Search

The significant proliferation of research papers in both conferences and journals has made it difficult for researchers to easily access relevant scholarly papers for academic learning. This has been a substantial problem for many researchers. Conferences, in comparison with journals, have an aspect of social learning and networking, which leads to personal familiarisation through various interactions among researchers. In this paper, we improve the social awareness of conference participants by proposing a novel folksonomy-based paper recommendation algorithm, called socially aware recommendation of scholarly papers (SARSP). SARSP recommends papers issued by active participants (APs), to other Group Profile Participants at the same conference based on preference similarity of their research interests. In addition, SARSP computes the social ties between an AP and other conference participants to effectively generate social recommendations of scholarly papers. We evaluate our proposed algorithm using a real-world data-set. Our experimental results confirm that SARSP has significant improvement over other existing methods. [ABSTRACT FROM AUTHOR]

In recent years, with the ageing of the population, environmental degradation and dietary abnormalities, the incidence of global cardiovascular disease has increased sharply, its serious impact on physical and mental health of humans is an important factor. Chinese medicine has a long history and significant efficacy in the treatment of cardiovascular disease. Based on the bibliometric method in the context of big data, this paper searched and screened the relevant literatures of TCM in the treatment of cardiovascular diseases included by SCI from 2004 to 2016 and analysed them from the aspects of annual change, regional distribution, institutional distribution, journal source, research field, highly cited literatures, high-frequency keywords and so on. The analysis results show that the total amount of literature in the treatment of cardiovascular diseases by traditional Chinese medicine is on the rise, mainly focusing on the application of traditional Chinese medicine and Chinese herbal compound, acupuncture and moxibustion, and taiji and other traditional Chinese medicine regimen. The research results of this paper provide a direction reference for TCM researchers to better understand the current research status of TCM in the treatment of cardiovascular diseases under the background of big data and for further research. [ABSTRACT FROM AUTHOR]

The 'neuropunk revolution' represents an innovative approach focused on the integration of human–machine interfaces through nerve and neural pathways. This cutting-edge concept seeks to push the boundaries of human–machine interaction by exploring the intricate connections between the human nervous system and artificial technologies. Neuropunk delves into the realm of cyborg technologies, blurring the lines between humans and machines and opening up new possibilities for augmenting human capabilities. By tapping into nerve and neural pathways, neuropunk envisions a future where individuals can seamlessly interface with technology, leading to enhanced sensory perception, cognitive abilities, and physical performance. This concept encapsulates a rebellious and unconventional spirit, challenging traditional notions of the human body and its relationship with technology. This paper discusses the challenges and potential of neuropunk, exploring the fusion of scientific exploration, technological innovation, and a punk-inspired ethos in advancing human–machine integration. It highlights the emergence of real-time neurosimulations and neuromorphic computing as key tools to achieve these aspirations. Additionally, the integration of neurological and hormonal bioinspiration is examined as a promising approach to the design of neural interfaces, fostering more efficient and effective technologies that align better with the human body. Finally, the paper addresses ethical considerations and research tasks to responsibly navigate the neuropunk revolution, ensuring a future that maximizes the benefits of neural interfaces while mitigating potential risks and promoting ethical principles. [ABSTRACT FROM AUTHOR]

In this paper, we prove that there is a strongly universal cellular automaton on the heptagrid with five states under the relaxation of the assumption of rotation invariance for the rules. The result is different from that of a previous paper of the author with six states but with rotationally invariant rules. Here, the structures is more constrained than in the quoted paper with six states and rotation invariance of the rules. [ABSTRACT FROM AUTHOR]

We have developed environment-adaptive software that enables high-performance operation by automatically converting application code in accordance with the deployed environment and setting appropriate amounts of resources. We only considered conversions and settings before the start of operation. In this paper, we verify that the logic is reconfigured in accordance with the usage characteristics during operation. We propose a FPGA reconfiguration method during operation and confirm that the application running on the FPGA is reconfigured into another application in accordance with the usage characteristics. Through confirmation, performance improvement and break time are checked, and the effectiveness of method is shown. [ABSTRACT FROM AUTHOR]

Due to the widespread penetration of wind energy, large-capacity wind turbines (WTs) are becoming more conspicuous. In this paper, a linear control-oriented large-capacity wind turbine (WT) model is redesigned based on the 15 MW WT in openFAST. Compared with the original model, the redesigned model is more efficient and conducive to the design of linear controllers. To verify the validity of the redesigned WT model, we design a distributed control scheme with deloading operation of the wind farm (WF) to fairly share the load. Simulations are performed to verify the effectiveness of the application in the WF. [ABSTRACT FROM AUTHOR]

Aspect-based sentiment analysis (ABSA) aims to analyze the emotional color contained in sentences or documents in more detail by classifying and evaluating different aspects and emotions in the text. However, the current research methods cannot effectively analyze the relationship between aspect words and context and extract grammatical information about sentences. Additionally, the extracted syntactic information is insufficient, and the combination of syntactic and semantic information is inefficient, leaving the model unable to correctly determine aspects' emotional orientations. This paper proposes an aspect-level sentiment analysis based on Fusion Graph Double Convolutional Neural Networks (FGD-GCN) to address these issues. Firstly, FGD-GCN proposes a multi-feature extraction module. Using BERT and bidirectional long-short-term memory models, this module extracts the hidden context between words. In addition, the positional attention module is used to capture important features in sentences, reducing noise and bias. Then, a semantic enhancement module is proposed, which fuses attention-focused information and feature information extracted from graphs to emphasize aspect words and context, and uses CNN model to classify on feature vectors. According to experiment results on three benchmark datasets, the model outperforms previous GCN methods for context-based aspect-level sentiment analysis. [ABSTRACT FROM AUTHOR]

In this paper, we construct a weakly universal cellular automaton in the heptagrid, the tessellation $ \{7,3\} $ { 7 , 3 } which takes place in the hyperbolic plane. The cellular automation is not rotation invariant but which is truly planar. This result, under these conditions, cannot be improved for the tessellations $ \{p,3\} $ { p , 3 } of the hyperbolic plane. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue including one by Kemal Akkaya and colleagues on sensor-actor network in which sensors and another by Keqin Li on multihop wireless networks.

The article discusses various reports published within the issue, including the article about OLSR as a proactive routing protocol in a mobile ad hoc network (MANET) and another on the dissemination of high volume data streams for low bandwidth mesh network.

The article discusses various reports published within the issue, including one on a method of using Belief-desire-intention agents to implement service-oriented workflow mapping, and another on applying it to the agent-based grid workflow management system.

Recent advances in quantum computing and machine learning have brought about a promising intersection of these two fields, leading to the emergence of quantum machine learning (QML). However, the integration of quantum computing and machine learning poses several challenges. One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). Recent studies have successfully identified the fundamental causes underlying the existence of BP in QNNs. This paper presents a framework designed to explore the interplay of multiple factors contributing to the BP problem in quantum neural networks (QNNs), which poses a critical challenge for the practical applications of QML. We focus on the combined influence of data encoding, qubit entanglement, and ansatz expressibility in hybrid quantum neural networks (HQNNs) for multi-class classification tasks. Our framework aims to empirically analyze the joint impact of these factors on the training landscape of HQNNs. Our results show that the occurrence of the BP problem in HQNNs is contingent upon the expressibility of the underlying ansatz and the type of the adopted data encoding technique. Additionally, we observe that qubit entanglement also plays a role in exacerbating the BP problem. Leveraging various evaluation metrics for classification tasks, we systematically evaluate the performance of HQNNs and provide recommendations tailored to different constraint scenarios. Our findings emphasize the significance of our framework in addressing the practical success of QNNs. [ABSTRACT FROM AUTHOR]

Given a graph G and an edge $ e\in E(G) $ e ∈ E (G) , let S be a vertex set of G. For any two vertices x, $ y\in S $ y ∈ S , if e belongs to all the shortest paths between x and y, then x and y can monitor the edge e. For each edge e of G, if there exists x and y in S such that x and y can monitor e, then the set S can be called a monitoring-edge-geodetic ( $ \operatorname {MEG} $ MEG for short) set of G. The $ \operatorname {MEG} $ MEG number, denoted by $ \operatorname {meg}(G) $ meg ⁡ (G) , is the size of the smallest $ \operatorname {MEG} $ MEG set of G. In this paper, we obtain the exact values of the $ \operatorname {MEG} $ MEG numbers for radix triangular mesh networks, Sierpiński graphs, Sierpiński gasket graphs and Sierpiński generalized graphs. [ABSTRACT FROM AUTHOR]

As distributed and multi-organization Machine Learning emerges, new challenges must be solved, such as diverse and low-quality data or real-time delivery. In this paper, we use a distributed learning environment to analyze the relationship between block size, parallelism, and predictor quality. Specifically, the goal is to find the optimum block size and the best heuristic to create distributed Ensembles. We evaluated three different heuristics and five block sizes on four publicly available datasets. Results show that using fewer but better base models matches or outperforms a standard Random Forest, and that 32 MB is the best block size. [ABSTRACT FROM AUTHOR]

For a set M of vertices and an edge e of a graph G, let $ P_G(M, e) $ P G (M , e) be the set of the pair $ (x, y) $ (x , y) with a vertex x of M and a vertex y of $ V(G) $ V (G) such that $ d_G(x, y)\neq d_{G-e}(x, y) $ d G (x , y) ≠ d G − e (x , y). For a vertex x, let $ EM(x) $ EM (x) be the edge set e such that there exists a vertex v in G with $ (x, v) \in P(\{x\}, e) $ (x , v) ∈ P ({ x } , e). A set M of vertices of a graph G is distance-edge-monitoring set if every edge e of G is monitored by some vertex $ v\in M $ v ∈ M , that is, for any $ e \in E(G) $ e ∈ E (G) , we have $ P_G(M, e)\neq \emptyset $ P G (M , e) ≠ ∅. The distance-edge-monitoring number of a graph G, denoted by $ \operatorname {dem}(G) $ dem ⁡ (G) , is defined as the smallest size of distance-edge-monitoring sets of G. In this paper, we study the distance edge monitoring number of pseudo wheel graphs, that is, some variants of wheel graph. [ABSTRACT FROM AUTHOR]

The fault tolerability of the network is usually measured by the classical or generalized connectivity of the graph. For any subset $ S \subseteq V\left (G \right) $ S ⊆ V (G) with $ \left | S \right | \ge 2 $ | S | ≥ 2 , a tree T is called an S-tree if $ S \subseteq V\left (T \right) $ S ⊆ V (T) . Furthermore, any two S-tree $ T_1 $ T 1 and $ T_2 $ T 2 are internally disjoint if $ E\left ({{T_1}} \right) \cap E\left ({{T_2}} \right) = \emptyset $ E ( T 1 ) ∩ E ( T 2 ) = ∅ and $ V\left ({{T_1}} \right) \cap V\left ({{T_2}} \right) = S $ V ( T 1 ) ∩ V ( T 2 ) = S. We denote by $ {\kappa _G}\left (S \right) $ κ G (S) the maximum number of pairwise internally disjoint S-trees in G. For an integer $ k \ge 2 $ k ≥ 2 , the generalized k-connectivity of a graph G is defined as $ {\kappa _k}\left (G \right) = \min \left \{ {{\kappa _G}\left (S \right) | S \subseteq V\left (G \right)} \right. $ κ k (G) = min { κ G (S) | S ⊆ V (G) and $ \left. {\left | S \right | = k} \right \} $ | S | = k } . In this paper, we establish the generalized 4-connectivity of the Cayley graph $ CT_n $ C T n generated by complete graphs. [ABSTRACT FROM AUTHOR]

The interplanetary File system (IPFS) provides data communication using plaintext over distributed and decentralized systems. Up till now, the security of data has mostly been established using keys. To facilitate classified data communication within a Closed User Group (CUG), services of IPFS private swarm are required to render additional content encryption. Currently, there is no inherent security built into IPFS. This paper presents an application DMaya on IPFS to provide keyless encryption on IPFS based on the Quasigroup-based Secret Sharing Scheme (QSS). IPFS is used as a storage medium, irrespective of the nature of data. Data security in decentralized mode with IPFS is provided with DMaya. The classified data of all types (i.e. video data, audio data, text data, and image data) when subjected to DMaya application, are fragmented into smaller fragments then processed by the probabilistic Quasigroup-based Secret Sharing (QSS) Scheme. DMaya keyless encryption generates the metadata tag file at the source node. The recipient node within the same private IPFS swarm, on receipt of metadata tag file reconstructs the original data with DMaya application. [ABSTRACT FROM AUTHOR]

Let G be a graph with vertex set $ V(G) $ V (G) and edge set $ E(G) $ E (G). For any $ e \in E(G) $ e ∈ E (G) and $ u,v\in V(G) $ u , v ∈ V (G) , the edge e is monitored by two vertices u and v in graph G if $ d_G(u, v) \neq d_{G-e}(u, v) $ d G (u , v) ≠ d G − e (u , v). A set M of vertices of G is a monitoring-edge-geodetic set of G if for any edge $ e \in E(G) $ e ∈ E (G) there exists a pair $ u, v\in M $ u , v ∈ M such that e is monitored by u, v. The monitoring-edge-geodetic number $ \operatorname {meg}(G) $ meg ⁡ (G) is the cardinality of the minimum MEG-set in G. In this paper, we obtain the exact values or bounds for the MEG numbers of graph products, including join, corona, cluster, lexicographic products and direct products. [ABSTRACT FROM AUTHOR]

This paper proposes an unconventional architecture and algorithm for implementing reservoir computing on FPGA. An architecture-oriented algorithm with improved throughput and architecture designed to reduce memory and hardware resource requirements are presented. The proposed architecture exhibits good performance in terms of benchmarks for reservoir computing. A prediction accelerator for reservoir computing that operates on 55.45 mW at 450 K fps with <3000 LEs is realized by implementing the architecture on FPGA. The proposed approach presents a novel FPGA implementation of reservoir computing focussing on both algorithms and architecture that may serve as a basis for applications of AI at network edge. [ABSTRACT FROM AUTHOR]

This paper investigates the coordination control of large-scale systems (LSSs) with unknown external disturbances. The disturbances exist in the channels from the controllers to the actuators. To compensate the impact of disturbances, an extended observer using the output states is constructed, and an observer-based event-triggered controller is designed to save communication resources. Moreover, based on the event-triggering strategy, a controller using dynamic information estimation is designed, and Zeno behavior is further excluded. Finally, a DC micro-grid model is used for simulations to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Analog computing is often considered to be an outdated technology only to be found and cared for in museums but not as the basis of modern cutting edge computing. Nothing could be further from reality. Together with quantum computers, analog computers complement today's stored program digital computers, acting as co-processors for certain types of computationally intensive tasks. They are highly energy efficient and exhibit a degree of parallelism that by far surpasses classic digital computers. In contrast to quantum computers, analog computers do not require exotic technologies, no intricate cooling systems, no elaborate shielding systems, etc. In addition to this there already exists a plethora of proven programs for analog computers to solve a wide variety of problems. This paper describes the necessity of analog computing for the twenty-first century, gives a short introduction to the structure and programming of analog computers, before discussing future application areas. Analog computing will drastically alter the way we think about computing in the years to come as it will become an integral part of every high performance computer. It will be an indispensable technology for future AI systems, it will revolutionize many medical applications, it might even replace or at least complement, certain types of quantum computers, etc. [ABSTRACT FROM AUTHOR]

It is well and widely known that sample pooling could provide an effective and efficient way for fast coronavirus testing among massive asymptomatic individuals. The method of multi-level acceleration for asymptomatic COVID-19 screening has been introduced, and for one and two levels, the optimal group sizes have been obtained. However, there are still multiple challenges. First, it is not clear how to find the optimal group sizes for three or more levels. Second, there is lack of closed-form expressions for the optimal group sizes for two or more levels. Third, it is not clear how to determine the optimal number of levels. And last, it is not known what the maximum achievable speedup is. The motivation of this paper is to address all the above challenges. The optimization of a hierarchical pooling strategy includes its number of levels and the group size of each level. In this paper, based on multi-variable optimization and Taylor approximation, we are able to derive closed-form expressions for the optimal number of levels d ∗ = ln ⁡ (1 / ln ⁡ (1 / q 0)) − 1 , the optimal group sizes m 1 ∗ = e d ∗ = 1 / (e p 0) , m 2 ∗ = e d ∗ − 1 = 1 / (e 2 p 0) ,..., m d ∗ ∗ = e = 1 / (e d ∗ p 0) , and the maximum possible speedup of a hierarchical pooling strategy of 1 / (e p 0 ln ⁡ (1 / p 0)) , where p 0 is the fraction of infected people. The above speedup is nearly a linear function of the reciprocal of p 0 , in the sense that it is asymptotically greater than any sub-linear function (1 / p 0) 1 − ϵ of the reciprocal of p 0 for any small ϵ > 0. Using the results in this paper, we can quickly and easily predict the performance of an optimal hierarchical pooling strategy. For instance, if the fraction of infected people is 0.0001, an 8-level hierarchical pooling strategy can achieve speedup of nearly 400. [ABSTRACT FROM AUTHOR]

This paper reviews memristive PUFs (Physical Unclonable Functions) reported in the literature. The paper explains the motivation for using memristor technology for implementing PUFs. It focuses on PUFs' applications, sizes, analysis, and physical variations. In addition, the paper presents the number of samples generated using Monte Carlo simulation for evaluating the PUF circuits. This paper also describes the protocols, functionality, and methodologies proposed in the memristive PUF literature. Although memristive PUFs are not commercialized yet, there is a high expectation of exploiting the memristors as fundamental elements in the next generation of hardware security primitives (e.g. PUF) due to their unique characteristics such as forming process, temporal drift, nonlinearity, bidirectionality, nonvolatility and model complexity. There have been some survey papers on memristor PUFs in the past, however, the field has continued to develop so a comprehensive survey including recent publications seemed in order at this time. Lately, memristor technology improvement has accelerated, therefore creating a need for an updated survey of the applications of memristors for PUFs. [ABSTRACT FROM AUTHOR]

Smart device networks form the backbone of many Internet of Things (IoT) applications. The performance of these systems depended on many factors. This includes their ability to connect to each other and network latency. In this paper, two algorithms are discussed that build a Peer-to-peer (P2P) overlay network. The focus is on real-time end-to-end remote instrumentation for IoT applications. P2P overlay networks are used for various purposes from content distribution through to media sharing. In contrast to traditional P2P systems, IoT systems can be highly sensitive to network latency and require low bandwidth. The main contributions of this paper are two algorithms to create overlay networks that assign peer nodes to super-peer nodes. The network contains a large number of smart devices and the key aim is to minimize system wide network latency. Other constraints regarding the nodes ability include the ability to become a super-peer node such as connectivity and limited processing capacities of the smart devices are also considered in context of a P2P remote instrumentation system. Both algorithms create a 3-hop network where the latency is lowered as much as possible with the given set of nodes. The algorithms have been validated through simulation. [ABSTRACT FROM AUTHOR]

In Wireless Rechargeable Sensor Networks (WRSNs), wireless chargers can recharge batteries of sensor nodes so that they can operate sustainably. Since wireless chargers are costly and have limited charging distances and angles, how to apply as few as possible chargers to cover all sensor nodes and satisfy their energy requirements is thus an important and challenging problem. This paper introduces the PSCD (Particle Swarm Charger Deployment) algorithm and the IPSCD (Improved PSCD) algorithm using the Particle Swarm Optimization (PSO) concept to nearly optimize WRSN charger deployment. PSCD and IPSCD estimate charging efficiency according to the distance and angle between chargers and sensor nodes. They then, on the basis of PSO, utilize the local optimum and the global optimum to adjust locations and antenna orientations of chargers to make WRSNs sustainable. We perform experiments using practical wireless chargers to obtain charging efficiency data. Based on the data, PSCD and IPSCD are simulated for obtaining the best parameter setting, and compared with two related greedy algorithms to show their superiority. This paper introduces the PSCD (Particle Swarm Charger Deployment) algorithm and the IPSCD (Improved PSCD) algorithm, which utilize the Particle Swarm Optimization (PSO) concept to deploy as few as possible wireless chargers with adjusted positions and antenna directions to fulfill the energy requirement of sensor nodes of a WRSN (Wireless Rechargeable Sensor Network) inside a cuboid with length L, width W and height H. [ABSTRACT FROM AUTHOR]

This paper presents efficient data structures for the implementation of matrix-free finite element methods on block-structured, hybrid tetrahedral grids. It provides a complete categorization of all geometric sub-objects that emerge from the regular refinement of the unstructured, tetrahedral coarse grid and describes efficient iteration patterns and analytical linearization functions for the mapping of coefficients to memory addresses. This foundation enables the implementation of fast, extreme-scalable, matrix-free, iterative solvers, and in particular geometric multigrid methods by design. Their application to the variable-coefficient Stokes system subject to an enriched Galerkin discretization and to the curl-curl problem discretized with Nédélec edge elements showcases the flexibility of the implementation. Finally, the solution of a curl-curl problem with $ 1.6\cdot 10^{11} $ 1.6 ⋅ 10 11 (more than one hundred billion) unknowns on more than 32,000 processes with a matrix-free full multigrid solver demonstrates its extreme-scalability. [ABSTRACT FROM AUTHOR]

The connectivity and diagnosability are two important parameters to evaluate the fault-tolerability of network. The enhance hypercube is a variant of the hypercube which not only retains some of the favorable properties of the hypercube, but also possesses some embedding properties that the hypercube does not have. In this paper, we obtain the connectivity and the conditional diagnosability of enhanced hypercube based on structure faults. [ABSTRACT FROM AUTHOR]

This paper reports a special class of cellular automata machines that can solve graph theoretic problems, such as spanning tree problem and single source shortest path problem. The machine deals with planar graphs only. We first develop two-dimensional cellular automata to solve the graph theoretic problems for planar graphs. Next, we design the hardware for implementation of those cellular automata. [ABSTRACT FROM AUTHOR]

Hypermedia Multi-Agent System (MAS) Simulation is a novel approach to building agent-based simulations in which the environment is modelled as a set of linked hypermedia resources that are implemented using microservices. This paper discusses the implementation of an prototypical simulation system based on this concept and the lessons learnt in the process. [ABSTRACT FROM AUTHOR]

The rapid adoption of Cloud, Fog, and Edge computing paradigms, along with Digital Twin (DT) technology, is being observed across numerous domains. Smart Agriculture is one such domain, where diverse requirements exist for applications that range from Augmented Reality, Satellite, and auto harvesters to a multitude of agricultural devices and sensors. While the integration of Cloud, Fog, and Edge computing can address various challenges, it can also pose some difficulties, including resource allocation, resource scheduling, and task scheduling. To address these challenges and enhance the productivity and sustainability of Smart Agriculture, this paper presents a novel architecture based on Cloud, Fog, Edge computing, and Multi-Agent Systems (MAS), incorporating the concept of Digital Twin. This proposed architecture is implemented in Smart Agricultural farms and fields, opening up new contemporary applications in the Agriculture domain. [ABSTRACT FROM AUTHOR]

This paper presents a parallel solution based on the coarse-grained multicomputer (CGM) model using the four-splitting technique to solve the optimal binary search tree problem. The well-known sequential algorithm of Knuth solves this problem in O (n 2) time and space, where n is the number of keys used to build the optimal binary search tree. To parallelise this algorithm on the CGM model, the irregular partitioning technique, consisting in subdividing the dependency graph into subgraphs (or blocks) of variable size, has been proposed to tackle the trade-off of minimising the number of communication rounds and balancing the load of processors. This technique, however, induces a high latency time of processors (which accounts for most of the global communication time) because varying the blocks' sizes does not enable them to start evaluating some blocks as soon as the data they need are available. The four-splitting technique proposed in this paper solves this shortcoming by evaluating a block as a sequence of computation and communication steps of four subblocks. This CGM-based parallel solution requires O (n 2 / p) execution time with O (k p) communication rounds, where p is the number of processors and k is the number of times the size of blocks is subdivided. An experimental study conducted to evaluate the performance of this CGM-based parallel solution showed that compared to the solution based on the irregular partitioning technique where the speedup factor is up to ×10.39 on 128 processors with 40,960 keys when k = 2, the speedup factor of this solution is up to ×13.12 and rises up to ×14.93 when k = 5. [ABSTRACT FROM AUTHOR]

Heterogeneous hardware other than a small-core central processing unit (CPU) such as a graphics processing unit (GPU), field-programmable gate array (FPGA), or many-core CPU is increasingly being used. However, to use heterogeneous hardware, programmers must have sufficient technical skills to utilise OpenMP, CUDA, and OpenCL. On the basis of this, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, in accordance with the hardware. However, although it has been considered to convert the code according to the offload devices, there has been no study where to place the offloaded applications to satisfy users’ requirements of price and response time. In this paper, as a new element of environment-adapted software, I examine a method to calculate appropriate locations using the linear programming method. I confirm that applications can be arranged appropriately through simulation experiments when some conditions such as application type and users’ requirements are changed. [ABSTRACT FROM AUTHOR]

Several traffic models for the Internet of Things (IoT) have been proposed in the literature. However, they can be considered as heuristic models since they only reflect the stochastic characteristic of the generated traffic. In this paper, we propose a model to represent the communication of IoT devices. The model was used to obtain the traffic generated by the devices. Therefore, the proposed model is able to capture a wider understanding of device behaviour than existing, state-of-the-art traffic models. The proposed model illustrates the behaviour of Machine-to-Machine uplink communication in a network with multiple-access limited information capacity shared channels. In this paper, we analysed the number of transmitted packets using the traffic model extracted from our proposed communication model and compared it with the state-of-the-art traffic models using simulations. The simulation results show that the proposed model has significantly higher accuracy in estimating the number of transmitted packets compared with the current models in the literature. [ABSTRACT FROM AUTHOR]

One of the most important challenges in information networks is to gather data from a larger set of nodes to a smaller set of nodes. This can be done via the use of a concentrator architecture in the connection topology. This paper is a proof-of-concept that demonstrates a quantum-based controller in large interconnection networks can asymptotically perform this task faster. We specifically present quantum algorithms for routing concentration assignments on full capacity fat-and-slim concentrators, bounded fat-and-slim concentrators, and regular fat-and-slim concentrators. Classically, the concentration assignment takes O (n) time on all these concentrators, where n is the number of inputs. Powered by Grover's quantum search algorithm, our algorithms take O (n c ln ⁡ c) time, where c is the capacity of the concentrator. Thus, our quantum algorithms are asymptotically faster than their classical counterparts, when c ln 2 ⁡ c = o (n). In general, c = n μ , satisfies c ln 2 ⁡ c = o (n) , implying a time complexity of O (n 0.5 (1 + μ) ln ⁡ n) , for any μ , 0 < μ < 1. [ABSTRACT FROM AUTHOR]

The traditional parallel Sparse matrix vector multiplication (SpMV) method has been optimized by an application-specific or compression format-specific. However, a single compression format cannot deal with all sparse matrix types effectively in practical applications. To solve this problem, an adaptive compression format based on Bagging ensemble learning algorithm is proposed in this paper. Experiments show that the adaptive compression format has higher prediction and computational performance on NVIDIA V100 and NVIDIA RTX 2080Ti. Compared with SpMV of the four compression formats, SpMV based on adaptive compression format reduces the execution time of 1.5×, 6.6×, 9× and 1.1×, respectively. [ABSTRACT FROM AUTHOR]

One of the important issues in evaluating an interconnection network is to study the Hamiltonian cycle embedding problems. For a positive integer k, a graph G is said to be spanning k-cyclable if for k prescribed vertices x 1 , x 2 , ... , x k , there exist k disjoint cycles C 1 , C 2 , ... , C k such that the union of C 1 , C 2 , ... , C k spans G, and each C j contains exactly one vertex x j of x 1 , x 2 , ... , x k . According to the definition, the problem of finding hamiltonian cycle focuses on k = 1. The notion of spanning cyclability can be applied to the problem of identifying faulty processors and other related issues in interconnection networks. The n-dimensional augmented cube A Q n is an important node-symmetric variant of the n-dimensional hypercube Q n . In this paper, we prove that A Q n with n ≥ 3 is spanning k-cyclable for 1 ≤ k ≤ 2 n − 4. [ABSTRACT FROM AUTHOR]

This paper proposed a new electrical synaptic transmission-based Spiking Neural P system (SNP system) based on SNP systems. Some new elements are added into the original definition of SNP systems, such as new synapses, bidirectional model, two types of neurons and cancelling the delay of axon. Because SNP system is easy to express the logical relationship between graphics and has strong ability to process information in parallel, the bidirectional characteristics of electrical synaptic transmission is effectively combined with the electrical quantity (direction of current) for fault location of distribution network with distributed generations (DGs) in this paper. The fault location model and reasoning algorithm of the electrical synaptic transmission-based SNP system are studied with the advantages of high accuracy, less computation, simple and intuitive model and reasoning. Furthermore, the algorithm is applied reasonably in the bidirectional power flow characteristics of a distribution network with DGs. Finally, this paper verifies the effectiveness, accuracy and reliability of the method through two cases which involve the single fault, multiple fault and misinformation fault. With the large-scale DGs (distributed generation) access to the distribution network, which changes the power flow structure and operation mode, the traditional protection strategy of the passive distribution network is no longer applicable. The fault location problem of distribution network with DGs is carried out. Firstly, Many fault location methods in the existing literatures have been anaylsised in this paper, then the electrical synaptic transmission-based spiking neural P system (ESSNP) has been proposed to solve the fault location problem. Foremore, the fault diagnosis mode for the power outage section with ESSNP has been established, which construct with Network description matrix and Fault current matrix. In order to verify the accuracy of the method in this paper, three cases have been studied, which the single fault, multiple faults and misinformation faults in each case. Finally, conclusions have been discussed. [ABSTRACT FROM AUTHOR]

Fog computing is a complementary computing paradigm to the existing cloud computing. A fundamental problem of fog computing is how to allocate the computing resources of fog nodes when scheduling tasks that arrive in an online manner. Other than task completion speed metrics, fairness of resource allocation between competing users is also an important metric to consider. One such metric is Dominant Resource Fairness (DRF), a fairness scheme that guarantees four key qualities: incentivised sharing, strategy-proof, Pareto-efficiency, and envy free. This paper examines the multi-resource, multi-server, and heterogeneous task resource allocation problem from a DRF perspective. Four different types of tasks are considered: ordered/unordered and splittable/unsplittable. Three low complexity heuristics are proposed to maximise fairness between users. Results show that the proposed heuristics are at least comparable to three baseline scheduling algorithms in terms of task completion speed while achieving higher fairness between users. [ABSTRACT FROM AUTHOR]

In this paper, we consider non-clairvoyant task offloading for random tasks in mobile edge computing within the framework of combinatorial optimisation. For offline non-clairvoyant task offloading, we propose a non-clairvoyant task offloading algorithm, which is able to determine a task offloading strategy without knowing the amount of computation and communication of any task. For online non-clairvoyant task offloading, we propose a randomised online task offloading algorithm, which is able to make an offloading decision for an arrival task without knowing anything about future tasks and other tasks. For both algorithms, we analyse the probability of certain performance guarantee. We also demonstrate numerical data. To the best of the author's knowledge, this is the first paper which considers both offline and online non-clairvoyant task offloading in mobile edge computing, together with analytical results on performance guarantee with high probability. [ABSTRACT FROM AUTHOR]

This paper introduces and tackles a special performance hazard in Hardware Transactional Memory (HTM): false abortion. False abortion causes many unnecessary transaction abortions in HTM and can greatly impact the performance, making HTM not that useful when it is adopted as a fast path for Software Transactional Memory. By introducing a new memory allocator design, we are able to put objects that are likely to be accessed together from different threads into different cache lines and thus avoid conflicts of hardware transactions in different threads. Experiments show that our method can reduce 47% of transaction abortion and achieve a speedup of up to 1.67× (averagely 22%), yet only consume 14% more memory, showing great potential to enhance current HTM technology. [ABSTRACT FROM AUTHOR]

The author's experiences over a span of more than 50 years are characterised as a journey. Early interests in computer system performance modelling, information storage and retrieval, and computer networks become secondary to research topics in computer simulation. Organisations, events, and, most important, people define the paths, waysides, excursions, side roads, and major stops along the way. Editorial positions constitute an enduring thread throughout the journey. Capturing and preserving the history of the modelling and simulation discipline, frequently a topical sojourn, emerges as a dominant activity in the latter years. Two evocative questions, based on the prediction of a prominent computing pioneer, conclude the paper. 1955 Oldsmobile Starfire (98 Convertible) [ABSTRACT FROM AUTHOR]

Logics for unconventional computing is an interdisciplinary research area which brings together computer scientists and engineers dealing with unconventional computing (such as biological, bio-inspired, chemical, physical, etc. computing) with logicians dealing with non-classical logical, algebraic, co-algebraic, and topological methods to initiate the development of novel nature-inspired computation paradigms. This paper is a Preface to the special issue devoted to Logics for unconventional computing. [ABSTRACT FROM AUTHOR]

This paper addresses the partition problem under the continuous domain in swarm robotics. In this problem, a swarm of n robots, randomly deployed over a rectangular workspace, are required to form K size-balanced groups within a finite amount of time. We aim to look into the problem in the presence of horizontal line obstacles. The obstacles are scattered randomly over the bounded region, and their positions remain unaltered throughout the process. In the proposed solutions, the robots are assumed to be identical, autonomous, and do not have any direct communication among themselves. The robots are memoryless, except they retain only the information of the two parameters n and K throughout the process and their states among three possible ones. Two different partition algorithms are proposed assuming full-compass axis agreement and half-compass axis agreement among the local coordinate systems of the robots. In the first case, the proposed algorithm works for both synchronous and semi-synchronous models, whereas, in the second case, the robots are assumed to be synchronous. As a pre-processing step of the partition algorithms, an assembling algorithm for the half-compass axis agreement model has also been proposed for synchronous and semi-synchronous robots. [ABSTRACT FROM AUTHOR]

The paper further refines the clan composition technique that is considered a way of matrix partitioning into a union of block-diagonal and block-column matrices. This enables solving the individual systems for each horizontal block on a separate computing node, followed by solving the composition system. The size of minimal clans, obtained as a result of matrix decomposition, varies considerably. For load balancing, early versions of ParAd software were using dynamic scheduling of jobs. The present paper studies a task of static balancing the clan size. Rather good results are obtained using a fast bin packing algorithm with the first fit on a sorted array which are considerably improved applying a multi-objective graph partitioning with software package METIS. Aggregation of clans allows us to obtain up to three times extra speed-up, including systems over fields of real numbers, on matrices from Model Checking Contest and Matrix Market. [ABSTRACT FROM AUTHOR]

Broadcast abstractions are among the most important concepts in the field of fault tolerant distributed computing. These abstractions are used by consensus algorithms as a fundamental building block for ensuring that all correct processes in the system decide the same value. The Timely Provable Reliable Send primitive is among these broadcast abstractions with which we guarantee that messages are delivered correctly and in a timely manner, even in the presence of faulty processes. In this paper, we present an authenticated algorithm implementing provable reliable send primitive with very few eventually synchronous links. In other words, this algorithm assumes that there is a ⋄ 〈 t + 1 〉 -sink in the system. A ⋄ 〈 t + 1 〉 -sink is a correct process where the number of incoming eventually timely links that connecting it with correct processes is (t + 1) (including itself). We also show that a ⋄ 〈 t + 1 〉 -sink is the minimal synchrony assumption for implementing this primitive in a Byzantine system where an authentication mechanism is available. [ABSTRACT FROM AUTHOR]

Serverless computing is a new way of delivering cloud services that abstracts a user from the burden of managing resources and infrastructure. Although a few serverless simulators have been developed, they do not compare to services that are offered by commercial providers. Developing a comprehensive serverless simulation framework is essential towards evaluating scenarios reliant on the serverless paradigm. This paper focuses on introducing a serverless computing model to the DIScrete event baSed Energy Consumption simulaTor for Clouds and Federations (DISSECT-CF) simulator to enable simulating realistic function-as-a-service (FaaS) solutions. This new model is capable of imitating serverless providers in terms of cost model, associating triggers, extracting performance metrics, and customising the configurations of functions. [ABSTRACT FROM AUTHOR]

Foucard, Krishna and Lekshmi introduced a new graph-theoretic concept in the area of network monitoring. Let G be a graph with vertex set V (G) , there exists a subset S ⊆ V (G) , if deleting any edge in G, one can find that there exist at least two vertices in S whose distance is changed, then we call S is a monitoring edge-geodetic set (MEG-set for short). The minimum size of the MEG-set of G is called the monitoring edge-geodetic number of G (meg(G) for short). In this paper, we study the monitoring edge-geodetic number of some well-known networks, including Ladder, butterfly, circulant and Benes networks and convex polytopes. [ABSTRACT FROM AUTHOR]

In his Turing Award Lecture, Jack Dongarra revealed a drastic problem of modern HPC – low efficiency on real-life task mixture, 0.8% for the best supercomputer Frontier. Born in Ukraine paradigm of Sleptsov net computing resolves this problem with the computing memory hardware implementation of an entirely graphical language of concurrent programming supplied with framework of formal methods for verification of concurrent programs. [ABSTRACT FROM AUTHOR]

This paper focuses on a mobile-crowd federated learning system that includes a central server and a set of mobile devices. The server, acting as a model requester, motivates all devices to train an accurate model by paying them based on their individual contributions. Each participating device needs to balance between the training rewards and costs for profit maximization. A Stackelberg game is proposed to model interactions between the server and devices. To match with reality, our model takes the training deadline and the device-side upload time into consideration. Two reward policies, i.e. the size-based policy and accuracy-based policy, are compared. The existence and uniqueness of Stackelberg equilibrium (SE) under both policies are analyzed. We show that there is a lower bound of 0.5 on the price of anarchy in the proposed game. We extend our model by considering the uncertainty in the upload time. We also utilize the blockchain technique to ensure a truthful, trust-free, and fair system. This paper also analyzes how devices maximize their utilities when making profits via training and blockchain mining in the fixed-upload-time setting. A blockchain-powered testbed is implemented, and experiments are conducted to validate our analysis. [ABSTRACT FROM AUTHOR]

The exchanged 3-ary n-cube E 3 C (r , s , t) , proposed by Lv et al. in 2021, is obtained by removing edges from a 3-ary n-cube Q n 3 , where r + s + t + 1 = n. The topological interconnection network of a multiprocessor system can be modeled as a connected graph. Analyzing the fault tolerance of its topological structure is critical in the course of design and maintenance of it. Given a connected graph G, let F be an edge subset of G. F is called an h-edge-cut of G, if G−F is disconnected and each remaining component has the minimum degree of at least h. The h-edge-connectivity λ h (G) is the minimum cardinality of all h-edge-cuts of G. For 1 ≤ r ≤ s ≤ t and 0 ≤ h ≤ r , in this paper, we determine the 2 h -edge-connectivity of exchanged 3-ary n-cubes, E 3 C (r , s , t) , and prove the exact values λ 2 h (E 3 C (r , s , t)) = 2 ⋅ 3 h (r + 1 − h). [ABSTRACT FROM AUTHOR]