Deployment Adviser Tool for Wireless Sensor Networks

This paper presents a system for the purpose of field deployment of nodes in wireless sensor networks. We propose a mobile phone based deployment adviser tool which is robust as well as practically implementable. The tool advises a layman deployer to create a optimized wireless sensor network by placing of the nodes according to application requirements. The tool is presented here as logically linked sub-modules. Each sub-modules are described in detail. Also we propose an algorithm which helps in distributing the power consumption among the nodes in the network, thus, increasing the network lifetime. The adviser tool has been verified by implementing it in IITH mote. The tool we propose has significant implication since it greatly eases, but more importantly extracts the best performance possible while deploying the wireless sensor network

Relay node placement in wireless sensor network for manufacturing industry

elay nodes are necessary to maintain scalability and increase longevity as the number of manufacturing industrial sensors grows. In a fixed-budget circumstance, however, the cost of purchasing the bare minimum of relay nodes to connect the network may exceed the budget. Although it is hard to establish a network that connects all sensor nodes, in this case, a network with a high level of connection is still desirable. This paper proposes two metrics for determining the connectedness of a disconnected graph of sensor nodes and determining the optimum deployment method for relay nodes in a network with the highest connectedness while staying within a budget restriction. The metrics are the number of connected graph components and the size of the most significant connected graph component. Prim's algorithm and the approximation minimum spanning tree algorithm are applied to construct a disconnected graph and discover the best relay node placement to solve these two criteria. Compared to the other metrics, simulation findings suggest that prioritizing the most significant connected components in the disconnected graph can yield superior outcomes by deploying the fewest number of relay nodes while retaining the connectedness of the graph

Nouveau modèle pour le positionnement des senseurs avec contraintes de localisation

RÉSUMÉ Les réseaux de capteurs sans fil continuent de constituer sans doute un développement technologique majeur. Le problème de la planification s'inscrit dans un objectif global d'amélioration des performances. Le problème de planification doit permettre d’optimiser l'emplacement des capteurs relativement à des critères afin d’obtenir une certaine qualité de service par exemple en terme de couverture et de connectivité. L’objectif de ce mémoire est de proposer une stratégie de planification des réseaux de capteurs sans fil. Cette stratégie va permettre de garantir une couverture et une connectivité accrue. L’approche commence par proposer un formalisme combinatoire du problème d’optimisation avec des contraintes qui permettent d’exprimer les objectifs de localisation, de couverture et de connectivité. L'espace de recherche est discret et le choix parmi les sites potentiels est directement lié aux caractéristiques de l'environnement du déploiement. Ainsi, on suppose qu’on connait les données concernant les coordonnées des positions probables pour mobiles et des sites potentiels, la portée du signal émis, la sensibilité de réception aussi bien des mobiles que des capteurs à installer, le nombre minimal des signaux pour la localisation et le nombre maximal de sauts permis pour le routage entre capteurs. Une heuristique initiale de type glouton et une autre basée sur la recherche avec tabous permettront d’approcher la solution optimale. Cette solution va être comparée à une borne inférieure définie à partir d’une relaxation de certaines contraintes du modèle. Les simulations réalisées ont permis de démonter la validité de l’approche de planification. Cependant certaines limitations surgissent surtout pour la modélisation de la propagation radio. En effet, nous proposons une amélioration qui se traduit par l’intégration des mesures ou des estimations pour le niveau d’interférence des signaux propagés aussi bien des mobiles que des capteurs. À notre avis, cette approche va essentiellement garantir une localisation exacte des mobiles ainsi qu’une meilleure connectivité des noeuds du réseau de capteurs sans fil.----------ABSTRACT Wireless sensor networks continue to be without doubts a major research area. The objective of the wireless sensors network planning problem is to locate the sensors while respecting a set of performance constraints. In this work we consider coverage and connectivity constraints. Moreover we impose that each mobile station be located by the sensors (i.e. location constraints). The purpose of this work is to propose a planning strategy of wireless sensor networks. It will ensure full coverage and increased connectivity. The approach begins by proposing a formalism of combinatorial optimization model with coverage, location and connectivity constraints. The search space is discrete and the choice of potential sites is directly related to the environment of deployment characteristics. Thus, we assume known the coordinates of positions for mobile stations and potential sites, the characteristics of radio propagation, the receiver sensitivity for mobiles as well as for sensors to be installed, the minimum number of signals for the location, the maximum hops allowed for routing between sensors. An initial greedy heuristic is proposed as well as search metaheuristic. Solutions found are compared to a lower bound obtained by a relaxed version of the model. The simulations show the validity of the planning approach. However, some limitations arise especially for the modeling of radio propagation. Indeed, we propose an improvement which is reflected in the integration of measures or estimates for the level of interference signals. From our perspective, this approach will essentially guarantee an exact location of mobiles and a better connectivity of the nodes of wireless sensor network

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

QoS Scheduling in IEEE 802.16 Broadband Wireless Access Networks

With the exploding increase of mobile users and the release of new wireless applications, the high bandwidth requirement has been taking as a main concern for the design and development of the wireless techniques. There is no doubt that broadband wireless access with the support of heterogeneous kinds of applications is the trend in the next generation wireless networks. As a promising broadband wireless access standard, IEEE 802.16 has attracted extensive attentions from both industry and academia due to its high data rate and the inherent media access control (MAC) mechanism, which takes the service differentiation and quality of service (QoS) provisioning into account. To achieve service differentiation and QoS satisfaction for heterogenous applications is a very complicated issue. It refers to many fields, such as connection admission control (CAC), congestion control, routing algorithm, MAC protocol, and scheduling scheme. Among these fields, packet scheduling plays one of the most important roles in fulfilling service differentiation and QoS provisioning. It decides the order of packet transmissions, and provides mechanisms for the resource allocation and multiplexing at the packet level to ensure that different types of applications meet their service requirements and the network maintains a high resource utilization. In this thesis, we focus on the packet scheduling for difficult types of services in IEEE 802.16 networks, where unicast and mulitcast scheduling are investigated. For unicast scheduling, two types of services are considered: non-real-time polling service (nrtPS) and best effort (BE) service. We propose a flexible and efficient resource allocation and scheduling framework for nrtPS applications to achieve a tradeoff between the delivery delay and resource utilization, where automatic repeat request (ARQ) mechanisms and the adaptive modulation and coding (AMC) technique are jointly considered. For BE service, considering the heterogeneity of subscriber stations (SSs) in IEEE 802.16 networks, we propose the weighted proportional fairness scheduling scheme to achieve the flexible scheduling and resource allocation among SSs based on their traffic demands/patterns. For multicast scheduling, a cooperative multicast scheduling is proposed to achieve high throughput and reliable transmission. By using the two-phase transmission model to exploit the spatial diversity gain in the multicast scenario, the proposed scheduling scheme can significantly improve the throughput not only for all multicast groups, but also for each group member. Analytical models are developed to investigate the performance of the proposed schemes in terms of some important performance measurements, such as throughput, resource utilization, and service probability. Extensive simulations are conducted to illustrate the efficient of the proposed schemes and the accuracy of the analytical models. The research work should provide meaningful guidelines for the system design and the selection of operational parameters, such as the number of TV channels supported by the network, the achieved video quality of each SS in the network, and the setting of weights for SSs under different BE traffic demands