scholarly journals A Reputation Value-Based Task-Sharing Strategy in Opportunistic Complex Social Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jia Wu ◽  
Fangfang Gou ◽  
Wangping Xiong ◽  
Xian Zhou
Keyword(s):  
Social Networks ◽  
Energy Consumption ◽  
Complex Networks ◽  
High Reliability ◽  
High Energy ◽  
Base Station ◽  
Particle Swarm Algorithm ◽  
Task Sharing ◽  
Sharing Strategy ◽  
Computationally Intensive

As the Internet of Things (IoT) smart mobile devices explode in complex opportunistic social networks, the amount of data in complex networks is increasing. Large amounts of data cause high latency, high energy consumption, and low-reliability issues when dealing with computationally intensive and latency-sensitive emerging mobile applications. Therefore, we propose a task-sharing strategy that comprehensively considers delay, energy consumption, and terminal reputation value (DERV) for this context. The model consists of a task-sharing decision model that integrates latency and energy consumption, and a reputation value-based model for the allocation of the computational resource game. The two submodels apply an improved particle swarm algorithm and a Lagrange multiplier, respectively. Mobile nodes in the complex social network are given the opportunity to make decisions so that they can choose to share computationally intensive, latency-sensitive computing tasks to base stations with greater computing power in the same network. At the same time, to prevent malicious competition from end nodes, the base station decides the allocation of computing resources based on a database of reputation values provided by a trusted authority. The simulation results show that the proposed strategy can meet the service requirements of low delay, low power consumption, and high reliability for emerging intelligent applications. It effectively realizes the overall optimized allocation of computation sharing resources and promotes the stable transmission of massive data in complex networks.

scholarly journals An improved cluster formation process in wireless sensor network to decrease energy consumption

2020 ◽  
Author(s):  
Hamid Reza Farahzadi ◽  
Mostafa Langarizadeh ◽  
Mohammad Mirhosseini ◽  
Seyed Ali Fatemi Aghda
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Information Transfer ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Death Time

AbstractWireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

scholarly journals A Study on Massive Mimo 5G Challenges

2020 ◽  
Author(s):  
Kanchana Devi A ◽  
Bhuvaneswari B
Keyword(s):  
Network Architecture ◽  
Massive Mimo ◽  
Channel Model ◽  
High Reliability ◽  
High Energy ◽  
Base Station ◽  
High Signal ◽  
Fifth Generation ◽  
5G Network ◽  
Mimo Technology

Massive MIMO is a advance of MIMO technology. M-MIMO use hundreds of Base station (BS) to simultaneously serve multiple users. It combines with millimeter wave (mmWave) to provide huge spectral efficient, high reliability and high energy efficiency. Massive MIMO gives huge antennas, high signal strength, less noise reduction and also using better channel model. This paper discusses the detail description of fifth generation (5G) network architecture and to improve massive MIMO in existing technology.

scholarly journals Lecr: Less Energy Consumption Routing in Internet of Things

2020 ◽  
Vol 8 (5) ◽  
pp. 855-859 ◽  
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Traffic Management ◽  
Routing Algorithm ◽  
High Energy ◽  
Base Station ◽  
Experimental Result ◽  
Battery Lifetime ◽  
Iot Devices ◽  
Information Collecting

Internet of Things (IoT) constitutes a network of various devices has an equipment with the mandatory facility of communication and optional facilities of sensing, information collecting, storage and processing. IoT network has been used for research and development purpose in many application areas such as military environment, traffic management, and e-healthcare system. IoT network was enormous in scale and complexity, mainly in terms of energy efficiency because battery lifetime is limited. The previous routing protocols for IoT are difficult and require a huge memory use and high energy consumption which are insufficient for IoT network processing. For that reason, an efficient routing algorithm needed to decrease energy consumption while communication. To tackle this problem, this paper proposes Less Energy Consumption Routing (LECR) algorithm. This algorithm reduces energy consumption using 4 ways in IoT, (1) Sleep and Wake up Scheduling, (2) Route Discovery in IoT Base Station (3) Less Power Consumption Route for Communication (4) Reduce Overhead while Routing. The experimental result proves the LECR algorithm reduces IoT devices battery drain and increases lifetime of the IoT network efficiently

scholarly journals Energy Efficient Cross Layer Based Multi-Hop Clustered Routing Protocol For Wireless Sensor Networks

2019 ◽  
Vol 8 (4) ◽  
pp. 11996-12003
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocols ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cross Layer ◽  
User Friendly

Wireless Sensor network becomes an essential part of Internet of things paradigm due their scalability, ease of deployment and user-friendly interface. However, certain issues like high energy consumption, low network lifetime and optimum quality of service requirement force researchers to develop new routing protocols. In WSNs, the routing protocols are utilized to obtain paths having high quality links and high residual energy nodes for forwarding data towards the sink. Clustering provide the better solution to the WSN challenges by creating access points in the form of cluster head (CH). However, CH must tolerate additional burden for coordinating network activities. After considering these issues, the proposed work designs a moth flame optimization (MFO) based Cross Layer Clustering Optimal (MFO-CLCO) algorithm to consequently optimize the network energy, network lifetime, network delay and network throughput. Multi-hop wireless communication between cluster heads (CHs) and base station (BS) is employed along with MFO to attain optimum path cost. The simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of energy consumption, network lifetime, delay and throughput.

Social and QoS based trust model for secure clustering for wireless body area network

2020 ◽  
pp. 002072092095313
Author(s):  
Sangeetha Ramaswamy ◽  
Jasmine Norman
Keyword(s):  
Energy Consumption ◽  
Service Providers ◽  
Wireless Body Area Network ◽  
High Energy ◽  
Trust Model ◽  
Base Station ◽  
Area Network ◽  
Body Area ◽  
Malicious Nodes ◽  
Main Challenge

Wireless Body Area Networks (WBAN) is an emerging technology, a subset of Wireless Sensor Network. WBAN is a collection of pieces of tiny wireless body sensors with small computational capability and communicates short distance using ZigBee or Bluetooth. The main application of WBAN is in healthcare industry like remote patient monitoring. The small pieces of sensor monitor health factors like body temperature, pulse rate, ECG, heart rate etc., and communicate it to the base station or central coordinator for aggregation or for data computation. The final data is communicated to remote monitoring devices through internet or cloud service providers. The main challenge of this technology is dead nodes due to high energy consumption with all the wireless node working on battery. Minimization of the energy consumption extends life of the network. Security is another major challenge. There are possibilities of internal attacks being executed by malicious nodes, creating problems for the network. This paper proposes a model which provides solution for extending the life span of the network by minimizing energy consumption and also proposes model to provide solution for internal soft attacks created within the network through calculation or trust, computation among nodes to identify malicious nodes with the help of social-and QoS-based trust computation for secure clustering and communication. The proposed model is compared with LEACH and LEACH-MM protocol and performance is measured with various parameters.

scholarly journals Energy-saving Scheme of 5G Base Station Based on LSTM Neural Network

2021 ◽  
Vol 2083 (3) ◽  
pp. 032026
Author(s):  
Yuxuan Wang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Power Saving ◽  
Original Data ◽  
High Energy ◽  
Base Station ◽  
Base Stations ◽  
Idle State ◽  
Single Station ◽  
Saving Effect

Abstract As China’s new infrastructure,5G has received national and social attention. 5G promotes economic to grow rapidly. But, the high energy consumption caused by the massive deployment of 5G base stations cannot be ignored. The total annual power consumption is expected to reach 243 billion degrees when the 5G base station is fully built. In the tidal scene, some 5G base station in an idle state still power fully, which causes great power waste. The historical volume of base station business data is used to train LSTM model, and predict the future base station business. When the business is lower than the threshold, the base station will be closed to avoid unnecessary power waste. And the LSTM model prediction results fits the original data ideally. By implementing the power saving strategy, the energy consumption of the base station is reduced by 18.97 %. A single station can save 1174 degrees of electricity yearly. It can be seen that the energy saving effect is remarkable.

scholarly journals IDBR: Iot Enabled Depth Base Routing Method for Underwater Wireless Sensor Network

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Umer Farooq ◽  
Mohib Ullah ◽  
Rafi Ullah Khan ◽  
Abdullah Alharbi ◽  
Muhammad Irfan Uddin ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Oil And Gas ◽  
High Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Network Stability ◽  
Simulation Based ◽  
Smart Farming ◽  
Major Application ◽  
Routing Method

Underwater wireless sensor networks (UWSNs) gained the attention of researchers due to their substantial applications in various fields. The major application areas of UWSN are environmental monitoring, underwater oil and gas extraction and military surveillance, smart farming, communication, and others. However, UWSNs are also prone to significant issues, such as limited network lifetime, the low processing capability of nodes, high energy consumption to run routing protocols, and difficult node replacement. Therefore, enhancing the lifetime of UWSN by reducing energy consumption and processing is a research issue. In this research, we proposed the IoT enabled depth base routing method (IDBR) to utilize energy efficiently. The performance of the proposed IDBR method is compared with conventional DBR protocol using simulation conducting in MATLAB. The performance of both the methods (i.e., IDBR and DBR) is evaluated in network energy consumption, the number of alive nodes, sink utilization, and end-to-end delay. The simulation-based experiment results show that IDBR consumes 27.7% less energy and increases network stability than the DBR. Similarly, the utilization of the surface sinks in IDBR is more as compared to DBR as in IDBR, and sinks work as relay forward data to the base station without processing which increases the power of field nodes. The proposed mechanism improves the network’s lifetime and increases the accessibility and security of the sensed data.

scholarly journals Hybrid Blockchain for IoT—Energy Analysis and Reward Plan

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 305
Author(s):  
Jiejun Hu ◽  
Martin J. Reed ◽  
Mays Al-Naday ◽  
Nikolaos Thomos
Keyword(s):  
Energy Consumption ◽  
High Energy ◽  
Byzantine Fault Tolerance ◽  
Public And Private ◽  
The Public ◽  
Iot Applications ◽  
Blockchain Technology ◽  
Puzzle Solving ◽  
Computationally Intensive ◽  
High Energy Consumption

Blockchain technology has brought significant advantages for security and trustworthiness, in particular for Internet of Things (IoT) applications where there are multiple organisations that need to verify data and ensure security of shared smart contracts. Blockchain technology offers security features by means of consensus mechanisms; two key consensus mechanisms are, Proof of Work (PoW) and Practical Byzantine Fault Tolerance (PBFT). While the PoW based mechanism is computationally intensive, due to the puzzle solving, the PBFT consensus mechanism is communication intensive due to the all-to-all messages; thereby, both may result in high energy consumption and, hence, there is a trade-off between the computation and the communication energy costs. In this paper, we propose a hybrid-blockchain (H-chain) framework appropriate for scenarios where multiple organizations exist and where the framework enables private transaction verification and public transaction sharing and audit, according to application needs. In particular, we study the energy consumption of the hybrid consensus mechanisms in H-chain. Moreover, this paper proposes a reward plan to incentivize the blockchain agents so that they make contributions to the H-chain while also considering the energy consumption. While the work is generally applicable to IoT applications, the paper illustrates the framework in a scenario which secures an IoT application connected using a software defined network (SDN). The evaluation results first provide a method to balance the public and private parts of the H-chain deployment according to network conditions, computation capability, verification complexity, among other parameters. The simulation results demonstrate that the reward plan can incentivize the blockchain agents to contribute to the H-chain considering the energy consumption of the hybrid consensus mechanism, this enables the proposed H-chain to achieve optimal social welfare.

scholarly journals Low-power and high-reliability scheduling algorithm based on sliding window

2020 ◽  
Author(s):  
Changyi Deng ◽  
Ruifeng Guo ◽  
Haotian Wu ◽  
Azhen Peng ◽  
Shaohua Du ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Time Allocation ◽  
High Reliability ◽  
Scheduling Algorithm ◽  
Sliding Window ◽  
High Energy ◽  
Cnc System ◽  
Open Cnc ◽  
Open Cnc System

To solve the problem of high energy consumption and poor reliability of open CNC systems, through optimizing the slack time allocation issues, a set of real-time tasks in the open CNC system was researched to minimize energy consumption while maintaining the reliability of open CNC system. A Low Power and Reliability Based on Sliding Window (LPRSW) algorithm was proposed.

scholarly journals AUTOMATED INSTALLATION FOR MILK COOLING USING A NATURAL COOLING AGENT

2021 ◽  
pp. 116-122
Author(s):  
V.V. Sadov ◽  
◽  
N.I. Kapustin ◽  
Keyword(s):  
Energy Consumption ◽  
High Reliability ◽  
Environmental Parameters ◽  
Operating Mode ◽  
Automatic Device ◽  
High Energy ◽  
Cooling Agent ◽  
Automated Installation ◽  
Direct Acting

In the chain from milk production to the sale of dairy products, the process of ensuring the required temperature is the main one. Moreover, to cool the milk, the tempera-ture of the cooling agent should be above milk freezing. Taking into account the fact that the process of cooling and storing milk in a chilled form imposes strict requirements for reliability and quality of management on farms, compressor refrigeration units have been used in recent years despite high energy consumption. Theanalysis of technical solu-tions in this direction by the example of farms of the Altai and Novosibirsk Regions showed that during the greatest boom of the livestock industry, film-tray, spray-cooling tow-er, and pipe and tank installations using natural cooling agents were widely used. Taking into account the climatic features of the area when choosing water cooling units as an intermediate coolant made it possible to significantly reduce energy consumption for milk cooling especially in winter. However, the complexity of controlling the process of preparing the intermediate coolant with unpredictable environmental parameters did not allow for high reliability and quality of manual control. A device for cooling the in-termediate coolant with the main -natural cold in winter with an automatic direct-acting regulator that provides the required operating mode of the cooling unit is proposed. The variants of automatic device operation both when the outdoor air temperature decreases and increases are con-sidered. An automated installation for cooling the interme-diate coolant with natural cold may be recommended both for cattle farms and processing enterprises

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