be a cellular network, an array of fire detection sensors, an array of solar receptors, and so on. As technology advances, opportunities arise to form large-scale cooperative systems in order to solve larger problems in an efficient way. As more large-scale systems are developed, there is a growing need to (i) measure the hardness of a given large-scale sensor network problem, (ii) compare a given system to other large-scale sensor networks in order to extract a suitable solution, (iii) predict the performance of the solution, and (iv) derive the value of each system property from the desired performance of the solution, the problem constraints, and the user's preferences. The following research proposes a novel system term, the coverage density, to define the hardness of a large-scale sensor network. This term can be used to compare two instances of large-scale sensor networks in order to find the suitable solutions for a given problem. Given a coverage density of a system, one may predict the solution performance and use it jointly with the preference and the constraints to derive the value of the system's properties.

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Section: Related Workmentioning

confidence: 99%

Coverage Density as a Dominant Property of Large-Scale Sensor Networks

Yadgar

Kraus

2006

Cooperative Information Agents X

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“…• Scalability (Turner et al, 2000). The number of the participating domains should be able to grow, without restricting the functionality of the system.…”

Section: Introductionmentioning

confidence: 99%

An Agent Based Architecture Benchmark

Belsis

Gritzalis

Lambrinoudakis

et al. 2014

Procedia - Social and Behavioral Sciences

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Agent based platforms provide a means for creating applications that run independently of operating system and network architecture; as a result, agents have become part of many systems and support a large number of interactions between different systems. Lately due to a shift to mobile computing paradigms, lightweight platforms, mainly oriented for resource constrained devices have emerged. To this end it is important to identify the load and to measure the performance of agent systems with appropriate benchmarks that provide details to direct future implementations.

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“…Researchers have applied a wide variety of methods for power system reconfiguration including artificial neural networks [14], [32], genetic algorithms [14], [15], fuzzy logic [33], [45], heuristics [1][2][3][4][5], [13], expert systems [4], [6][7][8][9][10][11], dynamic programming [11], simulated annealing, and Petri nets etc. Some of the most common of these methods and techniques have been discussed below.…”

Section: Methods and Techniques For Power Distribution System Reconfimentioning

confidence: 99%

“…In [8] the authors analyze the increase in communication load in terms of the number of messages, as the number of agents connected in a number of different topologies is increased. The concept of self building and self organizing MAS to achieve higher scale tolerance by defining scalability in terms of the total processing requirements for agents has been introduced in [9]. MAS that have fixed organizational structures are less scalable than those that adapt to the demands of an application.…”

Section: Overviewmentioning

confidence: 99%

“…Power system reconfiguration and restoration have been addressed using several different approaches. These include heuristics [1][2][3][4][5], [13], expert systems [4], [6][7][8][9][10][11], mathematical programming [11], soft computing [12], artificial neural networks, and genetic algorithm [14], [15]. However, such solutions do not adequately address the requirements of modern power systems.…”

Section: Multiagent Systems For Power System Reconfigurationmentioning

confidence: 99%

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A reconfigurable distributed multiagent system optimized for scalability

Moheuddin¹

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A RECONFIGURABLE DISTRIBUTED MULTIAGENT SYSTEM OPTIMIZED FOR SCALABILITY by Summiya Moheuddin This thesis proposes a novel solution for optimizing the size and communication overhead of a distributed multiagent system without compromising the performance. The proposed approach addresses the challenges of scalability especially when the multiagent system is large. A modified spectral clustering technique is used to partition a large network into logically related clusters. Agents are assigned to monitor dedicated clusters rather than monitor each device or node. The proposed scalable multiagent system is implemented using JADE (Java Agent Development Environment) for a large power system. The performance of the proposed topology-independent decentralized multiagent system and the scalable multiagent system is compared by comprehensively simulating different fault scenarios. The time taken for reconfiguration, the overall computational complexity, and the communication overhead incurred are computed. The results of these simulations show that the proposed scalable multiagent system uses fewer agents efficiently, makes faster decisions to reconfigure when a fault occurs, and incurs significantly less communication overhead. The proposed scalable multiagent system has been coupled with a scalable reconfiguration algorithm for an electric power system attempting to minimize the number of switch combination explored for reconfiguration. The reconfiguration algorithm reconfigures a power system while maintaining bus voltages within limits specified by constraints.

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Improving the Scalability of Multi-agent Systems

Cited by 34 publications

References 4 publications

Coverage Density as a Dominant Property of Large-Scale Sensor Networks

Coverage Density as a Dominant Property of Large-Scale Sensor Networks

An Agent Based Architecture Benchmark

A reconfigurable distributed multiagent system optimized for scalability

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