A game-theoretic approach to decentralized optimal power allocation for cellular networks

The rapidly growing demand for wireless communication makes efficient power allocation a critical factor in the network??s efficient operation. Power allocation in cellular networks with interference, where users are selfish, has been recently studied by pricing methods. However, pricing methods do not result in efficient/optimal power allocations for such systems for the following reason. Because of interference, the communication between the Base Station (BS) and a given user is affected by that between the BS and all other users. Thus, the power vector consisting of the transmission power in each BS-user link can be viewed as a public good which simultaneously affects the utilities of all the users in the network. It is well known (Mas-Colell et al., Microeconomic Theory, Oxford University Press, London, 2002, Chap. 11.C) that in public good economies, standard efficiency theorems on market equilibrium do not apply and pricing mechanisms do not result in globally optimal allocations. In this paper we study power allocation in the presence of interference for a single cell wireless Code Division Multiple Access (CDMA) network from a game theoretic perspective. We consider a network where each user knows only its own utility and the channel gain from the base station to itself. We formulate the uplink power allocation problem as a public good allocation problem. We present a game form the Nash Equilibria of which yield power allocations that are optimal solutions of the corresponding centralized uplink network.     

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.     

Throughput maximization in electromagnetic energy harvesting cognitive radio sensor networks

In the near future, billions of wireless devices are expected to be operational. To enable the required machine to machine communications, two major problems must be addressed. How to obtain the required spectrum efficiency, and how to deliver the required power to these devices. The most promising answers to these questions are cognitive radio and energy harvesting, respectively. Energy harvesting enables deployment of sensors and devices without having to worry about their battery lifetime. Cognitive radio increases the utilization of spectrum by accessing unused spectrum dynamically. Energy harvesting from electromagnetic waves is suitable for these low power, low cost devices used in machine to machine communications because only minimal additional hardware is required for such energy harvesting. With this idea as the starting point, we first present an analysis on how much throughput can be obtained from a cognitive, electromagnetic energy harvesting wireless network. Then, we show when and how cooperation among network nodes may increase performance. We believe that our results will provide insight for the development of future cooperative cognitive energy harvesting networks. Copyright © 2015 John Wiley & Sons, Ltd.     

基于蚁群算法的传感器网络节点部署设计

传感器网络节点的人工部署是一类重要的应用方式,为了解决传感器网络节点部署位置的优化问题,提出了基于蚁群算法的传感器网络节点部署设计算法Easidesign.针对蚁群算法在解决传感器节点部署的扩展性问题,提出了贪婪策略、额外信息素蒸发机制等改进方法.Easidesign算法最大特点是充分考虑到当sink节点处于不同位置时对传感器节点部署设计的影响,并且能保证每个部署的节点与sink的连通性,因此Easidesign具有很大的实用价值.通过大量仿真与实验,不仅证明了算法的有效性,而且给出了如何设计算法中的关键参数等问题.     

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...     

A power management system for energy harvesting and wireless sensor networks application based on a novel charge pump circuit

Energy Harvesting circuits are developed as an alternative solution to supply energy to autonomous sensor nodes in Wireless Sensor Networks. In this context, this paper presents a micro-power management system for multi energy sources based on a novel design of charge pump circuit to allow the total autonomy of self-powered sensors. This work proposes a low-voltage and high performance charge pump (CP) suitable for implementation in standard complementary metal oxide semiconductor (CMOS) technologies. The CP design was implemented using Cadence Virtuoso with AMS 0.35μm CMOS technology parameters. Its active area is 0.112 mm². Consistent results were obtained between the measured findings of the chip testing and the simulation results. The circuit can operate with an 800 mV supply and generate a boosted output voltage of 2.835 V with 1 MHz as frequency.     

A novel efficient clustering protocol for energy harvesting in wireless sensor networks

Wireless Networks - The utilization of wireless sensor networks (WSNs) is proliferating in our daily life. It depends on the environmental monitoring such as weather tracking, battled field, etc....     

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 multimedia sensor networks: A survey

In recent years, the growing interest in the wireless sensor network (WSN) has resulted in thousands of peer-reviewed publications. Most of this research is concerned with scalar sensor networks that measure physical phenomena, such as temperature, pressure, humidity, or location of objects that can be conveyed through low-bandwidth and delay-tolerant data streams. Recently, the focus is shifting toward research aimed at revisiting the sensor network paradigm to enable delivery of multimedia content, such as audio and video streams and still images, as well as scalar data. This effort will result in distributed, networked systems, referred to in this paper as wireless multimedia sensor networks (WMSNs). This article discusses the state of the art and the major research challenges in architectures, algorithms, and protocols for wireless multimedia sensor networks. Existing solutions at the physical, link, network, transport, and application layers of the communication protocol stack are investigated. Finally, fundamental open research issues are discussed, and future research trends in this area are outlined.     

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.     

Cross‐layer optimized routing in wireless sensor networks with duty cycle and energy harvesting

In this paper, we propose a cross‐layer optimized geographic node‐disjoint multipath routing algorithm, that is, two‐phase geographic greedy forwarding plus. To optimize the system as a whole, our algorithm is designed on the basis of multiple layers' interactions, taking into account the following. First is the physical layer, where sensor nodes are developed to scavenge the energy from environment, that is, node rechargeable operation (a kind of idle charging process to nodes). Each node can adjust its transmission power depending on its current energy level (the main object for nodes with energy harvesting is to avoid the routing hole when implementing the routing algorithm). Second is the sleep scheduling layer, where an energy‐balanced sleep scheduling scheme, that is, duty cycle (a kind of node sleep schedule that aims at putting the idle listening nodes in the network into sleep state such that the nodes will be awake only when they are needed), and energy‐consumption‐based connected k‐neighborhood is applied to allow sensor nodes to have enough time to recharge energy, which takes nodes' current energy level as the parameter to dynamically schedule nodes to be active or asleep. Third is the routing layer, in which a forwarding node chooses the next‐hop node based on 2‐hop neighbor information rather than 1‐hop. Performance of two‐phase geographic greedy forwarding plus algorithm is evaluated under three different forwarding policies, to meet different application requirements. Our extensive simulations show that by cross‐layer optimization, more shorter paths are found, resulting in shorter average path length, yet without causing much energy consumption. On top of these, a considerable increase of the network sleep rate is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

能量收集多跳D2D无线传感网络中的中继选择算法

针对无线功率传输技术的能量收集效率有限造成信噪比下降进而引发通信中断率增加的问题,在能量收集多跳D2D(Device to Device)无线传感网络中,提出一种基于改进K-means聚类的中继选择方法。首先,推导得到能量收集下的信噪比因子,使其作为K-means聚类特征。然后,利用最小欧氏距离原则得到距离聚类中心最近的实际节点的位置。最后,根据距离重排序得到中继节点,形成从源节点到目的节点的通信链路。仿真实验结果表明,相比最短路径算法和随机中继协作方案,所提出的改进算法链路信噪比更大,能够减小通信中断率,具有更好的中继性能。     

A non-cooperative game-theoretic approach to channel assignment in multi-channel multi-radio wireless networks

Channel assignment in multi-channel multi-radio wireless networks poses a significant challenge due to scarcity of number of channels available in the wireless spectrum. Further, additional care has to be taken to consider the interference characteristics of the nodes in the network especially when nodes are in different collision domains. This work views the problem of channel assignment in multi-channel multi-radio networks with multiple collision domains as a non-cooperative game where the objective of the players is to maximize their individual utility by minimizing its interference. Necessary and sufficient conditions are derived for the channel assignment to be a Nash Equilibrium (NE) and efficiency of the NE is analyzed by deriving the lower bound of the price of anarchy of this game. A new fairness measure in multiple collision domain context is proposed and necessary and sufficient conditions for NE outcomes to be fair are derived. The equilibrium conditions are then applied to solve the channel assignment problem by proposing three algorithms, based on perfect/imperfect information, which rely on explicit communication between the players for arriving at an NE. A no-regret learning algorithm known as Freund and Schapire Informed algorithm, which has an additional advantage of low overhead in terms of information exchange, is proposed and its convergence to the stabilizing outcomes is studied. New performance metrics are proposed and extensive simulations are done using Matlab to obtain a thorough understanding of the performance of these algorithms on various topologies with respect to these metrics. It was observed that the algorithms proposed were able to achieve good convergence to NE resulting in efficient channel assignment strategies.     

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...     

A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks

Energy balancing is an effective technique in enhancing the lifetime of a wireless sensor network (WSN). Specifically, balancing the energy consumption among sensors can prevent losing some critical sensors prematurely due to energy exhaustion so that the WSN's coverage can be maintained. However, the heterogeneous hostile operating conditions—different transmission distances, varying fading environments, and distinct residual energy levels—have made energy balancing a highly challenging task. A key issue in energy balancing is to maintain a certain level of energy fairness in the whole WSN. To achieve energy fairness, the transmission load should be allocated among sensors such that, regardless of a sensor's working conditions, no sensor node should be unfairly overburdened. In this paper, we model the transmission load assignment in WSN as a game. With our novel utility function that can capture realistic sensors’ behaviors, we have derived the Nash equilibrium (NE) of the energy balancing game. Most importantly, under the NE, while each sensor can maximize its own payoff, the global objective of energy balancing can also be achieved. Moreover, by incorporating a penalty mechanism, the delivery rate and delay constraints imposed by the WSN application can be satisfied. Through extensive simulations, our game theoretic approach is shown to be effective in that adequate energy balancing is achieved and, consequently, network lifetime is significantly enhanced. Copyright © 2012 John Wiley & Sons, Ltd.     

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     

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.