On a Mobile Agent Framework for an Internet of Things

Godfrey, W. Wilfred; Jha, Shashi Shekhar; Nair, Shivashankar B.

doi:10.1109/csnt.2013.79

Cited by 19 publications

(8 citation statements)

References 10 publications

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“…Architectures and use cases for IoT systems, that utilize software agents, have been presented in [2,3,7,16,17,19,23,24,27,29,33,47,51,61,64,71]. As presented, an agent-based IoT architecture is multilayered, where the agents operate on different roles on each layer for the management, control, coordination and organization of system components and to connect components into the system.…”

Section: Edge Computing With Mobile Agentsmentioning

confidence: 99%

Energy efficient opportunistic edge computing for the Internet of Things

Leppänen

Riekki

2019

WEB

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Edge computing in Internet of Things enhances application execution by retrieving cloud resources to the close proximity of resource-constrained end devices at the edge and by enabling task offloading from end devices to the edge. In this paper, edge computing platforms are extended into the data producing end devices, including wireless sensor network nodes and smartphones, with mobile agents. Mobile agents operate as a multi-agent system on the opportunistic network of heterogeneous end devices, where the benefits include autonomous, asynchronous and the adaptive execution and relocation of application-specific tasks, while taking into account local resource availability. In addition to the vertical edge connectivity, mobile agents enable horizontal sharing of the information between end devices. Use cases are presented, where mobile agents address challenges in current edge computing platforms. An edge application is evaluated, where mobile agents as a multi-agent system process sensor data in a heterogeneous set of end devices, control the operation of the devices and share their results with system components. Mobile agents operate atop a REST-based mobile agent software framework that relies on embedded Web services for interoperability. A real-world evaluation and large-scale simulations show that energy consumption is reduced significantly in the edge application execution.

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Section: Edge Computing With Mobile Agentsmentioning

confidence: 99%

Energy efficient opportunistic edge computing for the Internet of Things

Leppänen

Riekki

2019

WEB

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“…Godfrey et al [30] propose a mobile agent framework to achieve communication between heterogeneous devices, search for resources and provide services to devices in the network. The mobile agent is either runs on a dedicated node or computer connected to the network, or embedded in the device itself.…”

Section: Agent-based Iot Architectures and Frameworkmentioning

confidence: 99%

Towards a Reference Architecture for Swarm Intelligence-Based Internet of Things

Zedadra

Savaglio

Jouandeau

et al. 2018

Internet and Distributed Computing Systems

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The Internet of Things (IoT) represents the global network which interconnects digital and physical entities. It aims at providing objects with intelligence that allows them to perceive, decide and cooperate with other objects, machines, systems and even humans to enable a whole new class of applications and services. Agent-Based Computing paradigm has been exploited to deal with the IoT system development. Many research works focus on making objects able to think by themselves thus imitating human brain. Swarm Intelligence studies the collective behavior of systems composed of many individuals who interact locally with each other and with their environment using decentralized and selforganized control to achieve complex tasks. Swarm intelligence-based systems provide decentralized, self-organized and robust systems with consideration of coordination frameworks. We explore in this paper the exploitation of swarm intelligence-based features in IoT-based systems. Therefore, we present a reference swarm-based architectural model that enables cooperation among devices in IoT systems.

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“…Message broadcasting drastically increases the communication cost [Wu et al 2015] and can clutter a network. In the proposed mechanism, we have used a conscientious agent migration strategy [Minar et al 1999] which has least inter-node communication cost [Godfrey et al 2013] as compared to other agent based approaches such as CLInG [Sempe and Drogoul 2003], EVAP [Chu et al 2007] and Random-walk with cloning [Gaber and Bakhouya 2008]. 2) Synchronization in distributed settings is a major challenge and is traditionally achieved by using a single node (or a subset of nodes) which provide for clocking.…”

Section: Introductionmentioning

confidence: 99%

On Ordering Multi-Robot Task Executions within a Cyber Physical System

Semwal

Jha

Nair

2017

ACM Trans. Auton. Adapt. Syst.

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With robots entering the world of Cyber Physical Systems (CPS), ordering the execution of allocated tasks during run-time becomes crucial. This is so because, in a real world, there can be several physical tasks that use shared resources that need to be executed concurrently. In this paper, we propose a mechanism to solve this issue of ordering task executions within a CPS which inherently handles mutual exclusion. The mechanism caters to a decentralized and distributed CPS comprising nodes such as computers, robots and sensor nodes, and uses mobile software agents that knit through them to aid the execution of the various tasks while also ensuring mutual exclusion of shared resources. The computations, communications and control, are achieved through these mobile agents. Physical execution of the tasks is performed by the robots in an asynchronous and pipelined manner without the use of a clock. The mechanism also features addition and deletion of tasks and insertion and removal of robots facilitating On-The-Fly Programming. As an application, a Warehouse Management System as a CPS has been implemented. The paper concludes with the results and discussions on using the mechanism in both emulated and real world environments.

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On a Mobile Agent Framework for an Internet of Things

Cited by 19 publications

References 10 publications

Energy efficient opportunistic edge computing for the Internet of Things

Energy efficient opportunistic edge computing for the Internet of Things

Towards a Reference Architecture for Swarm Intelligence-Based Internet of Things

On Ordering Multi-Robot Task Executions within a Cyber Physical System

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