Energy-efficient resource allocation model for device-to-device communication in 5G wireless personal area networks

In general, there are several many devices that can overload the network and reduce performance. Devices can minimize interference and optimize bandwidth usage by using directional antennas and by avoiding overlapping communication ranges. In addition, devices need to carefully manage their use of resources, such as bandwidth and energy. Bandwidth is limited in wireless personal area networks (WPANs), so devices need to carefully select which data to send and receive. In this paper, an intelligent performance analysis of energy-efficient resource optimization model has been proposed for device-to-device (D2D) communication in fifth-generation (5G) WPAN. The proposed energy-efficient resource allocation in D2D communication is important because it helps reduce energy consumption and extend the lifespan of devices that are communicating with each other. By allocating resources in an efficient manner, communication between two devices can be optimized for maximum efficiency. This helps reduce the amount of energy needed to power the communication, as well as the amount of energy needed to power the device that is communicating with another device. Additionally, efficient resource allocation helps reduce the overall cost of communication, as the use of fewer resources results in a lower overall cost. The proposed efficient resource allocation helps reduce the environmental impact of communication, as less energy is used for communication. The proposed energy-efficient resource allocation model (EERAM) has reached 92.97% of energy allocation, 88.72% of power allocation, 87.79% of bandwidth allocation, 87.93% of spectrum allocation, 88.43% of channel allocation, 25.47% of end-to-end delay, 94.33% of network data speed, and 90.99% of network throughput.     

Energy-efficient DSPs for wireless sensor networks

There are many new challenges to be faced in implementing signal processing algorithms and designing energy-efficient DSPs for microsensor networks. We study system partitioning of computation to improve the energy efficiency of a wireless sensor networking application. We explore system partitioning between the sensor cluster and the base station, employing computation-communication tradeoffs to reduce energy dissipation. Also we show that system partitioning of computation within the cluster can also improve the energy efficiency by using dynamic voltage scaling (DVS)     

基于高能效RSSI的WSN定位

传感器自我定位是无线传感器网络中许多和定位有关的技术之一。虽然定位的主要目的是提高定位精度,但是能量消耗对定位提出了新的挑战。文中在考虑估计误差的同时,研究了最优功率分配的参考节点在一定意义上的最小能量消耗。为了对一个参考节点和一个利用了接收信号强度指示器(RSSI)的未知节点之间的相对距离有一个更好的估计,把接收到的信标的平均能量作为一种新的决策度量。基于此得到一个作为精度参数的平方位置误差和一个提高定位性能的优化问题。仿真结果表明,通过优化传输功率的配置可以实现能耗的大幅减少。     

面向全球能源互联网的天空地协同卫星通信网络架构

全球能源互联网的监测、调度、授时、同步及定位等业务均需要能提供广域覆盖、泛在灵活接入服务的可靠通信网络。针对该需求,首先分析阐述全球能源互联背景下各种新型业务需求及其特点,并总结各种业务的共性数据特征;然后论述卫星通信技术的特点以及与全球能源互联网业务特点与数据传输需求的高度契合性,最终提出融合卫星通信网络的全球能源互联网天空地协同网络体系架构。其以IP技术为基础,各层网络通过星间、星地、星空、空空、空地以及地面有线、无线链路连接起来,构建全球覆盖的一体化网络体系。     

低轨卫星通信网络中改进的综合加权接入算法

针对用户终端有效与可靠接入低轨卫星通信网络的需求,基于现有的接入算法,综合考虑了卫星对用户终端的覆盖时间、卫星空闲信道数以及卫星接收信号的信噪比因素,提出了一种改进的综合加权接入算法,对该算法的目标函数和参数进行了设计与计算.仿真结果表明,采用改进的综合加权接入算法,新呼叫阻塞率和强制中断率等性能都得到了明显的改善.     

Energy-efficient relaying in wireless networks

It has been shown that there is a certain distance beyond which multi-hop data transmission is more energy-efficient than direct transmission in wireless networks. In this letter we investigate the effects of noise level on the minimal energy-efficient relay distance. We find that under optimal conditions (i.e., optimal packet length and transmit power level) there is an inverse power-law relation between the noise level and the minimal energy-efficient relay distance.     

Energy-efficient detection in sensor networks

There is significant interest in battery-powered sensor networks to be used for detection in a wide variety of applications, from surveillance and security to health and environmental monitoring. Severe energy and bandwidth constraints at each sensor node demand system-level approaches to design that consider detection performance jointly with system-resource constraints. Our approach is to formulate detection problems with constraints on the expected cost arising from transmission (sensor nodes to a fusion node) and measurement (at each sensor node) to address some of the system-level costs in a sensor network. For a given resource constraint, we find that randomization over the choice of measurement and over the choice of when to transmit achieves the best performance (in a Bayesian, Neyman-Pearson, and Ali-Silvey sense). To facilitate design, we describe performance criteria in the send/no-send transmission scenario, where the joint optimization over the sensor nodes decouples into optimization at each sensor node.     

Energy-efficient location services for mobile ad hoc networks

Location-based routing protocols are stateless since they rely on position information in forwarding decisions. However, their efficiency depends on performance of location services which provide the position information of the desired destination node. Several location service schemes have been proposed, but the most promising among them, hierarchical hashing-based protocols, rely on intuitive design in the published solutions. In this paper, we provide full analysis of the efficiency of routing in hierarchical hashing-based protocols as a function of the placement of the routers. Based on the theoretical analysis of the gain and costs of the query and reply routing, we propose a novel location service protocol that optimizes the distance traveled by the location update and query packets and, thus, reduces the overall energy cost. These gains are further increased in the second presented protocol by the optimal location of servers that we established through analysis of geometrical relationships between nodes and location servers. Simulation results demonstrate that the proposed protocols achieve around 30–35% energy efficiency while improving or maintaining the query success rate in comparison to the previously proposed algorithms.     

Energy-efficient node deployment strategy for wireless sensor networks

To balancing energy consumption in wireless sensor networks, we proposed a fixed time interval node broadcasting scheme under variational acceleration straight-line movement model. Simulation results show that the approach proposed in this paper has a superior performance on energy consumption balance compared to uniform broadcasting methods.     

Energy-efficient routing for correlated data in wireless sensor networks

In this paper, we investigate the reduction in the total energy consumption of wireless sensor networks using multi-hop data aggregation by constructing energy-efficient data aggregation trees. We propose an adaptive and distributed routing algorithm for correlated data gathering and exploit the data correlation between nodes using a game theoretic framework. Routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function that is used for the proposed routing algorithm takes into account energy, interference and in-network data aggregation. The iterative algorithm is shown to converge in a finite number of steps. Simulations results show that multi-hop data aggregation can significantly reduce the total energy consumption in the network.     

Energy-efficient protocols for wireless networks with adaptive MIMO capabilities

Transmission power control has been used in wireless networks to improve the channel reuse and/or reduce energy consumption. It has been mainly applied to single-input single-output (SISO) systems, where each node is equipped with a single antenna. In this paper, we propose a power-controlled channel access protocol for MIMO-capable wireless LANs with two antennas per node. Our protocol, called E-BASIC, extends the classic CSMA/CA access scheme by allowing for dynamic adjustment of the transmission mode and the transmission power on a per-packet basis so as to minimize the total energy consumption. By transmission mode we mean one of the four possible transmit/receive antenna configurations: 1 × 1 (SISO), 2 × 1 (MISO), 1 × 2 (SIMO), and 2 × 2 (MIMO). Depending on the transmitter-receiver distance, any of the four modes can be the optimal one in terms of minimizing the total energy consumption. We study the performance of E-BASIC in both ad hoc and access point topologies. We also incorporate E-BASIC in the design of a power-aware routing (PAR) scheme that selects minimum-energy end-to-end paths. Our adaptive designs are first conducted assuming fixed-rate transmission, but later extended to multi-rate systems. To account for the energy-throughput tradeoff in our designs, we impose a constraint on the average packet delivery time. Simulations indicate that the proposed adaptations achieve a significant reduction in the overall energy consumption relative to non-adaptive MIMO systems.     

Energy-efficient neighbor discovery protocol for mobile wireless sensor networks

Low energy consumption is a critical design requirement for most wireless sensor network (WSN) applications. Due to minimal transmission power levels, time-varying environmental factors and mobility of nodes, network neighborhood changes frequently. In these conditions, the most critical issue for energy is to minimize the transactions and time consumed for neighbor discovery operations. In this paper, we present an energy-efficient neighbor discovery protocol targeted at synchronized low duty-cycle medium access control (MAC) schemes such as IEEE 802.15.4 and S-MAC. The protocol effectively reduces the need for costly network scans by proactively distributing node schedule information in MAC protocol beacons and by using this information for establishing new communication links. Energy consumption is further reduced by optimizing the beacon transmission rate. The protocol is validated by performance analysis and experimental measurements with physical WSN prototypes. Experimental results show that the protocol can reduce node energy consumption up to 80% at 1–3 m/s node mobility.     

WSN中能量有效分簇多跳路由算法

针对现有无线传感器网络(WSN)分簇路由算法存在的能耗不均衡问题,提出一种能量有效分簇多跳路由算法,该算法包括两个方面:一是选举簇首时引入簇内平均剩余能量因子,根据上一轮结束后簇内各节点剩余能量和簇内节点的平均剩余能量的比值更新簇首在所有节点中所占的百分比;二是要求簇首根据MTE多跳路由协议与基站通信,从而均衡WSN整...     

Energy-efficient cluster-based artificial intelligence routing for wireless sensor networks

Artificial intelligence (AI)-based wireless sensor network technology is the future of advancement for real-time applications. With AI wireless sensor network technology, it is possible to collect data from any environment, analyze in real time, and use it to optimize processes and operations. AI wireless sensor network technology provides an unprecedented level of accuracy as well as the ability to detect even the slightest changes in a given environment. The AI-based approach uses clustering-based techniques with self-organizing map (SOM) for energy conservation in resource-constrained networks. By clustering the network, it becomes more energy efficient, as data can be shared among members of a cluster without needing to be transmitted across multiple nodes. The proposed AI cluster-based routing approach outperforms in terms of energy consumption and computational challenges of the network. The results obtained demonstrate the proposed approach to achieve lower energy consumption than the existing algorithms while providing the same level of performance in terms of throughput and latency, as well as a comparison with traditional justification techniques.     

Improving communication energy efficiency in wireless networks powered by Renewable energy sources

Energy efficiency is an important issue in wireless networks where the nodes are powered by batteries. In this work, we analyze the energy consumption in one-transmitter-multiple-receiver communication and develop scheduling schemes to improve energy efficiency at the transmitter. Our focus is on systems powered by a renewable energy source such as solar power. We consider an environment where both energy and time to access the wireless channel and transmit data are limited, and data destined for different receivers have different values and incur different energy costs. We present optimal scheduling algorithms that selectively transmit data at calculated rates so that the throughput or the total transmission value is maximized under given time limits and energy constraints.     

Energy-efficient resource allocation scheme for device-to-device communication underlaying LTE-A uplink

To cope with the co-channel interference between cellular links and device-to-device (D2D) links concurrently transmitting with the long term evolution-advanced (LTE-A) uplink spectrum,a joint resource allocation scheme was pro-posed to maximize the global energy efficiency of D2D links.The above problem can be decomposed into the power control subproblem and the channel assignment subproblem.Specifically,the power control subproblem can be optimally solved with the help of Dinkelbach method and Lagrange duality.Based on the above results,the channel assignment subproblem turns out to be the set packing problem which was generally NP-hard problem,Therefore,a heuristic algo-rithm was further devised to achieve a tradeoff between performance and complexity.Simulations show that the proposed joint resource allocation scheme outperforms the ones where only single resource variable is optimized,and it achieves the polynomial-time complexity at only minor performance loss when compared to the global optimum.     

Energy-efficient dual-port cache architecture with improved performances

Low leakage current and area-efficient dual-port cache design, which uses isolation nodes and local sense amplifiers to facilitate dual-port accesses without duplicating the bit lines for the second port, is presented. Compared with conventional hardwired dual-port cache designs, the average bit line leakage current can be reduced by 50%     

Energy-efficient information routing in sensor networks for robotic target tracking

Target tracking problems have been studied for both robots and sensor networks. However, existing robotic target tracking algorithms require the tracker to have access to information-rich sensors, and may have difficulty recovering when the target is out of the tracker??s sensing range. In this paper, we present a target tracking algorithm that combines an extremely simple mobile robot with a networked collection of wireless sensor nodes, each of which is equipped with an unreliable, limited-range, boolean sensor for detecting the target. The tracker maintains close proximity to the target using only information sensed by the network, and can effectively recover from temporarily losing track of the target. We present two algorithms that manage message delivery on this network. The first, which is appropriate for memoryless sensor nodes, is based on dynamic adjustments to the time-to-live (TTL) of transmitted messages. The second, for more capable sensor nodes, makes message delivery decisions on-the-fly based on geometric considerations driven by the messages?? content. We present an implementation along with simulation results. The results show that our system achieves both good tracking precision and low energy consumption.     

Energy-efficient cluster-based cooperative FEC in wireless networks

In this article, we introduce a novel link layer cooperation technique in noisy wireless networks to improve overall system throughput and reliability, and to reduce the cost of retransmission and energy consumption. Under a cluster-based network design, Chase combining (Chase, IEEE Transactions on Communications 33(5):385–393, 1985) is used together with FEC to improve the link layer reliability. This approach is different from how combining is used in the conventional hybrid ARQ, which is in a sequential way. The analytical results and the simulations show that with the cooperation of nodes in a clustering network, the link reliability will be greatly improved with the same power consumption. We also show that not only transmission power is greatly reduced, but also the aggregate power consumption for a successful transmission and reception.     

Energy-efficient power allocation for NOMA heterogeneous networks with imperfect CSI

In this paper, an optimal user power allocation scheme is proposed to maximize the energy efficiency for downlink non-orthogonal multiple access (NOMA) heterogeneous networks (HetNets). Considering channel estimation errors and inter-user interference under imperfect channel state information (CSI), the energy efficiency optimization problem is formulated, which is non-deterministic polynomial (NP)-hard and non-convex. To cope with this intractable problem, the optimization problem is converted into a convex problem and address it by the Lagrangian dual method. However, it is difficult to obtain closed-form solutions since the variables are coupled with each other. Therefore, a Lagrangian and sub-gradient based algorithm is proposed. In the inner layer loop, optimal powers are derived by the sub-gradient method. In the outer layer loop, optimal Lagrangian dual variables are obtained. Simulation results show that the proposed algorithm can significantly improve energy efficiency compared with traditional power allocation algorithms.