1,720,985 research outputs found
The big bucket: An IoT cloud solution for smart waste management in smart cities
No full textResearch and industries are devoting a great effort in getting cities and communities smarter, thus to improve citizens’ Quality of Life (QoL) and paying serious attention to e-government and e-inclusion processes. This is a strategic but also very complex objective that involves both governance and citizens to address many challenges. Following this line, this paper discusses the necessity for new smart waste management systems and presents a comprehensive state of the art on the use of the Internet of Things (IoT) for smart waste recycling. In particular, we present and argue the Big Bucket IoT Cloud environment, where smart dumpsters are equipped with low-cost sensors and open source easy-to-use hardware and software. Its architectural model is discussed and compared with other existing solutions in the future perspective
Migration of Multi-container Services in the Fog to Support Things Mobility
No full textIntegration between fog computing and the Internet of Things (IoT) paves the way to a plethora of promising opportunities. Device mobility might however impair fog computing benefits (e.g., low latency), which are indeed an outcome of fog proximity to end users/devices. A solution to this problem is to migrate the fog service across the fog infrastructure, thus to keep the distance to the served mobile device as low as possible. In this paper, we consider a fog service to be implemented as the combination of two containers, and we detail the demo through which we plan to show the impact of fog service migration on application performance. To this purpose, we plan to deploy an Augmented Reality (AR) application that detects vehicles in video frames and augments the latter with bounding boxes built around the detected vehicles. We offer to the audience the possibility to: (i) interact with the employed testbed by triggering device mobility; (ii) visualise the difference between migrating and not migrating the fog service in response to device mobility
The Impact of Container Migration on Fog Services as Perceived by Mobile Things
No full textThe integration between fog computing and the Internet of Things (IoT) creates plenty of new opportunities. Fog computing nodes run complex tasks on behalf of IoT devices, and the topological proximity of fog computing to the IoT enables several advantages (e.g., low latency). However, some IoT devices are mobile, and mobility may compromise the fog advantages. When a device moves, the communication path to the corresponding fog service may increase, with an impact on the fog advantages (which are a consequence of fog proximity) and overall performance. To overcome this issue, the fog service may be migrated across the fog computing infrastructure and maintained close enough to the served IoT device(s). It is worth noting, though, that service migration comes at a cost and may affect application Quality of Service (QoS). In this paper, we consider a fog service to be implemented as multiple containers, having one of them encapsulating an MQTT broker. Our contribution is the evaluation of the impact of container migration, which is considered in various flavours, on application QoS as perceived by mobile things. To this purpose, we consider an augmented reality application based on the MQTT protocol and conduct a set of experiments over a real fog computing testbed. Results show how migrating the fog service gives some benefits on the experienced QoS with respect to a case where no migration is performed
Design and evaluation of a fog platform supporting device mobility through container migration
Full text linkThe integration between the Internet of Things (IoT) and fog computing can pave the way to a plethora of applications. Fog computing indeed allows IoT devices to offload complex tasks to computing resources, known as fog nodes, that are in their proximity (e.g., at the network edge). Fog proximity enables important advantages, first and foremost low latency. However, IoT device mobility endangers those advantages, as the IoT device gets farther away from the serving fog node. Migrating the fog service among fog nodes, following the device route, permits to maintain proximity and preserve low latency. In this work, we propose an OpenStack-based platform that implements a fog service as a container and migrates the latter to support device mobility. We performed experiments over a real testbed to: (i) evaluate the impact of hardware resources of fog nodes on migration performance; (ii) validate our platform. Results are encouraging, as the average round-trip latency between the mobile device and the fog layer was as low as 10ms and exceeded the maximum value allowed by the considered application (i.e., 20ms) in 1.5% of the experiment duration
Serverless computing in the cloud-to-edge continuum
No full textServerless computing is establishing itself as a way to efficiently run cloud applications while abstracting the underlying infrastructure complexity away from application developers. At the same time, edge computing provides cloud-like facilities toward the edge of the network, in closer proximity to client devices. Integration of serverless and edge computing is promising. However, many research challenges still need to be solved to let this integration unleash its full potential. This special issue brings together works making high-quality and original contributions in this field, either proposing innovative strategies, implementing and testing novel solutions, or making new serverless datasets available to the community
Extending ETSI MEC Towards Stateful Application Relocation Based on Container Migration
No full textEdge computing allows to run microservices in close proximity to end user devices. This proximity lets edge computing support emerging 5G application scenarios that need low latency and high bandwidth (e.g., augmented reality, autonomous vehicles). Given its interest, edge computing is fastly gaining momentum and is currently being standardised by the European Telecommunications Standards Institute (ETSI) as Multi-Access Edge Computing (MEC). Notwithstanding its strengths, edge computing is significantly challenged by device mobility, as this can reduce proximity to the edge microservice, putting edge
computing benefits at risk. A way to solve this problem is to migrate the edge microservice across edge servers, to let it follow the application component running on the mobile device. Besides, if the microservice is stateful (i.e., it maintains a state associated to the user), its state needs to be migrated as well. Within ETSI MEC, this concept is expressed as stateful application relocation. The standard identifies three different high-level ways to transfer the application state. However, all of them assume that it is up to the application to actually relocate the state. In this work, we assume that applications at the edge run as containers, and we extend ETSI MEC to let it support stateful application relocation
by leveraging container migration techniques. This approach allows to transfer the application state in a transparent way to the application itself. We implemented our solution and tested it over a small-scale edge computing testbed to extract initial results
Towards an ontology development for automated applications in smart city environment of SmartME project
No full textCities are becoming everyday smarter, with an increasing multitude of electronic nodes distributed throughout the territory. These range from rather simple ones, such as sensors/actuators, but also smartphones, to more complex ones, such as data centers and workstations. Citizens may have a central role in consuming, but also producing the data. The consequence of all this is that the amount of data collected is enormous and these data need to be properly processed in order to make the most of them. Unfortunately, there are several challenges in data processing, but exploiting the Semantic Web technologies and linking data among them is the right way to face them. This paper introduces the SmartME project developed by the University of Messina, Italy, and discusses the technologies and approached that cat be utilized to properly manage the collected data. In this paper, we are working towards the incorporation of semantic layer with the SmartME project of University of Messina. In this, our contribution is to built logic for maintaining sensors and their collected information query them in more meaningful way for getting accurate results. Also, we have presented a way of modifying a previously developed Ontology, SSN and customized it for our purpose. Other than manual entry of a new sensor, which mitigates the burden of manual entry. To build up this logic, we have exploited Jena API of Semantic Web in Java
J2CBROKER: A service broker simulation tool for cooperative clouds
No full textThe Internet and digital technologies are transforming our world, but existing barriers, mainly due to obsolete Information Technologies (IT), lead citizens to miss out on goods and services, enterprises and start-ups to limit their horizons, and businesses and governments to cannot fully benefit from digital tools. Recently, Cloud computing emerged as hot topic in IT, both in industrial and academic area, in order to overcome the above barriers. Its use in large scale distributed infrastructure, platform or software services is motivated by the possibility to promote a new economy of scale in different contexts. Such scenario demands timely, repeatable, and controllable methodologies for evaluation of algorithms, applications and policies before the development of Cloud services or products, especially to achieve a good compromise between several performance indicators. To this end, simulations-based environments allow to evaluate the hypothesis prior to the software development, thus reducing the risk of economic losses, scarce Quality of Service or Quality of Experience. In this paper we present and discuss a simulation-based approach for Cloud Brokerage ecosystems. More specifically, we propose the J2CBROKER Simulation Tool, mainly based on JAVA and JavaScript Object Notation (JSON) technologies. Its architecture, functionalities and technological choices are discussed and motivated. Moreover, we present a case of study to evaluate the goodness of the proposed approach
Extending the QUIC protocol to support live container migration at the edge
No full textIn modern cloud and edge computing environments, services are typically provided as Virtual Machines (VMs). More recently, containers have been gaining momentum as a lightweight form of VMs. Container migration is used for several reasons, one of which being to maintain proximity between edge computing services and mobile users. When migrating containers, however, it is important to consider that they typically have ongoing communications with other endpoints, e.g., users' applications. Moreover, in case of connection-oriented protocols, communicating endpoints share a state (i.e., the connection), which needs to be migrated as well. Connection-oriented protocols like TCP were not designed having connection migration in mind, thus their connections cannot survive a change of IP address or port number. On the other hand, the QUIC protocol provides a mechanism for client-side connection migration, i.e., when a client device changes IP address (e.g., after a wireless handover), QUIC transparently migrates ongoing connections to the new address. Nonetheless, server-side connection migration in QUIC is not yet implemented nor investigated. In this paper, we extend QUIC to support server-side connection migration when a container is migrated between hosts. More specifically, we design two different strategies to achieve this purpose. Besides, we describe a proof-of-concept implementation based on aioquic, a Python open-source implementation of QUIC. We also verify that our implementation does not break QUIC specification nor undermines aioquic interoperability. Finally, we evaluate our solution by testing both the considered strategies using different container migration techniques and against a no-migration scenario
- …
