具有能量收集管理的无线传感器节点设计

传感器网络作为物联网的底层核心和感知前端,在实际应用中要求能够长时间连续工作,但是基于电池的有限能源供给严重限制了其灵活设计和长期部署,成为许多领域中影响其应用的重大挑战.能量收集技术使得节点可以从环境获取能量给自身充电,为延长网络寿命提供了一个有效的技术手段.本文设计了一种基于CC2650的无线传感器网络节点,结合基于LTC3331的多源环境能量收集技术,形成了一套完整的带能量补充的微功耗传感器节点.实验通过太阳能板作为能量收集前端进行验证,结果表明其可以实现环境能量的收集和累积存储并驱动节点运行.该节点体积小,自治工作时间长,可以广泛用于环境和结构监测等领域.     

RF energy harvesting: an analysis of wireless sensor networks for reliable communication

Wireless Networks - In this paper, we consider a wireless energy harvesting network consisting of one hybrid access point (HAP) having multiple antennas, and multiple sensor nodes each equipped...     

An efficient bandwidth allocation scheme for hierarchical cellular networks with energy harvesting: an actor-critic approach

In this paper, we propose an efficient bandwidth allocation strategy for multiclass services in hierarchical cellular networks that consist of an operation controller, several small-cell base stations (SBSs), and a number of mobile users. Each SBS is equipped with a finite-capacity battery that is regularly recharged by a solar harvester. We aims to find the optimal bandwidth allocation policy in order to enhance the network performance in terms of user satisfaction and energy efficiency under energy harvesting and bandwidth sharing constraints. Since the arrivals of harvested energy and traffic requests are unknown due to users’ mobility and stochastic request generation, it is necessary to design a learning framework for the controller in order to predict these dynamics through interaction with the environment. For this purpose, we first formulate the resource allocation problem as the framework of a Markov decision process, and then, we employ an actor-critic algorithm to find the optimal policy under which the controller can effectively allocate the limited bandwidth to the SBSs for their data transmissions. We evaluate the performance of the proposed scheme through comprehensive simulations with different settings, and show that the proposed bandwidth allocation scheme can enhance the network’s performance in the long run.     

Wireless underground sensor networks: Research challenges

This work introduces the concept of a Wireless Underground Sensor Network (WUSN). WUSNs can be used to monitor a variety of conditions, such as soil properties for agricultural applications and toxic substances for environmental monitoring. Unlike existing methods of monitoring underground conditions, which rely on buried sensors connected via wire to the surface, WUSN devices are deployed completely belowground and do not require any wired connections. Each device contains all necessary sensors, memory, a processor, a radio, an antenna, and a power source. This makes their deployment much simpler than existing underground sensing solutions. Wireless communication within a dense substance such as soil or rock is, however, significantly more challenging than through air. This factor, combined with the necessity to conserve energy due to the difficulty of unearthing and recharging WUSN devices, requires that communication protocols be redesigned to be as efficient as possible. This work provides an extensive overview of applications and design challenges for WUSNs, challenges for the underground communication channel including methods for predicting path losses in an underground link, and challenges at each layer of the communication protocol stack.     

Throughput-oriented MAC for mobile ad hoc networks: A game-theoretic approach

The conservative nature of the 802.11 channel access scheme has instigated extensive research whose goal is to improve the spatial reuse and/or energy consumption of a mobile ad hoc network. Transmission power control (TPC) was shown to be effective in achieving this goal. Despite their demonstrated performance gains, previously proposed power-controlled channel access protocols often incur extra hardware cost (e.g., require multiple transceivers). Furthermore, they do not fully exploit the potential of power control due to the heuristic nature of power allocation. In this paper, we propose a distributed, single-channel MAC protocol (GMAC) that is inspired by game theory. In GMAC, each transmitter computes a utility function that maximizes the link’s achievable throughput. The utility function includes a pricing factor that accounts for energy consumption. GMAC allows multiple potential transmitters to contend through an admission phase that enables them to determine the transmission powers that achieve the Nash equilibrium (NE). Simulation results indicate that GMAC significantly improves the network throughput over the 802.11 scheme and over another single-channel power-controlled MAC protocol (POWMAC). These gains are achieved at no extra energy cost. Our results also indicate that GMAC performs best under high node densities and large data packet sizes.     

Machine learning based optimal renewable energy allocation in sustained wireless sensor networks

Wireless Networks - The environmental energy harvesting is adjudged as a reliable solution to power the wireless nodes for infinite time and assuring uninterrupted operation of deployed network...     

Wireless sensor networks: leveraging the virtual infrastructure

Overlaying a virtual infrastructure over a physical network is a time-honored strategy for conquering scale. We design a general-purpose virtual architecture for wireless sensor networks and show that it can be leveraged by a number of different protocols.     

Wireless sensor and actor networks: research challenges

Wireless sensor and actor networks (WSANs) refer to a group of sensors and actors linked by wireless medium to perform distributed sensing and acting tasks. The realization of wireless sensor and actor networks (WSANs) needs to satisfy the requirements introduced by the coexistence of sensors and actors. In WSANs, sensors gather information about the physical world, while actors take decisions and then perform appropriate actions upon the environment, which allows a user to effectively sense and act from a distance. In order to provide effective sensing and acting, coordination mechanisms are required among sensors and actors. Moreover, to perform right and timely actions, sensor data must be valid at the time of acting. This paper explores sensor-actor and actor-actor coordination and describes research challenges for coordination and communication problems.     

Integration of IEEE 802.11 WLANs with IEEE 802.16-based multihop infrastructure mesh/relay networks: A game-theoretic approach to radio resource management

One of the promising applications of IEEE 802.16 (WiMAX)-based wireless mesh/relay networks is to provide infrastructure/backhaul support for IEEE 802.11-based mobile hotspots. In this article we present an architecture for integrating IEEE 802.11 WLANs with IEEE 802.16-based multihop wireless mesh infrastructure to relay WLAN traffic to the Internet. The major research issues in this integrated architecture are outlined and related work is reviewed. A game-theoretic model is developed for radio resource management in this integrated network architecture. In particular, a multiplayer bargaining game formulation is used for fair bandwidth allocation and optimal admission control of different types of connections (e.g., WLAN connections, relay connections, and connections from standalone subscriber stations) in an IEEE 802.16 base station/mesh router. Both connection-level and inconnection-level performances for this bandwidth management and admission control framework are presented     

On delay-minimized data harvesting with mobile elements in wireless sensor networks

We consider the problem of routing and scheduling a set of mobile elements that act as mechanical carriers of data, harvesting them from sensor nodes and delivering them to a sink. The objective is to minimize the data delivery latency. Most of the existing work has focused on designing delay minimizing routes for the mobile nodes by leveraging variants of the Traveling Salesman Problem (TSP). We show that TSP-based routes can lead to delay that is arbitrarily worse than the optimal. The main insight is that as data generation rates of sensors may vary, some sensors need to be visited more frequently than others. To that end, we consider a network with a single sink and develop a path splitter algorithm that “splits” a TSP-based route into several loops intersecting at the sink. Numerical results show that our algorithm can improve average delay by more than 40% in some instances while requiring a modest computational effort to modify the TSP-based route. The work is useful in prolonging sensor network lifetime and in relaying data in partitioned networks.     

An optimal resource control scheme under fidelity and energy constraints in sensor networks

To control congestion, either the traffic from sources should be “reduced” (traffic controlling) or the available resources should be “increased” (resource controlling). Compared to the wired and other wireless counterparts, wireless sensor networks usually have elastic resource availability, and the applications require a certain level of throughput called fidelity. As a result, resource control strategies cannot only alleviate congestion but also ensure the required fidelity level during congestion by accommodating higher incoming traffic. In this paper, we first attempt to formally define the resource control framework that adjusts the resource provisioning at the hotspot nodes during congestion. In an effort to find the optimal resource control under the fidelity and energy constraints, we present a resource increase and decrease algorithm called Early Increase/Early Decrease (EIED) that tries to adjust the effective channel capacity quickly to suit the incoming traffic volume in an energy-efficient manner, thereby increasing the fidelity level observed by the application. Under the energy-constrained optimization, we prove this algorithm incurs the lowest overhead of energy consumption for the given fidelity level that is required by the application. We also prove that the EIED algorithm performed in a distributed manner also lowers the energy consumption per packet at an end-to-end level. The effectiveness of the EIED algorithm is verified by simulations based on realistic sensor network configurations.

MANNA: a management architecture for wireless sensor networks

Wireless sensor networks (WSNs) are becoming an increasingly important technology that will be used in a variety of applications such as environmental monitoring, infrastructure management, public safety, medical, home and office security, transportation, and military. WSNs will also play a key role in pervasive computing where computing devices and people are connected to the Internet. Until now, WSNs and their applications have been developed without considering a management solution. This is a critical problem since networks comprising tens of thousands of nodes are expected to be used in some of the applications above. This article proposes the MANNA management architecture for WSNs. In particular, it presents the functional, information, and physical management architectures that take into account specific characteristics of this type of network. Some of them are restrict physical resources such as energy and computing power, frequent reconfiguration and adaptation, and faults caused by nodes unavailable. The MANNA architecture considers three management dimensions: functional areas, management levels, and WSN functionalities. These dimensions are specified to the management of a WSN and are the basis for a list of management functions. The article also proposes WSN models to guide the management activities and the use of correlation in the WSN management. This is a first step into a largely unexplored research area.     

Performance analysis of energy harvesting cognitive relay networks with primary interference

This paper investigates the outage performance of multihop energy harvesting cognitive relay network (EH-CRN), in which the secondary nodes are powered by dedicated power beacons based on the time splitting strategy. Assuming a multihop secondary network, we derive an analytical expression for the outage probability experienced by a secondary user by taking into account the effect of interference power from primary source. The developed outage probability model can be used to assess the impact of some key parameters on the reliability of the secondary user’s link in an EH-CRN. We then investigate the optimal location of the relay node in a one dimensional two-hop secondary network that minimizes the outage probability. Next, we study how the various system parameters such as energy harvesting efficiency, path loss exponent, harvest-to-transmit time duration ratio and transmit power from primary source affect the optimal relay location. The outage improvement achieved when the relay is placed at the optimum location is also investigated. Furthermore, the sensitivity of optimal relay location to the variations in position of the primary receiver is examined. Extensive simulation results are used to corroborate the analytical findings.     

Secure communication in untrusted relay selection networks with wireless energy harvesting

In this paper, we consider the secrecy performance of an energy-harvesting relaying system with Kth best partial relay selection where the communication of a multi-antenna source-destination pair is assisted via single-antenna untrusted relays. To protect confidential source messages from untrusted relays, transmit beamforming and destination jamming signals are used. The relays are energy-constrained nodes that use the power-splitting policy to harvest energy through the wireless signals from both the source and destination. For performance evaluation, closed-form expressions of the secrecy outage probability and average secrecy capacity (ASC) are derived for Nakagami-m fading channels. The analytical results are confirmed via Monte Carlo simulations. Numerical results provide valuable insights into the effect of various system parameters, such as relay location, number of relays, and power splitting ratio, on the secrecy performance. Specifically, the maximum ASC is achieved when the relay is located between the source and destination.

     

Wireless sensor networks for intrusion detection: packet traffic modeling

Performance evaluation of wireless sensor network (WSN) protocols requires realistic data traffic models since most of the WSNs are application specific. In this letter, a sensor network packet traffic model is derived and analyzed for intrusion detection applications. Presented analytical work is also validated using simulations.     

Wireless sensor networks: applications and challenges of ubiquitous sensing

Sensor networks offer a powerful combination of distributed sensing, computing and communication. They lend themselves to countless applications and, at the same time, offer numerous challenges due to their peculiarities, primarily the stringent energy constraints to which sensing nodes are typically subjected. The distinguishing traits of sensor networks have a direct impact on the hardware design of the nodes at at least four levels: power source, processor, communication hardware, and sensors. Various hardware platforms have already been designed to test the many ideas spawned by the research community and to implement applications to virtually all fields of science and technology. We are convinced that CAS will be able to provide a substantial contribution to the development of this exciting field.     

A queueing model of an energy harvesting sensor node with data buffering

Battery lifetime is a key impediment to long-lasting low power sensor nodes and networks thereof. Energy harvesting—conversion of ambient energy into electrical energy—has emerged as a viable alternative to battery power. Indeed, the harvested energy mitigates the dependency on battery power and can be used to transmit data. However, unfair data delivery delay and energy expenditure among sensors remain important issues for such networks. We study performance of sensor networks with mobile sinks: a mobile sink moves towards the transmission range of the different static sensor nodes to collect their data. We propose and analyse a Markovian queueing system to study the impact of uncertainty in energy harvesting, energy expenditure, data acquisition and data transmission. In particular, the energy harvesting sensor node is described by a system with two queues, one queue corresponding to the battery and the other to the data buffer. We illustrate our approach by numerical examples which show that energy harvesting correlation considerably affects performance measures like the mean data delay and the effective data collection rate.