Energy Efficient Bandwidth Research Articles

Energy-Efficient Federated Learning With Resource Allocation for Green IoT Edge Intelligence in B5G

An edge intelligence-aided Internet-of-Things (IoT) network has been proposed to accelerate the response of IoT services by deploying edge intelligence near IoT devices. The transmission of data from IoT devices to the edge nodes leads to large network traffic in the wireless connections. Federated Learning (FL) is proposed to solve the high computational complexity by training the model locally on IoT devices and sharing the model parameters in the edge nodes. This paper focuses on developing an efficient integration of joint edge intelligence nodes depending on investigating an energy-efficient bandwidth allocation, computing Central Processing Unit (CPU) frequency, optimization transmission power, and the desired level of learning accuracy to minimize the energy consumption and satisfy the FL time requirement for all IoT devices. The proposal efficiently optimized the computation frequency allocation and reduced energy consumption in IoT devices by solving the bandwidth optimization problem in closed form. The remaining computational frequency allocation, transmission power allocation, and loss could be resolved with an Alternative Direction Algorithm (ADA) to reduce energy consumption and complexity at every iteration of FL time from IoT devices to edge intelligence nodes. The simulation results indicated that the proposed ADA can adapt the central processing unit frequency and power transmission control to reduce energy consumption at the cost of a small growth of FL time.

Energy-Efficient Bandwidth and Power Allocation in Relay-Assisted Multi-Layer Heterogeneous Networks with Energy Harvesting

Energy-Efficient Bandwidth and Power Allocation in Relay-Assisted Multi-Layer Heterogeneous Networks with Energy Harvesting

A Framework for an Energy-Efficient Bandwidth Allocation Approach through Dynamic ONTs Grouping in Flexible GPON Access Networks

The growing demands for high speed connectivity to keep pace with bandwidth intensive applications and services have spawned the idea of developing PONs with capabilities beyond those of copper and wireless-based technologies in access network. In this article, an approach for the design of an energy efficient bandwidth allocation mechanism for the shared upstream communication link in the Fiber to the Home (FTTH) access network is presented and evaluated using Mixed Integer Linear Programming (MILP) model. In the MILP model, two objective functions for minimization of power consumption and minimization of blocking were evaluated. The results have shown that with the objective of power minimization approach, Optical Network Terminals (ONTs) are efficiently grouped to the minimum number of active networking Optical Line Terminal (OLT) switches, traffic is groomed, ports are efficiently utilized, and hence total power consumption is minimized. Results have shown that with energy efficient bandwidth allocation approach consideration, energy savings can reach up to 80% for different examined traffic loads following uniform distribution.

A Reinforcement Learning Approach to Energy Efficiency and QoS in 5G Wireless Networks

Satisfying the huge demand for high bandwidth in 5G networks is in part achieved by vertical densification of the network infrastructure with so-called small-cell base stations. As a direct consequence, the performance of 5G networks intrinsically suffers from: 1) a huge inter-cell interference due to the network density and 2) a large energy waste that results from the high redundancy of lightly loaded, always-on, and small-cell base stations. In this paper, we use a game theoretic approach to design a distributed energy efficient bandwidth sharing mechanism for small-cell networks. To circumvent the combinatorial nature of searching in the huge strategy space, we invoke a reinforcement learning approach to intelligently guide the search toward good solutions. More precisely, our solution relies on dynamically learning good strategies for the user-equipment association and orthogonal frequency division multiple access (OFDMA) scheduling to strike a balance between energy efficiency and high bandwidth utilization. Our model takes into account inter-cell interference and the diversity of user quality of service requirements.

Energy Efficient Particle Swarm Optimization Based Multipath Routing in WSN

Wireless Networks includes a larger advantage in today’s communication application like environmental, traffic, military, and health observation. To realize these applications it's necessary to possess a reliable routing protocol. discusses about the working of proposed energy efficient bandwidth aware shortest path routing protocol for multipath routing in wireless sensor network. The proposed algorithm is based for choosing energy efficient shortest path. In routing algorithm, route that have shortest path among multipaths selected by particle swarm optimization algorithm. Among these shortest paths, that path is selected which require minimum route selection parameter. The proposed algorithm uses distance as well as energy of nodes as a parameter to find optimum paths using particle swarm optimization. Among these selected paths, only one optimum path is selected which reduces the energy requirement of the network. According to this work there would be improvement in other parameters also such as end to end delay as well as throughput.

Joint Wireless and Optical Power States Scheduling for Green Multi-Radio Fiber-Wireless Access Network

Due to the massive deployment of electrical network devices, Fiber-Wireless (FiWi) access network has to suffer from the challenge of high energy consumption. With the ever-increasing eager for green communication infrastructure, the issue of high energy consumption may become one of the major barriers for the advance of FiWi access network. Previous works proposed for green FiWi access network cover three aspects, including the optimized deployment of network devices such as optical network units (ONUs), the energy-efficient bandwidth allocation of ONUs with QoS guarantee, and the dynamic power states scheduling of ONUs (i.e., active/sleep) according to their traffic profile. However, these works did not take the energy-saving design of wireless subnetwork into account simultaneously. In fact, when some ONUs in the optical subnetwork are switched into sleep states, part of the radio interfaces originally forwarding traffic to the sleep ONUs would be idle or low-loaded. This provides a potential opportunity for energy-saving in wireless subnetwork by switching off the idle or low-loaded radios. This paper focuses on the design of green multi-radio FiWi access network by integrating the energy-savings of optical and wireless subnetworks. To support the energy-efficient design, the new power states are defined for ONUs and radios, respectively. Aiming at dynamic traffic profile, the heuristic algorithms are proposed for the energy saving of integrated wireless front-end and optical back-end of FiWi access network. First, the Energy-saving algorithm with ONU sleep mechanism (EAS) is proposed to dynamically schedule the power states of ONUs by judging their traffic profile with load thresholds. Then, the Energy-saving algorithm based on Radios Off (ERO) is proposed to reconfigure the topology of wireless subnetwork by controlling the power states of radios dynamically. Moreover, wireless rerouting is employed in both EAS and ERO to guarantee the QoS provisioning ability of network. Finally, a comprehensive energy-saving scheme called EE is proposed by combining the EAS and ERO algorithms strategically. Simulation results show that with the reasonable setting of parameters, the proposed EE scheme can save the energy of 33.14% to 64.35% and 8.56% to 36.42% in a wide range of traffic load compared to the No-energy-saving and QoS-aware energy-saving scenarios, respectively.

Energy-Efficient Bandwidth Aggregation for Delay-Constrained Video over Heterogeneous Wireless Networks

The spectrum limitation of single wireless networks prompts the bandwidth aggregation of heterogeneous access medium (e.g., LTE and Wi-Fi) to support high-quality real-time video services. Energy consumption of mobile devices is of vital significance to provide user-satisfied multimedia streaming applications. However, it is challenging to develop an energy-efficient bandwidth aggregation scheme with regard to the stringent delay and quality constraints imposed by wireless video transmission. To address the critical problem, this paper presents an Energy-quaLity aware Bandwidth Aggregation (ELBA) scheme. First, we develop an analytical framework to model the delay-constrained energy-quality tradeoff for multipath video transmission over heterogeneous wireless networks. Second, we propose a bandwidth aggregation framework that integrates energy-minimized rate adaptation, delay-constrained unequal protection, and quality-aware packet distribution. The proposed ELBA scheme is able to effectively leverage the wireless channel diversity and video frame priority for enabling energy-minimized quality-guaranteed streaming to multihomed devices within imposed deadline. We conduct the performance evaluation through both experiments over real wireless networks and extensive emulations in Exata platform. Experimental results demonstrate the performance advantages of ELBA over existing bandwidth aggregation schemes in energy conservation, video quality, and end-to-end delay.

Energy-Efficient Bandwidth and Power Allocation for Multi-Homing Networks

This paper investigates resource allocation for multi-homing networks where users can simultaneously transmit data to multiple radio access networks (RANs) using multiple air interfaces. We aim at optimally assigning the bandwidth and power to each user-RAN connection so as to maximize energy-efficiency of the entire network subject to user specific QoS requirements as well as the available resource budgets. First, we study the problem of resource allocation for scenarios where the connections between the users and the RANs are predefined, which naturally leads to a fractional program. To obtain the optimal solution efficiently and facilitate distributed implementations, we further equivalently transform the design problem into a convex program using a parameter-free approach and develop a decentralized algorithm based on the alternating direction method of multipliers. Second, we investigate the problem of joint link selection and resource allocation for energy-efficiency maximization. The problem is cast as a mixed integer nonlinear convex program for which we particularize the branch and bound method to find an optimal solution. Then, two suboptimal low-complexity designs are proposed: the first one is based on greedy algorithm, which gradually maximizes the virtual link energy-efficiency; the other one is based on the concept of sparsity-inducing norm. Simulation results are presented to demonstrate the potential gains in terms of energy-efficiency of the proposed methods.

An Adaptive Bandwidth Allocation for Energy Efficient Wireless Communication Systems

In this paper, an energy efficient bandwidth allocation scheme is proposed for wireless communication systems. An optimal bandwidth expansion (OBE) scheme is proposed to assign the available system bandwidth for users. When the system bandwidth does not reach the full load, the remaining bandwidth can be energy-efficiently assigned to the other users. Simulation results show that the energy efficiency of the proposed OBE scheme outperforms the traditional same bandwidth expansion (SBE) scheme. Thus, the proposed OBE can effectively assign the system bandwidth and improve energy efficiency.

Energy Efficient Bandwidth Allocation in Heterogeneous Wireless Networks

Wireless heterogeneous networks (HetNet) are continuing to bring the industrial networks and intelligent systems more smarter. In heterogeneous networks, energy saving is vital for a sustainable network development, which can be achieved through using various spectrum allocation schemes. It is significant that energy-efficient(EE) spectrum allocation should consider large-scale user behavior, which characterizes the macro BSs that guarantee traffic requirements in non-hotspot regions and the micro BSs that guarantee traffic requirements in hotspot regions. This paper presents four bandwidth allocation schemes for the (a) orthogonal, (b) shared, (c) shared/orthogonal frequency band allocation (SOFA) and (d) shared/orthogonal frequency band allocation under micro BSs transmit power change (SOFA-MPC), where the large-scale user behavior is taken into account. Then we give closed-form formulas of bandwidth allocation schemes which establish the quantitative relationship between the large-scale user behavior and bandwidth allocation strategy. Both theoretical and simulation results show that SOFA scheme is effective in guaranteeing both the demands of the large-scale user behavior and keeping low power consumption than orthogonal allocation scheme and shared scheme. SOFA-MPC scheme has a close relation with the large-scale user behavior too. We give the variation range of transmit power variation bias ? in all circumstances. Simulation and analytical results show that the SOFA-MPC EE is higher than the SOFA EE within the limits of ?.

Energy efficiency in the extended-reach fiber-wireless access networks

Telecommunication networks call for novel energy-efficient design and management schemes as a result of the increasing contribution of the ICT sector to electricity consumption and greenhouse gas emissions. Access networks, being one of the significant contributors in the last mile, require power saving protocols and architectures. As one of the emerging access network solutions, convergence of PONs and wireless access networks, also named as FiWi, offer to combine the robustness and high capacity of optical networks with the mobility and ubiquity of wireless networks. In this article, we present an overview and a brief comparison of energy-efficient protocols and design approaches in FiWi networks. We further propose an energy-efficient bandwidth allocation mechanism in FiWi networks that adopts an optical burst switching (OBS)-like report generation mechanism in LREPON. Through simulations, we show that the proposed scheme leads to significant energy savings in the long-reach FiWi network while overcoming the delay penalty of the ONU-BS sleep modes.

Energy-efficient bandwidth reservation for bulk data transfers in dedicated wired networks

The ever increasing number of Internet-connected end-hosts calls for high-performance end-to-end networks, which in turn leads to an increase in the energy consumed by the networks. Our work deals with the energy-consumption issue in dedicated networks with bandwidth provisioning and in-advance reservations of network equipments for Bulk Data transfers. First, we propose an end-to-end energy-cost model of such networks, which describes the energy consumed by a transfer for all the crossed equipments. This model is then used to develop a complete energy-efficient framework adapted to Bulk Data Transfers over dedicated networks. This framework enables switching unused network portions off during certain periods of time to save energy. This framework is also endowed with prediction algorithms to avoid useless switching off and with adaptive scheduling management to optimize the energy used by the transfers. Through network simulations, we show that, under given load and topology, the proposed framework can achieve 35% energy savings compared to the current approach, with no energy-management system.

Energy-efficient bandwidth allocation in wireless networks: algorithms, analysis, and simulations

In this paper, we present a new energy-efficient bandwidth allocation scheme for wireless networks. First of all, we investigate the intrinsic relationship between the energy consumption and transmission rates of mobile terminals, in which transmission rate is determined through channel allocations. Then, we propose two schemes for connection admission control: victim selection algorithm (VSA) and beneficiary selection algorithm (BSA) with the intent to reduce energy consumption of each terminal. Moreover, we introduce an adjustment algorithm to statistically meet the demands for quality of service (QoS) during the resource allocation. The performance of the proposed schemes is evaluated with respect to energy consumption rate of each successfully transmitted bit, throughput and call blocking probabilities. An extensive analysis and simulation study is conducted for Poisson and self-similar, multi-class traffic.