Cybersecurity challenges in vehicular communications

Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote locations. A large number of sensor nodes are deployed in the monitoring area. Therefore, deploying the minimum number of nodes that maintain full coverage and connectivity is of immense importance for research. Hence, coverage and connectivity issues, besides maximizing the network lifetime, represented the main concern to be considered in this paper. The key point of this paper is to classify different coverage techniques in WSNs into three main parts: coverage based on classical deployment techniques, coverage based on meta-heuristic techniques, and coverage based on self-scheduling techniques. Moreover, multiple comparisons among these techniques are provided considering their advantages and disadvantages. Additionally, performance metrics that must be considered in WSNs and comparison among different WSNs simulators are provided. Finally, open research issues, as well as recommendations for researchers, are discussed.

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Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey

Swarm Robotics (SR) is an extension of the study of Multi-Robot Systems that exploits concepts of communication, coordination and collaboration among a large number of robots. The massive parallelization yielded by the robots working together can make a task faster than in the case of the usage of a single complex robot. One of the main aspects in robotic swarms is that the control is decentralized by definition and distributed among the robots of the swarm, improving the system robustness and fault-tolerance. Furthermore, this characteristic often allows the emergence of collective behaviors from the robot's interaction with each other and with the environment through their embodied sensors and actuators. In most cases, the number of inputs from sensor readings turns analytical solutions hard or even impossible. Thus, many ad-hoc approaches are contributed to deal with the situation at hand. The main goal of this review is to find out, through the study of existing research works of the field, the reason behind the lack of exploitation of swarm robotic systems in real-world applications. For this purpose, we first review the different possibilities of study in SR: physical and simulated robotic platforms, development methodologies and the variety of basic tasks and collective behaviors. We then briefly describe some fields related do SR that have a big impact on the development of SR. After that, based on existing taxonomies found in literature, we categorize existing research works regarding SR in two large main groups: those that deal with SR design and those that deal with tasks as required in SR. The review of both existing robots and techniques in the literature show a diversity of approaches to discuss SR issues. Nonetheless, it is easily noticeable from these works that there is a clamant absence of solid real-world applications of SR. An analysis of the interests and bottlenecks of this field indicates that the number of research works is smaller than those in other related areas. This suggests that, even though with many research studies, the field of SR is not yet mature enough, mainly due the absence of a universal methodology and generic robots that can be used in any, or at least in many, applications. Thus, we emphasize, discuss and analyze the urgent need for standardization of many aspects in SR, including hardware and software, as to allow a possible flourishing of SR applicability to real-world applications. This standardization could accelerate a great deal the field of SR, thus facilitating the development of SR solutions for applications that impact our daily life.

Review of methodologies and tasks in swarm robotics towards standardization

Network Function Virtualization (NFV) has been emerging as an appealing solution that transforms complex network functions from dedicated hardware implementations to software instances running in a virtualized environment. Due to the numerous advantages such as flexibility, efficiency, scalability, short deployment cycles, and service upgrade, NFV has been widely recognized as the next-generation network service provisioning paradigm. In NFV, the requested service is implemented by a sequence of Virtual Network Functions (VNF) that can run on generic servers by leveraging the virtualization technology. These VNFs are pitched with a predefined order through which data flows traverse, and it is also known as the Service Function Chaining (SFC). In this article, we provide an overview of recent advances of resource allocation in NFV. We generalize and analyze four representative resource allocation problems, namely, (1) the VNF Placement and Traffic Routing problem, (2) VNF Placement problem, (3) Traffic Routing problem in NFV, and (4) the VNF Redeployment and Consolidation problem. After that, we study the delay calculation models and VNF protection (availability) models in NFV resource allocation, which are two important Quality of Service (QoS) parameters. Subsequently, we classify and summarize the representative work for solving the generalized problems by considering various QoS parameters (e.g., cost, delay, reliability, and energy) and different scenarios (e.g., edge cloud, online provisioning, and distributed provisioning). Finally, we conclude our article with a short discussion on the state-of-the-art and emerging topics in the related fields, and highlight areas where we expect high potential for future research.

Recent Advances of Resource Allocation in Network Function Virtualization

Dynamic service function chaining (SFC) is a technique that facilitates the enforcement of advanced services and differentiated traffic forwarding policies. It dynamically steers the traffic through an ordered list of service functions. Enabling SFC capabilities in the context of a software defined networking (SDN) architecture is promising, as it takes advantage of the SDN flexibility and automation abilities to structure service chains and improve the delivery time. However, the delivery time depends also on the traffic steering techniques used by an SFC solution. This paper provides a closer look at the current SDN architectures for SFC and provides an analysis of traffic steering techniques used by the current SDN-based SFC approaches. This study presents a comprehensive analysis of these approaches using efficiency criteria. It concludes that the studied solutions are not efficient enough to be deployed in real-life networks, principally due to scalability and flexibility limitations. Accordingly, this paper identifies relevant research challenges.

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Traffic Steering for Service Function Chaining

With the advent of Network Function Virtualization (NFV), Physical Network Functions (PNFs) are gradually being replaced by Virtual Network Functions (VNFs) that are hosted on general purpose servers. Depending on the call flows for specific services, the packets need to pass through an ordered set of network functions (physical or virtual) called Service Function Chains (SFC) before reaching the destination. Conceivably for the next few years during this transition, these networks would have a mix of PNFs and VNFs, which brings an interesting mix of network problems that are studied in this paper: (1) How to find an SFC-constrained shortest path between any pair of nodes? (2) What is the achievable SFC-constrained maximum flow? (3) How to place the VNFs such that the cost (the number of nodes to be virtualized) is minimized, while the maximum flow of the original network can still be achieved even under the SFC constraint? In this work, we will try to address such emerging questions. First, for the SFC-constrained shortest path problem, we propose a transformation of the network graph to minimize the computational complexity of subsequent applications of any shortest path algorithm. Second, we formulate the SFC-constrained maximum flow problem as a fractional multicommodity flow problem, and develop a combinatorial algorithm for a special case of practical interest. Third, we prove that the VNFs placement problem is NP-hard and present an alternative Integer Linear Programming (ILP) formulation. Finally, we conduct simulations to elucidate our theoretical results.

Shortest Path and Maximum Flow Problems Under Service Function Chaining Constraints

With the advent of Network Function Virtualization (NFV), network services that traditionally run on proprietary dedicated hardware can now be realized using Virtual Network Functions (VNFs) that are hosted on general-purpose commodity hardware. This new network paradigm offers a great flexibility to Internet service providers (ISPs) for efficiently operating their networks (collecting network statistics, enforcing management policies, etc However, introducing NFV requires an investment to deploy VNFs at certain network nodes (called VNF-nodes), which has to account for practical constraints such as the deployment budget and the VNF-node capacity. To that end, it is important to design a joint VNF-nodes placement and capacity allocation algorithm that can maximize the total amount of network flows that are fully processed by the VNF-nodes while respecting such practical constraints. In contrast to most prior work that often neglects either the budget constraint or the capacity constraint, we explicitly consider both of them. We prove that accounting for these constraints introduces several new challenges. Specifically, we prove that the studied problem is not only NP-hard but also non-submodular. To address these challenges, we introduce a novel relaxation method such that the objective function of the relaxed placement subproblem becomes submodular. Leveraging this useful submodular property, we propose two algorithms that achieve an approximation ratio of $\displaystyle \frac{1}{2} (1\ -\ 1/e)$ and $\displaystyle \frac{1}{3}(1\ -\ 1/e)$ for the original non-relaxed problem, respectively. Finally, we corroborate the effectiveness of the proposed algorithms through extensive evaluations using both trace-driven simulations and simulations based on synthesized network settings.

Joint Placement and Allocation of Virtual Network Functions with Budget and Capacity Constraints

Vehicular ad-hoc network (VANET) is a new emerging type of mobile ad-hoc network that is characterized by high speed and extreme topology changes over short time. These two characteristics dramatically affect the performance of the routing protocols employed in these networks. The evaluation of different routing protocols for general VANET configuration provides great insight into the performance of the entire network. In this work, we evaluate, analyze, and compare the performances of two prevalent routing protocols: ad-hoc on-demand distance vector (AODV) and optimized link-state routing protocol (OLSR). The evaluation is performed using Network Simulator 3 (NS3) and assumes high mobility and account for signal fading to present worst-case scenarios for the two protocols. We consider the architecture Network-as-a-service of VANET cloud computing. Simulation results indicate that while AODV outperforms OLSR in terms of packet delivery ratio for low transmission rates, statistical analysis shows that there is no significant difference between the performances of the two protocols.

Performance Evaluation of OLSR and AODV in VANET Cloud Computing Using Fading Model with SUMO and NS3

Robotics networks are an emerging technology that has a wide range of applications. Robots are used for many military and civilian applications. Applications such as search-and-rescue operations or area monitoring during an environmental disaster, cannot be effectively carried out by a single robot, but rather are carried out by several robots forming what is called a “robotic network”. In rescue operations, for example, robots can be used to help to discover bodies under the rubble or even to assist the injured. One of the main challenges in these applications is how to deploy the robots without central coordination. Virtual force (VF) technique appears to be one of the prominent approaches to perform multi-robot deployment autonomously. However, the effectiveness of this approach depends on how its parameters are calibrated in order to achieve the required deployment. There are two important factors: attractive force ( w a ) and repulsive force ( w r ). In this work, we investigate the best settings of these two factors in order to accommodate different kinds of scenarios. Additionally, and for the first time, an energy-aware virtual force approach is proposed to balance energy consumption among deployed robots and consequently maximize the network lifetime. Extensive simulation experiments are conducted to study and explore the effectiveness of the proposed settings. Finally, a proof of concept experiment using LegoTM Mindstorm robots is carried out to demonstrate the effectiveness of these settings.

https://www.mdpi.com/2079-9292/5/3/34/pdf

Gamal Sallam

Papers

Shortest Path and Maximum Flow Problems Under Service Function Chaining Constraints

Joint Placement and Allocation of Virtual Network Functions with Budget and Capacity Constraints

Joint Placement and Allocation of Virtual Network Functions with Budget and Capacity Constraints

Performance Evaluation of OLSR and AODV in VANET Cloud Computing Using Fading Model with SUMO and NS3

Multi-Robot Deployment Using a Virtual Force Approach: Challenges and Guidelines