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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…
Today's datacenters face important challenges for providing low-latency high-quality interactive services to meet user's expectation. For improving the application throughput, recent research works have embedded application deadline…
In wireless federated learning (FL), the clients need to transmit the high-dimensional deep neural network (DNN) parameters through bandwidth-limited channels, which causes the communication latency issue. In this paper, we propose a…
By leveraging deep learning based technologies, the data-driven based approaches have reached great success with the rapid increase of data generated of Industrial Indernet of Things(IIot). However, security and privacy concerns are…
As distributed machine learning (ML) workloads scale to thousands of GPUs connected by high-speed interconnects, tail latency in collective communication has become a major bottleneck. Existing RDMA transports, such as RoCE, IRN, SRNIC, and…
Communication for control-centric industrial applications is characterized by the requirements of very high reliability, very low and deterministic latency and high scalability. Typically, IEEE 802.11-based wireless local area networks…
In the last decades, technological developments in wireless communications have been coupled with an increasing demand of mobile services. From real-time applications with focus on entertainment (e.g., high quality video streaming, virtual…
Federated Learning (FL) is a popular distributed learning paradigm to break down data silo. Traditional FL approaches largely rely on gradient-based updates, facing significant issues about heterogeneity, scalability, convergence, and…
The Datagram Transport Layer Security (DTLS) protocol is the IETF standard for securing the Internet of Things. The Constrained Application Protocol, ZigBee IP, and Lightweight Machine-to-Machine (LWM2M) mandate its use for securing…
Ultra-reliable low latency communications (URLLC) service is envisioned to enable use cases with strict reliability and latency requirements in 5G. One approach for enabling URLLC services is to leverage Reinforcement Learning (RL) to…
Similarly to elsewhere on the Internet, practical security in the Internet of Things (IoT) is achieved by combining an array of mechanisms, at work at all layers of the protocol stack, in system software, and in hardware. Standard protocols…
Passive optical networks (PON) technology is increasingly becoming an attractive solution in modern data centres as it provides energy efficient, high capacity, low cost, scalable and flexible connectivity. In this paper we report the…
In this paper, we consider a bidirectional relay network with half-duplex nodes and block fading where the nodes transmit with a fixed transmission rate. Thereby, user 1 and user 2 exchange information only via a relay node, i.e., a direct…
In this work, we propose a deep learning (DL)-based approach that integrates a state-of-the-art algorithm with a time-frequency (TF) learning framework to minimize overall latency. Meeting the stringent latency requirements of 6G orthogonal…
We design and deploy in production the first flat datacenter networks. Our design, called RNG, is based on quasi-random graphs. While the cost and fault-tolerance benefits of such topologies have been long known, their practical realization…
High-performance industrial automation systems rely on tens of simultaneously active sensors and actuators and have stringent communication latency and reliability requirements. Current wireless technologies like WiFi, Bluetooth, and LTE…
Split Federated Learning (SFL) offers a promising approach for distributed model training in wireless networks, combining the layer-partitioning advantages of split learning with the federated aggregation that ensures global convergence.…
In this paper, we conduct systematic measurement studies to show that the high memory bandwidth consumption of modern distributed applications can lead to a significant drop of network throughput and a large increase of tail latency in…
Due to the enormous variety of application scenarios and ubiquity,Internet of Things (IoT) brought a new perspective of applications for the current and future Internet. The Wireless Sensor Networks provide key devices for developing the…
Internet of Things (IoT) services will use machine learning tools to efficiently analyze various types of data collected by IoT devices for inference, autonomy, and control purposes. However, due to resource constraints and privacy…