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A survey of communication/networking in Smart Grids

Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. However, it is challenging to strike compelling tradeoffs amongst the various conflicting optimization criteria, such as the network’s energy dissipation, packet-loss rate, coverage, and lifetime. This paper provides a tutorial and survey of recent research and development efforts addressing this issue by using the technique of multi-objective optimization (MOO). First, we provide an overview of the main optimization objectives used in WSNs. Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of mathematical programming-based scalarization methods, the family of heuristics/metaheuristics-based optimization algorithms, and a variety of other advanced optimization techniques. Furthermore, we summarize a range of recent studies of MOO in the context of WSNs, which are intended to provide useful guidelines for researchers to understand the referenced literature. Finally, we discuss a range of open problems to be tackled by future research.

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A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems

The reliability of delivering packets through multi-hop intermediate nodes is a significant issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish connections to form the MANET, which may include selfish and misbehaving nodes. Recommendation based trust management has been proposed in the literature as a mechanism to filter out the misbehaving nodes while searching for a packet delivery route. However, building a trust model that adopts recommendations by other nodes in the network is a challenging problem due to the risk of dishonest recommendations like bad-mouthing, ballot-stuffing, and collusion. This paper investigates the problems related to attacks posed by misbehaving nodes while propagating recommendations in the existing trust models. We propose a recommendation based trust model with a defence scheme, which utilises clustering technique to dynamically filter out attacks related to dishonest recommendations between certain time based on number of interactions, compatibility of information and closeness between the nodes. The model is empirically tested under several mobile and disconnected topologies in which nodes experience changes in their neighbourhood leading to frequent route changes. The empirical analysis demonstrates robustness and accuracy of the trust model in a dynamic MANET environment.

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Recommendation Based Trust Model with an Effective Defence Scheme for MANETs

Unmanned aerial vehicles (UAVs) can be deployed efficiently to provide high quality of service for Internet of Things (IoT). By using cooperative communication and relay technologies, a large swarm of UAVs can enlarge the effective coverage area of IoT services via multiple relay nodes. However, the low latency service requirement and the dynamic topology of UAV network bring in new challenges for the effective routing optimization among UAVs. In this paper, a layered UAV swarm network architecture is proposed and an optimal number of UAVs is analyzed. Furthermore, a low latency routing algorithm (LLRA) is designed based on the partial location information and the connectivity of the network architecture. Finally, the performance of the proposed LLRA is verified by numerical results, which can decrease the link average delay and improve the packet delivery ratio in contrast to traditional routing algorithms without layered architecture.

IoT Enabled UAV: Network Architecture and Routing Algorithm

The Routing Protocol for Low Power and Lossy Networks (RPL) is experiencing a wave of security threats, due to the need of its utility in the Internet of Things (IoT). RPL is so far considered as one of the most utilized routing protocols in new IoT applications, which is one of the reasons the latter may lead to confronting challenges later on. In other words, security is thus the primary interest in RPL, regarding the nature of objects and their different constraints that are regularly regarded as security vulnerabilities for cyber-attacks. To continue, it is evident to claim that it is mandatory to determine and analyze all the kinds of attacks that target this protocol, such as the rank attack which is best known for its strongest threats that lead to degraded topology performance and energy consumption of nodes in the network. This study presents an overview of RPL, a proposed taxonomy of all the recent published works about rank attacks as well as the different mitigation methods, and the damage caused on network parameters. To conclude, a comparison between several attacks has been adopted using the Friedman test, and a discussion has been presented with some other recent research concerning security against rank attack.

Security Against Rank Attack in RPL Protocol

In this paper we evaluate V-AODV a version of AODV (Ad-hoc On-demand Distance Vector) especially created for Vehicular Ad-hoc NETworks (VANETs) V-AODV is designed to run with a complex cross layered metric based on both delay from node to node and Bit Error Rate (BER) coming from the physical layer We conducted simulations with the NS2 simulator taking in account a realistic environment tool called Communication Ray Tracer (CRT) Our results show that the basic propagation models usually in use with NS2 are not suitable for VANETs simulations We also show that when using a routing metric based on delay and BER, the first parameter is more relevant in terms of QoS than the second one

https://hal.archives-ouvertes.fr/hal-00476738/document

An enhanced AODV protocol for VANETs with realistic radio propagation model validation

This paper is a study about deployment strategy for achieving coverage and connectivity as two fundamental issues in wireless sensor networks. To achieve the best deployment, a new approach based on elitist non-dominated sorting genetic algorithm (NSGA-II) is used. There are two objectives in this study, connectivity and coverage. We defined a fitness function to achieve the best nodes deployment. Further we performed simulation to verify and validate the deployment of wireless sensor network as an output from the proposed mechanism. Some performance parameters have been measured to investigate and analyze the proposed sensor-deployment. The simulation results show that the proposed algorithm can maintain the coverage and connectivity in a given sensing area with a relatively small number of sensor nodes.

Evolutionary multi-objective based approach for wireless sensor network deployment

The Internet of Things (IoT) is a fact today where a high number of nodes are used for various applications. From small home networks to large-scale networks, the aim is the same: transmitting data from the sensors to the base station. However, these data are susceptible to different factors that may affect the collected data efficiency or the network functioning, and therefore the desired quality of service (QoS). In this context, one of the main issues requiring more research and adapted solutions is the outlier detection problem. The challenge is to detect outliers and classify them as either errors to be ignored, or important events requiring actions to prevent further service degradation. In this paper, we propose a comprehensive literature review of recent outlier detection techniques used in the IoTs context. First, we provide the fundamentals of outlier detection while discussing the different sources of an outlier, the existing approaches, how we can evaluate an outlier detection technique, and the challenges facing designing such techniques. Second, comparison and discussion of the most recent outlier detection techniques are presented and classified into seven main categories, which are: statistical-based, clustering-based, nearest neighbour-based, classification-based, artificial intelligent-based, spectral decomposition-based, and hybrid-based. For each category, available techniques are discussed, while highlighting the advantages and disadvantages of each of them. The related works for each of them are presented. Finally, a comparative study for these techniques is provided.

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A Survey of Outlier Detection Techniques in IoT: Review and Classification

One of the greatest challenges in computing and estimating the important node metrics of a structural graph is centrality. Since centrality is an essential concept in social network analysis (SNA), it is used to define the importance of a node in a network like a wireless sensor network (WSN). Route optimization is another important feature in a wireless sensor network. This paper proposes an alternative solution to route optimization problems by using the multi-constrained optimal path (MCOP) approach. A new metric called path operator calculus (POC) is proposed as an alternative way to determine nodes with high centrality in wireless sensor network deployment. The estimation of this new metric is based on network topology by using the operator calculus approach, which produces the feasible paths for each node to the sink node. In order to define the path centrality of the network, the proposed approach takes into account two constraints for each node: energy and bit error rate (BER). The experimental evaluation shows improved performance in terms of delivery ratio, latency, throughput, delay, energy remaining and routing overhead.

Abdelhafid Abouaissa

Papers

Security Against Rank Attack in RPL Protocol

An enhanced AODV protocol for VANETs with realistic radio propagation model validation

Evolutionary multi-objective based approach for wireless sensor network deployment

A Survey of Outlier Detection Techniques in IoT: Review and Classification

New Path Centrality Based on Operator Calculus Approach for Wireless Sensor Network Deployment