arXiv subjects

Victor Cionca

Publications and source records attributed to Victor Cionca.

7 recordsLinked to original sources

arXiv2026

An experimental evaluation of satellite constellation emulators

Satellite emulation software is essential for research due to the lack of access to physical testbeds. To be useful, emulators must generate observations that are well-aligned with real-world ones, and they must have acceptable resource overheads for setting up and running experiments. This study provides an in-depth evaluation of three open-source emulators: StarryNet, OpenSN, and Celestial. Running them side-by-side and comparing them with real-world measurements from the WetLinks study identifies shortcomings of current satellite emulation techniques as well as promising avenues for research and development.

cs.DC↗

arXiv2025

Accuracy vs Performance: An abstraction model for deadline constrained offloading at the mobile-edge

In this paper, we present a solution for low-latency deadline-constrained DNN offloading on mobile edge devices. We design a scheduling algorithm with lightweight network state representation, considering device availability, communication on the network link, priority-aware pre-emption, and task deadlines. The scheduling algorithm aims to reduce latency by designing a resource availability representation, as well as a network discretisation and a dynamic bandwidth estimation mechanism. We implement the scheduling algorithm into a system composed of four Raspberry Pi 2 (model Bs) mobile edge devices, sampling a waste classification conveyor belt at a set frame rate. The system is evaluated and compared to a previous approach of ours, which was proven to outcompete work-stealers and a non-pre-emption based scheduling heuristic under the aforementioned waste classification scenario. Our findings show the novel lower latency abstraction models yield better performance under high-volume workloads, with the dynamic bandwidth estimation assisting the task placement while, ultimately, increasing task throughput in times of resource scarcity.

cs.DC↗

arXiv2025

Preemption Aware Task Scheduling for Priority and Deadline Constrained DNN Inference Task Offloading in Homogeneous Mobile-Edge Networks

This paper addresses the computational offloading of Deep Neural Networks (DNNs) to nearby devices with similar processing capabilities, to avoid the larger communication delays incurred for cloud offloading. We present a preemption aware scheduling approach for priority and deadline constrained task offloading in homogeneous edge networks. Our scheduling approach consists of two distinct scheduling algorithms, designed to accommodate the differing requirements of high and low priority tasks. To satisfy a task's deadline, our scheduling approach considers the availability of both communication and computational resources in the network when making placements in both the current time-slot and future time-slots. The scheduler implements a deadline-aware preemption mechanism to guarantee resource access to high priority tasks. When low-priority tasks are selected for preemption, the scheduler will attempt to reallocate them if possible before their deadline. We implement this scheduling approach into a task offloading system which we evaluate empirically in the real-world on a network of edge devices composed of four Raspberry Pi 2 Model B's. We evaluate this system under against a version without a task preemption mechanism as well as workstealing approaches to compare the impact on high priority task completion and the ability to complete overall frames. These solutions are evaluated under a workload of 1296 frames. Our findings show that our scheduling approach allows for 99\% of high-priority tasks to complete while also providing a 3 - 8\% increase in the number of frames fully classified end-to-end over both workstealing approaches and systems without a preemption mechanism.

cs.DC↗

arXiv2019

FREE -- Fine-grained Scheduling for Reliable and Energy Efficient Data Collection in LoRaWAN

LoRaWAN promises to provide wide-area network access to low-cost devices that can operate for up to 10 years on a single 1000 mAh battery. This makes LoRaWAN particularly suited to data collection applications (e.g. monitoring applications), where device lifetime is a key performance metric. However, when supporting a large number of devices, LoRaWAN suffers from a scalability issue due to the high collision probability of its Aloha-based MAC layer. The performance worsens further when using acknowledged transmissions due to the duty cycle restriction at the gateway. For this, we propose FREE, a fine-grained scheduling scheme for reliable and energy-efficient data collection in LoRaWAN. FREE takes advantage of applications that do not have hard delay requirements on data delivery by supporting synchronized bulk data transmission. This means data is buffered for transmission in scheduled time slots instead of transmitted straight away. FREE allocates spreading factors, transmission powers, frequency channels, time slots, and schedules slots in frames for LoRaWAN end-devices. As a result, FREE overcomes the scalability problem of LoRaWAN by eliminating collisions and grouping acknowledgments. We evaluate the performance of FREE versus different legacy LoRaWAN configurations. The numerical results show that FREE scales well and achieves almost 100% data delivery and the device lifetime is estimated to over 10 years independent of traffic type and network size. Comparing to poor scalability, low data delivery and device lifetime of fewer than 2 years for acknowledged data traffic in the standard LoRaWAN configurations.

cs.NI↗

arXiv2018

Fair Adaptive Data Rate Allocation and Power Control in LoRaWAN

In this paper, we present results of a study of the data rate fairness among nodes within a LoRaWAN cell. Since LoRa/LoRaWAN supports various data rates, we firstly derive the fairest ratios of deploying each data rate within a cell for a fair collision probability. LoRa/LoRaWAN, like other frequency modulation based radio interfaces, exhibits the \textit{capture effect} in which only the stronger signal of colliding signals will be extracted. This leads to unfairness, where far nodes or nodes experiencing higher attenuation are less likely to see their packets received correctly. Therefore, we secondly develop a transmission power control algorithm to balance the received signal powers from all nodes regardless of their distances from the gateway for a fair data extraction. Simulations show that our approach achieves higher fairness in data rate than the state-of-art in almost all network configurations.

cs.NI↗

arXiv2018

A Fair Adaptive Data Rate Algorithm for LoRaWAN

LoRaWAN exhibits several characteristics that can lead to an unfair distribution of the Data Extracted Rate (DER) among nodes. Firstly, the capture effect leads to a strong signal suppressing a weaker signal at the gateway and secondly, the spreading codes used are not perfectly orthogonal, causing packet loss if an interfering signal is strong enough. In these conditions, nodes experiencing higher attenuation are less likely to see their packets received correctly. We develop FADR, a Fair Adaptive Data Rate algorithm for LoRaWAN that exploits the different Spreading Factors (SFs) and Transmission Powers (TPs) settings available in LoRa to achieve a fair Data Extraction Rate among all nodes while at the same time avoiding excessively high TPs. Simulations show that FADR, in highly congested cells, achieves 300% higher fairness than the minimum airtime allocation approach and 22% higher fairness than Brechts approach, while consuming almost 22% lower energy.

cs.NI↗

arXiv2017

LSCHC: Layered Static Context Header Compression for LPWANs

Supporting IPv6/UDP/CoAP protocols over Low Power Wide Area Networks (LPWANs) can bring open networking, interconnection, and cooperation to this new type of Internet of Things networks. However, accommodating these protocols over these very low bandwidth networks requires efficient header compression schemes to meet the limited frame size of these networks, where only one or two octets are available to transmit all headers. Recently, the Internet Engineering Task Force (IETF) LPWAN working group drafted the Static Context Header Compression (SCHC), a new header compression scheme for LPWANs, which can provide a good compression factor without complex synchronization. In this paper, we present an implementation and evaluation of SCHC. We compare SCHC with IPHC, which also targets constrained networks. Additionally, we propose an enhancement of SCHC, Layered SCHC (LSCHC). LSCHC is a layered context that reduces memory consumption and processing complexity, and adds flexibility when compressing packets. Finally, we perform calculations to show the impact of SCHC/LSCHC on an example LPWAN technology, e.g. LoRaWAN, from the point of view of transmission time and reliability.

cs.NI↗