A Coverage Monitoring algorithm based on Learning Automata for Wireless Sensor Networks

To cover a set of targets with known locations within an area with limited or prohibited ground access using a wireless sensor network, one approach is to deploy the sensors remotely, from an aircraft. In this approach, the lack of precise sensor placement is compensated by redundant de-ployment of sensor nodes. This redundancy can also be used for extending the lifetime of the network, if a proper scheduling mechanism is available for scheduling the active and sleep times of sensor nodes in such a way that each node is in active mode only if it is required to. In this pa-per, we propose an efficient scheduling method based on learning automata and we called it LAML, in which each node is equipped with a learning automaton, which helps the node to select its proper state (active or sleep), at any given time. To study the performance of the proposed method, computer simulations are conducted. Results of these simulations show that the pro-posed scheduling method can better prolong the lifetime of the network in comparison to similar existing method

SDN-enabled Resource Provisioning Framework for Geo-Distributed Streaming Analytics

Geographically distributed (geo-distributed) datacenters for stream data processing typically comprise multiple edges and core datacenters connected through Wide-Area Network (WAN) with a master node responsible for allocating tasks to worker nodes. Since WAN links significantly impact the performance of distributed task execution, the existing task assignment approach is unsuitable for distributed stream data processing with low latency and high throughput demand. In this paper, we propose SAFA, a resource provisioning framework using the Software-Defined Networking (SDN) concept with an SDN controller responsible for monitoring the WAN, selecting an appropriate subset of worker nodes, and assigning tasks to the designated worker nodes. We implemented the data plane of the framework in P4 and the control plane components in Python. We tested the performance of the proposed system on Apache Spark, Apache Storm, and Apache Flink using the Yahoo! streaming benchmark on a set of custom topologies. The results of the experiments validate that the proposed approach is viable for distributed stream processing and confirm that it can improve at least 1.64× the processing time of incoming events of the current stream processing systems.</p

TEL: Low-Latency Failover Traffic Engineering in Data Plane

Modern network applications demand low-latency traffic engineering in the presence of network failure while preserving the quality of service constraints like delay and capacity. Fast Re-Route (FRR) mechanisms are widely used for traffic re-routing purposes in failure scenarios. Control plane FRR typically computes the backup forwarding rules to detour the traffic in the data plane when the failure occurs. This mechanism could be computed in the data plane with the emergence of programmable data planes. In this paper, we propose a system (called TEL) that contains two FRR mechanisms, namely, TEL-C and TEL-D. The first one computes backup forwarding rules in the control plane, satisfying max-min fair allocation. The second mechanism provides FRR in the data plane. Both algorithms require minimal memory on programmable data planes and are well-suited with modern line rate match-action forwarding architectures (e.g., PISA). We implement both mechanisms on P4 programmable software switches (e.g., BMv2 and Tofino) and measure their performance on various topologies. The obtained results from a datacenter topology show that our FRR mechanism can improve the flow completion time up to 4.6x$-$7.3x (i.e., small flows) and 3.1x$-$12x (i.e., large flows) compared to recirculation-based mechanisms, such as F10, respectively

RIFO: Pushing the Efficiency of Programmable Packet Schedulers

Packet scheduling is a fundamental networking task that recently received renewed attention in the context of programmable data planes. Programmable packet scheduling systems such as those based on Push-In First-Out (PIFO) abstraction enabled flexible scheduling policies, but are too resource-expensive for large-scale line rate operation. This prompted research into practical programmable schedulers (e.g., SP-PIFO, AIFO) approximating PIFO behavior on regular hardware. Yet, their scalability remains limited due to extensive number of memory operations. To address this, we design an effective yet resource-efficient packet scheduler, Range-In First-Out (RIFO), which uses only three mutable memory cells and one FIFO queue per PIFO queue. RIFO is based on multi-criteria decision-making principles and uses small guaranteed admission buffers. Our large-scale simulations in Netbench demonstrate that despite using fewer resources, RIFO generally achieves competitive flow completion times across all studied workloads, and is especially effective in workloads with a significant share of large flows, reducing flow completion time up to 2.9x in Datamining workloads compared to state-of-the-art solutions. Our prototype implementation using P4 on Tofino switches requires only 650 lines of code, is scalable, and runs at line rate

Implementation and Evaluation of Activity-Based Congestion Management Using P4 (P4-ABC)

Activity-Based Congestion management (ABC) is a novel domain-based QoS mechanism providing more fairness among customers on bottleneck links. It avoids per-flow or per-customer states in the core network and is suitable for application in future 5G networks. However, ABC cannot be configured on standard devices. P4 is a novel programmable data plane specification which allows defining new headers and forwarding behavior. In this work, we implement an ABC prototype using P4 and point out challenges experienced during implementation. Experimental validation of ABC using the P4-based prototype reveals the desired fairness results

Ultrasonic-assisted deposition of Ni-P-Al2O3 coating for practical protection of mild steel: Influence of ultrasound frequency on the corrosion behavior of the coating

In this paper, the precipitation of nickel-phosphorous (Ni-P) electroless coatings including Al2O3 nanoparticles (Ni-P-NA) using ultrasound waves on mild steel has been studied. Deposition process occurred in a lactic plating bath by the autocatalytic method using an ultrasound probe. The effect of radiation frequency on the properties of coatings was investigated, and the optimum frequency was determined. The obtained samples were evaluated for their corrosion resistance, surface morphology, and hardness by electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and scanning electron microscopy (SEM). The results showed that ultrasound waves caused an improvement in the corrosion resistance and uniformity of the coatings. Furthermore, five different wave frequencies applied during deposition disclosed the remarkable impact of frequency on the smoothness and corrosion resistance of the resultant coatings. On this basis, the Nyquist diagrams showed that the corrosion resistance of the prepared Ni-P-NA coating at an optimum frequency of 75 kHz was 2.59 kΩ·cm2. This value was about 2.5 times higher than the value obtained for the Ni-P-NA coating deposited without ultrasound power

Impact of ultrasound frequency on the corrosion resistance of electroless nickel-phosphorus-nanodiamond plating

The nickel-phosphorus (Ni-P) and nickel-phosphorus-nanodiamond (Ni-P-ND) coatings were deposited on mild steel via electroless plating without ultrasound and under ultrasonic agitation with different frequencies of 25, 50, 75, 100, and 150 kHz. The as-prepared coatings were characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD). The corrosion performance of the fabricated layers was evaluated in 3.5 wt% NaCl solution by electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization. Results of the corrosion tests demonstrated that deposition under ultrasonic power provided coatings with higher stability in the corrosive environment. The corrosion rate decreased with increasing ultrasound frequency from 25 to 75 kHz but increased with further increase in frequency. This introduced 75 kHz as the optimum ultrasound frequency for electroless plating of Ni-P. It was also observed that the corrosion resistance of the proposed coating was improved through the incorporation of 40 ppm nanodiamond into the Ni-P matrix

A framework for multi‐provider virtual private networks in software‐defined federated networks

Federated networks represent a remunerable operational way, allowing federated partners to increase their incomes through a sharing resource process. They have been primarily used in the context of cloud computing; nowadays, they are also used to provide connectivity services, like virtual private networks. However, providing such a service by using standard technologies in federated networks requires a nonnegligible effort from different points of view (e.g., configuration effort). In this paper, we propose an software‐defined network (SDN)–based framework aiming at overcoming limitations in currently adopted best practices to issue virtual private networks in federated networks. Relying on the SDN architecture, we propose a method allowing federated providers to quickly and easily create federated networks, reducing unneeded costs (e.g., new hardware), and a way for customers to fast‐access federated services, without any explicit actions from providers. We evaluate our framework by using SDNetkit. We focus on analyzing the impact of our implementation on both control and data plane, in terms of number of control messages exchanged in the network and size of the forwarding tables, respectively.BMBF, 01IS18025A, Verbundprojekt BIFOLD-BBDC: Berlin Institute for the Foundations of Learning and DataBMBF, 01IS18037A, Verbundprojekt BIFOLD-BZML: Berlin Institute for the Foundations of Learning and DataTU Berlin, Open-Access-Mittel – 202

Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement.

PURPOSE Image artefacts continue to pose challenges in clinical molecular imaging, resulting in misdiagnoses, additional radiation doses to patients and financial costs. Mismatch and halo artefacts occur frequently in gallium-68 (68Ga)-labelled compounds whole-body PET/CT imaging. Correcting for these artefacts is not straightforward and requires algorithmic developments, given that conventional techniques have failed to address them adequately. In the current study, we employed differential privacy-preserving federated transfer learning (FTL) to manage clinical data sharing and tackle privacy issues for building centre-specific models that detect and correct artefacts present in PET images. METHODS Altogether, 1413 patients with 68Ga prostate-specific membrane antigen (PSMA)/DOTA-TATE (TOC) PET/CT scans from 3 countries, including 8 different centres, were enrolled in this study. CT-based attenuation and scatter correction (CT-ASC) was used in all centres for quantitative PET reconstruction. Prior to model training, an experienced nuclear medicine physician reviewed all images to ensure the use of high-quality, artefact-free PET images (421 patients' images). A deep neural network (modified U2Net) was trained on 80% of the artefact-free PET images to utilize centre-based (CeBa), centralized (CeZe) and the proposed differential privacy FTL frameworks. Quantitative analysis was performed in 20% of the clean data (with no artefacts) in each centre. A panel of two nuclear medicine physicians conducted qualitative assessment of image quality, diagnostic confidence and image artefacts in 128 patients with artefacts (256 images for CT-ASC and FTL-ASC). RESULTS The three approaches investigated in this study for 68Ga-PET imaging (CeBa, CeZe and FTL) resulted in a mean absolute error (MAE) of 0.42 ± 0.21 (CI 95%: 0.38 to 0.47), 0.32 ± 0.23 (CI 95%: 0.27 to 0.37) and 0.28 ± 0.15 (CI 95%: 0.25 to 0.31), respectively. Statistical analysis using the Wilcoxon test revealed significant differences between the three approaches, with FTL outperforming CeBa and CeZe (p-value < 0.05) in the clean test set. The qualitative assessment demonstrated that FTL-ASC significantly improved image quality and diagnostic confidence and decreased image artefacts, compared to CT-ASC in 68Ga-PET imaging. In addition, mismatch and halo artefacts were successfully detected and disentangled in the chest, abdomen and pelvic regions in 68Ga-PET imaging. CONCLUSION The proposed approach benefits from using large datasets from multiple centres while preserving patient privacy. Qualitative assessment by nuclear medicine physicians showed that the proposed model correctly addressed two main challenging artefacts in 68Ga-PET imaging. This technique could be integrated in the clinic for 68Ga-PET imaging artefact detection and disentanglement using multicentric heterogeneous datasets