A Review on Proposed Implementation of VGDRA and its Comparative Analysis.

Recently, a virtual Grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks is introduced. This paper presents the proposed implementation of VGDRA and its comparative analysis, in which we are discussing the approach of efficient data delivery using communication of distance priority i.e. avoiding straight line communication which was used in previous VGDRA scheme. While maintaining nearly optimal routes to mobile sink’s latest location, our scheme aims to minimize the routes reconstruction cost of sensor nodes. In this approach energy model for reducing energy consumption of nodes is used, which will improves lifetime and also reduce cost consumption. DOI: 10.17762/ijritcc2321-8169.150614

VGDRA: A Virtual Grid-Based Dynamic Routes Adjustment Scheme for Mobile Sink-Based Wireless Sensor Networks

In wireless sensor networks, exploiting the sink mobility has been considered as a good strategy to balance the nodes energy dissipation. Despite its numerous advantages, the data dissemination to the mobile sink is a challenging task for the resource constrained sensor nodes due to the dynamic network topology caused by the sink mobility. For efficient data delivery, nodes need to reconstruct their routes toward the latest location of the mobile sink, which undermines the energy conservation goal. In this paper, we present a virtual gridbased dynamic routes adjustment (VGDRA) scheme that aims to minimize the routes reconstruction cost of the sensor nodes while maintaining nearly optimal routes to the latest location of the mobile sink. We propose a set of communication rules that governs the routes reconstruction process thereby requiring only a limited number of nodes to readjust their data delivery routes toward the mobile sink. Simulation results demonstrate reduced routes reconstruction cost and improved network lifetime of the VGDRA scheme when compared with existing work

4Sensing - decentralized processing for participatory sensing data

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática.Participatory sensing is a new application paradigm, stemming from both technical and social drives, which is currently gaining momentum as a research domain. It leverages the growing adoption of mobile phones equipped with sensors, such as camera, GPS and accelerometer, enabling users to collect and aggregate data, covering a wide area without incurring in the costs associated with a large-scale sensor network. Related research in participatory sensing usually proposes an architecture based on a centralized back-end. Centralized solutions raise a set of issues. On one side, there is the implications of having a centralized repository hosting privacy sensitive information. On the other side, this centralized model has financial costs that can discourage grassroots initiatives. This dissertation focuses on the data management aspects of a decentralized infrastructure for the support of participatory sensing applications, leveraging the body of work on participatory sensing and related areas, such as wireless and internet-wide sensor networks, peer-to-peer data management and stream processing. It proposes a framework covering a common set of data management requirements - from data acquisition, to processing, storage and querying - with the goal of lowering the barrier for the development and deployment of applications. Alternative architectural approaches - RTree, QTree and NTree - are proposed and evaluated experimentally in the context of a case-study application - SpeedSense - supporting the monitoring and prediction of traffic conditions, through the collection of speed and location samples in an urban setting, using GPS equipped mobile phones

Information distribution and recharging dispatch strategy in large wireless networks

Large wireless networks are envisioned to play increasingly important roles as more and more mobile wireless devices and Internet of Things (IoT) devices are put in use. In these networks, it is often the case that some critical information needs to be readily accessible, requiring a careful design of the information distribution technique. In this work, we at first propose PeB, Periodic Broadcast, that takes advantage of periodic broadcast from the information server(s) to leave traces for nodes requesting for the information while maintaining a low overhead. Similar to swarm intelligence, PeB requires each node to keep track of traces, or past records of information flow, through itself toward information servers. We present our extensive investigation of the PeB scheme on cost and network dynamics as compared to other state-of-the-art techniques. When the devices run out of battery, they become static and need to be recharged by the wireless charging vehicles (WCVs). Often times, WCV receives a number of charging requests and form a Hamiltonian cycle and visit these nodes one-by-one. We also propose a heuristic algorithm, termed Quad, that generates a Hamiltonian cycle in a square plane. We then focus on the theoretical study of the length of the Hamiltonian cycles in such networks

Strategies for Data Dissemination to Mobile Sinks in Wireless Sensor Networks

International audienceA wireless sensor network is a multihop wireless network consisting of spatially distributed autonomous sensors with sensing, computation, and wireless communication capabilities. Generally, each sensor has the task to monitor and measure ambient conditions and disseminate the collected data toward a base station, or sink, for data post-analysis and processing. Many data dissemination protocols have been proposed to allow the dissemination of the collected data toward a static sink. Recently, mobile sinks were shown to be more energy-effective than static ones. In this article, existing data dissemination protocols supporting mobile sinks are summarized. In addition, sink mobility is analyzed, as well as its impact on energy consumption and the network lifetime

Infraestrutura de beira de estrada para apoio a sistemas cooperativos e inteligentes de transportes

The growing need of mobility along with the evolution of the automotive industry and the massification of the personal vehicle amplifies some of the road-related problems such as safety and traffic congestion. To mitigate such issues, the evolution towards cooperative communicating technologies and autonomous systems is considered a solution to overcome the human physical limitations and the limited perception horizon of on-board sensors. Short-range vehicular communications such as Vehicle-to-Vehicle or Vehicle-to-Infrastructure (ETSI ITS-G5) in conjunction with long-range cellular communications (LTE,5G) and standardized messages, emerge as viable solutions to amplify the benefits that standalone technologies can bring to the road environment, by covering a wide array of applications and use cases. In compliance with the standardization work from European Telecommunications Standards Institute (ETSI), this dissertation describes the implementation of the collective perception service in a real road infrastructure to assist the maneuvers of autonomous vehicles and provide information to a central road operator. This work is focused on building standardized collective perception messages (CPM) by retrieving information from traffic classification radars (installed in the PASMO project) for local dissemination using ETSI ITS-G5 radio technology and creating a redundant communication channel between the road infrastructure and a central traffic control centre, located at the Instituto de Telecomunicações - Aveiro, taking advantage of cellular, point-to-point radio links and optical fiber communications. The output of the messages are shown to the user by a mobile application. The service is further improved by building an algorithm for optimizing the message dissemination to improve channel efficiency in more demanding scenarios. The results of the experimental tests showed that the time delay between the production event of the collective perception message and the reception by other ITS stations is within the boundaries defined by ETSI standards. Moreover, the algorithm for message dissemination also shows to increase radio channel efficiency by limiting the number of objects disseminated by CPM messages. The collective perception service developed and the road infrastructure are therefore, a valuable asset to provide useful information for improving road safety and fostering the deployment of intelligent cooperative transportation systems.A crescente necessidade de mobilidade em paralelo com a evolução da indústria automóvel e com a massificação do uso de meios de transportes pessoais, têm vindo a amplificar alguns problemas dos transportes rodoviários, tais como a segurança e o congestionamento do tráfego. Para mitigar estas questões, a evolução das tecnologias de comunicação cooperativas e dos sistemas autónomos é vista como uma potencial solução para ultrapassar limitações dos condutores e do horizonte de perceção dos sensores veículares. Comunicações de curto alcance, tais como Veículo-a-Veículo ou Veículo-a-Infrastrutura (ETSI ITS-G5), em conjunto com comunicações móveis de longo alcance (LTE,5G) e mensagens padrão, emergem como soluções viáveis para amplificar todos os beneficios que tecnologias independentes podem trazer para o ambiente rodoviário, cobrindo um grande leque de aplicações e casos de uso da estrada. Em conformidade com o trabalho de padronização da European Telecommunications Standards Institute, esta dissertação descreve a implementação do serviço de perceção coletiva, numa infrastrutura rodoviária real, para suporte a manobras de veículos autónomos e para fornecer informações aos operadores de estradas. Este trabalho foca-se na construção de mensagens de perceção coletiva a partir de informação gerada por radares de classificação de tráfego (instalados no âmbito do projeto PASMO) para disseminação local usando a tecnologia rádio ETSI ITS-G5 e criando um canal de comunicação redundante entre a infraestrutura rodóviaria e um centro de controlo de tráfego localizado no Instituto de Telecomunicações - Aveiro, usando para isso: redes móveis, ligações rádio ponto a ponto e fibra ótica. O conteúdo destas messagens é mostrado ao utilizador através de uma aplicação móvel. O serviço é ainda melhorado, tendo-se para tal desenvolvido um algoritmo de otimização de disseminação das mensagens, tendo em vista melhorar a eficiência do canal de transmissão em cenários mais exigentes. Os resultados dos testes experimentais efetuados revelaram que o tempo de atraso entre o evento de produção de uma mensagem de perceção coletiva e a receção por outra estação ITS, usando comunicações ITS-G5, se encontra dentro dos limites definidos pelos padrões da ETSI. Além disso, o algoritmo para disseminação de mensagens também mostrou aumentar a eficiência do canal de rádio, limitando o número de objetos disseminados pelas mesmas. Assim, o serviço de perceção coletiva desenvolvido poderá ser uma ferramenta valiosa, contribuindo para o aumento da segurança rodóviaria e para a disseminação da utilização dos sistemas cooperativos de transporte inteligente.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors

Wireless Sensors are an important component to develop the Internet of Things (IoT) Sensing infrastructure. There are enormous numbers of sensors connected with each other to form a network (well known as wireless sensor networks) to complete IoT Infrastructure. These deployed wireless sensors are with limited energy and processing capabilities. IoT infrastructure becomes a key factor to building cyber-physical-social networking infrastructure, where all these sensing devices transmit data towards the cloud data center. Data routing towards cloud data center using such low power sensor is still a challenging task. In order to prolong the lifetime of the IoT sensing infrastructure and building scalable cyber infrastructure, there is the requirement of sensing optimization and energy efficient data routing. Towards addressing these issues of IoT sensing, this paper proposes a novel rendezvous data routing protocol for low power sensors. The proposed method divides the sensing area into a number of clusters to lessen the energy consumption with data accumulation and aggregation. As a result, there will be less amount of data stream to the network. Another major reason to select cluster-based data routing is to reduce the control overhead. Finally, the simulation of the proposed method is done in the Castalia simulator to observe the performance. It has been concluded that the proposed method is energy efficient and it prolongs the networks lifetime for scalable IoT infrastructure

A virtual uneven grid-based routing protocol for mobile sink-based WSNs in a smart home system

In a non-uniformly distributed network, the dataconcentrating centre equipped with sparse nodes rapidly depletes its battery energy due to the hotspot problem. To solve this problem, a Virtual Uneven Grid-based Routing protocol (VUGR) is proposed in this paper, which aims to prolong the stable network operating time by dynamically partitioning grid cells, so as to handle energy resources into smaller cells to form such uneven grid cells. A maintenance mechanism in a smart home environment for the higher-layer virtual structure is also adopted in the VUGR to ensure the stable operation of the entire network. In addition, latest location information is updated regularly to all regions within the network. Simulation results demonstrate that the VUGR protocol performs better compared to existing solutions

Low-Complexity and Hardware-Friendly H.265/HEVC Encoder for Vehicular Ad-Hoc Networks

Real-time video streaming over vehicular ad-hoc networks (VANETs) has been considered as a critical challenge for road safety applications. The purpose of this paper is to reduce the computation complexity of high efficiency video coding (HEVC) encoder for VANETs. Based on a novel spatiotemporal neighborhood set, firstly the coding tree unit depth decision algorithm is presented by controlling the depth search range. Secondly, a Bayesian classifier is used for the prediction unit decision for inter-prediction, and prior probability value is calculated by Gibbs Random Field model. Simulation results show that the overall algorithm can significantly reduce encoding time with a reasonably low loss in encoding efficiency. Compared to HEVC reference software HM16.0, the encoding time is reduced by up to 63.96%, while the Bjontegaard delta bit-rate is increased by only 0.76–0.80% on average. Moreover, the proposed HEVC encoder is low-complexity and hardware-friendly for video codecs that reside on mobile vehicles for VANETs