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We consider the scheduling game with activation cost, where jobs as selfish agents compete for processing on serial-batching identical machines. Each job selects a machine (more precisely, a batch on a machine) for processing to minimize his disutility composed of the load of his machine and the fraction of activation cost. We claim that such a game may not admit any Nash equilibrium under the uniform sharing rule. We present an algorithm and prove that the schedule produced by the algorithm is a tight approximate Nash equilibria. [ABSTRACT FROM AUTHOR]

In the medical image analysis domain, medical image segmentation has a significant impact on the quantitative analysis of organ or tissue function, as the first and critical component of diagnosis and treatment pipeline. In this paper, a dense R‐CNN segmentation model based on dual‐attention are proposed for medical images multi‐target instance segmentation. The model combines channel and spatial attention mechanism to extract image features and fuse multi‐scale feature information hierarchically. It combines up‐sampling strategies such as dilated convolution and bilinear interpolation to strengthen the distinguishability between multi‐target instances and pixel‐level features in other regions. The multi‐target detection mechanism of R‐CNN is combined with the multi‐scale feature extraction and fusion ability of dense convolution network. In the encoding stage, the multi‐scale hybrid bottleneck module and deformable convolution are introduced to extract more accurate structural feature information and increase the receptive‐field. In the decoding stage, the bilinear interpolation and the adaptive hierarchical fusion mechanism are used to strengthen the distinguishability between the target region and other regions, and improve the accuracy of instance segmentation. Taking cardiac MRI segmentation as an example, the left and right ventricles, and left ventricular myocardium are selected as segmentation targets. The pixel accuracy is 90.82%, the class pixel accuracy is 87.91%, the mean intersection‐over‐union is 81.52%, the Dice coefficient is 89.82%, and Hausdorff distance is 9.2, which is improved compared with other methods. It verifies the accuracy and applicability of the proposed method for multi‐target instance segmentation of medical images. [ABSTRACT FROM AUTHOR]

Ultra-reliable low-latency communication (uRLLC) emerges as one of the three service categories in fifth-generation (5G) wireless networks, with a potential to support multiple advanced services for latency-sensitive communications. The inherent openness of the wireless environment makes security in 5G unprecedentedly urgent to be addressed. Accordingly, the physical layer security (PLS) technique exploits the randomness characteristics of the wireless channel to fulfill security and confidentiality of information transmission. Different from many current works, which ignored the significance of security in uRLLC, this paper studies secrecy improvement strategy design in uRLLC scenarios. First, we propose suitable performance metrics for evaluating PLS of uRLLC and make a compromise between reliability, latency, and security, while maximizing the network throughput. Next, we identify the key challenging issues for achieving PLS in the context of uRLLC, and discuss the role of cooperative communication and mobility in terms of possible solutions. To the best of our knowledge, this is the first paper to make a trade-off among reliability, security and network throughput. Simulations validate the theoretical analyses. [ABSTRACT FROM AUTHOR]

For the Social Internet of Things (SIoT), the interaction among ever increasing number of smart devices results in an exponential increase of services, which leads to an extreme difficulty for users to find suitable services. To address this issue, most existing recommendation algorithms are based on the data stored on the centralized server and distributed schemes are ignored. Meanwhile, distributed recommendation algorithms face the problems of privacy leakage and efficiency, which decrease the quality of experience (QoE). Therefore, we propose a novel SIoT service recommendation scheme called SIoT- SR, which adopts LSH Forest while combining with collaborative filtering algorithm to predict the Quality of Service (QoS) data of users. The LSH forest implements binary search by sorting and also has the ability to self-correct parameters. It can achieve a good tradeoff among memory, accuracy, efficiency, and privacy. Finally, we validate the effectiveness of the scheme based on the dataset WS-DREAM. The experimental results show that SIoT-SR has high prediction accuracy and efficiency while saving computing resources and are suitable for service recommendation of SIoT with resource-constrained devices. [ABSTRACT FROM AUTHOR]

Many shortest link scheduling algorithms adopt non-fading SINR interference model, which assumes that the received signal power will always remain determinate as long as the transmission power of the corresponding sender is fixed. In fact, because environment always influences the propagation of radio signals, the received signal power is by no means a certain value. Rayleigh fading is a statistical model for radio signals propagation. It assumes that the strength of a signal on a receiver is a random variable, varying with the Rayleigh distribution. This paper proposes a shortest link scheduling algorithm under the Rayleigh fading model (SLSRF). The SLSRF partitions the wireless network area into hexagons and colors the hexagons with three different colors such that two neighboring hexagons have different colors. The senders of the links scheduled simultaneously are arranged in hexagons with the same color. The correctness of the SLSRF is proved through theoretical analysis, and the efficiency is illustrated by elaborate simulations. Our simulation results demonstrate that the schedule delay of SLSRF is less than that of some results under the non-fading SINR interference model. Furthermore, we extend the SLSRF to a distributed version, which is suitable for large wireless networks. [ABSTRACT FROM AUTHOR]

Motivated by evaluating the reliability and fault tolerance of a network, we consider edge-disjoint paths in augmented cubes with faulty edges. We show that for any faulty edge set F ⊂ E (A Q n) and δ (A Q n − F) ≥ 2 , if | F | ≤ 4 n − 8 for n ≥ 4 , there are min { d e g A Q n − F (u) , d e g A Q n − F (v) } edge-disjoint paths connected any two vertices u and v in A Q n − F , where d e g A Q n − F (u) and d e g A Q n − F (v) are the degree of vertices u and v in A Q n − F , respectively. This result is optimal with respect to the maximum number of faulty edges. Simultaneously, we determine λ 1 (A Q n) for n ≥ 2 , and λ 2 (A Q n) for n ≥ 4 , where λ g (A Q n) is the g -extra edge-connectivity of A Q n . Given a graph G and a non-negative integer g , the g -extra edge-connectivity of G , denoted λ g (G) , is the minimum cardinality of a set of edges in G , if it exists, whose deletion disconnects G and leaves each remaining component with more than g vertices. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) have become one of the most vigorous techniques in the network domain. However, the sensor nodes of WSNs tend to become the target of attackers due to the broadcast communication mode and the unattended deployment nature. Although it can prevent the sensitive data from being compromised, Slice-Mix-AggRegaTe (SMART) needs to exchange messages frequently in a network, which put tremendous overhead on the sensor nodes with limited resources. Faced with these issues, this paper proposes an energy-efficient privacy-preserving data aggregation protocol based on slicing (EPPA) where a novel slicing mode is adopted to reduce the numbers of slices, which can significantly prevent the data from being compromised and decrease the communication overhead. Meanwhile, an enhanced scheme based on EPPA, called multi-function privacy-preserving data aggregation protocol (MPPA), is presented and it supports multiple functions in the process of data aggregation, such as max/min, count, and mean. The theoretical analysis and the simulation evaluation show that the proposed aggregation protocols demonstrate a better performance in the privacy preserving and the communication efficiency. [ABSTRACT FROM AUTHOR]

Resilience problem is defined on a database d , given a boolean query q where q (d) is initially t r u e , and an integer k , it is to find the tuple set d ′ of smallest size such that the query result q (d ∖ d ′) becomes f a l s e. As a potential explanation of a specified query, resilience plays a fundamental and important role in query explanation, database debugging and error tracing. Complexity results of resilience decision on relational algebraic queries have been studied previously. In this paper, we investigate the resilience decision problem on aggregation queries. New results on the hardness are provided. We show that, this problem is polynomially intractable on nested COUNT and SUM query both under data complexity and parametric complexity, and even it is NP - hard to approximate it within a constant ratio under the active domain constraint. [ABSTRACT FROM AUTHOR]

Abstract The Zhang neural network (ZNN) has attracted a great deal of interest from a large number of researchers because of its significant advantage in solving the various time-varying problems by the monotonously increasing odd activation functions. Many related models have been proposed for time-varying matrix solutions, however, provided that the noise is zero or the preprocessing of de-noising is conducted. Therefore, many of the models previously proposed are not suitable for real-world situations. In this study, a nonlinear and noise-tolerant ZNN model, named NNT-ZNN, is proposed and discussed based on the matrix-valued error function. Theoretically, we prove that the proposed NNT-ZNN model can be globally converged to the theory solution of the considered time-varying equation, regardless of any activation function being applied. In addition, we prove that the resultant NNT-ZNN model has the superior convergence performance beside the existing ZNN models, even when noise is not zero. After that, the simulative results of the resultant NNT-ZNN model are provided by using three illustrative examples to thoroughly validate the correctness of the theoretical analysis. Moreover, the simulation comparison between the proposed NNT-ZNN model and the existing ZNN-1 model is conducted, which further show that availability and excellence of the resultant NNT-ZNN model, and robustness to noise. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) consists of a large number of static or mobile, low-cost, and low-power sensor nodes. And energy is one of the most important factors that should be considered. In this paper, we propose clustering-based routing protocol for dynamic networks (CRPD) to reduce energy consumption and improve energy efficiency through clustering and routing algorithms. The basic idea is to periodically update the network topology and select the node with larger degree and high residual energy as the cluster head to be responsible for data aggregation and transmission. With the nodes moving, joining, and choosing the optimal clustering radius, the energy load of the whole network can be evenly distributed to each sensor node, which can significantly prolong the network lifetime. Extensive simulations show that CRPD is more energy-efficient than the existing protocols. [ABSTRACT FROM AUTHOR]

In this paper, we present a signcryption scheme called CP ABSC based on Ciphertext-Policy Attribute Based Encryption (CP ABE) [7] to secure the multicast communications in smart grids that require access control, data encryption, and authentication to ensure message integrity and confidentiality. CP ABSC provides algorithms for key management, signcryption, and designcryption. It can be used to signcrypt a message based on the access rights specified by the message itself. A user can designcrypt a ciphertext if and only if it possesses the attributes required by the access structure of the data. Thus CP ABSC effectively defines a multicast group based on the access rights of the data specified by the data itself, which differs significantly from the traditional Internet based multicast where the destination group is predetermined and must be known by the data source. CP ABSC provides collusion attack resistance, message authentication, forgery prevention, and confidentiality. It can be easily applied in smart grids to secure the instructions/commands broadcast from a utility company to multiple smart meters (push-based multicast) and the data retrieved from a smart meter to multiple destinations (pull-based multicast). Compared to CP ABE, CP ABSC combines encryption with signature at a lower computational cost for signcryption and a slightly higher cost in designcryption for signature verification. We also consider the adoption of attribute-based signature (ABS), and conclude that CP ABSC has a much lower computational cost than ABS. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel networking paradigm called Small-world SSDNet, servicing applications such as public safety, proximity based services, and fog computing based on device-todevice multi-hop wireless communications. The "small-world" feature is determined by the service area, whose size is usually within a community level, and the well known small-world properties existing in SSDNets; the "super-dense" feature comes from the fact that the increased direct communication range and the popularity of 5G and IoT devices jointly result in a large number of devices within a single-hop communication range. This article first formally defines SSDNet. Then the challenges and the opportunities brought by the design and the implementation of the SSDNet protocols and applications are addressed. Finally, the broader discussions on issues relevant to modeling, engineering, and dissemination are provided. [ABSTRACT FROM AUTHOR]

We study two scheduling games on parallel-batching machines with activation cost, where each game involves n jobs being processed on m parallel-batching identical machines. Each job, as an agent, selects a machine (more precisely, a batch on a machine) for processing to minimize his disutility. For the former game, on the basis of previous results, we find the conditions for the existence of Nash equilibrium, and present the parametric upper bounds of price of anarchy (PoA) and the price of stability (PoS) for the minimax and minisum objectives, and provide some mixed strategy Nash equilibria for two special cases. For the latter game, we first analyze the conditions for the nonexistence of Nash equilibrium, and provide tight approximate Nash equilibrium. Then, the conditions for the existence of Nash equilibrium are studied, and the constant-bounds of PoA and PoS for the minimax objective are given. [ABSTRACT FROM AUTHOR]

The advent of cloud computing technology has enabled users to invoke various web services in a “pay-as-you-go” manner. However, due to the flexible pricing model of web services in cloud environment, a cloud user’ service invocation cost may be influenced by many factors (e.g., service invocation time), which brings a great challenge for cloud users’ cost-effective web service invocation. In view of this challenge, in this paper, we first investigate the multiple factors that influence the invocation cost of a cloud service, for example, user’s job size, service invocation time, and service quality level; and afterwards, a novel Cloud Service Cost Optimization Method named CS-COM is put forward, by considering the above multiple impact factors. Finally, a set of experiments are designed, deployed, and tested to validate the feasibility of our proposal in terms of cost optimization. The experiment results show that our proposed CS-COM method outperforms other related methods. [ABSTRACT FROM AUTHOR]

This paper considers the shortest link scheduling problem in wireless networks under the signal-to-interference-plus-noise ratio (SINR) model. We propose an $O({}\log({}l_{\max}/l_{\min}{}){})-approximation algorithm called shortest link scheduling with power control (SLSPC) with oblivious power assignment and an O(\log1+\varphi(l\max/l\min)-approximation algorithm called shortest link scheduling with uniform or mean power assignment (SLSUM) with uniform or mean power control, where \varphi > 0 is a constant serving as a regulatory factor for slight transmit power adjustment, and where l\max and l\min denote the lengths of the longest and shortest links, respectively. We conduct a rigorous theoretical performance analysis to analyze the feasibility and approximation factors of the proposed algorithms. We also carry out an extensive comparison-based simulation study, whose results indicate that the performances of SLSPC and SLSUM are superior over the state of the art as the set of the so-called “black and gray” links, which are difficult to schedule and should be sequentially scheduled, is completely removed by adjusting the transmit power appropriately via $\varphi$. Our numerical analysis demonstrates that the approximation ratios of our algorithms are tighter than the best known ratios. [ABSTRACT FROM PUBLISHER]

In widely deployed wireless 'hot-spot' networks, nodes frequently join or leave, and inelastic/elastic and saturated/nonsaturated flows coexist. In such dynamic and diverse environments, it is challenging to maximize the channel utilization while providing satisfactory user experiences. In this paper, we propose a novel contention-on-demand (CoD) MAC scheme to address this problem. The CoD scheme consists of a fixed-CW algorithm, a dynamic-CW algorithm, and an admission control rule. The fixed-CW algorithm allows elastic flows to access limited system bandwidth; the dynamic-CW algorithm enables inelastic flows to contend for channel on demand and quickly adapt to network change; and the admission control rule rejects overloaded traffic for providing good user experiences. We then perform an asymptotic analysis to develop a simple and practical admission control rule for homogeneous and heterogeneous traffic; our rule can not only adapt to the change in offered loads and node number, but also maximize the system utilization . Finally, extensive simulations verify that our scheme is very effective and our theoretical result is very accurate. [ABSTRACT FROM AUTHOR]

Cognitive radio networks (CRNs) are drawing more and more attention along with the increasingly scarce spectrum resource. A CRN can be easily invalid due to stochastic activities of primary users. How to sustain the connectivity of CRNs and prolong the lifetime of CRNs become challenging issues. Inspired by the success of constructing a connected dominating set (CDS) as a virtual backbone in traditional wireless networks to prolong the lifetime of the network, we study the CDS construction in CRNs in this paper. We propose a three-phase centralized algorithm and a distributed algorithm. Theoretical analysis shows that our algorithms have better performance than that of existing results. [ABSTRACT FROM AUTHOR]

One-slot link scheduling is important for enhancing the throughput capacity of wireless sensor networks. It includes two aspects: maximum links scheduling (MLS) and maximum weighted links scheduling (MWLS). In this paper we propose two heuristic algorithms for the two NP-hard problems with obvious power assignments under the SINR (signal-to-interference-plus-noise-ratio) model. For MLS, we propose an algorithm MTMA (maximum tolerance and minimum affectance), which improves the currently best approximation algorithm by 28%–62% on average. For MWLS, we give an effective heuristic algorithm MWMA (maximum weighted and minimum affectance), which performs better on improving the throughput and reducing the running time. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations. [ABSTRACT FROM AUTHOR]

Highlights: [•] We propose a novel clustering protocol ECDS, which considers coverage and energy efficiency simultaneously. [•] We propose two new metrics CI p and CI a and for coverage performance. [•] ECDC has better performance compared with some other clustering protocols. [ABSTRACT FROM AUTHOR]

Abstract: One of the most important issues for wireless sensor networks is to get a long network lifetime without affecting either communication connectivity or sensing coverage. Many sensors that are deployed randomly in a dense sensor network in a redundant way waste a lot of energy. One effective way to save energy is to let only a subset of sensors work at any given time. In this paper, we mainly consider such a problem. Selecting the minimum number of connected sensor nodes that can provide k-coverage (k ≥1), i.e., selecting a subset S of working sensors, such that almost every point in the sensing region can be covered by at least k sensors and the sensors in S can form a connected communication subgraph. We propose a connected k-coverage working sets construction algorithm (CWSC) based on Euclidean distance to k-cover the sensing region while minimizing the number of working sensors. CWSC can produce different coverage degrees according to different applications, which can enhance the flexibility of the sensor network. Simulation results show that the proposed algorithm, which can conserve energy and prolong the lifetime of the sensor network, is better than the previous algorithms. [Copyright &y& Elsevier]

Coverage is one of the key issues to achieve energy efficiency of a wireless sensor network. Sensor scheduling is one of the most important methods to solve coverage problems. It can ensure the coverage degree of a region and prolong the network lifetime. In this paper, we focus on the k -coverage scheduling problem to guarantee k -coverage sensing and network connectivity. We consider both deterministic and stochastic sensing models of the sensors and adapt the results of deterministic sensing model to solve the sensor scheduling problem under the stochastic sensing model. We use regular pentagons to divide the sensing disks to solve the k -coverage problem. Each sensor node runs a stochastic k -coverage-preserving scheduling algorithm to determine its work modes, and redundant nodes can enter into sleep mode, while active nodes ensure the coverage of the network. Theoretical analysis and simulation results show that our algorithm can reduce the number of active nodes and extend the network lifetime significantly while maintaining a given coverage degree. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigates a simple discrete-time model, which produces the winner-take-all competition. The local and global stability of the model are both proven theoretically. Simulations are conducted for both the static competition and the dynamic competition scenarios. The numerical results validate the theoretical results and demonstrate the effectiveness of the model in generating winner-take-all competition. [Copyright &y& Elsevier]

Abstract: Due to the nonuniform node distribution, the energy consumption among nodes are more imbalanced in cluster-based wireless sensor networks. Based on this problem, in this paper, a cluster-based routing protocol for wireless sensor networks with nonuniform node distribution is proposed, which includes an energy-aware clustering algorithm EADC and a cluster-based routing algorithm. EADC uses competition range to construct clusters of even sizes. At the same time, the routing algorithm increases forwarding tasks of the nodes in scarcely covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes as their next hops, and finally, achieves load balance among cluster heads. Theoretical analysis and simulation results show that our protocol can balance the energy consumption among nodes and increase the network lifetime significantly. [Copyright &y& Elsevier]

Abstract: Motivated by cooperative communication in ad hoc networks, Wu et al. proposed extended dominating set (EDS) where each node in an ad hoc network is covered by either a dominating neighbor or several 2-hop dominating neighbors, and defined two types of dominating sets: extended strongly connected dominating set (ECDS) and extended weakly connected dominating set (EWCDS), according to the success of a broadcast process. An EWCDS is an effective method for clustering. In this paper, we extend the dominative capabilities of nodes such that each forward node dominates not only itself and its regular neighbors fully, but also its quasi-neighbors partly. Based on this extension, three novel algorithms to find EWCDSs in ad hoc networks are proposed. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations. [Copyright &y& Elsevier]

Abstract: The biomechanical changes in rabbit cornea preserved in storage media with different glucose concentrations are experimentally assessed. Two groups of eight fresh rabbit corneas were preserved for 10 days in storage medium Optisol-GS with glucose concentrations of 14 and 28 mM, respectively. Eight additional corneas preserved, glucose-free, in the same medium served as the control group. All specimens were tested under inflation conditions up to 45 mmHg posterior pressure, and the pressure-deformation data obtained experimentally were analyzed using shell theory to derive the stress–strain behavior. Comparisons were held between the three specimen groups in order to determine the effect of glucose concentration on corneal biomechanical behavior and thickness. After storage, the mean central corneal thickness in the control, low-glucose and high-glucose groups underwent statistically significant increases of 38.7 ± 11.3%, 45.4 ± 7.6% and 50.6 ± 8.6%, respectively. The corneas also demonstrated consistent stiffness increases with higher glucose concentrations. The tangent modulus values determined at different pressure levels between 10 and 40 mmHg underwent statistically significant increases with glucose level (P < 0.05). Compared to the control group, other specimens had higher tangent modulus by 17–20% on average with low glucose and 30–37% with high-glucose concentration. The results of the study indicate that the influence of the high-glucose level commonly experienced in diabetes on the biomechanical stiffness of the cornea should be considered in clinical management and in understanding corneal ectasia, glaucoma and the response to refractive surgery. [Copyright &y& Elsevier]

For a graph G, we assign a positive integer f(v) to each vertex v∈V(G). The f-chromatic index of G, denoted by [image omitted] , is the minimum number of f-matchings needed to partition E(G), where an f-matching of G is the edge set of a (0, f)-factor of G. In this paper, we give the exact value of the fractional f-chromatic index of a graph. [ABSTRACT FROM AUTHOR]

Remote sensing scene classification aims to automatically assign a specific semantic label to each image. It is challenging to classify remote sensing scene images due to the images' diversity and rich spatial information. Recently, convolutional neural networks have been widely used to overcome these difficulties, such as the famous Visual Geometry Group (VGG) network. However, the VGG network with local receptive fields cannot model the global information of remote sensing images well. It also needs a large number of parameters and floating point operations to achieve satisfactory accuracy. To overcome these challenges, we introduce the self‐attention mechanism to the VGG network. Specifically, we replace the last four convolutional layers in the VGG‐19 network with two cascaded self‐attention blocks, each consisting of two multi‐head self‐attention (MHSA) layers with the residual network structure. The new structure can simultaneously explore the local and global information from remote sensing scenes. Such improvements not only reduce model parameters but also improve the classification performance. The effectiveness of the proposed method is validated through experiments on four public data sets, i.e., NaSC‐TG2, WHU‐RS19, AID and EuroSAT. [ABSTRACT FROM AUTHOR]

In this information age, with the emergence of organizations, the number of various resources on the Internet of Things is also increasing. Generally, different users have different access permissions to different resources and most of the existing schemes have realized access control. But most of them are rough and not feasible in many organizations. Moreover, traditional access control schemes adopted a central entity or a trusted third party to centrally manage users' permissions and access information, which can easily lead to single point of failure. Therefore, a kind of secure, trusted, and fine-grained access control is urgently needed in some large-scale organizations or institutions that maintain thousands of IoT devices. In order to solve the above problems, in this paper, we propose a blockchain-based high-efficiency access control framework called BHE-AC to achieve secure and efficient access to resources for users. In BHE-AC, a registration model is designed to register users and resources, and it can evaluate the ability value for users according to their attributes which is an essential factor when requesting resources. Besides, we represent a blockchain-based token requesting mechanism to compare the capability values of users with requested resources; meanwhile, the mechanism also allows users to request multiple resources at the same time, which can avoid repeated requests. Then, an unforgeable token indicates the users' access to a specific resource is granted to a requester only if a requester meets the access requirements; from then on, the user can use a token to invoke the resource. Finally, security analysis and experiments of our framework are given in our paper. The experimental results show that BHE-AC can achieve low cost and efficient access. [ABSTRACT FROM AUTHOR]

In this paper, the leader-following consensus problem of a class of nonlinearly multi-dimensional multi-agent systems with actuator faults is addressed by developing a novel neural network learning strategy. In order to achieve the desirable consensus results, a neural network learning algorithm composed of adaptive technique is proposed to on-line approximate the unknown nonlinear functions and estimate the unknown bounds of actuator faults. Then, on the basis of the approximations and estimations, a robust adaptive distributed fault-tolerant consensus control scheme is investigated so that the bounded results of all signals of the resulting closed-loop leader-following system can be achieved by using Lyapunov stability theorem. Finally, efficiency of the proposed adaptive neural network learning strategy-based consensus control strategies is demonstrated by a coupled nonlinear forced pendulums system. [ABSTRACT FROM AUTHOR]

In this paper, we revisit the triangle edge deletion problem a variant of feedback arc set problem which is one of the Karp's 21 NP-complete problems. Given a graph G (V , E) , it is to find the edge set F such that | F | ≤ k and G ′ (V , E ∖ F) is a triangle-free graph. Yannakakis [1] showed it is hard for simple digraphs as well. The latest results showed that triangle edge deletion problem is still hard even for (a) planar undirected graphs of maximum degree seven [2] and (b) RGB-digraphs [3] which is a special class of digraphs. To make a further step, we show a new result in this paper that triangle edge deletion problem is still NP-complete even for planar RGB-digraphs of maximum degree eight with no glasses. On the other hand, we can find a kernel consisting of 11 k / 3 vertices for planar RGB-digraphs with no glasses. The results have an interesting application for the derivation of a tighter dichotomy on resilience decision problem in database theory. [ABSTRACT FROM AUTHOR]

A graph is 1-planar if it can be drawn on a plane so that each edge is crossed by at most one other edge. In this paper, we first give a useful structural theorem for 1-planar graphs, and then apply it to the list edge and list total coloring, the (p, 1)-total labelling, and the equitable edge coloring of 1-planar graphs. More precisely, we verify the well-known List Edge Coloring Conjecture and List Total Coloring Conjecture for 1-planar graph with maximum degree at least 18, prove that the (p, 1)-total labelling number of every 1-planar graph G is at most Δ (G) + 2 p - 2 provided that Δ (G) ≥ 8 p + 2 and p ≥ 2 , and show that every 1-planar graph has an equitable edge coloring with k colors for any integer k ≥ 18 . These three results respectively generalize the main theorems of three different previously published papers. [ABSTRACT FROM AUTHOR]

Abstract The star chromatic index of a multigraph G , denoted χ s ′ (G) , is the minimum number of colors needed to properly color the edges of G such that no path or cycle of length four is bi-colored. A multigraph G is star k -edge-colorable if χ s ′ (G) ≤ k. Dvořák et al. (2013) proved that every subcubic multigraph is star 7-edge-colorable. They conjectured in the same paper that every subcubic multigraph should be star 6-edge-colorable. In this paper, we consider this problem in a more general setting, we investigate star list edge coloring of general graph G and obtain an upper bound for the choice number of star edge coloring of graphs, namely, we proved that χ s l ′ ≤ ⌈ 2 Δ 3 2 (1 Δ + 2) 1 2 + 2 Δ ⌉. [ABSTRACT FROM AUTHOR]

Abstract Suppose that s , t are two positive integers, and ℋ is a set of graphs. Let g (s , t ; ℋ) be the least integer g such that any ℋ -free graph with minimum degree at least g can be partitioned into two sets which induced subgraphs have minimum degree at least s and t , respectively. For a given graph H , we simply write g (s , t ; H) for g (s , t ; ℋ) when ℋ = { H }. In this paper, we show that if s , t ≥ 2 , then g (s , t ; K 2 , 3) ≤ s + t and g (s , t ; { K 3 , C 8 , K 2 , 3 }) ≤ s + t − 1. Moreover, if ℋ is the set of graphs obtained by connecting a single vertex to exactly two vertices of K 4 − e , then g (s , t ; ℋ) ≤ s + t on ℋ -free graphs with at least five vertices, which generalize a result of Liu and Xu (2017). [ABSTRACT FROM AUTHOR]

Smart mobile devices and mobile apps have been rolling out at swift speeds over the last decade, turning these devices into convenient and general-purpose computing platforms. Sensory data from smart devices are important resources to nourish mobile services, and they are regarded as innocuous information that can be obtained without user permissions. In this article, we show that this seemingly innocuous information could cause serious privacy issues. First, we demonstrate that users' tap positions on the screens of smart devices can be identified based on sensory data by employing some deep learning techniques. Second, it is shown that tap stream profiles for each type of apps can be collected, so that a user's app usage habit can be accurately inferred. In our experiments, the sensory data and mobile app usage information of 102 volunteers are collected. The experiment results demonstrate that the prediction accuracy of tap position inference can be at least 90 percent by utilizing convolutional neural networks. Furthermore, based on the inferred tap position information, users' app usage habits and passwords may be inferred with high accuracy. [ABSTRACT FROM AUTHOR]

Location-based services (LBSs) are becoming an increasingly important component in our social and business life. All existing LBS providers support the nearest place searching via a single point of interest (POI) query. That is, in one query, a user is allowed to search for only one type of service. However, in real life, people usually need to search multiple different types of services and hope that their locations are as close as possible for convenience. For example, one user would like to search for a restaurant with a KTV nearby. To support this application scenario, we propose a novel LBS termed “ $N$ -in-One,” which is the first scheme to extend the function of single-POI LBS to multiple-POI LBS such that a single query can be employed to request multiple POIs that are geographically close. Providing “ $N$ -in-One” is challenging because: 1) serving a “ $N$ -in-One” query is not equivalent to serving $N$ queries independently due to the distance correlation among the $N$ POIs; and 2) the cask effect is getting worse in the service area mode of “ $N$ -in-one” as most of the returned results may be rendered useless when some hot POIs are blocked. To overcome these challenges, we propose several algorithms using computational geometry techniques to identify the best $K$ POIs that are geographically close and the service area (denoted by a given-sized rectangle) that can cover as many the best $Q$ clusters as possible while reducing the cask effect in the service area mode. Extensive simulations based on both synthetic and real world data demonstrate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Robot manipulators are playing increasingly significant roles in scientific researches and engineering applications in recent years. Using manipulators to save labors and increase accuracies are becoming common practices in industry. Neural networks, which feature high-speed parallel distributed processing, and can be readily implemented by hardware, have been recognized as a powerful tool for real-time processing and successfully applied widely in various control systems. Particularly, using neural networks for the control of robot manipulators have attracted much attention and various related schemes and methods have been proposed and investigated. In this paper, we make a review of research progress about controlling manipulators by means of neural networks. The problem foundation of manipulator control and the theoretical ideas on using neural network to solve this problem are first analyzed and then the latest progresses on this topic in recent years are described and reviewed in detail. Finally, toward practical applications, some potential directions possibly deserving investigation in controlling manipulators by neural networks are pointed out and discussed. [ABSTRACT FROM AUTHOR]

Social network data can help with obtaining valuable insight into social behaviors and revealing the underlying benefits. New big data technologies are emerging to make it easier to discover meaningful social information from market analysis to counterterrorism. Unfortunately, both diverse social datasets and big data technologies raise stringent privacy concerns. Adversaries can launch inference attacks to predict sensitive latent information, which is unwilling to be published by social users. Therefore, there is a tradeoff between data benefits and privacy concerns. In this paper, we investigate how to optimize the tradeoff between latent-data privacy and customized data utility. We propose a data sanitization strategy that does not greatly reduce the benefits brought by social network data, while sensitive latent information can still be protected. Even considering powerful adversaries with optimal inference attacks, the proposed data sanitization strategy can still preserve both data benefits and social structure, while guaranteeing optimal latent-data privacy. To the best of our knowledge, this is the first work that preserves both data benefits and social structure simultaneously and combats against powerful adversaries. [ABSTRACT FROM PUBLISHER]

Blockchain creates a secure environment on top of strict cryptographic assumptions and rigorous security proofs. It permits on-chain interactions to achieve trustworthy properties such as traceability, transparency, and accountability. However, current blockchain trustworthiness is only confined to on-chain, creating a “trust gap” to the physical, off-chain environment. This is due to the lack of a scheme that can truthfully reflect the physical world in a real-time and consistent manner. Such an absence hinders further blockchain applications in the physical world, especially for the security-sensitive ones. In this paper, we propose a framework to extend blockchain trust from on-chain to off-chain, and take trustworthy vaccine tracing as an example scheme. Our scheme consists of 1) a Trusted Execution Environment (TEE)-enabled trusted environment monitoring system built with the Arm Cortex-M33 microcontroller that continuously senses the inside of a vaccine box through trusted sensors and generates anti-forgery data; and 2) a consistency protocol to upload the environment status data from the TEE system to blockchain in a truthful, real-time consistent, continuous and fault-tolerant fashion. Our security analysis indicates that no adversary can tamper with the vaccine in any way without being captured. We carry out an experiment to record the internal status of a vaccine shipping box during transportation, and the results indicate that the proposed system incurs an average latency of 84 ms in local sensing and processing followed by an average latency of 130 ms to have the sensed data transmitted to and been available in the blockchain. [ABSTRACT FROM AUTHOR]

Blockchain technologies can enable secure computing environments among mistrusting parties. Permissioned blockchains are particularly enlightened by companies, enterprises, and government agencies due to their efficiency, customizability, and governance-friendly features. Obviously, seamlessly fusing blockchain and cloud computing can significantly benefit permissioned blockchains; nevertheless, most blockchains implemented on clouds are originally designed for loosely-coupled networks where nodes communicate asynchronously, failing to take advantages of the closely-coupled nature of cloud servers. In this paper, we propose an innovative cloud-oriented blockchain – CloudChain, which is a modularized three-layer system composed of the network layer, consensus layer, and blockchain layer. CloudChain is based on a shared-memory model where nodes communicate synchronously by direct memory accesses. We realize the shared-memory model with the Remote Direct Memory Access technology, based on which we propose a shared-memory consensus algorithm to ensure presistence and liveness, the two crucial blockchain security properties countering Byzantine nodes. We also implement a CloudChain prototype based on a RoCEv2-based testbed to experimentally validate our design, and the results verify the feasibility and efficiency of CloudChain. [ABSTRACT FROM AUTHOR]

In wireless cyber-physical systems (CPS), more and more traffic with different priorities is required to be timely transmitted over wireless networks such as 802.11. In order to make full use of 802.11 networks to provide quality of service for wireless CPS, we are concerned with the throughput stability issue (i.e., how much traffic load can be sustained in an 802.11 network). Recent studies on the stability in 802.11 networks have arrived at contradictory conclusions. In this paper, we first delve into the reasons behind these contradictions. Our study manifests that the maximum stable throughput is not simply larger than, less than, or equal to the saturation throughput as argued in previous works. Instead, there exist two intervals, over which the maximum stable throughput follows different rules: over one interval, it may be far larger than the saturated throughput; over the other, it is tightly bounded by the saturated throughput. Most existing related research fails to differentiate the two intervals, implying that the derived results are inaccurate or hold true partially. We then point out that for the parameter settings in the 802.11 enhanced distributed channel access (EDCA) standard, high-priority (HP) traffic can achieve a stable throughput far higher than the saturated throughput, according to the rules we find. This indicates that the prior recommendation by other authors, advocating operating a wireless LAN far below the saturation load to achieve stable throughput and avoid unbounded delay, might be too conservative for many settings. We next propose an idle-sense-based scheme to maximize the stable throughput that HP traffic can achieve, when they coexist with low-priority (LP) traffic. Finally, we ran extensive simulations to verify the effectiveness of the revealed rules and the proposed scheme. This study helps utilize the limited bandwidth of wireless networks fully. [ABSTRACT FROM AUTHOR]

Periodical broadcasts of individual vehicle’s safety information such as velocity and acceleration are critical in vehicular ad hoc networks (VANETs). However, current contention-based media access control (MAC) protocols cannot guarantee high performance in high density VANETs. In this paper, we propose a MAC protocol based on s-disjunct code to achieve reliable and real-time broadcasts via assigning a channel to each vehicle as the vehicle enters the network. Our protocol is adaptive as vehicles are required to adjust their communication ranges according to the network density in order to avert the interference among them. We conduct an extensive simulation study, and our results indicate that the proposed scheme can successfully achieve the requirements of the dedicated short range communication (DSRC) standard, that is, to broadcast safety information 10 times per second. Even at a high vehicle density, our scheme still guarantees that the success rates of both transmission and reception are greater than 95%, and the collision rates of access collision and merging collision are lower than 10 collisions/period. [ABSTRACT FROM AUTHOR]

The tremendous growth of Internet of Medical Things has led to a surge in medical user data, and medical data publishing can provide users with numerous services. However, neglectfully publishing the data may lead to severe leakage of user's privacy. In this article, we investigate the problem of data publishing in Internet of Medical Things with privacy preservation. We present a novel system model for Internet of Medical Things user data publishing which adopts the proposed multiple partition differential privacy k -medoids clustering algorithm for data clustering analysis to ensure the security of user data. Particularly, we propose a multiple partition differential privacy k -medoids clustering algorithm based on differential privacy in data publishing. Based on the traditional k -medoids clustering, multiple partition differential privacy k -medoids clustering algorithm optimizes the randomness of selecting initial center points and adds Laplace noise to the clustering process to improve data availability while protecting user's privacy information. Comprehensive analysis and simulations demonstrate that our method can not only meet the requirements of differential privacy but also retain the better availability of data clustering. [ABSTRACT FROM AUTHOR]

Let D be a digraph. The circular chromatic number $${\chi_c(D)}$$ and chromatic number $${\chi(D)}$$ of D were proposed recently by Bokal et al. Let $${\vec{\chi_c}(G)={\rm max}\{\chi_c(D)| D\, {\rm is\, an\, orientation\, of} G\}}$$. Let G be a planar graph and n ≥ 2. We prove that if the girth of G is at least $${\frac{10n-5}{3},}$$ then $${\vec{\chi_c}(G)\leq \frac{n}{n-1}}$$. We also study the circular chromatic number of some special planar digraphs. [ABSTRACT FROM AUTHOR]

As an important concept to depict the freshness of an information when it arrives at the destination, the Age-of-Information (AoI) and its relative scheduling works can be a very useful tool to aggregate the information from the end devices to the edge servers in Internet of Vehicles, which can strongly support those time-sensitive services in intelligent transportation system. However, most of the previous works about the AoI scheduling on edge computing are the centralized ones, rely on the reliable communications, and ignore the mobility of vehicles, which may not suit the dynamic environment in Internet of Vehicles. In this paper, we consider the AoI optimization problem in a more comprehensive vehicle model, and present a distributed AoI optimization algorithm based on a single hop end-to-edge wireless network. With an arbitrary power control technique, our algorithm reaches an asymptotically optimal performance on minimizing the expectation of AoI. Both of theoretical analysis and extensive simulations are conducted to verify the correctness and efficiency of our proposed algorithm. [ABSTRACT FROM AUTHOR]

Influence maximization problem has been studied extensively with the development of online social networks. Most of the existing works focus on the maximization of influence spread under the assumption that the number of influenced users determines the success of a product promotion. However, the profit of some products such as online game depends on the interactions among users besides the number of users. In this paper, we take both the number of active users and the user-to-user interactions into account and propose the interaction-aware influence maximization problem. To address this practical issue, we analyze its complexity and modularity, propose the sandwich theory which is based on decomposing the non-submodular objective function into the difference of two submodular functions and design two iterated sandwich algorithms which are guaranteed to get data dependent approximation solution. Through real data sets, we verify the effectiveness of our proposed algorithms. [ABSTRACT FROM AUTHOR]

Two-way communication is required to support control functions like packet acknowledgement and channel feedback. Most previous works on the transmission capacity of wireless ad hoc networks, however, focused on one-way communication; reverse communication from the destination to the source was ignored. In this paper, we first establish mathematical expression for two-way transmission capacity under the fixing transmission distance (i.e., the distance between the source and the destination is a constant), by introducing the concept of two-way outage and setting different rate requirements in both directions. Next, based on the concept of guard zone and cooperative communication, methods of increasing two-way transmission capacity are proposed. Simulation results show that the proposed methods can improve two-way transmission capacity significantly. [ABSTRACT FROM AUTHOR]

Highlights • Average RNFL thickness in schizophrenia patients was significantly reduced. • OCT is currently often applied to evaluate progressive thinning of RNFL. • RNFL thinning in schizophrenia patients could be an effect of neurodegeneration. • OCT may be a useful tool for the diagnosis of schizophrenia. Abstract Studies using optical coherence tomography (OCT) to compare retinal nerve fiber layer thickness in subjects with schizophrenia and healthy controls have yielded inconsistent results. We aimed to compare changes in retinal nerve fiber layer thickness in schizophrenia and healthy controls via a meta-analysis. Relevant studies were selected via an electronic search of the Cochrane Controlled Trials Register, Pubmed, and Embase. All included studies measured average and 4-quadrant (temporal, superior, nasal, and inferior) retinal nerve fiber layer thickness via OCT. Statistical analysis was performed using RevMan 5.0 software. Seven case–control studies involving collective totals of 245 eyes in patients with schizophrenia and 220 eyes in healthy controls were ultimately included in this meta-analysis. Statistical analysis revealed that average retinal nerve fiber layer thickness in patients with schizophrenia was significantly reduced compared to that of healthy controls. Additionally, retinal nerve fiber layer thickness in the inferior quadrant, nasal quadrant, and temporal quadrant differed significantly between the two groups, while differences in the superior quadrant did not. In view of these results, we suggest that peripapillary retinal nerve fiber layer thickness as measured by OCT may be a useful tool for the diagnosis of schizophrenia. [ABSTRACT FROM AUTHOR]