RAINBOW’s motivation

What is the problem that the project is solving? Why a novel fog computing platform, such as the one offered by RAINBOW, is needed?

RAINBOW aspires to address the need to timely process the ever-increasing amount of data continuously gathered from heterogeneous IoT devices and appliances and enable fog computing to reach its true potential by providing the following services tailored-made to support scalable and secure edge applications:

  1. Deployment
  2. Security
  3. Orchestration
  4. Network fabric
  5. Data management & analytics

Our solution will provide significant benefits for popular cloud platforms, fog middleware, and distributed data management engines, and will extend the open-source ecosystem by pushing intelligence to the network edge while also ensuring security and privacy primitives across the device-fog-cloud-application stack.

RAINBOW provides a set of innovative mechanisms and middleware tools for IoT orchestration, data collection and decentralized analytics that guarantees network security, data protection, identity management and resource integrity. The key characteristic of the middleware will be the embedded intelligence and remote attestation mechanisms for establishing trust and QoS requirements while coping with performance and network uncertainties.

RAINBOW aspires to develop a fog orchestration framework on top of popular cloud management stacks by rethinking the current de-centralized computing and network algorithms for rapid resource provisioning, monitoring and seamless management of IoT services and cross-cloud applications. The framework will support affinity-aware and multi-objective offloading, enabling the execution of IoT services partitioned into segments (i.e., microservices) on different and heterogeneous fog and edge devices. The algorithmic process of determining where IoT services, and their partitioned segments must run, will be based on user defined QoS, energy, network dynamics and cost optimization constraints. RAINBOW will additionally embrace low-cost approximate and adaptive monitoring techniques to dynamically adjust the processing and data dissemination rate of IoT services, allowing edge devices to reduce energy consumption and ease the pressure on fog networks. RAINBOW will also support offline operation of IoT services and edge devices, enabling them to maintain execution of scheduled or responsive operations in the local environment despite having lost connection.

RAINBOW will enable the distribution of intelligence within overlay mesh networks so that data does not have to leave the network logical boundaries for fog service analytics. This will allow IoT services to maintain offline intelligence in order to reduce communication overheads and cope with network uncertainties. Addressing these challenges will allow analytic jobs to run low-power, mobile, and geodistributed infrastructure for the creation of insights on top of raw data produced and stored across the overlay mesh network. In turn, RAINBOW will provide rich and declarative query abstractions decoupled from the underlying infrastructure and distributed processing engine.

RAINBOW will enable IoT service operators to quickly express complex analytics through high-level directives without knowledge of the programming model of the data processing engine. Thus, IoT operators have the opportunity to only focus on business logic, leaving to RAINBOW the burden of how and where data is stored, and dealing with low-level data analysis aspects including heterogeneous fog resources and optimizing data movement.

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