A green framework for energy efficient management in TDMA-based wireless mesh networks

Wireless Mesh Networks (WMNs) provide a novel network architecture to extend broadband network coverage with low costs. Additionally, we see an increased interest in supporting demanding multimedia applications in next-generation wireless mesh networks. Provision of Quality of Service (QoS) in wireless mesh networks requires end-to-end support for routing packets via a suitable multihop route to the destination. However, in wireless mesh networks, if the medium access control layer does not support mechanisms for QoS support at a per-link level, all efforts for providing end-to-end QoS are futile. Hence, we see a trend towards standards for wireless mesh networks which support QoS at the Medium Access Control (MAC) level on a per-link basis.

International audience

Providing end-to-end quality of service (QoS) for delay-sensitive flows with variable-bit-rate (VBR) traffic in wireless mesh networks is a major challenge. There are several reasons for this phenomenon, including time-varied bandwidth requirements, competition for transmission opportunities from flows on the same link, and interference from other wireless links. In this paper, we propose a flexible bandwidth allocation and uncoordinated scheduling scheme, called two-stage link scheduling (2SLS), to support flow delay control in TDMA-based wireless mesh networks. The scheme is implemented in two stages: slot allocation and on-the-go scheduling. The slot allocation mechanism allocates contiguous time slots to each link in each frame based on predefined maximum and minimum bandwidth requirements. Then, each link's on-the-go scheduling mechanism dynamically schedules the transmissions within the allocated time slots. The objective is to maximally satisfy the demand of all flows on the link according to the bandwidth requirements and channel condition. Compared with traditional slot allocation approaches, 2SLS achieves higher channel utilization and provides better end-to-end QoS for delay-sensitive flows with VBR traffic.

One of the most critical issues in wireless sensor networks is the limited availability of energy within the network nodes. Recently, the idea of deploying a high capacity overlay using virtual sinks with long range 802.11 links to ease congestion in the underlying sensor network has been explored. Since the VSs are battery powered, it is important to conserve energy in them too. To reduce the energy consumption, usually the shortest path (SP) route is preferred in networks that do not use topology control. However, if only a few of the VS nodes are sending data, routing along the SP may require some additional VS nodes to be turned on just for the relaying purpose which otherwise could be turned off. Since the link bandwidth is high in 802.11 (Mbps) and the sensory data generation rate is low (Kbps) in comparison to the bandwidth, a high idle-mode energy cost may be incurred in the relaying VS nodes. In this paper, we explore the idea of using minimum connected dominating set (MCDS) based routes, since more energy can be saved by switching the non-dominator VSs to sleep mode and by funneling all the data through the MCDS nodes. We propose an energy-aware routing scheme that considers both the SP route and the MCDS nodes to discover a path along the VS network to the physical sink. Performance evaluation of the routing scheme shows a notable reduction in the overall energy consumption in the network with respect to SP routing while simultaneously maintaining an acceptable packet delivery rate.

A key problem in wireless mesh networks is forwarding packets to/from one or more gateways with connectivity to the Internet. In this respect, a short link schedule, which determines the transmission time of links, is critical. To date, existing link schedulers do not consider routers that incorporate advances in multiple input multiple output communications, i.e., interference cancellation and spatial multiplexing. In particular, these routers are able to transmit or receive distinct packets on all their links concurrently as well as deliver multiple packets to a neighbor simultaneously. To this end, we consider the problem of deriving a time division multiple access schedule that forwards packets to their respective destination quickly. We first consider the personalized broadcast problem, which assumes a single gateway and present Algo-PB, a solution that produces a schedule that is within 34.5% of the lower bound, and is 45.5% shorter than those computed by the state-of-the-art algorithms. We then extend the problem to consider multiple gateways. This so-called forest construction problem is modeled as an integer linear program (ILP). We then outline Algo-FC, a novel heuristic that generates a balanced forest by repeatedly picking a node from the heaviest tree and migrating it to another tree if doing so reduces the overall load. Experiment results show that the resulting forest generated by Algo-FC is within 9.1% of the ILP solution.

Impact of multiple channels and radios on the performance of a TDMA based wireless mesh network

We study end-to-end delay performance of different routing algorithms in networks with random failures. Specifically, we compare delay performances of differential backlog (DB) and shortest path (SP) routing algorithms and show that DB routing outperforms SP routing in terms of throughput when the network is heavily loaded and/or the failure rate is high while SP routing achieves better delay performance in the low load regime. Then, we investigate delay performance of a hybrid routing algorithm that combines principles of both SP and DB routing algorithms and show that it outperforms both of these routing algorithms. Finally, we demonstrate improvements in delay performance of DB routing through the use of a digital fountain approach which was originally proposed for multicast applications. In addition, our results show that there exists an optimal coding rate where digital fountain based DB routing achieves minimum end-to-end delay. To the best of our knowledge, this is the first work which investigates delay performance of DB routing and its enhanced versions for networks with link failures.

Machine learning is expected to be a key enabler in 5G wireless self-organizing networks (SONs) that will be significantly more autonomous, smarter, adaptable and user-centric than current networks. This paper proposes a methodology, User Specific-Optimal Capacity Shortest Path (US-OCSP) routing, that uses machine learning to determine the resource-based optimum-capacity shortest path for a user between source and destination. The methodology takes into account two primary metrics, available capacity at network nodes (eNodeBs/gNodeBs) and distance, that are critical in determining the optimal path for an end-user. An ns-3 simulation determines the capacity, which is measured by the availability of resources [i.e., Physical Resource Blocks (PRBs)] at all possible serving network nodes between the source and destination, that is followed by implementation of Q-learning, a reinforcement type of machine learning algorithm that determines the shortest path avoiding congested network nodes so as to achieve the required throughput and/or bit rate. The ability to determine the optimal-capacity shortest path route will facilitate effective resource allocation that will optimize end-user satisfaction in a 5G SON network.

With the enhancement in channel bandwidth and mobile devices, more broadcast applications will be deployed in the wireless mesh networks (WMNs). While traditional approaches focus on finding a single broadcast tree in the network, we aim at maximizing the number of broadcast trees/calls that can be carried. In this paper, we first formulate an Integer Linear Program (ILP) for solving the minimum-channel-utilization broadcast tree problem in multi-channel multi-interface WMNs. In our ILP, channel assignment, routing, and scheduling are jointly considered for finding a broadcast tree that can minimize the maximum channel utilization. Intuitively, this balances all the accepted traffic load in the network, which in turn maximizes the chance of accepting future calls. However, solving ILP usually takes time and is less suitable for a system with real-time call arrival. An efficient heuristic algorithm is then designed. Our simulation results show that the proposed heuristic gives real-time response and provides comparable good performance as the ILP approach.

The researcher wants to make a KWH meter monitoring tool with estimated usage costs so that the tools he makes can help the community to minimize costs in the electricity consumption area, especially in the workshop room located on the 1st floor of building C at Medan State Polytechnic. The long-term goal of this research is to develop an Internet of Things (IoT)--based KWH meter monitoring tool that can read current, voltage, frequency, power factor, and power consumption. This utilization shows the use of costs that have been incurred in real-time by displaying the results on the LCD and can also be from the user's mobile phone. In this study, the strategy used in the energy management framework was determined using SWOT analysis. From the results of the measurement and monitoring of electrical energy consumption obtained the results that, energy management is carried out by applying Standard Operating Procedures for the use of electrical energy in the electrical engineering workshop room in order to save more minimal energy consumption with a large error (Error) PZEM in measuring Voltage is 0.0198% in measuring Current is 0.612%. in measuring Cosphi is 0.01%. in measuring Frequency is 0.003%. in measuring Power is 0.183%. And the average measurement error rate is below 0.5%, namely 0.23%.

In this paper, we develop an ontology-based framework for energy management in buildings. We divide the functional architecture of a building energy management system into three interconnected modules that include building management system (BMS), benchmarking (BMK), and evaluation & control (ENC) modules. The BMS module is responsible for measuring several useful environmental parameters, as well as real-time energy consumption of the building. The BMK module provides the necessary information required to understand the context and cause of building energy efficiency or inefficiency, and also the information which can further differentiate normal and abnormal energy consumption in different scenarios. The ENC module evaluates all the information coming from BMS and BMK modules, the information is contextualized, and finally the cause of energy inefficiency/abnormality and mitigating control actions are determined. Methodology to design appropriate ontology and inference rules for various modules is also discussed. With the help of actual data obtained from three different rooms in a commercial building in Singapore, a case study is developed to demonstrate the application and advantages of the proposed framework. By mitigating the appropriate cause of abnormal inefficiency, we can achieve 5.7%, 11.8% and 8.7% energy savings in Room 1, Room 2, and Room 3 respectively, while creating minimum inconvenience for the users.

Throughput maximization is a key challenge to numerous applications in wireless mesh networks (WMNs). As a potential solution, cooperative communications, which may increase link capacity by exploiting spatial diversity, has attracted a lot of attention. However, if link scheduling is considered, this transmission mode may perform worse than direct transmission in terms of end-to-end throughput, since the sending/receiving of cooperative relays incurs extra interferences. In this paper, we propose to employ directional antennas to alleviate those negative effects and comprehensively investigate the throughput maximization problem in cooperative WMNs. Regarding the features of cooperative communications and antenna modes (omnidirectional antennas or directional ones), we extend the links into cooperative links/general links, form an antenna based cooperative (ABC) conflict graph to characterize the interference relationship among those extended links, and design beamforming strategies w.r.t. link scheduling. Given all ABC independent sets in this graph, we mathematically formulate the end-to-end throughput maximization problem under cross-layer constraints and solve it by linear programming. Our simulation results show that the end-to-end throughput of cooperative WMNs can be notably improved, when transmission selection and antenna mode selection are jointly considered.

Regarding the association between information and communication technology (ICT) and economic growth and energy consumption, particularly in developing economies, there is a great deal of controversy and a lack of empirical study. This study applies Quantile Autoregressive Distributed Lag Model (QARDL) approach to empirically probe into the effect of ICT on energy consumption and economic growth in China. Two corresponding models for energy consumption and economic growth are formulated and the data of all of the variables spanning over 1995-2021 period is taken from different secondary sources. The findings of the study reveal significant and positive impact of ICT on economic growth at all quantiles in the short and long run. Similarly ICT has significant and positive impact on energy consumption also at all quantiles. The Quantile Granger Causality test provides evidence for bidirectional causality between ICT and economic growth and ICT and energy consumption. Wald test proved the presence of and symmetric and linear association between ICT and economic growth and ICT and energy consumption at quantiles in the long and short run both. In the light of these findings, the study recommends the Chinese government and investors to have more investment in energy efficient ICT products that consume less energy and help increase in economic growth in China.

This study aims to investigate the effects of information and communication technology (ICT), energy consumption, economic growth, and financial development on carbon dioxide emissions using 1993–2013 panel data from 12 Asian countries. The study employs a panel unit root test accounting for the presence of cross-sectional dependence and found that Internet usage is stationary and carbon dioxide emissions, energy consumption, gross domestic production (GDP), and financial development are first-difference stationary. The results form Pedroni panel cointegration test confirms that the variables are cointegrated. The results of the cointegration test indicate that the ICT-energy-GDP-carbon dioxide emissions nexus has long-run equilibrium. Both energy consumption and GDP have significant, positive impacts on carbon dioxide emissions; energy consumption and GDP have an effect on carbon dioxide emissions growth. ICT has a significantly negative effect on carbon dioxide emissions; the promotion of ICT becomes one of the important strategies introduced to mitigate carbon dioxide emissions for various countries. Causality results show that energy consumption, GDP, and financial development cause more carbon dioxide emissions. Energy consumption, GDP, and carbon dioxide emissions cause ICT. GDP causes financial development, whereas energy consumption and GDP are interdetermined. The feedback hypothesis exists in the region; those countries need to develop alternative energy to replace fossil fuels. ICT does not threaten the environment and ICT policy can be seen as a part of carbon dioxide emissions reduction policy.

Wireless Mesh Networks (WMNs) consist of a high-density of hundreds to thousands of mesh routers (MRs) deployed in corporate offices and university campuses. The main purpose of this deployment is to meet user demands for high bandwidth, mobility, and reliability. However, our recent consideration of such networks revealed that they are rarely used at their peak capacity besides the fact that the entire MRS remains active continuously. Thus, during lower traffic periods the energy consumption is the same as in busy hours, while it would be possible to save a large amount of power. Green networking has recently been proposed; consist of rethink how networks are constructed and operated so that not only the cost and performance are taken into consideration but also their energy consumption and carbon footprint. In this paper, we draw attention that a large part of idle MRs results in considerable energy losses. Thousands of WMNs worldwide jointly aggravate this problem, while raising serious worry about the energy wastage that will happen in the future. In response to this problem, we first propose an optimal approach called Optimal Energy Efficiency Management Design (OEEMD) by formulating the problem as a Mixed Integer Linear Program (MILP) model to investigate the power consumption in WMN. As this problem is known to be NP-hard, we then propose an efficient heuristic algorithm called Green Energy Efficiency Management Design (GEEMD) for wireless mesh networks. GEEMD uses a sleep mechanism to power on/off underutilized MRs, based on the traffic load and solar energy generation. For the performance evaluation, we used OEEMD and GEEMD to study the performance of WMN deployment scenario in the university and campus area of Tlemcen city in Algeria over dynamic traffic profiles. Illustrative numerical examples show that, with suitable design parameters, we can efficiently reduce energy consumption in WMN without significantly impacting the network performance.