An agent-based hybrid service delivery for coordinating internet of things and 3rd party service providers

Wang, Junping; Zhu, Qiliang; Ma, Yan

doi:10.1016/j.jnca.2013.04.014

Cited by 32 publications

(17 citation statements)

References 16 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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“…Now the most common view of IoT refers to a giant dynamic global network infrastructure for the ubiquitous connection of numerous physical objects (e.g., everyday things equipped with RFIDs, various sensors and actuators, embedded and mobile electronic devices, low capacity and powerful computers) that rely on advanced communication and information processing technologies. IoT aims at fusion of real (physical) and virtual (information) worlds, and the IoT concept evolves to service-oriented information interconnection and convergence (Kortuem, 2010), (Wang, 2013), (Perera, 2014), (Korzun, 2016).…”

Section: Industrial Internet Of Thingsmentioning

confidence: 99%

Secure Communication and Data Processing Challenges in the Industrial Internet

Gurtov¹,

Liyanage²,

Korzun³

2016

BJMC

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Abstract. The next industrial revolution is foreseen to happen with upcoming Industrial Internet that combines massive data collected by industrial sensors with data analysis for improving the efficiency of operations. Collecting, pre-processing, storing and analyzing such real-time data is a complex task with stringent demands on communication intelligence, QoS and security. In this paper we outline some challenges facing the Industrial Internet, namely integration with 5G wireless networks, Software Defined Machines, ownership and smart processing of digital sensor data. We propose a secure communication architecture for the Industrial Internet based on Smart Spaces and Virtual Private LAN Services. It is a position paper, describing state-of-the-art and a roadmap for future research on the Industrial Internet.

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“…Furthermore, this communication based on radio-frequency identification (RFID) technology enables companies to provide improved parcel-tracking services to customers. A recent work by Wang, Zhu, & Ma (2013) describes a novel approach based on an agentbased hybrid service delivery, that enables third party service providers to efficiently manage IoT services. Another breakthrough idea based on sensor equipment and Internetconnected cars is the Google driveless-car project (Saitoh, Kondoh, & Komatsu, 1989).…”

Section: Business Opportunities Of Iot and MCCmentioning

confidence: 99%

Convergence of Internet of things and mobile cloud computing

Psannis

Xinogalos

Sifaleras

2014

Systems Science & Control Engineering

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As an integral element of future Internet, Internet of things (IoT) could be described as a real-world interaction with everything connected via intelligent network infrastructure and advanced communication technologies. Mobile cloud computing (MCC), on the other hand, offers an infrastructure wherein both data storage and data processing take place outside of the mobile device. As a more mature infrastructure, MCC offers several advantages, while the relatively new IoT has several limitations. In this paper, we present a survey of IoT limitations and MCC advantages. Specifically, we present the most advantageous aspects of MCC and how they alleviate the limitations of IoT. Furthermore, we discuss several IoT-enabled business services to highlight the benefits of converging IoT and MCC.

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An agent-based hybrid service delivery for coordinating internet of things and 3rd party service providers

Cited by 32 publications

References 16 publications

Energy efficient opportunistic edge computing for the Internet of Things

Energy efficient opportunistic edge computing for the Internet of Things

Secure Communication and Data Processing Challenges in the Industrial Internet

Convergence of Internet of things and mobile cloud computing

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