Combining two well-known types, we present a new class of partial latin squares which are not completable and minimal with respect to this property.

In wireless sensor and IoT networks dedicated to smart-cities, a leader node performs critical tasks such as generating encryption/decryption keys. In this paper, the leader is the node situated at the extreme left of the network. It is the node which starts the algorithm of searching the boundary nodes. These nodes will be used to monitor any sensitive, dangerous or inaccessible site. For this type of application, the used algorithm must be robust and fault-tolerant because it is difficult or even impossible to intervene in the presence of node failures. If this node is the leader, such a situation can be catastrophic. In this article, we present a new algorithm called DoTRo, which is based on a tree routing protocol. It starts with local leaders which will launch the flooding process to determine a spanning tree. During this process, their values will be forwarded. If two spanning trees meet, the tree that routes the best value continues its process while the other tree stops. The remaining tree root will be the leader. This algorithm is low energy consuming with reduction rates that can exceed 85 % with respect to the classical minium finding algorithm. It is efficient and fault-tolerant since it works even in the presence of node failures and communication disconnectivity. Additionally, the energy consumption is well balanced between nodes. Finally, the complexity and the proof of convergence of the proposed algorithm is presented.

Many real‐life problems arising within the fields of wireless communication, image processing, combinatorial optimization, etc, can be modeled by means of Euclidean graphs. In the case of wireless sensor networks, the overall topology of the graph is not known because sensor nodes are often randomly deployed. One of the significant problems in this field is the search for boundary nodes. This problem is important in cases such as the surveillance of an area of interest, image contour reconstruction, graph matching problems, routing or clustering data, etc. In the literature, many algorithms are proposed to solve this problem, a recent one of which is the least polar‐angle connected node (LPCN) algorithm and its distributed version D‐LPCN, which are both based on the concept of a polar angle visit. An inconvenience of these algorithms is the determination of the starting vertex. In effect, the point with the minimum x ‐coordinate is a possible starting point, but it has to be known at the beginning, which considerably increases the algorithms' complexity. In this article, we propose a new method called RRLPCN (reset and restart with least polar‐angle connected node), which is based on the LPCN algorithm to find the boundary vertices of a Euclidean graph. The main idea is to start the LPCN algorithm from an arbitrary vertex, and whenever it finds a vertex with an x ‐coordinate smaller than that of the starting one, LPCN is reset and restarted from this new vertex. The algorithm stops as soon as it visits the same edge for the second time in the same direction. In addition to finding the boundary vertices, RRLPCN also finds the vertex with minimum x ‐coordinate, which is the last starting point of our algorithm. The distributed version of the proposed algorithm, called D‐RRLPCN, is then applied to boundary node detection in the wireless sensor network. It has been implemented using real sensor nodes (Arduino/XBee and TelosB). The simulation results have shown our algorithm to be very effective in comparison to other algorithms.

The digitalisation of the environment surrounding human beings in their daily life is a major challenge facing today's technological progress. Building digital replicas of humans and systems help us to understand our environment, to anticipate its variations and to better explain its behaviour. Research in digital twins is continuously developing due to the various benefits it offers. This paper describes how the simulation and modelling community is switching towards digital twins using smart cities as a use case scenario. It also reviews the common digital twin-enabling tools used in today's research. Finally, the key research trends, challenges and future directions are given.

Nowadays, cloud computing offers a digital infrastructure for smart city development. Cognitive cities are steadily automating daily urban processes. The ever expanding objective‐driven communities gather and share sensitive data that must be stored securely. Cloud computing offers a suitable platform that allows cognitive smart cities to access and re‐access data to learn from their past to adapt its current behaviour. However, the cloud is an untrusted entity that may expose data when decrypted for processing by systems. In this paper, we treat the issue of encrypted data processing. Often, the data is encrypted prior to transferring it to the cloud, where the cloud must have the data in clear to be able to make calculations which raises security and privacy threats if the cloud is considered untrusted. The scenario of asking users to make the calculations after decrypting the received cloud data and encrypting the obtained results before sending them back to the cloud is not a practical solution in distributed multi‐tenant architectures. Homomorphic encryption allows offers a solution for processing encrypted data. Many existing homomorphic encryption schemes suffer from limitations that hinder their usability. This paper presents an efficient fully homomorphic encryption scheme using twin key encryption and magic number fragmentation. The details of the scheme are presented along with cryptanalytic attacks to assess its effectiveness. The proposed scheme exhibits strong resilience against brute‐force attacks compared to its rivals from the literature. Finally, we illustrate the applicability of the proposed scheme using a cognitive smart city application.

Several trusted tasks use consensus algorithms to solve agreement challenges. Usually, consensus agreements are used to ensure data integrity and reliability in untrusted environments. In many distributed networking fields, the Proof of Work (PoW) consensus algorithm is commonly used. However, the standard PoW mechanism has two main limitations, where the first is the high power consumption and the second is the 51% attack vulnerability. In this paper, we look to improve the PoW consensus protocol by introducing several proof rounds. Any given consensus node should resolve the game of the current round Roundi before participating in the next round Roundi+1. Any node that resolves the game of Roundi can only pass to the next round if a predetermined number of solutions has been found by other nodes. The obtained evaluation results of this technique show significant improvements in terms of energy consumption and robustness against the 51% and Sybil attacks. By fixing the number of processes, we obtained an energy gain rate of 15.63% with five rounds and a gain rate of 19.91% with ten rounds.

The multi-depot vehicle routing problem is a variant of the vehicle routing problem that tries to minimize the total cost of providing the service from several depots to satisfy several client demands. This paper presents a multi-ant colony system to solve the multi-depot vehicle routing problem using a reactive agent-based approach. This approach is designed to effectively solve the problem, in which each reactive agent is inspired by modeling the behavior of the ant. We define two types of reactive agents whose behavior differs in the use of two kinds of pheromone trail. In order to refer to the two phases of the execution process, i.e., the assignment phase and the routing phase, every reactive agent cooperates with others to provide a scalable solution for the overall problem. The solution of the multi-depot vehicle routing problem is beneficial and helpful for many real applications. The performance evaluation of the proposed approach is done using instances from the literature, and the results obtained demonstrate good performance when compared with other approaches

We prove that there is no circulant Hadamard matrix H with first row [h1,…,hn] of order n > 4, under some linear conditions on the hi’s. All these conditions hold in the known case n = 4, so that our results can be thought as characterizations of properties that only hold when n = 4. Our first conditions imply that some eigenvalue λ of H is a sum of √ -- n terms h jωj, where ω is a primitive n-th root of 1. The same conclusion holds also if some complex arithmetic means associated to λ are algebraic integers (second conditions). Moreover, our third conditions, related to the recent notion of robust Hadamard matrices, implies also the nonexistence of these circulant Hadamard matrices. If some of the conditions fail, it appears (to us) very difficult to be able to prove the result.

IoT promises a new era of connectivity that goes beyond laptops and smart connected devices to connected vehicles, smart homes, smart cities and connected healthcare. The huge volume of data that is collected from millions of IoT devices raises information security and privacy concerns for users. This paper presents a new scalable encryption technique, called Flexible encryption Technique (FlexenTech), to protect IoT data during storage and in transit. FlexenTech is suitable for resource constrained devices and networks. It offers a low encryption time, defends against common attacks such as replay attacks and defines a configurable mode, where any number of rounds or key sizes may be used. Experimental analysis of FlexenTech shows its robustness in terms of its multiple configurable confidentiality levels by allowing various configurations. This configurability provides several advantages for resource constrained devices, including reducing the encryption computation time by up to 9.7% when compared to its best rivals in the literature. (C) 2020 Elsevier B.V. All rights reserved.

Nowadays, multimedia and visual computing advances in digital technology make a potential change in human life. Many applications exploit the captured images from autonomous entities as data sources for several goals. In fact, these captured images need to be interpreted in order to extract their external environment. The researchers of this domain will meet some challenges such as how to detect and interpret the images’ context. This paper is to propose an efficient technique that detects objects of a given image based on the color divergence. The results clearly show the accuracy and the computation speed of the proposed technique compared with other methods.

In the fast moving field of computer cryptography, researchers are actively working on addressing various emerging challenges to keep tomorrow’s systems secure. Many efforts are focused on addressing the computation speed and the massive data size requirements of today’s systems. Significant research efforts are targeting the computational complexity by focusing on the number of cryptographic operations or the scope of application. In this paper, we present an asymmetric homomorphic encryption scheme that relies on converting base numbers to a given base in such a way that Leveled Fully Homomorphic Encryption (LFHE) is performed. This lightweight technique is easy to implement and applicable in many fields, especially those that require high speed and safety.

The challenge in the deployment of wireless sensor networks is to ensure the coverage of targets with high energy efficiency, particularly when coverage and energy constraints must be taken into account. Many algorithms have been suggested over the years to enhance network lifetime as sensor nodes are powered by batteries. These algorithms divide a set of sensor nodes into a number of subsets which can monitor all targets. The subsets are either joint or disjoint. In this paper, we propose an efficient method to compute the maximum lifetime target coverage. Our proposed method is centred around a target that is covered by a minimum number of sensor nodes. Based on this approach, we also propose an algorithm to expand the network lifetime which guarantees the monitoring of all targets by forming subsets of sensor nodes. Our obtained results are compared with the work reported in Cardei et al. (In: INFOCOM 24th annual joint conference of the IEEE computer and communications societies. Proceedings IEEE, 3:1976–1984, 2005). They are also compared with a method of computing the maximum lifetime target coverage. The results obtained by simulation show that the proposed algorithm enhances the network lifetime, which illustrates the efficiency of this algorithm.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. A game theory approach to solve linear bi-objective programming problems Madani Bezoui, Ahcène Bounceur, Reinhardt Euler, Moulaï Mustapha, Youcef Djeddi

One of the interesting techniques for leader election is used in the WBS (Wait Before Starting) algorithm, in which each node in the network will wait for a time corresponding to its value before starting to send the first message to neighbours. This means that the node with the smallest value becomes the leader and it also starts first. This approach is impracticable in the case of real values (case of GPS-coordinates). Also, if the values are very large, the waiting time becomes too long. In this paper, we propose a fast, fault-tolerant and low energy leader election algorithm dedicated to smart-cities, which is based on the technique of waiting before starting, with minimum complexity and in which every node sends one and only one message. Here, the leader is the node with the smallest x-coordinate and the total of sent and received messages is used to represent the global consumption in the network. We give a detailed description of the algorithm, prove its accuracy, discuss its complexity in terms of exchanged messages and evaluate its performance using the CupCarbon simulator. We show that our algorithm is well balanced in terms of energy consumption, it is efficient and adapts well to the increase of the nodes number in the network.

Analog/RF built-in test (BIT) techniques are essential for reducing the very high costs of specification-based tests and for high-safety applications. The adoption of a BIT technique needs to be decided at the design stage, and this can be facilitated by estimating the test quality in terms of errors such as test escapes ( ${T_{E}}$ ) and yield loss ( ${Y_{L}}$ ). Test quality estimation at the design stage has been traditionally very difficult for analog/RF circuits due to the lack of fault models that properly cover parametric faulty behavior. In recent years, statistical simulation has been considered in combination with learning techniques for the estimation of parametric test metrics. Extreme value theory (EVT) has provided a rigorous tool for the computation of parametric test metrics. However, test metrics estimation has been limited to the use of a univariate model. In this paper, we extend this approach by using a multivariate extreme value model. We illustrate this for the evaluation of an RF LNA BIT technique using a bivariate model.

The main parameter studied in a simulation of a Wireless Sensor Network is the lifetime of the network. In other words, the state of the battery of each node. That is why modelling correctly the battery is very important to obtain realistic results. In real applications, many types of batteries can be considered, where their lifetime depends on the weather variations and on the type of the considered sensor node. In this paper, we present some models of batteries simulated with the CupCarbon simulator. The models are obtained by estimating the consumption of real batteries. This is done by studying series of discharging current values with respect to different voltage values and different temperatures. Furthermore, we implement a new module in the CupCarbon simulator to allow testing the proposed models and to implement new personal models.

A leader node in Ad hoc networks and especially in WSNs and IoT networks is needed in many cases, for example to generate keys for encryption/decryption, to find a node with minimum energy or situated in an extreme part of the network. In our work, we need as a leader the node situated on the extreme left of the network to start the process of finding its boundary nodes. These nodes will be used to monitor any sensitive, dangerous or non-accessible site. For this kind of applications, algorithms must be robust and fault-tolerant since it is difficult and even impossible to intervene if a node fails. Such a situation can be catastrophic in case that this node is the leader. In this paper, we present a new algorithm called DoTRo, which is based on a tree routing protocol. It starts from local leaders which will start the process of flooding to determine a spanning tree. During this process their value will be routed. If two spanning trees meet each other then the tree routing the best value will continue its process while the other tree will stop it. The remaining tree is the dominating one and its root will be the leader. This algorithm turns out to be low energy consuming with reduction rates that can exceed 85%. It is efficient and fault-tolerant since it works in the case where any node can fail and in the case where the network is disconnected.

In the European Union, truck drivers must comply with Regulation (EC) No 561/2006, which provides a set of rules on the daily or weekly working time and on break or rest periods after specific working times. Truck drivers can be back to the depot much earlier than the end of their working period, and be able to perform other trips. The resulting problem is a Multi-Trip Vehicle Routing Problem with Time Windows, where truck drivers have the possibility to accomplish, during their time horizon, more than one trip, combined with a Truck Driver Scheduling Problem. It aimed to find and assign a set of routes to a fleet of vehicles allowing each customer to be visited within its given time window, and the accumulated load to be delivered (or collected) not exceeding the capacity of the vehicle. Each truck driver must comply with applicable hours of service regulations, and the objective is to minimize total transportation cost. To solve this problem, we have developed a hybrid method composed of a genetic algorithm and a local neighborhood search. Experiments have been conducted on instances from the literature and real-life cases from SYSTRANS, a specialized French software company.

Wireless sensor networks (WSNs) find extensive applications in various sensitive domains such as tracking, monitoring, environmental data collection and border surveillance. In these cases, the collected data are considered as a critical resource and used to detect any anomalies or abnormal behavior, providing information about an occurring event or a node failure. An outlier detection process must be set up to ensure the proper functioning of the monitoring system. The existing approaches are limited by assumptions on a specific distribution or a predefined data range of the collected data. Often these assumptions do not hold in practice, the data distribution is not known or determining reliable upper and lower bounds for the set of data is not possible. To overcome this, we propose a new copula-based probabilistic multivariate outlier detection method for faulty node detection in wireless sensor networks (WSNs). The joint probability density function of the copula is constructed considering dependency among the captured n−sensed measures without making any assumptions on the distribution of the collected data. The samples having probabilities violating a predetermined control limit are classified to be faulty. The performance of the proposed technique is observed to be better than the existing statistical methods.