Periodic Reporting for period 2 - LightKone (Lightweight Computation for Networks at the Edge)
Período documentado: 2018-07-01 hasta 2019-12-31
LightKone’s main objective is to build the future Edge Computing architecture for Internet of Things (IoT). Current Edge Computing architectures extend Cloud Computing to exploit resources at the edge of the network (closer to the clients). However, the immense volumes of data generated through social networks, data analytics, and IoT impose new challenges that surpass the capability of Cloud Computing infrastructures. For example, the data generated in an IoT scenario can overwhelm a data center and devices may lack the connectivity to reach the data center. These problems are becoming acute as the number of IoT devices grows exponentially. LightKone provides solutions to these problems.
The LightKone project is developing a new Edge Computing model for general-purpose computation in which computations can be done directly at the edge. This is in contrast to existing Edge Computing models which are based on the cloud: in existing models edge data is aggregated and sent to the cloud where the computations are done, and decisions are sent back to the edge. In the LightKone model, the computations are done directly at the edge, which makes it more scalable and flexible, preparing it for the future where the edge will continue to grow faster than the cloud.
The LightKone project is developing a new Edge Computing model for general-purpose computation in which computations can be done directly at the edge. This is in contrast to existing Edge Computing models which are based on the cloud: in existing models edge data is aggregated and sent to the cloud where the computations are done, and decisions are sent back to the edge. In the LightKone model, the computations are done directly at the edge, which makes it more scalable and flexible, preparing it for the future where the edge will continue to grow faster than the cloud.
We have identified a set of industrially relevant application scenarios for edge computing, covering a large design space: sensor-based scenarios such as precision agriculture, edge-centric database applications, community networks, and embedded systems for manufacturing. For the Guifi.net community network, we define a monitoring system at the edge, a data storage system at the edge, and service provision support for the Cloudy platform, which provides services for Guifi.net. For the Scality petascale database, we define pre-indexing support at the edge. To reduce latency and improve search quality, we propose lambda functions at the edge to perform arbitrary computations, and we propose an S3 local cache of client data at the edge. For industrial manufacturing, we propose to extend a decentralized transport system based on RFID tags, so that data can be shared quickly and consistently between tags and manufacturing posts, to perform without stopping, which will significantly increase performance. For IoT sensor networks, we propose systems to do analytics directly on the edge, for precision agriculture including winery management. We also propose smart metering gateways, to enable local decision making for smart grid management.
We provide a single unified reference architecture for the cloud-edge spectrum, called LiRA (LightKone Reference Architecture), published in a white paper as an extension of the OpenFog Reference Architecture. Our architecture is practical because we focus on data and not on the cloud. Data is managed throughout the cloud-edge spectrum following two principles of data consistency, namely decentralized lateral data sharing (between devices in the same layer on the spectrum) and convergent vertical data semantics (between devices in different layers on the spectrum). In the final project period, we implement this reference architecture as three released application frameworks, AntidoteDB, Achlys, and Legion, which cover widely different parts of the cloud-edge spectrum. It is impractical and unwieldy to cover this spectrum with a single platform, since it would greatly encumber our progress with little advantage. Instead, we have three application development platforms that provide a coherent service and overlap in functionality where this is necessary. First AntidoteDB, which is a causally consistent transactional data store based on CRDTs and extended for the edge. Antidote supports a new programming methodology called Just-Right Consistency. Second Achlys, which is an application platform for edge applications that run directly on the sensor networks themselves. Achlys contains a task model for defining applications, a resilient CRDT-based data store called Lasp, and a resilient communications library using hybrid gossip called Partisan. Achlys runs on highly dynamic networks using highly resilient communication and is able to perform dataflow computation within the store while maintaining resilience. Third Legion, which is a platform for developing mobile Web-based applications based on shared objects containing CRDTs inside mobile phones. Legion uses peer-to-peer communication between mobile nodes to reduce latency, and the use of CRDTs guarantees data consistency.
In addition to the three application frameworks, we have released the GRiSP embedded programming platform and the Yggdrasil network protocol development framework. GRiSP consists of software and hardware that allows Internet-of-Things applications to run directly on embedded systems boards on the sensor networks themselves. GRiSP provides out-of-the-box support for standard Pmod sensors and actuators and the full Erlang OTP programming system, allowing the fast and efficient prototyping of robust edge applications. Yggdrasil is a software framework that allows developing efficient network protocols, including hybrid gossip communication, directly for ad hoc wired and wireless networks. Yggdrasil and Achlys are ported on the GRiSP embedded programming platform, thus providing an innovative powerful and comprehensive development platform for edge applications.
We provide a single unified reference architecture for the cloud-edge spectrum, called LiRA (LightKone Reference Architecture), published in a white paper as an extension of the OpenFog Reference Architecture. Our architecture is practical because we focus on data and not on the cloud. Data is managed throughout the cloud-edge spectrum following two principles of data consistency, namely decentralized lateral data sharing (between devices in the same layer on the spectrum) and convergent vertical data semantics (between devices in different layers on the spectrum). In the final project period, we implement this reference architecture as three released application frameworks, AntidoteDB, Achlys, and Legion, which cover widely different parts of the cloud-edge spectrum. It is impractical and unwieldy to cover this spectrum with a single platform, since it would greatly encumber our progress with little advantage. Instead, we have three application development platforms that provide a coherent service and overlap in functionality where this is necessary. First AntidoteDB, which is a causally consistent transactional data store based on CRDTs and extended for the edge. Antidote supports a new programming methodology called Just-Right Consistency. Second Achlys, which is an application platform for edge applications that run directly on the sensor networks themselves. Achlys contains a task model for defining applications, a resilient CRDT-based data store called Lasp, and a resilient communications library using hybrid gossip called Partisan. Achlys runs on highly dynamic networks using highly resilient communication and is able to perform dataflow computation within the store while maintaining resilience. Third Legion, which is a platform for developing mobile Web-based applications based on shared objects containing CRDTs inside mobile phones. Legion uses peer-to-peer communication between mobile nodes to reduce latency, and the use of CRDTs guarantees data consistency.
In addition to the three application frameworks, we have released the GRiSP embedded programming platform and the Yggdrasil network protocol development framework. GRiSP consists of software and hardware that allows Internet-of-Things applications to run directly on embedded systems boards on the sensor networks themselves. GRiSP provides out-of-the-box support for standard Pmod sensors and actuators and the full Erlang OTP programming system, allowing the fast and efficient prototyping of robust edge applications. Yggdrasil is a software framework that allows developing efficient network protocols, including hybrid gossip communication, directly for ad hoc wired and wireless networks. Yggdrasil and Achlys are ported on the GRiSP embedded programming platform, thus providing an innovative powerful and comprehensive development platform for edge applications.
The LightKone project has delivered the following results that extend the state of the art. First, the LightKone Reference Architecture (LiRA) for edge computing, which is defined as being a companion to the standard OpenFog Reference Architecture. Second, an ongoing start-up effort that is developing an innovative mobile application and development framework, aiming for fast response time and high availability beyond the state of the art. Third, three application development frameworks for edge computing, namely AntidoteDB, Legion, and Achlys. Together, these three frameworks cover the full edge-cloud spectrum as defined by LiRA. Fourth, the GRiSP embedded programming platform, both hardware and software, for fast out-of-the-box prototyping of edge applications. Fifth, the Yggdrasil framework for network protocol development. Achlys and Yggdrasil are ported to GRiSP, thus providing an innovative and powerful prototyping platform for edge applications out-of-the-box. Sixth, four significant industrial use cases that validate LiRA and showcase its technology: precision agriculture with self management abilities, scalable decentralized monitoring of community networks, scalable fast meta-data search for cloud databases, and fast non-stop RFID-based transport systems for manufacturing. All these results are part of the fast-growing edge computing sector, commonly known as Internet of Things. LightKone technology gives the scientific and technological foundations to manage this sector, which is expected to grow exponentially for at least the next decade with substantial effects on general society.