Mobile-C: a mobile agent platform for mobile C/C++ agents

Chen, Bin; Cheng, Harry H.; Palen, Joe

doi:10.1002/spe.742

Cited by 70 publications

(50 citation statements)

References 39 publications

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“…Agent-based computing emerged in the 1990s and has since become a powerful new programming paradigm [25]. Essentially, agent-based software development allows complex problems or systems to be broken down into high-level abstractions.…”

Section: The Hybrid Agent Real-time Platformmentioning

confidence: 99%

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A hybrid real-time agent platform for fault-tolerant, embedded applications

Erlank

Bridges

2017

Auton Agent Multi-Agent Syst

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This paper describes an agent platform based on the Foundation for Intelligent Physical Systems Abstract Architecture, which, together with a highly fault tolerant, bioinspired hardware architecture, aims to increase the reliability of future, low-cost satellites. To achieve the stringent operational requirements imposed by the real-time and resourceconstrained environment of a satellite, the Hybrid Agent Real-Time Platform (HARP) distinguishes itself from other platforms in three areas. Firstly, the HARP middleware uses discrete processors, instead of virtual machines or interpreters, as its agent execution environment. This has the advantage of reducing the agency memory footprint and enabling agents to perform real-time tasks. Secondly, the HARP communication stack makes use of ISO-TP over CAN 2.0A as its transfer level protocol, cutting out resource-intensive layers such as HTTP and IIOP. In addition, the communication stack allows real-time CAN traffic to share the network and be given priority over Agent Communication Language messages. Finally, the HARP middleware embeds a peer-to-peer task manager in each agency, allowing systems which are built using the bio-inspired Artificial Stem Cell Architecture and HARP middleware to autonomously reconfigure in the event of failures. The detailed design of the HARP middleware is given, together with details of an implementation of the HARP middleware on a set of prototype satellite hardware. The performance and scaling potential of the middleware, determined through a set of physical experiments, provide evidence of the practical feasibility of the proposed architecture.

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Section: The Hybrid Agent Real-time Platformmentioning

confidence: 99%

“…Mobile-C was developed to have a small memory footprint and be FIPA compliant, but differs from the majority of agent platforms by using an embedded C/C++ interpreter as its agent execution environment [25]. The embedded interpreter, named Ch, is claimed to be smaller than the Java ME Embedded runtime environment.…”

Section: Introductionmentioning

confidence: 99%

A hybrid real-time agent platform for fault-tolerant, embedded applications

Erlank

Bridges

2017

Auton Agent Multi-Agent Syst

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“…The IEEE FIPA [23] is an international agent standard. The majority of actively maintained Java-based or C-based multi-agent platforms, such as JADE and Mobile-C [24,25], are IEEE FIPA compliant platforms. Additionally, members of the IEEE FIPA standard include researchers and experts from many academic institutions and industrial companies.…”

Section: Design Considerations Of Sensor Agent Cloudmentioning

confidence: 99%

“…With regard to software, Mobile-C [24,25], an embeddable multi-agent agent platform supporting C/C++ mobile agents, is employed in Sensor Agent Cloud as the sensor node agency and client agency, as shown in Figure 5. Among the Mobile-C modules shown in Figure 5, by default, the three FIPA mandatory modules, the Agent Management System (AMS), Agent Communication Channel (ACC), and Directory Facilitator (DF), are initialized when Mobile-C is started.…”

Section: A Prototype Sensor Nodementioning

confidence: 99%

An Agent-Based System for Sensor Cloud Management

Chou¹,

Huang²,

Peng³

2012

Embedded Systems - High Performance Systems, Applications and Projects

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“…To this end, a complete review of literature about agent-based approaches well suited to the domain of traffic and transportation system, because transportation systems are often geographically distributed in dynamics changing environments as presented in Ref. [16]. In particular, the paper reviews agent-based traffic applications classified in five categories: (1) agent-based traffic control and management system architecture and platforms; (2) agent-based systems for roadway transportation; (3) agent-based systems for air-traffic control and management; (4) agent-based systems for railway transportation; and (5) multi-agent traffic modeling and simulation.…”

mentioning

confidence: 99%

Improving Traffic Conditions by Using Neural Networks

C.¹,

R.²,

M.³

et al. 2016

CTA

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Abstract:The paper promotes the implementation of a neural network approach to improve one of the most transcendent traffic conditions: the mobility of the cars in any particular junction. Neural networks have proven to be an effective paradigm of modern computing, providing extensive benefits in a wide range of applications. In this sense, the paper uses a BPNN (backpropagation neural network) model. The three input nodes are related to: n1: the amount of cars in the road; n2: the green light interval; and n3: the distance (taking into account the quantity of cars) between the first car in the intersection and the last car in the longest line in front of it. In particular, the paper promotes that each traffic light signal will be capable of offering a new green light interval according to the requirement and constrains of the vitality, ensuring a vehicular mobility level greater than 65%. To assess this idea, the paper presents two experiments confronting the real world data versus experimental results. For example, in the first experiment, the BPNN improves the performance of the real data about vehicular mobility in almost 30%. Finally, some conclusions and future work are presented.

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Mobile-C: a mobile agent platform for mobile C/C++ agents

Cited by 70 publications

References 39 publications

A hybrid real-time agent platform for fault-tolerant, embedded applications

A hybrid real-time agent platform for fault-tolerant, embedded applications

An Agent-Based System for Sensor Cloud Management

Improving Traffic Conditions by Using Neural Networks

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