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Demos: Robust Orchestration for Autonomous Networking
(2024)EWSN '23: Proceedings of the 2023 International Conference on Embedded Wireless Systems and NetworksResearch in wireless sensor networks has resulted in a remarkable breadth of highly capable systems. However, while specialized protocols perform well in the setting they were designed for, they often lack the ability to quickly adapt once operating conditions change drastically. Of particular importance is resilience to node and link failures, as clusters of nodes that lost their leader or split apart need to re-organize and find each ...Conference Paper -
Localised Adaptive Spatial-Temporal Graph Neural Network
(2023)KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningSpatial-temporal graph models are prevailing for abstracting and modelling spatial and temporal dependencies. In this work, we ask the following question: whether and to what extent can we localise spatial-temporal graph models? We limit our scope to adaptive spatial-temporal graph neural networks (ASTGNNs), the state-of-the-art model architecture. Our approach to localisation involves sparsifying the spatial graph adjacency matrices. To ...Conference Paper -
Combating Distribution Shift for Accurate Time Series Forecasting via Hypernetworks
(2023)2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)Time series forecasting has widespread applications in urban life ranging from air quality monitoring to traffic analysis. However, accurate time series forecasting is challenging because real-world time series suffer from the distribution shift problem, where their statistical properties change over time. Despite extensive solutions to distribution shifts in domain adaptation or generalization, they fail to function effectively in unknown, ...Conference Paper -
BUTLER: Increasing the Availability of Low-Power Wireless Communication Protocols
(2023)EWSN '22: Proceedings of the 2022 International Conference on Embedded Wireless Systems and NetworksOver the past years, various low-power wireless protocols based on synchronous transmissions (ST) have been developed to meet the high dependability requirements of emerging cyber-physical applications. For example, Wireless Paxos provides consensus, a key mechanism for building fault-tolerant systems through replication. However, Wireless Paxos and other ST-based protocols are themselves not fault-tolerant: They suffer from a single point ...Conference Paper -
Energy-Efficient Bootstrapping in Multi-hop Harvesting-Based Networks
(2023)2023 18th Wireless On-Demand Network Systems and Services Conference (WONS)Short-range multi-hop communication is an energy-efficient way to collect, share, and distribute large amounts of data with Internet of Things (IoT) systems. Nevertheless, the resource demands of wireless communication impose a burden on battery-operated IoT nodes, limiting their lifetime. Energy harvesting can address the energy limitation but introduces significant power variability, which affects reliable operation causing nodes to ...Conference Paper -
Hydra: Concurrent Coordination for Fault-tolerant Networking
(2023)22th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN’23)Low-power wireless networks have the potential to enable applications that are of great importance to industry and society. However, existing network protocols do not meet the dependability requirements of many scenarios as the failure of a single node or link can completely disrupt communication and take significant time and energy to recover. This paper presents Hydra, a low-power wireless protocol that guarantees robust communication ...Conference Paper -
p-Meta: Towards On-device Deep Model Adaptation
(2022)KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data MiningConference Paper -
Deep Partial Updating: Towards Communication Efficient Updating for On-device Inference
(2022)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2022Emerging edge intelligence applications require the server to retrain and update deep neural networks deployed on remote edge nodes to leverage newly collected data samples. Unfortunately, it may be impossible in practice to continuously send fully updated weights to these edge nodes due to the highly constrained communication resource. In this paper, we propose the weight-wise deep partial updating paradigm, which smartly selects a small ...Conference Paper -
Stitching Weight-Shared Deep Neural Networks for Efficient Multitask Inference on GPU
(2022)2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)Intelligent personal and home applications demand multiple deep neural networks (DNNs) running on resource-constrained platforms for compound inference tasks, known as multitask inference. To fit multiple DNNs into low-resource devices, emerging techniques resort to weight sharing among DNNs to reduce their storage. However, such reduction in storage fails to translate into efficient execution on common accelerators such as GPUs. Most DNN ...Conference Paper -
Accurate Onboard Predictions for Indoor Energy Harvesting using Random Forests
(2022)2022 11th Mediterranean Conference on Embedded Computing (MECO)Indoor energy harvesting has recently enabled long-term deployments of sustainable IoT sensor nodes. The performance of such systems operating in an energy-neutral manner can be optimized by exploiting energy prediction models. Numerous prediction algorithms have been developed, yet they are primarily intended for outdoor (solar) energy harvesting. Indoor environments are much more challenging to predict since the primary energy is very ...Conference Paper