A reliable and resource aware framework for data dissemination in wireless sensor networks

Distinctive from traditional wireless ad hoc networks, wireless sensor networks (WSN) comprise a large number of low-cost miniaturized nodes each acting autonomously and equipped with short-range wireless communication mechanism, limited memory, processing power, and a physical sensing capability. Since sensor networks are resource constrained in terms of power, bandwidth and computational capability, an optimal system design radically changes the performance of the sensor network. Here, a comprehensive information dissemination scheme for wireless sensor networks is performed. Two main research issues are considered: (1) a collaborative flow of information packet/s from the source to sink and (2) energy efficiency of the sensor nodes and the entire system. For the first issue, we designed and evaluated a reactive and on-demand routing paradigm for distributed sensing applications. We name this scheme as IDLF-Information Dissemination via Label ForwarDing IDLF incorporates point to point data transmission where the source initiates the routing scheme and disseminates the information toward the sink (destination) node. Prior to transmission of actual data packet/s, a data tunnel is formed followed by the source node issuing small label information to its neighbors locally. These labels are in turn disseminated in the network. By using small size labels, IDLF avoids generation of unnecessary network traffic and transmission of duplicate packets to nodes. To study the impact of node failures and to improve the reliability of the network, we developed another scheme which is an extension to IDLF. This new scheme, RM-IDLF - Reliable Multipath Information dissemination by Label Forwarding, employ an alternate disjoint path. This alternate path scheme (RM-IDLF) may have a higher path cost in terms of energy consumption, but is more reliable in terms of data packet delivery to sink than the single path scheme (IDLF). In the latter scheme, the protocol establishes multiple (alternate) disjoint path/s from source to destination with negligible control overhead to balance load due to heavy data traffic among intermediate nodes from source to the destination. Another point of interest in this framework is the study of trade-offs between the achieved routing reliability using multiple disjoint path routing and extra energy consumption due to the use of additional path/s. Also, the effect of the failed nodes on the network performance is evaluated within the sensor system; Performance of the label dissemination scheme is evaluated and compared with the classic flooding and SPIN. (Abstract shortened by UMI.)

Fault Tolerant Wireless Sensor MAC Protocol for Efficient Collision Avoidance

In sensor networks communication by broadcast methods involves many hazards, especially collision. Several MAC layer protocols have been proposed to resolve the problem of collision namely ARBP, where the best achieved success rate is 90%. We hereby propose a MAC protocol which achieves a greater success rate (Success rate is defined as the percentage of delivered packets at the source reaching the destination successfully) by reducing the number of collisions, but by trading off the average propagation delay of transmission. Our proposed protocols are also shown to be more energy efficient in terms of energy dissipation per message delivery, compared to the currently existing protocol.Comment: 14 page

Self-* distributed query region covering in sensor networks

Wireless distributed sensor networks are used to monitor a multitude of environments for both civil and military applications. Sensors may be deployed to unreachable or inhospitable areas. Thus, they cannot be replaced easily. However, due to various factors, sensors\u27 internal memory, or the sensors themselves, can become corrupted. Hence, there is a need for more robust sensor networks. Sensors are most commonly densely deployed, but keeping all sensors continually active is not energy efficient. Our aim is to select the minimum number of sensors which can entirely cover a particular monitored area, while remaining strongly connected. This concept is called a Minimum Connected Cover of a query region in a sensor network. In this research, we have designed two fully distributed, robust, self-* solutions to the minimum connected cover of query regions that can cope with both transient faults and sensor crashes. We considered the most general case in which every sensor has a different sensing and communication radius. We have also designed extended versions of the algorithms that use multi-hop information to obtain better results utilizing small atomicity (i.e., each sensor reads only one of its neighbors\u27 variables at a time, instead of reading all neighbors\u27 variables). With this, we have proven self-* (self-configuration, self-stabilization, and self-healing) properties of our solutions, both analytically and experimentally. The simulation results show that our solutions provide better performance in terms of coverage than pre-existing self-stabilizing algorithms

Smart Sensor Data Acquisition in trains

Whether for work or leisure, we see a large number of people traveling by train every day. In order to ensure the comfort and safety of passengers, it must be checked whether the composition is working normally. For this purpose, a constant monitoring of a train must be done, followed by a diagnosis of the com-position, prediction of failures and production of alarms in the event of any anomaly. To perform monitoring on a train, it is necessary to collect data from sensors distributed along its carriages and send them to a software system that performs the diagnosis of the composition in a fast and efficient way. The description of the activities necessary for monitoring of a train imme-diately refers to topics such as distributed systems, since the intended system will have to integrate several sensors distributed along the train, or Smart Systems, since each sensor must have the capacity to not only acquire data, but also trans-mit it, preferably, wirelessly. However, there are some obstacles to the implementation of such a system. Firstly, the existence of sources of distortions and noise in the medium interferes both in the acquisition and transmission of data and secondly the fact that the sensors distributed along the train are not prepared to be connected directly to a software system. This dissertation seeks to find a solution for the problems described by im-plementing a data acquisition system that is distributed and takes advantage of the current technologies of low-cost sensor nodes as well as web technologies for sensor networks

Development of mobile agent framework in wireless sensor networks for multi-sensor collaborative processing

Recent advances in processor, memory and radio technology have enabled production of tiny, low-power, low-cost sensor nodes capable of sensing, communication and computation. Although a single node is resource constrained with limited power, limited computation and limited communication bandwidth, these nodes deployed in large number form a new type of network called the wireless sensor network (WSN). One of the challenges brought by WSNs is an efficient computing paradigm to support the distributed nature of the applications built on these networks considering the resource limitations of the sensor nodes. Collaborative processing between multiple sensor nodes is essential to generate fault-tolerant, reliable information from the densely-spatial sensing phenomenon. The typical model used in distributed computing is the client/server model. However, this computing model is not appropriate in the context of sensor networks. This thesis develops an energy-efficient, scalable and real-time computing model for collaborative processing in sensor networks called the mobile agent computing paradigm. In this paradigm, instead of each sensor node sending data or result to a central server which is typical in the client/server model, the information processing code is moved to the nodes using mobile agents. These agents carry the execution code and migrate from one node to another integrating result at each node. This thesis develops the mobile agent framework on top of an energy-efficient routing protocol called directed diffusion. The mobile agent framework described has been mapped to collaborative target classification application. This application has been tested in three field demos conducted at Twentynine palms, CA; BAE Austin, TX; and BBN Waltham, MA

Stochastic Models and Adaptive Algorithms for Energy Balance in Sensor Networks

We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment. We consider the data gathering problem where data are generated by the sensors and must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering the data to a neighbouring sensor. Direct and neighbouring transmissions require different levels of energy consumption. Basically, the protocols balance the energy consumption among the sensors by computing the adequate ratios of direct and neighbouring transmissions. An abstract model of energy dissipation as a random walk is proposed, along with rigorous performance analysis techniques. Two efficient distributed algorithms are presented and analyzed, by both rigorous means and simulation. The first one is easy to implement and fast to execute. The protocol assumes that sensors know a-priori the rate of data they generate. The sink collects and processes all these information in order to compute the relevant value of the protocol parameter. This value is transmitted to the sensors which individually compute their optimal ratios of direct and neighbouring transmissions. The second protocol avoids the necessary a-priori knowledge of the data rate generated by sensors by inferring the relevant information from the observation of the data paths. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental change

Low-Cost Energy-Efficient Air Quality Monitoring System Using Wireless Sensor Network

Due to rapid industrialization and urbanization, Mauritius is witnessing an unprecedented increase in air pollution. The release of hazardous gases such as carbon monoxide and sulphur dioxide are not only harmful to the health of the population but are also causing irreversible impact to the environment. Currently, there are only two fixed air quality monitoring units on the island and therefore, air pollution cannot be monitored in real-time. The objective of this chapter is to describe the implementation of a low-cost and energy-efficient air quality monitoring system using wireless sensor network (WSN) that can be easily deployed in highly polluted areas of Mauritius. A Hierarchical Based Genetic Algorithm (HBGA) is proposed to address the issue of sensor nodes with limited energy. Based on hierarchical routing and genetic algorithm, HBGA has been designed to extend the lifetime of the network by minimizing the energy consumption. The proposed air quality monitoring system uses an air quality index that can be easily interpreted. The evaluation results confirm the potential of the proposed system for real-time temporal and spatial monitoring of air quality. Moreover, it possible for the general public to have access to the air quality monitoring results in real time