Maximizing Service Reliability in Distributed Computing Systems with Random Node Failures: Theory and Implementation

In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliability, defined as the probability of serving all the tasks queued in the DCS before all the nodes fail. This paper presents a rigorous probabilistic framework to analytically characterize the service reliability of a DCS in the presence of communication uncertainties and stochastic topological changes due to node deletions. The framework considers a system composed of heterogeneous nodes with stochastic service and failure times and a communication network imposing random tangible delays. The framework also permits arbitrarily specified, distributed load-balancing actions to be taken by the individual nodes in order to improve the service reliability. The presented analysis is based upon a novel use of the concept of stochastic regeneration, which is exploited to derive a system of difference-differential equations characterizing the service reliability. The theory is further utilized to optimize certain load-balancing policies for maximal service reliability; the optimization is carried out by means of an algorithm that scales linearly with the number of nodes in the system. The analytical model is validated using both Monte Carlo simulations and experimental data collected from a DCS testbed

Tunability of the topological nodal-line semimetal phase in ZrSiX-type materials

The discovery of a topological nodal-line (TNL) semimetal phase in ZrSiS has invigorated the study of other members of this family. Here, we present a comparative electronic structure study of ZrSiX (where X = S, Se, Te) using angle-resolved photoemission spectroscopy (ARPES) and first-principles calculations. Our ARPES studies show that the overall electronic structure of ZrSiX materials comprises of the diamond-shaped Fermi pocket, the nearly elliptical-shaped Fermi pocket, and a small electron pocket encircling the zone center ($\Gamma$) point, the M point, and the X point of the Brillouin zone, respectively. We also observe a small Fermi surface pocket along the M-$\Gamma$-M direction in ZrSiTe, which is absent in both ZrSiS and ZrSiSe. Furthermore, our theoretical studies show a transition from nodal-line to nodeless gapped phase by tuning the chalcogenide from S to Te in these material systems. Our findings provide direct evidence for the tunability of the TNL phase in ZrSiX material systems by adjusting the spin-orbit coupling (SOC) strength via the X anion.Comment: 7 pages, 4 figure

Spin and charge dynamics in [TbPc2_2]0^0 and [DyPc2_2]0^0 single molecule magnets

Magnetization, AC susceptibility and $\mu$SR measurements have been performed in neutral phthalocyaninato lanthanide ([LnPc$_2]^0$) single molecule magnets in order to determine the low-energy levels structure and to compare the low-frequency spin excitations probed by means of macroscopic techniques, such as AC susceptibility, with the ones explored by means of techniques of microscopic character, such as $\mu$SR. Both techniques show a high temperature thermally activated regime for the spin dynamics and a low temperature tunneling one. While in the activated regime the correlation times for the spin fluctuations estimated by AC susceptibility and $\mu$SR basically agree, clear discrepancies are found in the tunneling regime. In particular, $\mu$SR probes a faster dynamics with respect to AC susceptibility. It is argued that the tunneling dynamics probed by $\mu$SR involves fluctuations which do not yield a net change in the macroscopic magnetization probed by AC susceptibiliy. Finally resistivity measurements in [TbPc$_2]^0$ crystals show a high temperature nearly metallic behaviour and a low temperature activated behaviour.Comment: 8 pages, 12 figure

Obfuscated Malware Detection: Investigating Real-world Scenarios through Memory Analysis

In the era of the internet and smart devices, the detection of malware has become crucial for system security. Malware authors increasingly employ obfuscation techniques to evade advanced security solutions, making it challenging to detect and eliminate threats. Obfuscated malware, adept at hiding itself, poses a significant risk to various platforms, including computers, mobile devices, and IoT devices. Conventional methods like heuristic-based or signature-based systems struggle against this type of malware, as it leaves no discernible traces on the system. In this research, we propose a simple and cost-effective obfuscated malware detection system through memory dump analysis, utilizing diverse machine-learning algorithms. The study focuses on the CIC-MalMem-2022 dataset, designed to simulate real-world scenarios and assess memory-based obfuscated malware detection. We evaluate the effectiveness of machine learning algorithms, such as decision trees, ensemble methods, and neural networks, in detecting obfuscated malware within memory dumps. Our analysis spans multiple malware categories, providing insights into algorithmic strengths and limitations. By offering a comprehensive assessment of machine learning algorithms for obfuscated malware detection through memory analysis, this paper contributes to ongoing efforts to enhance cybersecurity and fortify digital ecosystems against evolving and sophisticated malware threats. The source code is made open-access for reproducibility and future research endeavours. It can be accessed at https://bit.ly/MalMemCode.Comment: Accepted and Presented at IEEE-ICTP2023, Dhaka, Banglades

Direct-write, focused ion beam-deposited,7 K superconducting C-Ga-O nanowire

We have fabricated C-Ga-O nanowires by gallium focused ion beam-induced deposition from the carbon-based precursor phenanthrene. The electrical conductivity of the nanowires is weakly temperature dependent below 300 K, and indicates a transition to a superconducting state below Tc = 7 K. We have measured the temperature dependence of the upper critical field Hc2(T), and estimate a zero temperature critical field of 8.8 T. The Tc of this material is approximately 40% higher than that of any other direct write nanowire, such as those based on C-W-Ga, expanding the possibility of fabricating direct-write nanostructures that superconduct above liquid helium temperaturesComment: Accepted for AP

Participatory Ranking of Fodders in the Western Hills of Nepal

Fodder is an important source of feed of the ruminants in Nepal. In the mid hills of Nepal, farmers generally practice integrated farming system that combines crop cultivation with livestock husbandry and agroforestry. Tree fodders are good sources of protein during the forage and green grass scarcity periods especially in dry season. Local communities possess indigenous knowledge for the selection of grasses and tree fodders at different seasons in mid hills of western Nepal. A study was conducted on the perception of farmers with respect to selection of fodder species in eight clusters in Kaski and Lumjung districts that range 900-2000 meter above sea level and receive average precipitation of 2000- 4500mm per annum. During the fodder preference ranking, farmers prepared the inventory of fodders found around the villages and nearby forests and selected top ten most important fodders in terms of their availability, palatability, fodder yield, milk yield and milk fat yield. In total, 23 top ranking fodders species were selected from the eight clusters. These fodder species were also ranked using pairwise ranking and weighted scoring methods and ranking was done on the basis of merit numbers obtained from weighted scores. The analysis revealed Artocarpus lakoocha as best tree fodder followed by Ficus semicordata, Thysanolena maxima and Ficus calvata. Similarly, the calendar of fodders trees for lopping season and the best feeding time was prepared on the basis of farmers\u27 local knowledge. This study suggests strategies for promotion of locally preferred tree fodder species and supplementing tree fodder with feed in different seasons depending on their availability and local preferences

Effects of Row Spacings and Varieties on Grain Yield and Economics of Maize

Maize is the second most important crop of Nepal. The yield of the crop is low due to lack of appropriate plant density for the varieties. The field experiment was carried out to study the effect of different row spacings on different maize varieties at Deupur, Lamahi municipality of the dang district in province No. 5, Nepal during the rainy season from June to September, 2018. Four levels of spacings (boardcasting and three row spacings of 45, 60 and 75 cm) and two maize varieties (Rampur Composite and Arun-2) were evaluated using randomized complete block design with three replications. The highest grain yield was found in Rampur Composite and Arun-2 while they were planted with row spacing of 60 cm with plant to plant spacing of 25 cm. The highest grain yield, cob length, cob circumference, number of rows per cob, thousand grain weight  were reported when maize was planted in the  row spacing 60×25cm. Among the maize varieties, Rampur Composite produced the highest grain yield, cob length, cob circumference, number of rows per cob as compared to Arun-2. This study suggested that maize production can be maximized by cultivating maize varieties with row spacing of 60 cm with plant to plant spacing of 25 cm

Prediction of spatially distributed seismic demands in specific structures: Structural response to loss estimation

A companion paper has investigated the effects of intensity measure (IM) selection in the prediction of spatially distributed response in a multi-degree-of-freedom structure. This paper extends from structural response prediction to performance assessment metrics such as: probability of structural collapse; probability of exceeding a specified level of demand or direct repair cost; and the distribution of direct repair loss for a given level of ground motion. In addition, a method is proposed to account for the effect of varying seismological properties of ground motions on seismic demand that does not require different ground motion records to be used for each intensity level. Results illustrate that the conventional IM, spectral displacement at the first mode, Sde(T1), produces higher risk estimates than alternative velocity-based IM’s, namely spectrum intensity, SI, and peak ground velocity, PGV, because of its high uncertainty in ground motion prediction and poor efficiency in predicting peak acceleration demands

Prediction of spatially distributed seismic demands in specific structures: Ground motion and structural response

The efficacy of various ground motion intensity measures (IM’s) in the prediction of spatially distributed seismic demands (Engineering Demand Parameters, EDP’s) within a structure is investigated. This has direct implications to building-specific seismic loss estimation, where the seismic demand on different components is dependent on the location of the component in the structure. Several common intensity measures are investigated in terms of their ability to predict the spatially distributed demands in a 10-storey office building, which is measured in terms of maximum interstorey drift ratios and maximum floor accelerations. It is found that the ability of an IM to efficiently predict a specific EDP depends on the similarity between the frequency range of the ground motion which controls the IM and that of the EDP. An IM’s predictability has a direct effect on the median response demands for ground motions scaled to a specified probability of exceedance from a ground motion hazard curve. All of the IM’s investigated were found to be insufficient with respect to at least one of magnitude, source-to-site distance, or epsilon when predicting all peak interstorey drifts and peak floor accelerations in a 10-storey RC frame structure. Careful ground motion selection and/or seismic demand modification is therefore required to predict such spatially distributed demands without significant bias