Speedy Routing Recovery Protocol for Large Failure Tolerance in Wireless Sensor Networks

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

A framework for traffic flow survivability in wireless networks prone to multiple failures and attacks

Transmitting packets over a wireless network has always been challenging due to failures that have always occurred as a result of many types of wireless connectivity issues. These failures have caused significant outages, and the delayed discovery and diagnostic testing of these failures have exacerbated their impact on servicing, economic damage, and social elements such as technological trust. There has been research on wireless network failures, but little on multiple failures such as node-node, node-link, and link–link failures. The problem of capacity efficiency and fast recovery from multiple failures has also not received attention. This research develops a capacity efficient evolutionary swarm survivability framework, which encompasses enhanced genetic algorithm (EGA) and ant colony system (ACS) survivability models to swiftly resolve node-node, node-link, and link-link failures for improved service quality. The capacity efficient models were tested on such failures at different locations on both small and large wireless networks. The proposed models were able to generate optimal alternative paths, the bandwidth required for fast rerouting, minimized transmission delay, and ensured the rerouting path fitness and good transmission time for rerouting voice, video and multimedia messages. Increasing multiple link failures reveal that as failure increases, the bandwidth used for rerouting and transmission time also increases. This implies that, failure increases bandwidth usage which leads to transmission delay, which in turn slows down message rerouting. The suggested framework performs better than the popular Dijkstra algorithm, proactive, adaptive and reactive models, in terms of throughput, packet delivery ratio (PDR), speed of transmission, transmission delay and running time. According to the simulation results, the capacity efficient ACS has a PDR of 0.89, the Dijkstra model has a PDR of 0.86, the reactive model has a PDR of 0.83, the proactive model has a PDR of 0.83, and the adaptive model has a PDR of 0.81. Another performance evaluation was performed to compare the proposed model's running time to that of other evaluated routing models. The capacity efficient ACS model has a running time of 169.89ms on average, while the adaptive model has a running time of 1837ms and Dijkstra has a running time of 280.62ms. With these results, capacity efficient ACS outperforms other evaluated routing algorithms in terms of PDR and running time. According to the mean throughput determined to evaluate the performance of the following routing algorithms: capacity efficient EGA has a mean throughput of 621.6, Dijkstra has a mean throughput of 619.3, proactive (DSDV) has a mean throughput of 555.9, and reactive (AODV) has a mean throughput of 501.0. Since Dijkstra is more similar to proposed models in terms of performance, capacity efficient EGA was compared to Dijkstra as follows: Dijkstra has a running time of 3.8908ms and EGA has a running time of 3.6968ms. In terms of running time and mean throughput, the capacity efficient EGA also outperforms the other evaluated routing algorithms. The generated alternative paths from these investigations demonstrate that the proposed framework works well in preventing the problem of data loss in transit and ameliorating congestion issue resulting from multiple failures and server overload which manifests when the process hangs. The optimal solution paths will in turn improve business activities through quality data communications for wireless service providers.School of ComputingPh. D. (Computer Science

Sparsity-Based Spatial Interpolation in Wireless Sensor Networks

In wireless sensor networks, due to environmental limitations or bad wireless channel conditions, not all sensor samples can be successfully gathered at the sink. In this paper, we try to recover these missing samples without retransmission. The missing samples estimation problem is mathematically formulated as a 2-D spatial interpolation. Assuming the 2-D sensor data can be sparsely represented by a dictionary, a sparsity-based recovery approach by solving for l1 norm minimization is proposed. It is shown that these missing samples can be reasonably recovered based on the null space property of the dictionary. This property also points out the way to choose an appropriate sparsifying dictionary to further reduce the recovery errors. The simulation results on synthetic and real data demonstrate that the proposed approach can recover the missing data reasonably well and that it outperforms the weighted average interpolation methods when the data change relatively fast or blocks of samples are lost. Besides, there exists a range of missing rates where the proposed approach is robust to missing block sizes

A Crosslayer Routing Protocol (XLRP) for Wireless Sensor Networks

The advent of wireless sensor networks with emphasis on the information being routed, rather than routing information has redefined networking from that of conventional wireless networked systems. Demanding that need for contnt based routing techniques and development of low cost network modules, built to operate in large numbers in a networked fashion with limited resources and capabilities. The unique characteristics of wireless sensor networks have the applicability and effectiveness of conventional algorithms defined for wireless ad-hoc networks, leading to the design and development of protocols specific to wireless sensor network. Many network layer protocols have been proposed for wireless sensor networks, identifying and addressing factors influencing network layer design, this thesis defines a cross layer routing protocol (XLRP) for sensor networks. The submitted work is suggestive of a network layer design with knowledge of application layer information and efficient utilization of physical layer capabilities onboard the sensor modules. Network layer decisions are made based on the quantity of information (size of the data) that needs to be routed and accordingly transmitter power leels are switched as an energy efficient routing strategy. The proposed routing protocol switches radio states based on the received signal strength (RSSI) acquiring only relevant information and piggybacks information in data packets for reduced controlled information exchange. The proposed algorithm has been implemented in Network Simulator (NS2) and the effectiveness of the protocol has been proved in comparison with diffusion paradigm

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

Design and evaluation of wireless dense networks : application to in-flight entertainment systems

Le réseau sans fil est l'un des domaines de réseautage les plus prometteurs avec des caractéristiques uniques qui peuvent fournir la connectivité dans les situations où il est difficile d'utiliser un réseau filaire, ou lorsque la mobilité des nœuds est nécessaire. Cependant, le milieu de travail impose généralement diverses contraintes, où les appareils sans fil font face à différents défis lors du partage des moyens de communication. De plus, le problème s'aggrave avec l'augmentation du nombre de nœuds. Différentes solutions ont été introduites pour faire face aux réseaux très denses. D'autre part, un nœud avec une densité très faible peut créer un problème de connectivité et peut conduire à l'optension de nœuds isolés et non connectes au réseau. La densité d'un réseau est définit en fonction du nombre de nœuds voisins directs au sein de la portée de transmission du nœud. Cependant, nous croyons que ces métriques ne sont pas suffisants et nous proposons une nouvelle mesure qui considère le nombre de voisins directs et la performance du réseau. Ainsi, la réponse du réseau, respectant l'augmentation du nombre de nœuds, est considérée lors du choix du niveau de la densité. Nous avons défini deux termes: l'auto-organisation et l'auto-configuration, qui sont généralement utilisés de façon interchangeable dans la littérature en mettant en relief la différence entre eux. Nous estimons qu'une définition claire de la terminologie peut éliminer beaucoup d'ambiguïté et aider à présenter les concepts de recherche plus clairement. Certaines applications, telles que Ies systèmes "In-Flight Entertainment (IFE)" qui se trouvent à l'intérieur des cabines d'avions, peuveut être considérées comme des systèmes sans fil de haute densité, même si peu de nœuds sont relativement présents. Pour résoudre ce problème, nous proposons une architecture hétérogène de différentes technologies à fin de surmonter les contraintes spécifiques de l'intérieur de la cabine. Chaque technologie vise à résoudre une partie du problème. Nous avons réalisé diverses expérimentations et simulations pour montrer la faisabilité de l'architecture proposée. Nous avons introduit un nouveau protocole d'auto-organisation qui utilise des antennes intelligentes pour aider certains composants du système IFE; à savoir les unités d'affichage et leurs systèmes de commande, à s'identifier les uns les autres sans aucune configuration préliminaire. Le protocole a été conçu et vérifié en utilisant le langage UML, puis, un module de NS2 a été créé pour tester les différents scénarios.Wireless networking is one of the most challenging networking domains with unique features that can provide connectivity in situations where it is difficult to use wired networking, or when ! node mobility is required. However, the working environment us! ually im poses various constrains, where wireless devices face various challenges when sharing the communication media. Furthermore, the problem becomes worse when the number of nodes increase. Different solutions were introduced to cope with highly dense networks. On the other hand, a very low density can create a poor connectivity problem and may lead to have isolated nodes with no connection to the network. It is common to define network density according to the number of direct neighboring nodes within the node transmission range. However, we believe that such metric is not enough. Thus, we propose a new metric that encompasses the number of direct neighbors and the network performance. In this way, the network response, due to the increasing number of nodes, is considered when deciding the density level. Moreover, we defined two terms, self-organization and self-configuration, which are usually used interchangeably in the literature through highlighting the difference ! between them. We believe that having a clear definition for terminology can eliminate a lot of ambiguity and help to present the research concepts more clearly. Some applications, such as In-Flight Entertainment (IFE) systems inside the aircraft cabin, can be considered as wirelessly high dense even if relatively few nodes are present. To solve this problem, we propose a heterogeneous architecture of different technologies to overcome the inherited constrains inside the cabin. Each technology aims at solving a part of the problem. We held various experimentation and simulations to show the feasibility of the proposed architecture

Wireless Sensor Networks

The aim of this book is to present few important issues of WSNs, from the application, design and technology points of view. The book highlights power efficient design issues related to wireless sensor networks, the existing WSN applications, and discusses the research efforts being undertaken in this field which put the reader in good pace to be able to understand more advanced research and make a contribution in this field for themselves. It is believed that this book serves as a comprehensive reference for graduate and undergraduate senior students who seek to learn latest development in wireless sensor networks

A survey of communication protocols for internet of things and related challenges of fog and cloud computing integration

The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput. These findings are thereafter used to place the protocols in each segment of the system (IoT, fog, cloud), and thus opens up the discussion on their choice, interoperability, and wider system integration. The survey is expected to be useful to system architects and protocol designers when choosing the communication protocols in an integrated IoT-to-fog-to-cloud system architecture.Peer ReviewedPostprint (author's final draft