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The Internet of Things (IoT) makes it conceivable to communicate among distinctive things. The use of IoT in the farming industry is critical for increasing utility. Smart agricultural practices may boost crop yield while also creating more output with the same amount of input. The majority of farmers, however, are still unaware of the most recent technologies and procedures. In this study, a revolutionary wireless mobile robot based on the Internet of Things (IoT) is created and installed to perform a variety of outdoor tasks. The benefits of this work include more accurate and efficient data, as well as a reduction in manpower. This research has applications in agriculture, arrival, and water division. Keen agrarian frameworks have been built up in different parts of the world utilising the Internet of Things (IoT) and remote sensor systems. One of the branches that springs to intellect in this respect is exactness cultivating. Numerous analysts have made checking and robotization frameworks for different cultivating capacities. Information collection and transmission between IoT gadgets set in ranches will be basic utilising WSN. The Kalman Filter (KF) is used with expectation investigation within the proposed method to get high-quality information free of commotion and exchange it with cluster-based WSNs. The quality of information utilised for examination is progressed as a result of this strategy, and information transport overhead within the wireless sensor network application is decreased. A decision tree is used for forecast analytics decision making for trim surrender expectation, trim classification, soil classification, climate expectation, and trim malady expectation. IoT components integrated with IoT cloud are coordinates in proposed framework to supply keen arrangement for edit development observing to clients. [ABSTRACT FROM AUTHOR]

The IEEE 802.11ah standard, marketed as Wi-Fi Halow, introduces a new channel access mechanism called the Restricted Access Window (RAW), aiming to provide connectivity for the Internet of Things (IoT) applications over broad areas. RAW aspires to alleviate the contention by splitting the channel access into periods and allocating each period to a given group of stations. This paper develops an analytical framework based on Probability and Renewal theories for modeling and evaluating an IEEE 802.11ah-based network implementing the RAW mechanism. We consider a Rayleigh-fading channel with the presence of the capture effect: a realistic scenario for IoT networks deployed in dense urban environments. Considering a single-hop scenario of stations randomly distributed around an Access Point (AP) and the power attenuation of transmitted packets, we model the channel access under capture awareness. As the RAW mechanism presents a time-limited contention for channel access, we develop a counting process that tracks transmissions up to the end of the contention time interval. Henceforth, we evaluate the network performance in terms of throughput. We meticulously validate the derived analytical results through extensive campaigns of discrete-event simulations. Our study evaluates the impact of different parameters on the overall performance, including the contention time, the number of stations, the number of groups, and the capture threshold. We henceforth study the impact of the capture effect on enhancing the network performance under the grouping feature introduced by the RAW mechanism. This work contributes to developing an analytical modeling framework to evaluate the performance of time-limited random access mechanisms accurately and can be an excellent basis for proposing practical scheduling algorithms to configure the RAW mechanism under non-ideal channel conditions. [ABSTRACT FROM AUTHOR]

Since the beginning of the COVID-19 pandemic, many countries have deployed digital contact tracing apps to help prevent the spread of the SARS-CoV-2 pandemic. Bluetooth-based smartphone contact tracing apps are considered one of the most effective measures for containing the COVID-19 pandemic and its new variants. When two app users come near each other, their phones exchange tokens via Bluetooth connection, recording that they've had close contact. If one of these users is tested positive for coronavirus, then the app will notify the other user to get tested or selfquarantine. However, when two or more app users' phones transmit their tokens at the same time for looking for another phone that might be running the app within Bluetooth range, collisions may occur. Due to the tokens' collision, the users' phones can not record the tokens of each other. In addition, a basic Bluetooth system consists of one master phone and up to seven active slave phones within a small area, typically 10 meters or fewer. The study of this model is simple because it focuses only on one small zone with eight persons, based on Bluetooth technology. To handle these issues effi- ciently, we propose an approach called ZigZag Decoding (ZD) and zone partitioning. With ZD, the master phone can receive tokens from slaves phones despite the presence of collision. Zone partitioning allows us to study and forecast the paths of people who tested positive with COVID-19 in large areas with a big population. Then, we present a multidimensional Markov chain to model the proposed communication architecture. We have performed extensive simulations to show that our approach drastically enhances Bluetooth performance in terms of its metrics of interest, which certainly improving the COVID-19 contact tracing app's performance. [ABSTRACT FROM AUTHOR]

The use of mobile cellular communication is growing all over the world, with the increasing popularity of mobile devices. Fifth Generation (5G) has recently emerged to satisfy the increasing demand for high data bit rates, to maintain network connectivity every time and everywhere, opening the possibility of connecting all the devices in the network. A key piece of this shift is the deployment of Small Cells over the Macrocells layer which introduces a new type of network called Heterogeneous Networks (HetNets), which involve more Handovers. In addition, the user has to select instantly and at inferior energy cost, the suitable base station in the midst of thousands. In this paper, to decide of the best Handover with reduced complexity of computation, we apply a Handover technique based on Distribution Analysis Detector combined with Compressive Sampling Techniques, after that, we propose to estimate the performance of networks in terms of Channel Capacity and Outage Probability based on Rice and Nakagami distribution models. We obtain Channel Capacity and Outage Probability by using concepts from Information Theory. Through numerical evaluations, we show that the Nakagami distribution model is more efficient than the Rice distribution model. [ABSTRACT FROM AUTHOR]

Mobile Cloud Computing (MCC) is a modern architecture that brings together cloud computing, mobile computing and wireless networks to assist mobile devices in storage, computing and communication. A cloud environment is developed to support a wide range of users that request the cloud resources in a dynamic environment with possible constraints. Burstiness in users service requests causes drastic and unpredictable increases in the resource requests that have a crucial impact on policies of resource allocation. How can the cloud system efficiently handle such burstiness when the cloud resources are limited? This problem becomes a hot issue in the MCC research area. In this paper, we develop a system model for the resource allocation based on the Semi-Markovian Decision Process (SMDP), able of dynamically assigning the mobile service requests to a set of cloud resources, to optimize the usage of cloud resources and maximize the total long-term expected system reward when the arrival process is a finite-state Markov-Modulated Poisson Process (MMPP). Numerical results show that our proposed model performs much better than the Greedy algorithm in terms of achieving higher system rewards and lower service requests blocking probabilities, especially when the burstiness degree is high, and the cloud resources are limited. [ABSTRACT FROM AUTHOR]

3D augmented reality (AR) has a photometric aspect of 3D rendering and a geometric aspect of camera tracking. In this paper, we will discuss the second aspect, which involves feature matching for stable 3D object insertion. We present the different types of image matching approaches, starting from handcrafted feature algorithms and machine learning methods, to recent deep learning approaches using various types of CNN architectures, and more modern end-to-end models. A comparison of these methods is performed according to criteria of real time and accuracy, to allow the choice of the most relevant methods for a 3D AR system. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has spread with alarming speed and resulted in substantial loss of lives. In the COVID-19 pandemic response, the Internet of Things (IoT) technology provides an extensive integrated network of IoT devices to prevent the spread of contagion. Rapid access of the data transmitted by COVID-19 IoT devices simply means better decision-making and better response plans. Unfortunately, packets collision further delays the arrival of that data and thus the large-wide spreading of the pandemic. In this paper, we propose an approach that ensures fast and successful transmission of the data transmitted by COVID-19 IoT devices in a scenario comprising other types of IoT devices. We have proposed a three-dimensional Markov chain for modeling the proposed IoT network. Detailed mathematical expressions of the average throughput of transmitted packets, the average delay of transmitted packets, the average throughput of the backlogged packets, and the average delay of backlogged packets are given in order to compare the performance of each type of IoT devices. Numerical results show that our approach achieves a significant throughput increase and a low average delay for COVID-19 IoT devices due to the priority channel access given to that type of devices. Thereby mitigating the spread of the pandemic. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel pricing mechanism to enhance the performance of the Slotted ALOHA mechanism combined with ZigZag Decoding (SA-ZD). We model the system using a stochastic game approach where the game state is given as a Markov process. We assume a cooperative game framework where users seek to optimize the same utility function. In our previous pricing mechanism [1], we associated a cost C ∊ [0; 1] for every transmission and retransmission attempt. Thus, if the transmission succeeds, the user receives a reward equal to 1°C. Otherwise, in the case of collision, he pays a penalty equal to C. Following this approach, users prefer to not take the risk of paying the penalty cost, which means they choose to wait rather than transmitting, especially in heavy traffic conditions. Even though it seems optimal to not transmit in such conditions, our results show that this behavior yields a dramatic decrease in the system performance. Besides, it leads to an inherent tradeoff between the backlogged and newly arrived traffic. Toward this end, we propose in this paper a novel pricing strategy where we associate a cost not only to transmission attempts but also to the idle event (i.e when no one is transmitting). Moreover, we address the tradeoff problem by associating different costs Cb and Cs, respectively, to backlogged and newly arrived packets. Therefore, when a successful transmission is going through the channel, users pay a cost denoted by Cs or Cb. If a collision occurs, they pay a cost Cc, and when no one is transmitting, they pay the idling cost Cidle. Compared to the old pricing mechanism, our results show that the proposed approach achieves the best performance and maintains a fairness level between backlogged and newly arrived packets. [ABSTRACT FROM AUTHOR]

Software-Defined Networking (SDN) is a new method that aims to virtualize networking by decoupling data plan from the control plan. As this technique impacted many actors in the networking community because of its suppleness, programmability, and central decision management. Many interrogations have been raised about problems that come with it. One of the biggest concerns related to SDN is security. This trait is crucial when determining to implement the SDN as a solution or not. Applications plane contains applications that can generate flow rules, those applications are allowed to access the data store present within the controller to store their rules, which introduces vulnerabilities in the network making the flow rules untrustworthy. Access to data store can only be trusted if the security problems inherent in software-defined networks are resolved. In this paper, we propose an enhanced SOLIDFLOW to improve flow rules database integrity inside the SDN controller. First, we discuss security threats related to SDN mechanisms regarding the control layer. Secondly, we debate appropriate solutions that have been presented in the literature to address security-related issues. Then we present our enhanced mechanism. Finally, we discuss our implementation use case and its results. The last section will provide a conclusion and an overview of future works. [ABSTRACT FROM AUTHOR]

Among the most critical issues in VANETare the frequent failures of the route caused by the high mobility of vehicles, the increase of the network overload caused by control messages, and the increase of the data packet delivery time. Short communication route lifetime often breaks down during data packet transmission between the source and the destination vehicles, which results in a relaunch of a new route reconstruction that becomes more frequent and depletes a significant amount of network resources. To face these issues, much research has considered the route stability and the route lifetime determination between source and destination vehicles as important factors to improve the quality of service in the VANETnetwork. However, this research did not take into account the route that has the longest lifetime as the most stable route and assumes that vehicles move at a constant speed during a direct communication between them. Furthermore, it did not model the data packet delivery time between the source and the destination vehicles. For this reason, we propose two protocols that use vehicles density to predict the data packet delivery time before sending the data and use vehicles movement information to determine the longest lifetime route, taking into account the variation of the vehicles velocity for comfort applications on highway. Our schemes are evaluated in function of vehicles density by measuring the average route lifetime, the percentage of packets delivery, the control overhead, the average end-to-end delay, the throughput, and the average number of route failures generated during the transmission of data packets. [ABSTRACT FROM AUTHOR]

Combinatorial optimization problems have several industrial applications such as Network routing, IOT network routing, path Planning for robotics and manufacturing for which the travelling Salesman Problem, TSP, can serve as typical test bench. This paper investigates new variants of the Fuzzy Ant Supervised by PSO, FAS-PSO and Simplified Ant Supervised by PSO, SAS-PSO coupled with a local search, Ls, mechanism. The proposed method is based on the Fuzzy PSO to supervise and tune ACO parameters, in addition to a local search mechanism helping in avoiding cities local crossing. The SAS-PSO-Ls uses the same idea while with the simplified PSO as supervisor. Experimentations (a space is missed before "Experimentations") and results are based TSP test benches with a statistical analysis and a comparative study with the standard AS-PSO and similar state of art methods. FAS-PSO-Ls gives better than the state of art for eil51, berlin52, while the SAS-PSO-Ls is giving better results for the following cases: eil51, berlin52, st70. [ABSTRACT FROM AUTHOR]

In Slotted ALOHA (SA), mobile nodes tend to be more aggressive when they compete to get access to the common channel, which leads to a dramatic decreases of the Quality of Service (QoS). In this paper, we analyze the Slotted ALOHA and Slotted ALOHA combined with ZigZag Decoding (SA-ZD) within a stochastic game framework. First, we start with the cooperative model of the proposed mechanism in which we propose several approach to optimize the system. Then, we model the system by a non-cooperative game using a bi-dimensional Markov chain that integrates the effect of ZigZag Decoding (ZD). We then propose an adjustable transmission cost to compromise between throughput and the delay of backlogged packets. All found results show that our approach improves significantly the QoS of the system. [ABSTRACT FROM AUTHOR]

One of the most critical issues of VANET is the frequent failure of the route caused by the high mobility of vehicles. Short communication route lifetime often breaks down in progress data packet transmission between the source and the destination vehicles, and launches a new route reconstruction that becomes more frequent and depletes a significant amount of network resources. To face these frequent communication disconnections much research has considered the stability of route between source and destination vehicles as an important factor to improve the quality of service in the VANET network. however, this research did not take into account the longest route lifetime as the most stable route and assumes that vehicles move at a constant speed during a direct communication between them. For this reason, we propose two protocols that use vehicles' movement information to determine the longest route lifetime as the most stable route taking into account the variation of the vehicles' velocity for comfort applications in a highway environment. One of them uses the beacon message and the other does not use it. Our schemes are evaluated as function of vehicles density by measuring the route duration, the percentage of packets delivery, the control overhead, the throughput and the number of link failures generated during the transmission of data packets. The Intelligent Driver Model with Lane Changing (IDM-LC) based on VanetMobiSim tool is used to generate realistic mobility traces in highway. [ABSTRACT FROM AUTHOR]

Distributed Denial of Service (DDOS) is one of the most common threats that is growing in size and frequency in cloud computing environments due to its significant features. The good capacities of software-defined networking (SDN) (e.g. traffic examination based on software, centralized control and dynamic network reconfiguration) offer us new opportunities to defeat DDoS attacks in cloud environments. Although SDN brings numerous benefits while separating the control and data planes, it has important vulnerabilities that can be exploited by DDOS attacks. In this paper, we study how to defense SYN Flooding attacks at the switch level, so this latter will prevent and mitigate traffic anomalies without any switch-controller communication. To address this challenge, we propose a SYN flooding dynamic defensive mechanism which exploits the capabilities of SDN data plane using the programming language P4. The proposed approach activates the data plane with customized statistical information databases, traffic anomaly detection algorithm and SYN cookie techniques. These extensions enable the switch to prevent flow rate anomalies, realize the existence of SYN flooding attacks and then deploy adaptive countermeasures. Our system takes advantage of the switch programmability (i.e., using P4 language), distributed packet processing, and centralized SDN control, to offer an active defense mechanism against SYN flood attacks in cloud environments. [ABSTRACT FROM AUTHOR]

Because of the dynamic and scalable nature of multitenant Cloud platforms, which are becoming more and more complex, it is not easy to assess the system performance or to pick up the best configuration just based on human experience. In this work, we elaborated a framework using stochastic modeling instead of exhaustive experiments to assess the system performance. Moreover, The framework uses dynamic programming (here, we use value iteration algorithm) as a resource management and planning tool. In such complex systems, picking up the best system configuration is a challenge, for this reason we designed a heuristic algorithm that finds a treads-off between the tenants' budgets and the overall system performance. As a use case scenario of this framework, we addressed the problem of routing security requests, coming from the Cloud tenants, between different execution agents. The simulation results have demonstrated the benefit of using our framework in terms of identifying the optimal routing policy of security requests and improving system configuration. [ABSTRACT FROM AUTHOR]

In Cloud Computing environment, the allocation of virtual machines (VMs) to clients without taking into consideration the programs that they execute in their VMs could be a great threat to the entire cloud environment. Indeed the hypervisor cannot isolate the VMs totally and these machines have a lot of vulnerabilities that could be exploited then spread the attack in the other servers even if there is such an intrusion prevention or detection system. For this reason the process of monitoring the file that should be executed in an allocated VM is an important strategy to mitigate such a threat. The sandbox security mechanism is one of the solutions that are used in complex environment to isolate malicious or unknown files for execution than allow it thereafter to be used in a real context. In this paper, a Bayesian game theoretic approach is used in order to take into consideration the type of the client based on his previous activities to predict his actions and to determine in which case the monitoring process should be used. For this reason, we model the system as a Bayesian non-cooperative game firstly, then we resolve the game and finally we provide some numerical results to predict user's action and show the appropriate actions that should be taken by the administrator. [ABSTRACT FROM AUTHOR]

Nobody can deny that Cloud computing, a rapidly developing information technology, has attired the concern of the whole world. However, this emergent technology is Internetbased computing, allows on demand network access to a shared resources, software and information where it becomes an important security issue. Consequently, we must have a clear understanding of potential security benefits and risks associated with cloud computing. Since security is increasingly the principal concern in the conception and implementation of software systems, it is very important that the security mechanisms are designed so as to protect the computer systems against cyber attacks. An Intrusion Tolerance Systems play a crucial role in maintaining the service continuity and enhancing the security compared with the traditional security. In this paper, we propose to combine a preventive maintenance with existing intrusion tolerance system to improve the system security. We use a Semi-Markov Process to model the system behavior. We quantitatively analyze the system security using the measures such as system availability, Mean Time To Security Failure and cost. The numerical analysis is presented to show the feasibility of the proposed approach. An Intrusion-Tolerant System (ITS) aims to maintain a useful level of operational capability throughout ongoing cyber-attacks. The applications that are part of an ITS, especially those that provide critical services for the systems mission therefore, must survive the failures and unwanted changes in the system caused by malicious acts of intruders. Keywords: Intrusion Tolerance, Preventive Maintenance, System Availability, Cloud ComputingNobody can deny that Cloud computing, a rapidly developing information technology, has attired the concern of the whole world. However, this emergent technology is Internetbased computing, allows on demand network access to a shared resources, software and information where it becomes an important security issue. Consequently, we must have a clear understanding of potential security benefits and risks associated with cloud computing. Since security is increasingly the principal concern in the conception and implementation of software systems, it is very important that the security mechanisms are designed so as to protect the computer systems against cyber attacks. An Intrusion Tolerance Systems play a crucial role in maintaining the service continuity and enhancing the security compared with the traditional security. In this paper, we propose to combine a preventive maintenance with existing intrusion tolerance system to improve the system security. We use a Semi-Markov Process to model the system behavior. We quantitatively analyze the system security using the measures such as system availability, Mean Time To Security Failure and cost. The numerical analysis is presented to show the feasibility of the proposed approach. An Intrusion-Tolerant System (ITS) aims to maintain a useful level of operational capability throughout ongoing cyber-attacks. The applications that are part of an ITS, especially those that provide critical services for the systems mission therefore, must survive the failures and unwanted changes in the system caused by malicious acts of intruders. [ABSTRACT FROM AUTHOR]

Security assessment and mitigation have gained considerable attention over the recent years according to the information technology evolution and its broad adoption. Organizations are more aware of their data security, and they also have become more exigent in terms of extensibility and flexibility of their Information Technology infrastructures. Cloud computing is introduced as an evolution of information technology that offers major solutions and techniques to meet the evolving requirements of both tenants and clients. Therefore, extensibility and dynamic adjustment, which are among the most essential Cloud advantages, can make the security analysis a very hard task. There have been many approaches to analyze automatically the cyber security of traditional IT infrastructures without taking into account the dynamic nature of Cloud computing and its new features, such as the nested virtualization. Until now, there is a few work to assess the security of Cloud computing. In this paper, we propose a novel approach to design and develop Model-based Automated Security Assessment Tool for Cloud Computing named MASAT. [ABSTRACT FROM AUTHOR]