Balanced Transmissions Based Trajectories of Mobile Sink in Homogeneous Wireless Sensor Networks

Mobile Sink (MS) based routing strategies have been widely investigated to prolong the lifetime of Wireless Sensor Networks (WSNs). In this paper, we propose two schemes for data gathering in WSNs: (i) MS moves on random paths in the network (RMS) and (ii) the trajectory of MS is defined (DMS). In both the schemes, the network field is logically divided into small squares. The center point of each partitioned area is the sojourn location of the MS. We present three linear programming based models: (i) to maximize network lifetime, (ii) to minimize path loss, and (iii) to minimize end to end delay. Moreover, a geometric model is proposed to avoid redundancy while collecting information from the network nodes. Simulation results show that our proposed schemes perform better than the selected existing schemes in terms of the selected performance metrics

DESIGN OF MOBILE DATA COLLECTOR BASED CLUSTERING ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSNs) consisting of hundreds or even thousands of nodes, canbe used for a multitude of applications such as warfare intelligence or to monitor the environment. A typical WSN node has a limited and usually an irreplaceable power source and the efficient use of the available power is of utmost importance to ensure maximum lifetime of eachWSNapplication. Each of the nodes needs to transmit and communicate sensed data to an aggregation point for use by higher layer systems. Data and message transmission among nodes collectively consume the largest amount of energy available in WSNs. The network routing protocols ensure that every message reaches thedestination and has a direct impact on the amount of transmissions to deliver messages successfully. To this end, the transmission protocol within the WSNs should be scalable, adaptable and optimized to consume the least possible amount of energy to suite different network architectures and application domains. The inclusion of mobile nodes in the WSNs deployment proves to be detrimental to protocol performance in terms of nodes energy efficiency and reliable message delivery. This thesis which proposes a novel Mobile Data Collector based clustering routing protocol for WSNs is designed that combines cluster based hierarchical architecture and utilizes three-tier multi-hop routing strategy between cluster heads to base station by the help of Mobile Data Collector (MDC) for inter-cluster communication. In addition, a Mobile Data Collector based routing protocol is compared with Low Energy Adaptive Clustering Hierarchy and A Novel Application Specific Network Protocol for Wireless Sensor Networks routing protocol. The protocol is designed with the following in mind: minimize the energy consumption of sensor nodes, resolve communication holes issues, maintain data reliability, finally reach tradeoff between energy efficiency and latency in terms of End-to-End, and channel access delays. Simulation results have shown that the Mobile Data Collector based clustering routing protocol for WSNs could be easily implemented in environmental applications where energy efficiency of sensor nodes, network lifetime and data reliability are major concerns

MBSR: MIMO Based Sink Relocation for Path Selection in IoT Based WSN

Wireless Sensor Networks have extended its functionalities by integrating with the Internet of Things and are highly proficient when it is incorporated with other technologies. This demands communication with lesser energy consumption and one such idea of low energy consumption is low energy path selection by a mobile sink node. Path selection requires a good Signal Interference Noise Ratio (SINR) which is calculated for the positioned mobile sink. Thus, a high-quality transmission path is selected by choosing a path to obtain better SINR. MBSR algorithm considers hierarchical clustering schemes and heads are elected to monitor the network. Heads of the clusters communicate to IoT applications using Multiple Input and Multiple Output Dual Antennas. The proposed MBSR scheme utilizes a path optimization technique and finds a suitable path to establish links to end user and real-time environments. The proposed MBSR mechanism employs three phases of execution. Phase 1: Cluster Creation, Phase 2: SINR Analysis for Path Selection. Phase 3: Data transmission to MIMO Devices and in turn forwards to static sinks that connect to end-user using the internet. MBSR improves transmission quality and the proposed scheme is tested for various network parameters to check transmission quality and is compared with existing methodologies

Performance optimization of wireless sensor networks for remote monitoring

Wireless sensor networks (WSNs) have gained worldwide attention in recent years because of their great potential for a variety of applications such as hazardous environment exploration, military surveillance, habitat monitoring, seismic sensing, and so on. In this thesis we study the use of WSNs for remote monitoring, where a wireless sensor network is deployed in a remote region for sensing phenomena of interest while its data monitoring center is located in a metropolitan area that is geographically distant from the monitored region. This application scenario poses great challenges since such kind of monitoring is typically large scale and expected to be operational for a prolonged period without human involvement. Also, the long distance between the monitored region and the data monitoring center requires that the sensed data must be transferred by the employment of a third-party communication service, which incurs service costs. Existing methodologies for performance optimization of WSNs base on that both the sensor network and its data monitoring center are co-located, and therefore are no longer applicable to the remote monitoring scenario. Thus, developing new techniques and approaches for severely resource-constrained WSNs is desperately needed to maintain sustainable, unattended remote monitoring with low cost. Specifically, this thesis addresses the key issues and tackles problems in the deployment of WSNs for remote monitoring from the following aspects. To maximize the lifetime of large-scale monitoring, we deal with the energy consumption imbalance issue by exploring multiple sinks. We develop scalable algorithms which determine the optimal number of sinks needed and their locations, thereby dynamically identifying the energy bottlenecks and balancing the data relay workload throughout the network. We conduct experiments and the experimental results demonstrate that the proposed algorithms significantly prolong the network lifetime. To eliminate imbalance of energy consumption among sensor nodes, a complementary strategy is to introduce a mobile sink for data gathering. However, the limited communication time between the mobile sink and nodes results in that only part of sensed data will be collected and the rest will be lost, for which we propose the concept of monitoring quality with the exploration of sensed data correlation among nodes. We devise a heuristic for monitoring quality maximization, which schedules the sink to collect data from selected nodes, and uses the collected data to recover the missing ones. We study the performance of the proposed heuristic and validate its effectiveness in improving the monitoring quality. To strive for the fine trade-off between two performance metrics: throughput and cost, we investigate novel problems of minimizing cost with guaranteed throughput, and maximizing throughput with minimal cost. We develop approximation algorithms which find reliable data routing in the WSN and strategically balance workload on the sinks. We prove that the delivered solutions are fractional of the optimum. We finally conclude our work and discuss potential research topics which derive from the studies of this thesis

Energy-Efficient Querying of Wireless Sensor Networks

Due to the distributed nature of information collection in wireless sensor networks and the inherent limitations of the component devices, the ability to store, locate, and retrieve data and services with minimum energy expenditure is a critical network function. Additionally, effective search protocols must scale efficiently and consume a minimum of network energy and memory reserves. A novel search protocol, the Trajectory-based Selective Broadcast Query protocol, is proposed. An analytical model of the protocol is derived, and an optimization model is formulated. Based on the results of analysis and simulation, the protocol is shown to reduce the expected total network energy expenditure by 45.5 percent to 75 percent compared to current methods. This research also derives an enhanced analytical node model of random walk search protocols for networks with limited-lifetime resources and time-constrained queries. An optimization program is developed to minimize the expected total energy expenditure while simultaneously ensuring the proportion of failed queries does not exceed a specified threshold. Finally, the ability of the analytical node model to predict the performance of random walk search protocols in large-population networks is established through extensive simulation experiments. It is shown that the model provides a reliable estimate of optimum search algorithm parameters

DESIGN AND IMPLEMENTATION OF INFORMATION PATHS IN DENSE WIRELESS SENSOR NETWORKS

In large-scale sensor networks with monitoring applications, sensor nodes are responsible to send periodic reports to the destination which is located far away from the area to be monitored. We model this area (referred to as the distributed source) with a positive load density function which determines the total rate of traffic generated inside any closed contour within the area. With tight limitations in energy consumption of wireless sensors and the many-to-one nature of communications in wireless sensor networks, the traditional definition of connectivity in graph theory does not seem to be sufficient to satisfy the requirements of sensor networks. In this work, a new notion of connectivity (called implementability) is defined which represents the ability of sensor nodes to relay traffic along a given direction field, referred to as information flow vector field $\vec{D}$. The magnitude of information flow is proportional to the traffic flux (per unit length) passing through any point in the network, and its direction is toward the flow of traffic. The flow field may be obtained from engineering knowledge or as a solution to an optimization problem. In either case, information flow flux lines represent a set of abstract paths (not constrained by the actual location of sensor nodes) which can be used for data transmission to the destination. In this work, we present conditions to be placed on $\vec{D}$ such that the resulting optimal vector field generates a desirable set of paths. In a sensor network with a given irrotational flow field $\vec{D}(x,y)$, we show that a density of $n(x,y)=O(|\vec{D}(x,y)|^2)$ sensor nodes is not sufficient to implement the flow field as $|\vec{D}|$ scales linearly to infinity. On the other hand, by increasing the density of wireless nodes to $n(x,y)=O(|\vec{D}(x,y)|^2 \log |\vec{D}(x,y)|)$, the flow field becomes implementable. Implementability requires more nodes than simple connectivity. However, results on connectivity are based on the implicit assumption of exhaustively searching all possible routes which contradicts the tight limitation of energy in sensor networks. We propose a joint MAC and routing protocol to forward traffic along the flow field. The proposed tier-based scheme can be further exploited to build lightweight protocol stacks which meet the specific requirements of dense sensor networks. We also investigate buffer scalability of sensor nodes routing along flux lines of a given irrotational vector field, and show that nodes distributed according to the sufficient bound provided above can relay traffic from the source to the destination with sensor nodes having limited buffer space. This is particularly interesting for dense wireless sensor networks where nodes are assumed to have very limited resources

Self-organizing Fast Routing Protocols for Underwater Acoustic Communications Networks

To address this problem, in this thesis we propose a cross-layer proactive routing initialization mechanism that does not require additional measurements and, at the same time, is energy efficient. Two routing protocols are proposed: Self-Organized Fast Routing Protocol for Radial Underwater Networks (SOFRP) for radial topology and Self-organized Proactive Routing Protocol for Non-uniformly Deployed Underwater Networks (SPRINT) for a randomly deployed network. SOFRP is based on the algorithm to recreate a radial topology with a gateway node, such that packets always use the shortest possible path from source to sink, thus minimizing consumed energy. Collisions are avoided as much as possible during the path initialization. The algorithm is suitable for 2D or 3D areas, and automatically adapts to a varying number of nodes. In SPRINT the routing path to the gateway is formed on the basis of the distance, measured by the signal strength received. The data sending node prefers to choose the neighbor node which is closest to it. It is designed to achieve high data throughput and low energy consumption of the nodes. There is a tradeoff between the throughput and the energy consumption: more distance needs more transmission energy, and more relay nodes (hops) to the destination node affects the throughput. Each hop increases the packet delay and decreases the throughput. Hence, energy consumption requires nearest nodes to be chosen as forwarding node whereas the throughput requires farthest node to be selected to minimize the number of hops. Fecha de lectura de Tesis Doctoral: 11 mayo 2020Underwater Wireless Sensor Networks (UWSNs) constitute an emerging technology for marine surveillance, natural disaster alert and environmental monitoring. Unlike terrestrial Wireless Sensor Networks (WSNs), electromagnetic waves cannot propagate more than few meters in water (high absorption rate). However, acoustic waves can travel long distances in underwater. Therefore, acoustic waves are preferred for underwater communications, but they travel very slow compare to EM waves (typical speed in water is 1500 m/s against 2x10^8 m/s for EM waves). This physical effect makes a high propagation delay and cannot be avoided, but the end-to-end packet delay it can be reduced. Routing delay is one of the major factors in end-to-end packet delay. In reactive routing protocols, when a packet arrives to a node, the node takes some time to select the node to which the data packet would be forwarded. We may reduce the routing delay for time-critical applications by using proactive routing protocols. Other two critical issues in UWSNs are determining the position of the nodes and time synchronization. Wireless sensor nodes need to determine the position of the surrounding nodes to select the next node in the path to reach the sink node. A Global Navigation Satellite System (GNSS) cannot be used because of the very short underwater range of the GNSS signal. Timestamping to estimate the distance is possible but the limited mobility of the UWSN nodes and variation in the propagation speed of the acoustic waves make the time synchronization a challenging task. For these reasons, terrestrial WSN protocols cannot be readily used for underwater acoustic networks

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications

Energy-efficient mobile sink routing scheme for clustered corona-based wireless sensor networks

Wireless Sensor Networks (WSNs) are generally composed of several tiny, inexpensive and self-configured sensor nodes, which are able to communicate with each other via wireless communication devices. The main duty of the nodes is to sense data and transmit to a sink via multi- or single-hop data transmission manners. Since the sensor nodes generally are limited in power resources, they deplete their energy rapidly. In addition, sensor nodes are usually distributed in places, where may be too harsh to be accessible for human. Consequently, exchanging or recharging the power supplies of the sensor nodes is difficult. Therefore, energy efficiency is the most critical issue in design of WSN, which affects the lifetime and performance of the network. Several cluster-based schemes are proposed to enhance the energy efficiency; however, most of them generate sub-optimal clusters without considering both coverage and energy issues simultaneously. Furthermore, several mobility-based schemes are proposed in order to achieve balanced energy consumption through optimizing the sojourn time and sojourn location of Mobile Sinks (MS). Nevertheless, most of them adjust the sojourn time of MS under predictable mobility pattern. Moreover, in most of existing mobility based schemes, time limitation is not considered for optimizing the sojourn location of MS. The aim behind this research is to develop an Energy-efficient Mobile Sink Routing (EMSR) Scheme, which improves the energy efficiency. The EMSR is the incorporation of three schemes: Energyefficient based Unequal-sized Clustering (EUC) mechanism aims to construct the optimal sized clusters, which ensures the energy conservation and coverage preservation. Collaborative Mobile Sink-based Inter-Cluster Routing (CMSICR) mechanism aims to optimize the sojourn time of MS to balance the energy consumption among Cluster Heads (CH). An Energy-efficient Intra-cluster Movement of Mobile Sink (EIM2S) mechanism, which identifies the optimal sojourn locations of the MS within clusters in order to balance the energy consumption among Member Nodes (MN). The EMSR partitions the network field into optimal clusters and employs MSs in order to balance the energy consumption among CHs and MNs. Simulation results show that EMSR achieved improved performance in terms of network lifetime by 51%, total energy consumption by 28% wasted energy by 36% compared to existing schemes. In conclusion, the proposed routing scheme proves to be a viable solution for multi hop cluster based WSN

Opportunistic data collection and routing in segmented wireless sensor networks

La surveillance régulière des opérations dans les aires de manoeuvre (voies de circulation et pistes) et aires de stationnement d'un aéroport est une tâche cruciale pour son fonctionnement. Les stratégies utilisées à cette fin visent à permettre la mesure des variables environnementales, l'identification des débris (FOD) et l'enregistrement des statistiques d'utilisation de diverses sections de la surface. Selon un groupe de gestionnaires et contrôleurs d'aéroport interrogés, cette surveillance est un privilège des grands aéroports en raison des coûts élevés d'acquisition, d'installation et de maintenance des technologies existantes. Les moyens et petits aéroports se limitent généralement à la surveillance de quelques variables environnementales et des FOD effectuée visuellement par l'homme. Cette dernière activité impose l'arrêt du fonctionnement des pistes pendant l'inspection. Dans cette thèse, nous proposons une solution alternative basée sur les réseaux de capteurs sans fil (WSN) qui, contrairement aux autres méthodes, combinent les propriétés de faible coût d'installation et maintenance, de déploiement rapide, d'évolutivité tout en permettant d'effectuer des mesures sans interférer avec le fonctionnement de l'aéroport. En raison de la superficie d'un aéroport et de la difficulté de placer des capteurs sur des zones de transit, le WSN se composerait d'une collection de sous-réseaux isolés les uns des autres et du puits. Pour gérer cette segmentation, notre proposition s'appuie sur l'utilisation opportuniste des véhicules circulants dans l'aéroport considérés alors comme un type spécial de nœud appelé Mobile Ubiquitous LAN Extension (MULE) chargé de collecter les données des sous-réseaux le long de son trajet et de les transférer vers le puits. L'une des exigences pour le déploiement d'un nouveau système dans un aéroport est qu'il cause peu ou pas d'interruption des opérations régulières. C'est pourquoi l'utilisation d'une approche opportuniste basé sur des MULE est privilégiée dans cette thèse. Par opportuniste, nous nous référons au fait que le rôle de MULE est joué par certains des véhicules déjà existants dans un aéroport et effectuant leurs déplacements normaux. Et certains nœuds des sous- réseaux exploiteront tout moment de contact avec eux pour leur transmettre les données à transférer ensuite au puits. Une caractéristique des MULEs dans notre application est qu'elles ont des trajectoires structurées (suivant les voies de circulation dans l'aéroport), en ayant éventuellement un contact avec l'ensemble des nœuds situés le long de leur trajet (appelés sous-puits). Ceci implique la nécessité de définir une stratégie de routage dans chaque sous-réseau, capable d'acheminer les données collectées des nœuds vers les sous-puits et de répartir les paquets de données entre eux afin que le temps en contact avec la MULE soit utilisé le plus efficacement possible. Dans cette thèse, nous proposons un protocole de routage remplissant ces fonctions. Le protocole proposé est nommé ACME (ACO-based routing protocol for MULE-assisted WSNs). Il est basé sur la technique d'Optimisation par Colonies de Fourmis. ACME permet d'assigner des nœuds à des sous-puits puis de définir les chemins entre eux, en tenant compte de la minimisation de la somme des longueurs de ces chemins, de l'équilibrage de la quantité de paquets stockés par les sous-puits et du nombre total de retransmissions. Le problème est défini comme une tâche d'optimisation multi-objectif qui est résolue de manière distribuée sur la base des actions des nœuds dans un schéma collaboratif. Nous avons développé un environnement de simulation et effectué des campagnes de calculs dans OMNeT++ qui montrent les avantages de notre protocole en termes de performances et sa capacité à s'adapter à une grande variété de topologies de réseaux.The regular monitoring of operations in both movement areas (taxiways and runways) and non-movement areas (aprons and aircraft parking spots) of an airport, is a critical task for its functioning. The set of strategies used for this purpose include the measurement of environmental variables, the identification of foreign object debris (FOD), and the record of statistics of usage for diverse sections of the surface. According to a group of airport managers and controllers interviewed by us, the wide monitoring of most of these variables is a privilege of big airports due to the high acquisition, installation and maintenance costs of most common technologies. Due to this limitation, smaller airports often limit themselves to the monitoring of environmental variables at some few spatial points and the tracking of FOD performed by humans. This last activity requires stopping the functioning of the runways while the inspection is conducted. In this thesis, we propose an alternative solution based on Wireless Sensor Network (WSN) which, unlike the other methods/technologies, combines the desirable properties of low installation and maintenance cost, scalability and ability to perform measurements without interfering with the regular functioning of the airport. Due to the large extension of an airport and the difficulty of placing sensors over transit areas, the WSN might result segmented into a collection of subnetworks isolated from each other and from the sink. To overcome this problem, our proposal relies on a special type of node called Mobile Ubiquitous LAN Extension (MULE), able to move over the airport surface, gather data from the subnetworks along its way and eventually transfer it to the sink. One of the main demands for the deployment of any new system in an airport is that it must have little or no interference with the regular operations. This is why the use of an opportunistic approach for the transfer of data from the subnetworks to the MULE is favored in this thesis. By opportunistic we mean that the role of MULE will be played by some of the typical vehicles already existing in an airport doing their normal displacements, and the subnetworks will exploit any moment of contact with them to forward data to the sink. A particular characteristic of the MULEs in our application is that they move along predefined structured trajectories (given by the layout of the airport), having eventual contact with the set of nodes located by the side of the road (so-called subsinks). This implies the need for a data routing strategy to be used within each subnetwork, able to lead the collected data from the sensor nodes to the subsinks and distribute the data packets among them so that the time in contact with the MULE is used as efficiently as possible. In this thesis, we propose a routing protocol which undertakes this task. Our proposed protocol is named ACME, standing for ACO-based routing protocol for MULE-assisted WSNs. It is founded on the well known Ant Colony Optimization (ACO) technique. The main advantage of ACO is its natural fit to the decentralized nature of WSN, which allows it to perform distributed optimizations (based on local interactions) leading to remarkable overall network performance. ACME is able to assign sensor nodes to subsinks and generate the corresponding multi-hop paths while accounting for the minimization of the total path length, the total subsink imbalance and the total number of retransmissions. The problem is defined as a multi-objective optimization task which is resolved in a distributed manner based on actions of the sensor nodes acting in a collaborative scheme. We conduct a set of computational experiments in the discrete event simulator OMNeT++ which shows the advantages of our protocol in terms of performance and its ability to adapt to a variety of network topologie