RETRACTED ARTICLE: Stable route selection for adaptive packet transmission in 5G-based mobile communications

In this paper, we propose an algorithm which is capable of forming reuse sets of links in time division multiple access (TDMA) based wireless sensor networks (WSNs) to gain less frame length. For each reuse set, we use linear programming to achieve optimal energy consumption. We further show how to apply this algorithm with end-to-end packet loss rate constraint. The major contribution of this paper is twofold. First, the proposed scheme gives an energy efficient way to support quality of service (QoS) requests such as delay (by reduced frame length) and end-to-end packet loss rate. Secondly, the relationships amongst energy consumption, frame length (thus delay) and packet loss rate in WSNs revealed in this paper can be utilized in designing WSNs with delay and packet loss constraints.

The development of various applications of wireless sensor networks has aroused great interest in using these types of networks in various fields. These networks, without infrastructure and self‐organization, are easily deployed in most environments and collect information about environmental phenomena for analysis and proper response to accidents and send them to the basic centers. They do. Wireless sensor networks are made up of some sensor nodes that both act as sensors and act as relay nodes concerning to each other. On the other hand, the lack of infrastructure in these networks has limited resources so that the nodes of the battery are fed with limited energy. Due to the location of networks in difficult and impassable areas, it is not possible to recharge or replace the node battery. Therefore, saving energy consumption in this type of network is one of the most important challenges. Since the rate of energy consumption when sensing information and receiving data packets from another node is a fixed value, so sensor nodes have the highest energy consumption when sending data. Therefore, routing methods try to reduce energy consumption based on systematic approaches. One of the most promising solutions to reduce energy consumption in wireless sensor networks is to cluster the nodes and select the threaded node based on the data transfer parameters so that the average energy consumption in the nodes is reduced and the network lifetime is increased. Therefore, in this research, a new optimization approach using multiobjective genetic algorithm and cuckoo algorithm for clustering wireless sensor networks is presented. In this study, in order to select clustered nodes from a multiobjective genetic algorithms based on reducing intracluster distances and reducing energy consumption in cluster member nodes and near‐optimal routing based on cuckoo optimization algorithm to transfer information between nodes have been used in the direction of the cavity. The implementation results show that considering the evolutionary capabilities of the multiobjective genetic algorithm and the cuckoo optimization algorithm, the proposed method in terms of energy consumption, efficiency, delivery rate, and packet transmission latency, compared to previous methods, has improved.

Neighbour discovery (ND) is an important process for self-configuration as it provides useful information, such as neighbour nodes with some power saving parameters, for other processes. In wireless sensor networks, transmission power adjustment is one of the possible ways to minimise energy consumption and prolong network lifetime. This paper proposes the ND technique which provides the received signal strength indicator (RSSI) value for dynamic transmit power adjustment in IEEE 802.15.4. This work focuses on a single-hop network of wireless devices with different maximum transmission powers, where an asymmetric wireless link is very common. The energy consumption and packet loss rate are investigated through testbed experimentation. The proposed algorithm shows transmission efficiency which does not affect the packet loss rate. Moreover, it supports both environment change and the change of distance between nodes.

The traditional wireless network scheduling model has some problems, such as low energy efficiency, high delay and idle resources, which is difficult to meet the demand. In this paper, an energy efficiency scheduling model of smart campus wireless network based on multi-objective optimization is constructed, which adopts a three-layer architecture of spatio-temporal feature perception layer, multi-objective optimization layer and dynamic scheduling execution layer. By defining the multi-objective optimization problem, comprehensively considering the goals of energy consumption, delay and packet loss rate, and setting the constraints of coverage, quality of service (QoS) and spectrum resources, the optimization of network performance and energy efficiency is ensured. A hybrid optimization algorithm based on MOEA/D and Deep Reinforcement Learning (DRL) is proposed, which combines offline optimization and online adjustment to improve scheduling efficiency and adaptability. The experiment was carried out in the main campus of a 985 university. The results show that the model can significantly improve the energy efficiency while ensuring QoS. The energy consumption is reduced by 27.5% to 31.2%, the time delay is reduced by 24% to 55%, the packet loss rate is reduced by 49.5% to 63.4%, and the resource utilization rate is significantly improved. The average utilization rate of AP (access point) is increased by 49%, and the number of channel conflicts is reduced by 32.4%. In addition, the spatio-temporal dynamic adaptation mechanism effectively improves the traffic prediction accuracy and QoS stability, and verifies the effectiveness and practicability of the model in smart campus scenarios.

Aiming at the problems of high energy consumption and packet loss rate, long delay and poor fault tolerance of existing information transmission rate control methods, a practical vehicle-based passive vehicle communication information transmission rate control method is proposed. The average relative speed of vehicles and the number of neighbour vehicle nodes are selected as input parameters. The cluster head is selected by using fuzzy logic, and the cluster stability is set to the long duration of the cluster. The effective connection time model of the cluster vehicles' communication link is constructed. Taking the effective connection time model and channel capacity as constraints, the Shannon information concept and the maximum utility function are used to obtain the optimal information transmission rate of the current node. Experimental results show that the proposed method has lower-energy consumption and delay, less packet loss, and better fault-tolerant performance than the current research results.

Aiming at the problems of high energy consumption and packet loss rate, long delay and poor fault tolerance of existing information transmission rate control methods, a practical vehicle-based passive vehicle communication information transmission rate control method is proposed. The average relative speed of vehicles and the number of neighbour vehicle nodes are selected as input parameters. The cluster head is selected by using fuzzy logic, and the cluster stability is set to the long duration of the cluster. The effective connection time model of the cluster vehicles' communication link is constructed. Taking the effective connection time model and channel capacity as constraints, the Shannon information concept and the maximum utility function are used to obtain the optimal information transmission rate of the current node. Experimental results show that the proposed method has lower-energy consumption and delay, less packet loss, and better fault-tolerant performance than the current research results.

In recent trends, Cognitive Radio Sensor Networks (CRSNs) are investigated in‐depth and getting momentum in all types of applications. CRSN can make use of the underutilized frequency spectrum in a suitable manner. Due to the above‐mentioned advantage, the scholars have initiated to study of the domain of cognitive radio routing. Network congestion produces transmission delays and packet loss, as well as time and energy wasted on recovery. In order to fulfill the energy efficiency and network lifetime in CRSN, Congestion Centric Multi‐Objective Reptile Search Algorithm (CC‐MORSA)‐based Clustering and Routing are used. The main objective of proposed CC‐MORSA is to improve the lifetime by minimizing the distance among the designated Cluster Head nodes which creates the fitness function by multiple objectives like energy, distance, and load. This technique is appropriate for common sensor nodes in coordinated communications infrastructure and large networks. The simulation results are analyzed through MATALB in terms of remaining energy (999.5 J), average delay (0.36 s), Packet Delivery Ratio (99.8%), Energy Consumption (24.1 J), Throughput (0.98 Mbps), routing overhead (0.54), and Packet Loss Rate (0.2%). From the outcomes, it shows that the presented CC‐MORSA outperformed conventional Stability‐Aware Cluster‐based Routing and Drop Factor‐Based Energy Efficient Routing technique.

With the development of wireless communications technology and sensor technology, wireless sensor network (WSN) have been widely used in a wide variety of fields of fields. However, energy consumption has become the bottleneck in the development of wireless sensor networks. This paper studies the intelligence algorithm theory—ant colony algorithm, and combines the characteristics of wireless sensor networks, and proposes an enhance ant colony algorithm AODV (EACAODV). EACAOD algorithm based on a practical application case, and was proved by network simulation tool. Packet loss rate and energy consumption was given to contrast in NS2. Finally, simulation results show that EACAODV algorithm can improve the network utilization rate and reduce energy consumption.

<div class="htmlview paragraph">The rapid progress of industrialization and urbanization due to economic growth and concentration of social function in the urban areas have made the urban environment worse and worse. In most of urban cities, it has become more and more distinct that the increase of energy consumption is causing environmental problems including the temperature rise in the urban atmosphere(urban warming), and air pollution[<span class="xref">1</span>]. The present paper reports the results of field observation and three-dimensional simulation of urban warming in Tokyo metropolitan area. The three-dimensional governing equations in an urban atmospheric boundary layer were formulated by virtue of vorticity-velocity vector potential method. A particular attention was focused on the representation of a buoyancy term in equation of motion in the vertical direction, thereby describing the crossover and stratification effects near the ground surface. The vorticity-velocity potential method is superior from the view point of numerical stability and suitable for the simulation of an urban heat island. We first made a survey on the energy consumption in Tokyo metropolitan area. Next, the three-dimensional simulations were carried out using these data. The simulation results were then compared with the data of field observation of the surface temperature by automobiles. Further future prediction of urban warming was performed when the energy consumption rate is increased five times as large as the present rate, which will correspond to the year 2030 if the present consumption rate were maintained until then.</div>

Nodes in Mobile Ad-hoc Networks (MANETs) are battery powered and hence have limited life time. Due to excessive utilization a node may die which can result in energy depletion problem and thereby affect overall network performance. Local rate of energy consumption based on application (e.g.: audio, video, word, etc) can be monitored. We can estimate the remaining battery life (residual energy in a node) based on the application (rate of consumption). Thus early detection and avoidance of energy depletion problem is possible based on monitoring of power (rate of energy consumption) and remaining battery life (residual energy in a node). To avoid energy depletion problem due to excessive energy consumption at a higher rate, we introduce the mobile relays. These mobile relays reduce the power consumption in the node by balancing the load. As and when the rate of energy consumption based on the application returns to efficient levels, the mobile relay is released so that it can be made available for other critical nodes. This technique can be applied to any protocol used in Mobile Ad-hoc Networks (DSDV, DSR, AODV, etc). A history of the use of the Mobile Relay is maintained for further analysis of network performance.

For a moderate-size, multi-hop, sensor network, we present experimental measurements of radio energy consumption and packet reliability. We categorize the energy measurements by energy consumed in each radio state and for each traffic type. Packet reliability results are presented from a network and link perspective, whereas prior work only considered the former. We introduce a novel technique of application-aware radio duty cycling called on-demand spatial TDMA. When compared to the non-cycling case, this technique can achieve greater than an order of magnitude reduction in idle energy consumption, while not sacrificing reliability. We show end-to-end packet loss rates as low as 0.04 when averaged over the network. Even with substantial idle energy savings, we identify radio idling as the dominate energy consumer and overhearing as the dominate traffic type.

When mobile devices equipped with multiple wireless network interfaces access the Internet through Wi-Fi, 4G, and 5G, external factors such as radio waves can lead to an increased packet loss rate, resulting in a slowdown in communication speed. To address this issue, two solutions exist: BBR, a congestion control algorithm designed to reduce the impact of packet loss and bicast in multihomed networks. Bicast in multihomed networks leverages multiple networks for communication, allowing simultaneous transmission of the same packet across multiple networks to reduce packet loss rates and prevent communication speed reduction. This paper introduces a novel network architecture that uses QUIC and SDN, both of which can be implemented in the userland. This network architecture enables the realization of a multihomed network independent of the operating system, and the congestion control algorithm can be easily configured. Additionally, because QUIC lacks bicast capabilities for multihomed networks, this deficiency is addressed through SDN implementation. By using the proposed multihomed network, we measure communication speeds for unicast and bicast packets from the server when varying the packet loss rate. The results indicate that the communication speed could be maintained even with a 15% packet loss rate for unicast communication and 32% for bicast communication.

Due to the fact that the European Union is striving to achieve its sustainable development goals, in particular goal No. 7, which is to provide users with low-emission, and cheap access to, energy, this article’s aim is to verify whether there is a relationship between R&D expenditure and key energy variables in the EU countries in 2010–2020. Data on R&D expenditures incurred by the EU Member States in the period 2010–2020 were used for the research and were tested using the Autoregressive Distributed Lags Model (ARDL). The study identified a strong positive relationship between total R&D expenditure and the increase in energy consumption from renewable energy sources, and a smaller impact of total R&D expenditure as well as enterprise R&D expenditure on the increase in fossil energy consumption. Also noted was a weak relationship between R&D expenditure and electricity and gas prices for both household and non-household customers. The obtained results prove that in the context of the level of implementation of SDG No. 7 in the EU countries, R&D expenditure results in greater access to low-emission energy from renewable sources, but the achievement of the aforementioned sustainable development goal in other aspects (reduction in energy consumption from fossil fuels and ensuring lower price energy) is not possible with the current level of R&D expenditure.

The rapid development of urbanization has led to a rapid increase in total energy consumption. The proportion of domestic energy consumption to total energy consumption has gradually increased and has become the major driving force for energy consumption. With the pressure from urbanization and domestic energy consumption, it is necessary to study the impact of urbanization on domestic energy consumption of the regional level and to explore the function paths of these two factors. The findings are helpful to realize sustainable development based on the actual situation analysis, horizontal survey data and statistical yearbook panel data. The current situation and changing trends in domestic energy consumption of Shandong Province are systematically examined through field investigation and survey questionnaire. The time-series econometric model is applied to analyze the relationship between urbanization rate and total domestic energy consumption. The research results show that the total domestic energy consumption and urbanization rate of Shandong are generally increasing. The urbanization rate development and domestic energy consumption have a long-term stable and balanced relationship. An increase in urbanization rate can cause an increase in domestic energy consumption. There is a slight difference between the average total energy consumption levels of urban and rural residents, but their energy consumption structures differ a lot. These findings provide basic data support and reference for local governments to formulate energy- conservation and emission-reduction policies.

IPTV (Internet Protocol Television) provides interactive function, which greatly improves subjective experience of users. However, IP network is a best-effort network and does not guarantee a reliable connection, which makes video transmission based on IP network prone to problems. This paper focuses on the relationship between packet loss and video perception quality in IPTV transmission. Through subjective evaluation experiments, the influence of different packet loss rate and packet loss distributions (burst loss and random loss) are quantitatively studied. Experimental results show: When packet loss rate is the same, video with burst loss has a better quality than one with random loss. The proportion of burst loss in total packet loss increases, and subjective perception quality increases exponentially. Based on experimental results, this paper also designs an objective evaluation model of video quality based on packet loss rate and packet loss distribution.