Distributed artificial intelligence with multi-agent systems for MEC

Abstract In this paper, the Multi-access Edge Computing (MEC) system architecture, as defined by the ETSI standards, is modeled as a multi-agent system. MEC system management services and application execution components are designed as software agents, facilitating distributed artificial intelligence capabilities in their operation and cooperation. Further, the integration of current agent technologies into the standardized MEC system is discussed. Lastly, a case study is presented on how to integrate an existing Internet of Things agent framework and agent-based edge application seamlessly to the MEC system

Resource-oriented mobile agent and software framework for the Internet of Things

Abstract The Internet of Things vision proposes a global platform in an unforeseen scale for distributed applications that rely on data provided by interconnected resource-constrained things. In such large-scale systems, centralized control of system operation by a single component through vertical interactions becomes unfeasible. Ideally, decentralized control in the proximity of things enables to take into account the local dynamic resource availability and environmental characteristics that are used to optimize the application execution. To realize decentralization, capabilities for horizontal interactions, that complement the vertical interactions, and for opportunistic participation of things are needed. This thesis explores mobile agent technology to implement distributed Internet of Things applications that benefit from both vertical and horizontal interactions of the application components. First, a resource-oriented reactive mobile agent architecture and a software framework are presented. The framework facilitates RESTful interactions between agents and other system components and provides a REST-based interface to build opportunistic agent-based applications. Two agent platforms are presented that integrate resource-constrained things into the framework as mobile agent hosts. Second, mobile agent based mobile crowdsensing and edge computing applications are evaluated with large-scale simulations and real-world experiments. The results show that energy consumption is decreased in the participating things, in comparison with the existing approaches, by agent-based in-network data processing and control of the thing operation. This thesis makes a valuable contribution by enabling mobile agent operations in a heterogeneous set of resource-constrained things. The presented empirical evidence shows how mobile agent technology increases energy efficiency in distributed application execution. The presented mobile agent architecture and software framework potentially accelerate the utilization of mobile agent technology in the Internet of Things.Tiivistelmä Esineiden Internet liittää resurssirajoitteiset sulautetut laitteet laajamittaisesti Internet-verkkoon, jossa niiden tuottamaa tietoa hyödynnetään hajautettujen järjestelmien sovelluksissa. Esineiden Internetin järjestelmien odotetaan skaalautuvan niin laajoiksi, ettei keskitetty, vertikaaliseen vuorovaikutukseen perustuva järjestelmähallinta ole enää käyttökelpoinen ratkaisu. Hajautettu hallinta lähellä tietoa tuottavia laitteita tuo etuja, kun paikallisesti sovelluksen suorituksessa otetaan huomioon toimintaympäristön tila ja voidaan reagoida dynaamisesti resurssien saatavuuteen. Hajautus Esineiden Internetin sovellusalustoilla edellyttää menetelmiä sekä laitteiden vertikaaliseen ja horisontaaliseen vuorovaikutukseen, että niiden dynaamisen osallistumisen mahdollistamiseksi sovelluksen suorittamisessa. Tässä työssä tutkittiin mobiiliagentti-teknologiaa hajautettujen sovellusten toteuttamiseen Esineiden Internet-ympäristössä. Työssä esitettiin resurssisuuntautunut arkkitehtuuri reaktiivisille mobiiliagenteille sekä ohjelmistokehys, joita käyttäen voidaan toteuttaa agenttipohjaisia hajautettuja sovelluksia. Ohjelmistokehys perustuu REST-arkkitehtuurimalliin, jonka pohjalta esitettiin yhdenmukainen rajapinta agenttien ja järjestelmäkomponenttien väliseen vuorovaikutukseen. Ohjelmistokehyksen osana toteutettiin kaksi mobiiliagentti-ohjelmistoalustaa resurssirajoitteisille sulautetuille laitteille. Työssä tarkasteltiin mobiiliagentti-pohjaisten Esineiden Internet-sovellusten energiatehokkuutta simuloinneilla sekä tosielämän kokeilla. Tarkastelun kohteeksi valittiin joukkoistettu mobiilihavainnointi sekä reunalaskennan ulottaminen resurssirajoitteisiin laitteisiin. Saadut tulokset osoittavat, että laitteiden energiankulutusta voidaan pienentää verrattuna aiemmin esitettyihin ratkaisuihin hyödyntämällä mobiiliagentteja tiedonkäsittelyyn laitteessa sekä laitteen toiminnan ohjaamiseen. Työssä esitetty resurssisuuntautunut mobiiliagenttiarkkitehtuuri sekä ohjelmistokehys edesauttavat mobiiliagentti-teknologian hyödyntämistä resurssirajoitteisissa sulautetuissa laitteissa. Tosielämän kokeista saadut tulokset osoittavat mobiiliagenttiteknologian hyötyjä hajautettujen sovellusten toteuttamisessa Esineiden Internetiin

Energy efficient opportunistic edge computing for the Internet of Things

Abstract 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 these 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. The benefits include autonomous, asynchronous and adaptive execution and relocation of application-specific computational tasks, while taking into account the local resource availability. In addition to the vertical edge connectivity, mobile agents enable horizontal sharing of information between these 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 tasks results in the system. The mobile agents operate atop a REST-compliant software agent framework that relies on embedded Web services for interoperability. A real-world evaluation and large-scale simulations show that energy consumption is reduced significantly, up to 60%, in the edge application execution

Service modeling for opportunistic edge computing systems with feature engineering

Abstract The complex and opportunistic environment in which edge computing systems operate, poses a fundamental challenge for online edge system orchestration, resource provisioning and real-time responsiveness in response to user movement. Such a challenge needs to addressed throughout the edge system lifecycle, starting from the software development methodologies. In this paper, we propose a novel development process for modeling opportunistic edge computing services, which rely on (i) ETSI MEC reference architecture and Opportunistic Internet of Things Service modeling for the early stage of system analysis and design, i.e. domain model and service metamodel; and on (ii) feature engineering for evaluating those opportunistic aspects with data analysis. To address the identified opportunistic properties, at the service design phase we construct (both automatically and through domain expertise) Opportunistic Feature Vectors for Edge, containing the numerical representations of those properties. Such vectors enable further data analysis and machine learning techniques in the development of distributed, effective and efficient edge computing systems. Lastly, we exemplify the integrated process with a microservice-based user mobility management service, based on a real-world data set, for online analysis in MEC systems

1st International workshop on edge of things:enabling internet of things ecosystems through the edge computing (EoT 2019):message from the workshop chairs

Abstract Presents the introductory welcome message from the conference proceedings. May include the conference officers’ congratulations to all involved with the conference event and publication of the proceedings record

Situation awareness for autonomous vehicles using blockchain-based service cooperation

Abstract Efficient Vehicle-to-Everything enabling cooperation and enhanced decision-making for autonomous vehicles is essential for optimized and safe traffic. Real-time decision-making based on vehicle sensor data, other traffic data, and environmental and contextual data becomes imperative. As a part of such Intelligent Traffic Systems, cooperation between different stakeholders needs to be facilitated rapidly, reliably, and securely. The Internet of Things provides the fabric to connect these stakeholders who share their data, refined information, and provided services with each other. However, these cloud-based systems struggle to meet the real-time requirements for smart traffic due to long distances across networks. Here, edge computing systems bring the data and services into the close proximity of fast-moving vehicles, reducing information delivery latencies and improving privacy as sensitive data is processed locally. To solve the issues of trust and latency in data sharing between these stakeholders, we propose a decentralized framework that enables smart contracts between traffic data producers and consumers based on blockchain. Autonomous vehicles connect to a local edge server, share their data, or use services based on agreements, for which the cooperating edge servers across the system provide a platform. We set up proof-of-concept experiments with Hyperledger Fabric and virtual cars to analyze the system throughput with secure unicast and multicast data transmissions. Our results show that multicast transmissions in such a scenario boost the throughput up to 2.5 times where the data packets of different sizes can be transmitted in less than one second

Programming sensor networks with nomadic NFC transponders

Abstract We present how NFC transponders can be used for energy efficient programming of closed-loop sensor networks, to update or augment the existing functionality. Use cases include road tunnel inspection, water pipeline monitoring and maintaining safety information on behalf of mine workers. We utilize opportunistic movement of the human operator, the flow of fluid in a pipeline or material in mines, to move the NFC transponder in the system effortlessly and without external network connectivity. Transponders contain mobile agents in their memory, which are injected into the system when transponder comes to the proximity of a node with NFC reader component. Then mobile agents autonomously operate their tasks, i.e. collect and process sensor data in the devices, detect events from data, control physical components and report their results. Mobile agents can adapt to the operational conditions of the system and physical environment, e.g. to save energy or operate in isolated network segments in fault situations. Real-world evaluation shows that this method is energy efficient in comparison with communications atop similar wireless sensor network

Open-source RANs in practice:an Over-The-Air deployment for 5G MEC

Abstract Edge computing that leverages cloud resources to the proximity of user devices is seen as the future infrastructure for distributed applications. However, developing and deploying edge applications, that rely on cellular networks, is burdensome. Such network infrastructures are often based on proprietary components, each with unique programming abstractions and interfaces. To facilitate straightforward deployment of edge applications, we introduce open-source software (OSS) based radio access network (RAN) on over-the-air (OTA) commercial spectrum with Development Operations (DevOps) capabilities. OSS allows software modifications and integrations of the system components, e.g., Evolved Packet Core (EPC) and edge hosts running applications, required for new data pipelines and optimizations not addressed in standardization. Such an OSS infrastructure enables further research and prototyping of novel end-user applications in an environment familiar to software engineers without telecommunications background. We evaluated the presented infrastructure with end-to-end (E2E) OTA testing, resulting in 7.5MB/s throughput and latency of 21ms, which shows that the presented infrastructure provides low latency for edge applications

Edge-supported microservice-based resource discovery for mist computing

Abstract Mist computing extends the Internet of Things computing infrastructures to the IoT devices at the edges of the networks. The dynamic characteristics of the IoT environments and resource limitations of the devices introduce challenges to the orchestration of the mist platform resources. In this paper, we present a hybrid resource discovery solution for mist, based on the IETF CoRE Resource Directories deployed as containerized Microservices to the supporting edge devices. This way the directory instances can be deployed on-demand as part of the edge platform, where each instance serves a mist network connected to the hosting edge device. This enables low latency resource queries at one-hop distance for the mist applications. At the edge layer, the directories form a distributed discovery infrastructure, connecting resources in disparate mist networks with each other and cloud and edge applications. A real-world prototype of such discovery infrastructure is implemented, based on low resource edge devices hosting the directory instances and low-power embedded devices as the mist resource servers and clients. The prototype is evaluated with latency and power consumption measurements, where the results show that discovery latency is as low as half a millisecond with a low power consumption