Refine
Document Type
- Conference Proceeding (14)
- Article (2)
Language
- English (16)
Has Fulltext
- no (16)
Is part of the Bibliography
- yes (16)
Keywords
- Distributed Computing (3)
- Information Centric Networking (3)
- Network protocols (3)
- Dataflow (2)
- ICN (2)
- In-network processing (2)
- Internet of Things (2)
- Link-Layer protocols (2)
- Network architectures (2)
- Network components (2)
Institute
- Fachbereich Technik (16)
In this poster, we discuss design options for a LoRaWAN and LoRa transmission system to employing Information-Centric Networking (ICN). ICN has been successfully applied to LoWPAN scenarios and can provide many benefits with respect to object-based security, performance, disruption tolerance and usability. Our findings indicate that the current LoRaWAN MAC layer is impractical for an ICN request-response with caching. We present ideas for a new MAC layer that harmonizes the long-range LoRa radios with ICN.
We present some results on integrating computing with networking so as to optimize the placement of workloads within a distributed network. We describe INCA, an In-Network Computing Architecture that allows clients to request functions that are then instantiated at a place within the network that attempts to meet both the QoE constraints of the application and the incentives of the operator of the network. We have implemented INCA, including network monitoring capability as well as a function placement optimization capability. In our evaluation, INCA demonstrates the benefit of a joint optimization of the networking and computing aspects.
Modern distributed computing frameworks and domain-specific languages provide a convenient and robust way to structure large distributed applications and deploy them on either data center or edge computing environments. The current systems suffer however from the need for a complex underlay of services to allow them to run effectively on existing Internet protocols. These services include centralized schedulers, DNS-based name translation, stateful load balancers, and heavy-weight transport protocols. In contrast, ICN-oriented remote invocation methodologies provide an attractive match for current distributed programming languages by supporting both functional programming and stateful objects such as Actors. In this paper we design a computation graph representation for distributed programs, realize it using Conflict-free Replicated Data Types (CRDTs) as the underlying data structures, and employ RICE (Remote Method Invocation for ICN) as the execution environment. We show using NDNSim simulations that it provides attractive benefits in simplicity, performance, and failure resilience.
A Dagstuhl seminar on Compute-First Networking (CFN) was held online from June 14th to June 16th 2021. We discussed the opportunities and research challenges for a new approach to in-network computing, which aims to overcome limitations of traditional edge/in-network computing systems.
The seminar discussed relevant use cases such as privacy-preserving edge video processing, connected and automated driving, and distributed health applications leveraging federated machine learning. A discussion of research challenges included an assessment of recent and expected future developments in networking and computing platforms and the consequences for in-network computing as well as an analysis of hard problems in current edge computing architectures.
We exchanged ideas on a variety of research topics and about the results of corresponding activities in the larger fields of distributed computing and network data plane programmability. We also discussed a set of suggested PhD topics and promising future research directions in the CFN space such as split learning that is supported by in-network computing.
Connecting long-range wireless networks to the Internet imposes challenges due to vastly longer round-trip-times (RTTs). In this paper, we present an ICN protocol framework that enables robust and efficient delay-tolerant communication to edge networks. Our approach provides ICN-idiomatic communication between networks with vastly different RTTs. We applied this framework to LoRa, enabling end-to-end consumer-to-LoRa-producer interaction over an ICN-Internet and asynchronous data production in the LoRa edge. Instead of using LoRaWAN, we implemented an IEEE 802.15.4e DSME MAC layer on top of the LoRa PHY and ICN protocol mechanisms in RIOT OS. Executed on off-the-shelf IoT hardware, we provide a comparative evaluation for basic NDN-style ICN [60], RICE [31]-like pulling, and reflexive forwarding [46]. This is the first practical evaluation of ICN over LoRa using a reliable MAC. Our results show that periodic polling in NDN works inefficiently when facing long and differing RTTs. RICE reduces polling overhead and exploits gateway knowledge, without violating ICN principles. Reflexive forwarding reflects sporadic data generation naturally. Combined with a local data push, it operates efficiently and enables lifetimes of ≥1 year for battery powered LoRa-ICN nodes.
This paper presents LoRa-ICN, a comprehensive IoT networking system based on a common long-range communication layer (LoRa) combined with Information-Centric Networking (ICN) principles. We have replaced the LoRaWAN MAC layer with an IEEE 802.15.4 Deterministic and Synchronous Multi-Channel Extension (DSME). This multifaceted MAC layer allows for different mappings of ICN message semantics, which we explore to enable new LoRa scenarios. We designed LoRa-ICN from the ground-up to improve reliability and to reduce dependency on centralized components in LoRa IoT scenarios. We have implemented a feature-complete prototype in a common network simulator to validate our approach. Our results show design trade-offs of different mapping alternatives in terms of robustness and efficiency.
The emergence of novel architectures such as fog and edge computing have blurred the boundaries between the network core and its periphery leading the Internet towards a computer board equivalent, while keeping the inherent distribution of the original Internet. In this paper, we present a novel architecture using an Intelligence Orchestration approach that is needed in this new network continuum computing paradigm. We aim to tackle the series of challenges of such as heterogeneity of stakeholders, use case and type of business dynamics, in addition to hardware and platforms by providing an “operating system” (OS) like design. The principles of the architecture are described and its advantages and needed next steps are also discussed.
To secure all communications, Named Data Networking (NDN) requires that each entity joining an NDN network go through a bootstrapping process first, to obtain its initial security credentials. Several solutions have been developed to bootstrap IoT devices in localized environments, where the devices being bootstrapped are within the physical reach of their bootstrapper. However, distributed applications need to bootstrap remote users and devices into an NDN-based system over insecure Internet connectivity. In this work, we take Hydra, a federated distributed file storage system made of servers contributed by multiple participating organizations, as a use case to drive the design and development of a remote bootstrapping solution, dubbed Cornerstone. We describe the design of Cornerstone, evaluate its effectiveness, and discuss the lessons learned from this process.
This paper describes an Information-Centric Dataflow system that is based on name-based access to computation results, NDN PSync dataset synchronization for enabling consuming compute functions to learn about updates and for coordinating the set of compute functions in a distributed Dataflow pipeline. We describe how relevant Dataflow concepts can be mapped to ICN and how data-sharing, data availability and scalability can be improved compared to state-of-the-art systems. We also provide a specification of an application-independent namespace design and report on our experience with a first prototype implementation.