14 research outputs found

    Hierarchical Routing in Low-Power Wireless Networks

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    Steen, M.R. van [Promotor

    Bio-Inspired Tools for a Distributed Wireless Sensor Network Operating System

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    The problem which I address in this thesis is to find a way to organise and manage a network of wireless sensor nodes using a minimal amount of communication. To find a solution I explore the use of Bio-inspired protocols to enable WSN management while maintaining a low communication overhead. Wireless Sensor Networks (WSNs) are loosely coupled distributed systems comprised of low-resource, battery powered sensor nodes. The largest problem with WSN management is that communication is the largest consumer of a sensor node’s energy. WSN management systems need to use as little communication as possible to prolong their operational lifetimes. This is the Wireless Sensor Network Management Problem. This problem is compounded because current WSN management systems glue together unrelated protocols to provide system services causing inter-protocol interference. Bio-inspired protocols provide a good solution because they enable the nodes to self-organise, use local area communication, and can combine their communication in an intelligent way with minimal increase in communication. I present a combined protocol and MAC scheduler to enable multiple service protocols to function in a WSN at the same time without causing inter-protocol interference. The scheduler is throughput optimal as long as the communication requirements of all of the protocols remain within the communication capacity of the network. I show that the scheduler improves a dissemination protocol’s performance by 35%. A bio-inspired synchronisation service is presented which enables wireless sensor nodes to self organise and provide a time service. Evaluation of the protocol shows an 80% saving in communication over similar bio-inspired synchronisation approaches. I then add an information dissemination protocol, without significantly increasing communication. This is achieved through the ability of our bio-inspired algorithms to combine their communication in an intelligent way so that they are able to offer multiple services without requiring a great deal of inter-node communication.Open Acces

    The impact of message replication on the performance of opportunistic networks for sensed data collection

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    Opportunistic networks (OppNets) provide a scalable solution for collecting delay-tolerant data from sensors to their respective gateways. Portable handheld user devices contribute significantly to the scalability of OppNets since their number increases according to user population and they closely follow human movement patterns. Hence, OppNets for sensed data collection are characterised by high node population and degrees of spatial locality inherent to user movement. We study the impact of these characteristics on the performance of existing OppNet message replication techniques. Our findings reveal that the existing replication techniques are not specifically designed to cope with these characteristics. This raises concerns regarding excessive message transmission overhead and throughput degradations due to resource constraints and technological limitations associated with portable handheld user devices. Based on concepts derived from the study, we suggest design guidelines to augment existing message replication techniques. We also follow our design guidelines to propose a message replication technique, namely Locality Aware Replication (LARep). Simulation results show that LARep achieves better network performance under high node population and degrees of spatial locality as compared with existing techniques

    Design of an energy-efficient geographic routing protocol for mobile ad-hoc networks

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    Mobile Ad-hoc networks extend communications beyond the limit of infrastructure based networks. Future wireless applications will take advantage of rapidly deployable, self-configuring multi-hop mobile Ad-hoc networks. In order to provide robust performance in mobile Ad-hoc networks and hence cope with dynamic path loss conditions, it is apparent that research and development of energy efficient geographic routing protocols is of great importance. Therefore various mobile Ad-hoc routing protocols have been studied for their different approaches. Forwarding strategies for geographic routing protocols are discussed and there is a particular focus on the pass loss model used by those routing protocols, the restriction and disadvantage of using such path loss model is then discussed. A novel geographic routing protocol which incorporates both the link quality and relay node location information has been developed to determine an energy efficient route from source to destination. The concepts of a gain region and a relay region to minimize the energy consumption have been proposed to define the area in where the candidate relay nodes will be selected with the minimized hop count. The signalling overhead required by the protocol has been analyzed in various scenarios with different traffic load, node densities and network sizes. Discrete event simulation models are therefore developed to capture the behaviour and characteristics of the operation of the developed routing protocol under different path loss conditions and network scenarios. A non-free space path loss model has been developed with a random loss between the nodes to simulate a realistic path loss scenario in the network. An enhanced signalling process has been designed in order to achieve advanced routing information exchange and assist routing determination. Comparison of simulated characteristics demonstrates the significant improvement of the new routing protocol because of its novel features, the gain region to ensure the deductiono f the energyc onsumptiont,h e relay region to ensuret he forward progress to the destination and hence maintain an optimised hop count. The simulation results showed that the energy consumption under the operation of the developed protocol is 30% of that with a conventionagl eographicarl outing protocol

    Collecting sensed data with opportunistic networks: The case of contact information overhead

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    The rising human population in urban environments drives the mission towards smart cities, which envisions a wide deployment of sensors in order to improve the quality of living. In this regard, opportunistic networks (OppNets) present an economical means of collecting delay tolerant data from sensors to their respective gateways for providing various Smart City services. Due to the distributed nature of the network, encounter-based routing protocols achieve acceptable throughput by requiring nodes to exchange and update contact information on an encounter basis. Unfortunately, sufficient insight into the associated overhead is lacking in the literature. Hence, we contribute by modelling contact information overhead and investigating its impact on OppNet routing, particularly in terms of data exchange success and energy consumption on portable handheld devices. Our findings reveal that the expected contact information overhead in Smart City scenarios significantly reduces data exchange success and increases energy consumption on portable handheld devices, thereby threatening the feasibility of the technology. We address this issue by proposing an algorithm that can be incorporated into encounter-based routing protocols to reduce contact information overhead without compromising throughput. Simulation results show that our proposed algorithm reduces the average contact information overhead, increases throughput and reduces average energy consumption

    Dependability of Wireless Sensor Networks

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    As wireless sensor networks (WSNs) are becoming ever more prevalent, the runtime characteristics of these networks are becoming an increasing issue. Commonly, external sources of interference make WSNs behave in a different manner to that expected from within simplistic simulations, resulting in the need to use additional systems which monitor the state of the network. Despite dependability of WSNs being an increasingly important issue, there are still only a limited number of works within this specific field, with the majority of works focusing on ensuring that specific devices are operational, not the application as a whole. This work instead aims to look at the dependability of WSNs from an application-centric view, taking into account the possible ways in which the application may fail and using the application's requirements to focus on assuring dependability

    A Bio-inspired Load Balancing Technique for Wireless Sensor Networks

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    Wireless Sensor Networks (WSNs) consist of multiple distributed nodes each with limited resources. With their strict resource constraints and application-specific characteristics, WSNs contain many challenging trade-offs. This thesis is concerned with the load balancing of Wireless Sensor Networks (WSNs). We present an approach, inspired by bees’ pheromone propagation mechanism, that allows individual nodes to decide on the execution process locally to solve the trade-off between service availability and energy consumption. We explore the performance consequences of the pheromone-based load balancing approach using a system-level simulator. The effectiveness of the algorithm is evaluated on case studies based on sound sensors with different scenarios of existing approaches on variety of different network topologies. The performance of our approach is dependant on the values chosen for its parameters. As such, we utilise the Simulated Annealing to discover optimal parameter configurations for pheromone-based load balancing technique for any given network schema. Once the parameter values are optimised for the given network topology automatically, we inspect improving the pheromone-based load balancing approach using robotic agents. As cyber-physical systems benefit from the heterogeneity of the hardware components, we introduce the use of pheromone signalling-based robotic guidance that integrates the robotic agents to the existing load balancing approach by guiding the robots into the uncovered area of the sensor field. As such, we maximise the service availability using the robotic agents as well as the sensor nodes

    Sophisticated Batteryless Sensing

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    Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

    High Performance Communication Framework for Mobile Sinks Wireless Sensor Networks

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    A wireless sensor networks typically consist of thousand of nodes and each node has limited power, processing and bandwidth resources. Harvesting advances in the past decade in microelectronics, sensing, wireless communications and networking, sensor networks technology is expected to have a significant impact on our lives in the twenty-first century. Proposed applications of sensor networks include environmental monitoring, natural disaster prediction and relief, homeland security, healthcare, manufacturing, transportation, and home appliances and entertainment. However, Communication is one of the major challenges in wireless sensor networks as it is the main source for energy depletion. Improved network lifetime is a fundamental challenge of wireless sensor networks. Many researchers have proposed using mobile sinks as one possible solution to improve the lifetime of wireless sensor networks. The reason is that the typical manyto- one communication traffic pattern in wireless sensor networks imposes a heavy forwarding load on the nodes close to the sinks. However, it also introduces many research challenges such as the high communication overhead for updating the dynamic routing paths to connect to mobile sinks and packet loss problems while transmitted messages to mobile sinks. Therefore, our goal is to design a robust and efficient routing framework for both non-geographic aware and geographic aware mobile sinks wireless sensor networks. In order to achieve this goal in non-geographic based mobile sinks wireless sensor networks, we proposed a spider-net zone routing protocol to improve network efficiency and lifetime. Our proposed routing protocol utilise spider web topology inspired by the way spiders hunt prey in their web to provide reliable and high performance data delivery to mobile sinks. For routing in geographic aware based mobile sinks wireless sensor networks, we proposed a fault-tolerant magnetic coordinate routing algorithm to allow these network sensors to take advantage of geographic knowledge to build a routing protocol. Our proposed routing algorithm incorporates a coordinated routing algorithm for grid based network topology to improve network performance. Our third contribution is a component level fault diagnosis scheme for wireless sensor networks. The advantage of this scheme, causal model fault diagnosis, is that it can "deeply understand" and express the relationship among failure behaviours and node system components through causal relations. The above contributions constitute a novel routing framework to address the routing challenges in mobile sinks wireless sensor networks, Our framework considers both geographic and non-geographic aware based sensor networks to achieve energy efficient, high performance and network reliability. We have analyzed the proposed protocols and schemes and evaluated their performances using analytical study and simulations. The evaluation was based on the most important metries in wireless sensor networks, such as: power consumption and average delay. The evaluation shows that our solution is more energy efficient, improves the network performance, and provides data reliability in mobile sinks wireless sensor networks
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