Energy Efficient Deployment Research Articles

Online energy-efficient deployment based on equivalent continuous DFS for large-scale web cluster

How to dynamically deploy web cluster so as to reduce energy consumption and mean-while satisfy performance requirements is an urgent problem to be resolved. In this paper, we propose an online energy-efficient deployment strategy to minimize cluster’s energy consumption on the premise of guaranteeing server’s CPU utilization equal to a given target value. It adopts CPU equivalent continuous Dynamic Frequency Scaling to reduce server power. First, we propose an approach of CPU utilization guarantee. Then, we describe cluster’s energy-efficient deployment problem as a constrained Mixed Integer Programming problem. Compared with similar works, our variable definition manner can reduce variable number significantly. Finally, we propose an improved differential evolution algorithm to solve the problem. Because of few variable number and high solving efficiency, even if applied to large-scale clusters, our strategy can still dynamically deploy the cluster online. Evaluation results verify the feasibility and effectiveness of the proposed deployment strategy.

Design of Probability Density Function Targeting Energy Efficient Network for Coalition Based WSNs

Energy consumption is one of the important issues in wireless sensor network that rely on non chargeable batteries for power. Also, the sensor network has to maintain a desired sensing coverage area along with periodically sending of the sensed data to the base station. Therefore, coverage and the lifetime are the two important issues that need to be addressed. Effective deployment of wireless sensors is a major concern as the coverage and lifetime of any wireless sensor network depends on it. In this paper, we propose the design of a Probability Density Function (PDF) targeting the desired coverage, and energy efficient node deployment scheme. The suitability of the proposed PDF based node distribution to model the network architecture considered in this work has been analyzed. The PDF divides the deployment area into concentric coronas and provides a probability of occurrence of a node within any corona. Further, the performance of the proposed PDF is evaluated in terms of the coverage, the number of transmissions of packets and the lifetime of the network. The scheme is compared with the existing node deployment schemes based on various distributions. The percentage gain of the proposed PDF based node deployment is 32\(\%\) more than that when compared with the existing schemes. Thus, the simulation results obtained confirm the schemes superiority over the other existing schemes.

User Association in Energy-Aware Dense Heterogeneous Cellular Networks

Mobile traffic demand has been increasing exponentially over the last few years and forecasts show that this trend will continue in the foreseeable future. As a result, operators are forced to densify and upgrade their networks to meet this demand. This has created concerns, such as increasing greenhouse gas emissions, high capital expenditures, and associated energy costs. This paper uses tools from stochastic geometry to analyze and formulate energy-efficient deployment strategies for multi-tier heterogeneous networks (HetNets) using various user association schemes. We use simple approximations to combine the required base station (BS) density and associated transmit power per tier subject to both coverage probability and average user rate constraints. In this paper, this combination is called the deployment factor and it can be expressed in closed form for unbiased HetNets. We then formulate area power consumption (APC) minimization framework, which optimizes the deployment factor to derive specific optimal BS density and transmit power values. Furthermore, we perform a comprehensive study of the effect of biasing on the APC performance of biased HetNets. Our results show that for HetNets using the maximum average-biased-received-power association scheme, significant energy savings are possible with appropriate biasing.

Key design of driving industry 4.0: joint energy-efficient deployment and scheduling in group-based industrial wireless sensor networks

In the Industry 4.0 framework based on IoT and smart manufacturing, it is essential to support factory automation and flexibility in harsh or dynamic industrial environments. State-of-the-art technology suggests building a controlled workspace using large-scale deployment of wireless sensors. To overcome the technological challenges in scalability and heterogeneity for large-scale industrial deployment, group-based industrial wireless sensor networks (GIWSNs) are suggested, in which wireless sensors are divided into multiple groups for multiple monitoring tasks, and each group of sensors is deployed densely within a subarea in a large plant or along a long production/assembly line, while connectivity between groups is required. As wireless sensors are equipped with batteries with limited power, it has been challenging to plan sleep schedules of sensors, which are influenced significantly by deployment of such a large-scale GIWSN. However, most previous works on wireless sensor networks independently investigated deployment and sleep scheduling problems, both of which have been shown to be NP-hard. Therefore, this work jointly considers deployment and sleep scheduling of sensors in a GIWSN along a production line. Via the theory of symmetries, we alleviate the computational concerns from multiple groups to one group and another medium-size group. Then we propose a hybrid harmony search and genetic algorithm, which incorporates deployment and sleep schedules to reduce energy consumption. Simulations verify this joint methodology to effectively achieve energy efficiency.

Feasibility of Green Network Deployment for Heterogeneous Networks

Green technology is a new term which is used to describe the energy efficient technologies. In the context of mobile communications industry, complying with the green technology strategy is a challenge. This is because of the tradeoff between the Quality of Service (QoS) provided and the total energy used in the transmission. Reducing the transmission energy may cause degradation in the QoS, more distinctively, in highly populated areas. This paper explores the possibility of achieving the green technology goal in planning and deployment of the HetNet mobile network with efficient network QoS. A decoupled two stage multi-objective genetic algorithm is developed to provide the network base station distribution that would satisfy both the network QoS and green network demands. In the first stage the algorithm estimates the base station parameters for more energy efficient HetNet deployment for optimum network coverage. The initial base station candidate locations are provided by a network operator in Kuala Lumpu, Malaysia. The second stage of the developed algorithm selects the number and location of RS associated with each base station optimized in the first stage to improve the network capacity. To optimize the network power, a novel arrival rate based HetNet total power consumption model is derived to investigate the parameters that affect the network power expenditure. Results show that a remarkable energy saving of about 40 % of the operator transmission power could be achieved with full network coverage. The addition of RS associated with each base station would greatly improve network capacity on the expense of its power expenditure. The relative RS to base station capacity plays major rule in reducing HetNet power expenditure.

Power Modeling and Exploration of Dynamic and Partially Reconfigurable Systems

Although fairly known for a long time, the vast potential of Dynamic and Partial Reconfigu-ration (DPR) for high energy efficiency is still difficult to exploit, for reasons that are more methodological than purely technical. This work addresses this problem and provides a contri-bution by seeking to improve energy efficient deployment and analysis for embedded hetero-geneous multiprocessor platforms representative of current and upcoming systems. This paper explores the potential energy efficiency improvements of DPR on the concrete implementation of a H.264/AVC video decoder. The methodology used to explore the different implementations is presented and formalized. This formalization is based on pragmatic power consumption models of all the tasks of the application that are derived from real measurements. Results allow to identify low energy / high performance mappings, and by extension, condi-tions at which partial reconfiguration can achieve energy efficient application processing. The improvements are expected to be of 57% in energy and 37% in performance over pure software execution, corresponding also to 16% energy savings over static implementation of the same accelerators for 10% less performance.

An Energy Efficient Sink Deployment Scheme aiming at extending the Lifespan for Wireless Sensor Networks

The issue “Sink’s Neighbor Problem” hinders the applications of Wireless Sensor Networks (WSNs). Owing to the heavier traffic burden they bear, the nodes close to the sink tend to dissipate their energy faster than others. They die earlier when their energy is used up. The energy efficiency is vital for WSNs because it is unpractical for the sensor nodes to be recharged. An Energy Efficient sink Deployment Scheme (EEDS) aiming at extending the lifespan for wireless sensor networks is proposed. It alleviates the energy consumption imbalance by adopting a mobile sink and regulating its route. Specifically speaking, a mobile sink moves in the monitor area with a certain rate and lingers at the fixed stops. During its move, the sensor nodes collect the data and store them in their memorizers. It is proved that the network lifetime is extended to be approximately six times compared with the static sink used only schemes via mathematical analysis. Besides, the scheme is extensible when the monitor area is enlarged. Finally, the energy efficiency of EEDS is evaluated through comparisons with the strategies only using static or mobile sinks. Experiment results show that EEDS has a good energy efficiency and can extend the network lifespan to be approximately 6 times compared with that of static-sink-used-only schemes. Besides, it is prolonged to be 148 percent of that of strategy using the mobile sink such as GMRE.

An economic viability analysis on energy-saving solutions for wireless access networks

As the energy bill for mobile operators rises with the continuing traffic growth, energy efficiency problems attract an increasing attention in the telecommunication industry. However, the investment for the implementation of any energy-saving solution could be so costly that it may not achieve the total cost reduction. Therefore, the economic viability of the proposed solutions is of substantial importance for the operators in the process of investment decisions. In this paper, we present a methodology for assessing the economic viability of energy-saving solutions. We conduct two case studies using the proposed methodology, and analyze the cost-benefit tradeoff for: (i) hardware upgrade enabling dynamic sleep mode operation at the base stations (BSs), and (ii) energy efficient network deployment minimizing the network energy consumption. Simulation results show that the hardware upgrade can save up to 60% of energy consumption particularly when the high data rate requirement forces low network resource utilization. Consequently, the solution is shown to be increasingly cost effective as the unit energy cost increases. Network deployment optimized for energy efficiency is shown to bring about further energy savings, but it demands denser deployment of BSs. Thus, it is not deemed as economically viable considering today’s cost values.

Energy-Efficient Combination of Small Cells and Multi-Antenna Under Separation Architecture

Splitting the control plane (C plane) and data plane (D plane) is a key feature of future cellular networks. This letter studies the energy-efficient deployment strategy to guarantee the coverage and throughput of functionality separated network. While previous works mostly focused on single-antenna networks, our focus is the performance and energy consumption of cellular networks with multi-antenna base stations (BSs). Instead of just optimizing the BS density, we jointly optimize the BS density, the number of antennas and spectrum allocation to minimize the network energy consumption (NEC). Efficient algorithms have been proposed to solve the non-convex problem.

Joint Connectivity-Coverage Temperature-Aware Algorithms for Wireless Sensor Networks

Temperature variations have a significant effect on low power wireless sensor networks as wireless communication links drastically deteriorate when temperature increases. A reliable deployment should take temperature into account to avoid network connectivity problems resulting from poor wireless links when temperature increases. A good deployment needs also to adapt its operation and save resources when temperature decreases and wireless links improve. Taking into account the probabilistic nature of the wireless communication channel, we develop a mathematical model that provides the most energy efficient deployment in function of temperature without compromising the correct operation of the network by preserving both connectivity and coverage. We use our model to design three temperature-aware algorithms that seek to save energy (i) by putting some nodes in hibernate mode as in the Stop-Operate (SO) algorithm, or (ii) by using transmission power control as in Power-Control (PC), or (iii) by doing both techniques as in Stop-Operate Power-Control (SOPC). All proposed algorithms are fully distributed and solely rely on temperature readings without any information exchange between neighbors, which makes them low overhead and robust. Our results identify the optimal operation of each algorithm and show that a significant amount of energy can be saved by taking temperature into account.

Energy-Aware Cellular Deployment Strategy Under Coverage Performance Constraints

The last ten years have witnessed explosive growth in mobile data traffic, which leads to rapid increases in energy consumption of cellular networks. One potential solution to this issue is to seek out a green deployment strategy. In this paper, we investigate the energy-efficient deployment strategy under coverage performance constraints for both homogeneous and heterogeneous cellular networks. Unlike just considering the base station (BS) density in previous work, we jointly optimize the BS density and the BS transmission power. First, we derive the relation between the average coverage probability and deployment strategy (i.e., BS density and BS transmission power) with stochastic geometry tools. Then, based on the expression results, we formulate a network energy consumption minimization framework considering coverage performance constraints and jointly determine the optimal macro BS (MaBS) density, MaBS transmission power, and micro BS (MiBS) density. With practical data sets, numerical simulation results show the following: 1) compared with homogeneous network deployment, heterogeneous network deployment has the advantage in energy efficiency performance, and 2) our joint BS density and BS transmission power optimization strategy exceeds the existing strategy, which just considers the BS density optimization in terms of energy efficiency.

Design of a Probability Density Function Targeting Energy-Efficient Node Deployment in Wireless Sensor Networks

In wireless sensor networks the issue of preserving energy requires utmost attention. One primary way of conserving energy is judicious deployment of sensor nodes within the network area so that the energy flow remains balanced throughout the network and prevents the problem of occurrence of energy holes. Firstly, we have analyzed network lifetime, found node density as the parameter which has significant influence on network lifetime and derived the desired parameter values for balanced energy consumption. Then to meet the requirement of energy balancing, we have proposed a probability density function (PDF), derived the PDF's intrinsic characteristics and shown its suitability to model the network architecture considered for the work. A node deployment algorithm is also developed based on this PDF. Performance of the deployment scheme is evaluated in terms of coverage-connectivity, energy balance and network lifetime. In qualitative analysis, we have shown the extent to which our proposed PDF has been able to provide desired node density derived from the analysis on network lifetime. Finally, the scheme is compared with three existing deployment schemes based on various distributions. Simulation results confirm our scheme's supremacy over all the existing schemes in terms of all the three performance metrics.

Energy Efficient Network Deployment With Cell DTX

Cell discontinuous transmission (DTX) is a new feature that enables sleep mode operations at base station (BS) side during the transmission time intervals when there is no traffic. In this letter, we analyze the maximum achievable energy saving of the cell DTX. We incorporate the cell DTX with a clean-slate network deployment and obtain optimal BS density for lowest energy consumption satisfying a certain quality of service requirement considering daily traffic variation. The numerical result indicates that the fast traffic adaptation capability of cell DTX favors dense network deployment with lightly loaded cells, which brings about considerable improvement in energy saving.

Wind Energy System and Efficient Deployment in Owerri via Distributed Generation Scheme

Wind energy is one of the fastest growing technologies in the energy generation industry nowadays. The erratic and epileptic state of power supply in Nigeria resulting from insufficient generation to meet the load demands, and issues about global warming is of great concern to all. This has led to load shedding; blackout in some parts of the country lasting for hours, closure of some industries due to high operational cost. However the nation is currently diversifying its power generation capabilities through distributed generation using renewable resources. In order to ameliorate the situation, and to curb the global warming challenge, deployment of distributed generation (DG) using wind for electricity generation has become a novel idea. This is so because wind is abundantly available for all hours of the day and the resource is environmentally friendly. This paper therefore evaluated the wind energy potential of Owerri using the available data; considered how best it could be utilized to generate electricity through stand alone scheme and integration with the utility grid for most efficient operation.

Energy Efficient Deployment of Heterogeneous Networks

A novel energy efficient heterogeneous networks (HetNet) deployment scheme is proposed in this paper. Unlike the traditional deployment, we consider the scenario with picocell eNodeB (PeNB) at the edge instead of under the umbrella of macrocells in HetNet. In the novel scheme, one PeNB with directional antennas is deployed on the border of neighbor macrocells which is equivalent to a combiner of PeNBs to associate MeNBs around. Compared with the traditional scheme, we have proved that the novel scheme performs better in fairness and efficiency, in terms of coverage area (proportional to offload rate), spectrum and energy efficiency for both edge users and overall users. Meanwhile, the technologies that try to reduce the difference and imbalance of the transmit power in HetNet obtain more inherent gains in the novel scheme, such as cell range expanded (CRE). Our results show that, the scheme proposed is also a spectrum and energy efficient heterogeneous deployment scheme that the energy efficiency is increased from 20% up to nearly 60%

Energy consumption of radio access networks in Finland

Energy consumption of radio access networks is related to the speed and volume of mobile data traffic. Finland aims to achieve two conflicting targets by 2015, the one of 100 Mbps user data rate provision to nearly all citizens and the other of the reduction of Information and Communications Technology industry carbon footprint. The purpose of this paper is to evaluate the energy consumption for several radio access networks deployment scenarios. Mobile operators can advance energy efficiency through (1) energy optimization of individual sites and (2) choice of energy efficient network deployment strategies. Models for the site power consumption, the average site traffic load factor and the average subscription mobile data traffic, are developed. The results show a reduction of energy consumption for mobile network based on LTE radio access technology which operates at 1800 MHz in urban region and 800 MHz in suburban and rural regions. In the dense urban region the LTE base stations are installed on the existing sites and in the less-dense urban region, wide-to-local area offloading is required.

Green heterogeneous small-cell networks: toward reducing the CO2 emissions of mobile communications industry using uplink power adaptation

Heterogeneous small cell networks, or Het- SNets, are considered as a standard part of future mobile networks in which multiple lowpower low-cost user deployed base stations complement the existing macrocell infrastructure. This article proposes an energy-efficient deployment of the cells where the small cell base stations are arranged around the edge of the reference macrocell, and the deployment is referred to as cell-on-edge (COE) deployment. The proposed deployment ensures an increase in the network spectral and energy efficiency by facilitating cell edge mobile users with small cells. Moreover, COE deployment guarantees reduction of the carbon footprint of mobile operations by employing adaptive uplink power control. In order to calibrate the reduction in CO2 emissions, this article quantifies the ecological and associated economical impacts of energy savings in the proposed deployment. Simulation results quantify the improvements in CO2 emissions and spectral and energy gains of the proposed COE deployment compared to macro-only networks and typical small cell deployment strategies where small cells are randomly deployed within a given macrocell.

An Energy-Efficient Dense PicoStation Deployment and Power Control Strategy for Heterogeneous Networks

Deploying PicoStations in traditional Macro-cellular networks, especially in hot-spot areas, is a promising strategy to boost system throughput and enhance indoor coverage. However, PicoStations’ introduction brings some new problems, such as severe interference and energy consumption, which may result in performance degradation. In order to improve energy efficiency, throughput fairness and PicoStation coverage, a practical energy-efficient dense PicoStation deployment and power control algorithm is proposed. The proposed scheme maximizes both the number of active PicoStations that can achieve the required capacity and the sum cell capacity under individual capacity constraints in two steps. Finally, simulation results demonstrate that the proposed algorithm outperforms the traditional cell capacity maximum scheme in terms of user fairness and energy saving.

무선 셀룰라 시스템에서 에너지 효율적인 마이크로 기지국 배치 방안

본 논문은 셀룰러 시스템에서 에너지 효율적인 마이크로 기지국 배치 방안에 관한 것이다. 먼저 기지국 배치는 영역에 대한 고려가 필요하기 때문에 공간 스펙트럼 효율(ASE)을 제한조건으로 하여, 제한조건을 만족하면서 에너지 사용을 최소로 하는 최적화 문제를 제시한다. 최적화 문제의 계산 복잡도를 감소시키기 위하여 마이크로 기지국 배치에 따른 기지국 서비스 영역과 ASE간의 관계를 기반으로 하는 마이크로 기지국 배치 방안을 제안한다. 모의실험을 통하여 제한된 알고리즘이 일정 범위 안에서 최적해의 성능을 만족시킴을 보인다. In this paper, we study the energy-efficient deployment strategy for micro base station (BS) in wireless cellular systems. Firstly, we formulate a general problem pertaining to total energy consumption minimization with the requirement of area spectral efficiency (ASE). We start from an observation about the correlation between the area covered by an additional micro BS and the increment of ASE. Under such an observation, we propose an efficient greedy micro BS deployment algorithm. Simulations show that the proposed deployment algorithm can deploy micro BSs with a slight performance reduction comparing with the optimal solution.

Energy-efficient deployment strategies in structural health monitoring using wireless sensor networks

SUMMARY Structural health monitoring using wireless sensor networks has drawn considerable attention in recent years. The ease of deployment of tiny wireless devices that are coupled with sensors and actuators enhances the data collection process and makes prognostic and preventive maintenance of an infrastructure much easier. In this paper, the deployment problem is considered for finding node locations to reliably diagnose the health of a structure while consuming minimum energy during data collection. A simple shear structure is considered and modal analysis is performed. The example verifies the expectation that placing nodes further apart from each other reduces the mode shape errors but increases the energy consumption during data collection. A min–max, energy-balanced routing tree and an optimal grid separation formulation are proposed that minimize the energy consumption as well as provide fine grain measurements. Copyright © 2012 John Wiley & Sons, Ltd.