The requirements for this platform are derived from a review of literature, identifying the shortcomings of existing platforms. As a result, cloneMAP is an enabler for the combination of MAS and the IoT.
Its design goals are high scalability and fault-tolerance. cloneMAP is designed to tackle the aforementioned challenges. This work proposes a cloud-native Multi-Agent Platform (cloneMAP).
Given the tremendous amount of research work done in the field of MASs, the IoT can benefit from that experience. Both, MAS and IoT, consist of distributed autonomous entities able to exchange information. Furthermore, IoT devices often have restricted hardware capabilities limiting the execution of complex applications. However, many different frameworks for IoT-devices exist, making interoperability difficult. Geographically distributed devices, or things, are connected to the Internet and therefore able to communicate. In fact these approaches show strong similarities. As a key feature of MASs, messaging among agents has to be enabled while hiding the underlying complexity of the network.Īn emerging field of application for large-scale MASs is the Internet of Things (IoT). Second, it has to implement standardized tools for MAS developers, such as an agent management system (AMS) or the directory facilitator (DF). First, an additional layer between the cloud platform level (often container orchestration) and the MAS application is required for managing the MAS and translating its requirements to the underlying orchestration tool. The challenges in exploiting this potential synergy are the following. While cloud computing enables resource provision and management on platform level, MAS constitutes a paradigm for a distributed application design utilizing possibly distributed resources. MAS and cloud computing, have the potential to complement each other. Orchestration tools such as Kubernetes in conjunction with container technology allow to compose distributed applications consisting of many distinct components, often referred to as microservices. It allows for an efficient, easy and on-demand provisioning of resources on infrastructure, platform and application layer.
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Ĭloud computing offers techniques to achieve high scalability and fault-tolerance, i. e., the recovery from hardware or software failures. Besides, such platforms have single-points of failure, which may prevent them from being used in critical real world applications. Additionally, literature shows that MAPs do not offer good performance when it comes to large-scale and distributed MAS applications. Moreover, these applications often comprise only a small number of agents. īesides the wide-spread use of MASs in the scientific community, only few real world use cases adopt MAS based approaches. One of the most popular MAPs is the Java Agent DEvelopment Framework (JADE). For the implementation and execution of MASs many different Multi-Agent Platforms (MAP) have been proposed. They allow for a distributed, robust and scalable design of applications in the field of, e. g., simulation, monitoring and control. Multi-Agent Systems (MAS) have been around for decades and have been applied to various use cases. This leads to the conclusion that cloneMAP extends the range of possible MAS applications and enables the integration with IoT concepts. Furthermore, the implementation of a large-scale use case verifies cloneMAP’s suitability for IoT applications.
A comparison with JADE via relevant performance metrics indicates the massively improved scalability. Thereby, bottlenecks and single-points of failure are conceptually avoided. A microservice architecture is used to implement it in a distributed way utilizing the open-source container orchestration system Kubernetes.
To this aim, we present a cloud-native Multi-Agent Platform (cloneMAP) as a modern MAP based on cloud-computing techniques to enable scalability and fault-tolerance. However, well known multi-agent platforms (MAP), e. g., Java Agent DE-velopment Framework (JADE), are not able to deal with these challenges. The key enabler for utilizing MAS in the IoT is the ability to build large-scale and fault-tolerant MASs since IoT concepts comprise possibly thousands or even millions of devices. The combination of MAS and IoT would allow the transfer of the experience gained in MAS research to the broader range of IoT applications. Both share many similarities such as the interconnection of distributed devices and their cooperation. Multi-agent systems (MAS) represent a distributed computing paradigm well suited to tackle today’s challenges in the field of the Internet of Things (IoT).
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