72 research outputs found
Design and comparative analysis of single-path and epidemic approaches to information and energy management in wireless sensor networks
No full textIntelligent energy management is a key challenge in Wireless Sensor Networks. The choice of an appropriate routing algorithm constitutes a critical factor, especially in unstructured networks where, due to their dynamic nature, a reactive routing protocol is necessary. Such networks often favour packet flooding to fulfil this need. One such algorithm is IDEALS, a technique proposed in the literature, which balances energy consumed with information delivered. This paper evaluates the use of a single-path solution with IDEALS to increase efficiency. Simulation results comparing the two approaches show that the single-path algorithm outperforms flooding in terms of energy consumption for any network size. Furthermore the benefit of IDEALS is preserved as its combination with the single-path algorithm maximises information throughput
Energy Controlled Reporting for Industrial Monitoring Wireless Sensor Networks
No full textThis paper proposes a technique to extend the lifetime of a wireless sensor network through a combination of energy management and information control. Each sensor node locally decides its own network involvement as a result of balancing available energy resources with the information content of each packet. The information content is ascertained through a system of rules which describe prospective events in the sensed environment. These rules specify when reporting should occur, and the importance of each packet. While energy management and information content have been individually considered elsewhere, our technique utilizes a combination of both to incur greater benefits. Results obtained from a simulation depicting an industrial Wireless Sensor Network (WSN) monitoring a water pumping station have shown that a considerable increase in lifetime and connectivity can be obtained. In addition, when coupled with energy harvesting, our technique permits sustained operation
Energy Devices for Sensor Networks: Properties for Simulation and Deployment
No full textRecent developments in microcontroller, radio transceiver, and energy harvesting device design now permit wireless sensor nodes to operate indefinitely from power scavenged from their environment. Many algorithms for conventional sensor networks assume that nodes run directly from non-rechargeable batteries and therefore attempt to conserve energy rather than carefully exploiting it when available. Effectively incorporating energy harvesting into wireless sensor network deployments, and simulations, poses unique problems related to energy-awareness and performance optimization. This paper presents a characterization of energy devices for sensor nodes and outlines their use in simulation and deployment. A case study of an energy-aware sensor node operating from a photovoltaic module and supercapacitor is explored. This paper also presents a modular software and hardware architecture which encourages energy-aware algorithm design and allows the automatic configuration of energy-aware sensor nodes
A practical self-powered sensor system with a tunable vibration energy harvester
No full textVibration energy harvesters are typically narrow-band devices that are designed to operate at line frequency (or a multiple thereof), hence are only suitable for deployment on electrical machinery powered from the grid. Tunable vibration energy harvesters offer the potential to harvest energy in a wider range of applications but have, to date, only been demonstrated in the lab and have not matched the vibration characteristics found on real machines. This paper reports on the considerations, design, and results from deployment of a tunable vibration energy harvesting system aimed at a real application – wireless monitoring of a vehicle ferry engine
Energy managed reporting for wireless sensor networks
No full textIn this paper, we propose a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its individual network involvement based on its own energy resources and the information contained in each packet. The information content is ascertained through a system of rules describing prospective events in the sensed environment, and how important such events are. While the packets deemed most important are propagated by all sensor nodes, low importance packets are handled by only the nodes with high energy reserves. Results obtained from simulations depicting a wireless sensor network used to monitor pump temperature in an industrial environment have shown that a considerable increase in the network lifetime and network connectivity can be obtained. The results also show that when coupled with a form of energy harvesting, our technique can enable perpetual network operatio
Energy Harvesting and Management for Wireless Autonomous Sensors
No full textWireless autonomous sensors that harvest ambient energy are attractive solutions, due to their convenience and economic benefits. A number of wireless autonomous sensor platforms which consume less than 100?W under duty-cycled operation are available. Energy harvesting technology (including photovoltaics, vibration harvesters, and thermoelectrics) can be used to power autonomous sensors. A developed system is presented that uses a photovoltaic module to efficiently charge a supercapacitor, which in turn provides energy to a microcontroller-based autonomous sensing platform. The embedded software on the node is structured around a framework in which equal precedent is given to each aspect of the sensor node through the inclusion of distinct software stacks for energy management and sensor processing. This promotes structured and modular design, allowing for efficient code reuse and encourages the standardisation of interchangeable protocols
Iterative Decoding for Redistributing Energy Consumption in Wireless Sensor Networks
No full textIn this paper, we propose a method for desirably redistributing a wireless sensor network's energy consumption from its sensor nodes (which may have scarce energy resources obtained through energy harvesting, for example) to its central node (which often has an abundant energy resource, such as the mains). At the cost of increasing the central node's decoding complexity, our method facilitates (1) a significant reduction in the number of times the sensor nodes are required to retransmit data owing to transmission errors and/or (2) a reduction of up to 3.99 dB in the sensor node's total transmit energy consumption. We show that our approach can reduce the overall energy consumption of transmitting sensor nodes by more than 20% in practice
Internet of MIMO things: UAV-assisted wireless-powered networks for Future Smart cities
No full textWidespread and pervasive IoT adoption is threatened by finite-capacity batteries of wireless devices. To mitigate this issue, energy harvesting (EH) and wireless power transfer (WPT), in addition to energy-efficient communication techniques, have been widely explored. Although these efforts achieved longevity to some extent, ever-evolving IoT services seek fully autonomous things without energy constraints. To meet this demand and relieve the ongoing networking challenges, we propose a new concept called the Internet of MIMO Things (IoMIMO). The IoMIMO envisions a self-sufficient architecture that adopts only single- and double-hop energy and data transitions to enable efficient energy sharing and reduced data traffic in networks. In particular, single-hops are performed by hybrid access points (HAPs), while relaying via double-hops are actuated by unmanned aerial vehicles (UAVs). The HAPs will handle multiple-input and multiple-output (MIMO) of energy and data, and coordinate their transitions between the network components in a concurrent and automated manner. Benefiting from the recent advances in multi-source EH, WPT, and UAVs, the IoMIMO can fulfill Smart City services without being limited by energy and networking challenges. Device types specialized for the IoMIMO, and their operation modes are evaluated in a simple network scenario to clearly explain the principles and the potential benefits of the envisioned concept. Future research directions are also identified to ease the realization of such a next-generation networking architecture
Adaptive sampling in context-aware systems: a machine learning approach
No full textAs computing systems become ever more pervasive, there is an increasing need for them to understand and adapt to the state of the environment around them: that is, their context. This understanding comes with considerable reliance on a range of sensors. However, portable devices are also very constrained in terms of power, and hence the amount of sensing must be minimised. In this paper, we present a machine learning architecture for context awareness which is designed to balance the sampling rates (and hence energy consumption) of individual sensors with the significance of the input from that sensor. This significance is based on predictions of the likely next context. The architecture is implemented using a selected range of user contexts from a collected data set. Simulation results show reliable context identification results. The proposed architecture is shown to significantly reduce the energy requirements of the sensors with minimal loss of accuracy in context identification
Energy- and information-managed wireless sensor networks: modelling and simulation
No full textWireless Sensor Networks (WSNs) allow the remote and distributed monitoring of parameters in their deployed environment. WSNs are receiving increasing research interest, due to their ability to enable a wide range of applications, and their potential to have a major impact on ubiquitous computing. Many research challenges are encountered in retaining a useful network lifetime under constraints imposed by the limited energy reserves that are inherent in the small, locally-powered sensor nodes. This research addresses some of these challenges through the development and evaluation of energy- and information-managed algorithms leading to increased network lifetime.The first contribution of this research is the development of an Information manageD Energy-aware ALgorithm for Sensor networks with Rule Managed Reporting (IDEALS/RMR). IDEALS/RMR is an application-independent, localised system to control and manage the degradation of a network through the positive discrimination of packets. This is achieved by the novel combination of energy management (through IDEALS) and information management (through RMR) which increases the network lifetime at the possible expense of often trivial data. IDEALS/RMR is particularly suited to applications where sensor nodes are small, energy constrained, embedded devices particularly those that feature energy harvesting) that are required to report data in an unassisted fashion.The second contribution of this research is the analysis of various environmental and physical aspects of WSNs, and the effect that they have on the operation of nodes and networks. These aspects include energy components (stores, sources and consumers), sensing devices, wireless communication, and timing; these aspects are independently modelled and, through simulation, their effect on the operation of the network is quantified.The third contribution of this research is the evaluation of IDEALS/RMR using a simulator that has been specifically developed to integrate both the proposed environmental and physical models, and a novel node architecture that facilitates structured software design. A scenario depicting the use of a WSN to monitor pump temperature in a water pumping station is simulated, and highlights the benefits of the developed algorithms
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