Edge computing aims to make internet-based services and remote computing power close to the user by placing information technology (IT) infrastructure at the network edges. This proximity provides data centers with low-latency and context-aware services. Edge computing power consumption is mainly caused by data centers, network equipment, and user equipment. With edge computing (EC), energy management platforms for residential, industrial, and commercial sectors are built. Energy efficiency is considered to be one of the key aspects of edge power constraints. This paper provides the state of the art of power consumption and energy management for edge computing, the computation offloading methods, and more important highlights the power efficiency of edge computing systems. Furthermore, renewable energy and related concepts will also be explored and presented since no human participation is required in replacing or recharging batteries when using such energy sources. Based on such study, a recommendation is to develop a dynamic system for energy management in real-time with the assessment of local renewable energy so that the system be reliable with minimum power consumption. Also, regarding energy management, we recommend providing backup energy sources (or using more than one energy source) or (a hybrid technique).
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
Approach to minimizing consumption of energy in wireless sensor networks IJECEIAES
The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Development of methods for managing energy consumption and energy efficiency...IJECEIAES
The work aims to analyze and examine renewable energy sources (RES) to develop interconnected energy efficiency and energy consumption management system by integrating the software-defined machine-tomachine (M2M) communication. The article’s objectives include analysis of using RES as alternative raw materials for electricity production, the study of intelligent technologies for integrating RES into monitoring and control systems, research of devices and methods for monitoring energy production and consumption, analysis of sensor application for automation of control systems in the energy sector, a study of data transmission and information processing rates. The study results showed that the data transfer rate was delayed by 6 seconds to process 1,000 MB of information. It has been proven that wind energy can be used most efficiently within a 12-hour daily cycle, in contrast to tidal energy and solar energy. It is shown that due to the cyclical nature of obtaining energy from renewable sources, they do not fully provide energy to a large city, on the basis of which it is necessary to additionally use other energy sources. Three different types of power generation facilities were examined and compared. Wind farms were found to have the highest potential for electricity generation, amounting to 1,600-1,700 kW.
A SURVEY ON DYNAMIC ENERGY MANAGEMENT AT VIRTUALIZATION LEVEL IN CLOUD DATA C...cscpconf
Data centers have become indispensable infrastructure for data storage and facilitating the development of diversified network services and applications offered by the cloud. Rapid
development of these applications and services imposes various resource demands that results in increased energy consumption. This necessitates the development of efficient energy management techniques in data center not only for operational cost but also to reduce the amount of heat released from storage devices. Virtualization is a powerful tool for energy
management that achieves efficient utilization of data center resources. Though, energy management at data centers can be static or dynamic, virtualization level energy management
techniques contributes more energy conservation than hardware level. This paper surveys various issues related to dynamic energy management at virtualization level in cloud data
centers.
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
Approach to minimizing consumption of energy in wireless sensor networks IJECEIAES
The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Novel Optimization to Reduce Power Drainage in Mobile Devices for Multicarrie...IJECEIAES
With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
Development of methods for managing energy consumption and energy efficiency...IJECEIAES
The work aims to analyze and examine renewable energy sources (RES) to develop interconnected energy efficiency and energy consumption management system by integrating the software-defined machine-tomachine (M2M) communication. The article’s objectives include analysis of using RES as alternative raw materials for electricity production, the study of intelligent technologies for integrating RES into monitoring and control systems, research of devices and methods for monitoring energy production and consumption, analysis of sensor application for automation of control systems in the energy sector, a study of data transmission and information processing rates. The study results showed that the data transfer rate was delayed by 6 seconds to process 1,000 MB of information. It has been proven that wind energy can be used most efficiently within a 12-hour daily cycle, in contrast to tidal energy and solar energy. It is shown that due to the cyclical nature of obtaining energy from renewable sources, they do not fully provide energy to a large city, on the basis of which it is necessary to additionally use other energy sources. Three different types of power generation facilities were examined and compared. Wind farms were found to have the highest potential for electricity generation, amounting to 1,600-1,700 kW.
A SURVEY ON DYNAMIC ENERGY MANAGEMENT AT VIRTUALIZATION LEVEL IN CLOUD DATA C...cscpconf
Data centers have become indispensable infrastructure for data storage and facilitating the development of diversified network services and applications offered by the cloud. Rapid
development of these applications and services imposes various resource demands that results in increased energy consumption. This necessitates the development of efficient energy management techniques in data center not only for operational cost but also to reduce the amount of heat released from storage devices. Virtualization is a powerful tool for energy
management that achieves efficient utilization of data center resources. Though, energy management at data centers can be static or dynamic, virtualization level energy management
techniques contributes more energy conservation than hardware level. This paper surveys various issues related to dynamic energy management at virtualization level in cloud data
centers.
A survey on dynamic energy management at virtualization level in cloud data c...csandit
Data centers have become indispensable infrastructure for data storage and facilitating the
development of diversified network services and applications offered by the cloud. Rapid
development of these applications and services imposes various resource demands that results
in increased energy consumption. This necessitates the development of efficient energy
management techniques in data center not only for operational cost but also to reduce the
amount of heat released from storage devices. Virtualization is a powerful tool for energy
management that achieves efficient utilization of data center resources. Though, energy
management at data centers can be static or dynamic, virtualization level energy management
techniques contributes more energy conservation than hardware level. This paper surveys
various issues related to dynamic energy management at virtualization level in cloud data
centers.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A LOW-ENERGY DATA AGGREGATION PROTOCOL USING AN EMERGENCY EFFICIENT HYBRID ME...IJCNCJournal
Recent wireless sensor network focused on developing communication networks with minimal power and cost. To achieve this, several techniques have been developed to monitor a completely wireless sensor network. Generally, in the WSN network, communication is established between the source nodes and the destination node with an abundant number of hops, an activity which consumes much energy. The node existing between source and destination nodes consumes energy for transmission of data and maximize network lifetime. To overcome this issue, a new Emergency Efficient Hybrid Medium Access Control (EEHMAC) protocol is presented to reduce consumption of energy among a specific group of WSNs which will increase the network lifetime. The proposed model makes a residual battery is utilized for effective transmission of data with minimal power consumption. Compared with other models, the experimental results strongly showed that our model is not only able to reduce network lifetime but also to increase the overall network performance.
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGSIJCNCJournal
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR
P LACEMENT O F E NERGY A WARE W IRELESS M ESH N ODES F OR E-L EARNING...IJCI JOURNAL
Energy efficiency solutions are more vital for Gree
n Mesh Network (GMN) campuses. Today students are
benefited using these e-learning methodologies. Ren
ewable energies such as solar, wind, hydro has
tremendous applications on energy efficient wireles
s networks for sustaining the ever growing traffic
demands. One of the major issues in designing a GMN
is minimizing the number of deployed mesh routers
and gateways and satisfying the sustainable QOS bas
ed energy constraints. During low traffic periods t
he
mesh routers are switched to power save or sleep mo
de. In this paper we have mathematically formulated
a
single objective function with multi constraints to
optimize the energy. The objective is to place min
imum
number of Mesh routers and gateways in a set of can
didate location. The mesh nodes are powered using
the solar energy to meet the traffic demands. Two g
lobal optimisation algorithms are compared in this
paper to optimize the energy sustainability, to gua
rantee seamless connectivity
Recent many works have concentrated on
dynamically turning on/off some base stations (BSs) in order to
improve energy efficiency in radio access networks (RANs). In
this survey, we broaden the research over BS switching
operations, which should competition up with traffic load
variations. The proposed method formulate the traffic variations
as a Markov decision process which should differ from dynamic
traffic loads which are still quite challenging to precisely forecast.
A reinforcement learning framework based BS switching
operation scheme was designed in order to minimize the energy
consumption of RANs. Furthermore a transfer actor-critic
algorithm (TACT) is used to speed up the ongoing learning
process, which utilizes the transferred learning expertise in
historical periods or neighboring regions. The proposed TACT
algorithm performs jumpstart and validates the feasibility of
significant energy efficiency increment.
Energy Splitting for SWIPT in QoS-constraint MTC Network: A Non-Cooperative G...IJCNCJournal
This paper studies the emerging wireless energy harvesting algorithm dedicated for machine type communication (MTC) in a typical cellular network where one transmitter (e.g. the base station, a hybrid access point) with constant power supply communicates with a set of users (e.g. wearable devices, sensors). In the downlink direction, the information transmission and power transfer are conducted simultaneously by the base station. Since MTC only transmits several bits control signal in the downlink direction, the received signal power can be split into two parts at the receiver side. One is used for information decoding and the other part is used for energy harvesting. Since we assume that the users are without power supply or battery, the uplink transmission power is totally from the energy harvesting. Then, the users are able to transmit their measured or collected data to the base station in the uplink direction. Game theory is used in this paper to exploit the optimal ratio for energy harvesting of each user since power splitting scheme is adopted. The results show that this proposed algorithm is capable of modifying dynamically to achieve the prescribed target downlink decoding signal-to-noise plus interference ratio (SINR) which ensures the high reliability of MTC while maximizing the uplink throughput.
EEIT2-F: energy-efficient aware IT2-fuzzy based clustering protocol in wirel...IJECEIAES
Improving the network lifetime is still a vital challenge because most wireless sensor networks (WSNs) run in an unreached environment and offer almost impossible human access and tracking. Clustering is one of the most effective methods for ensuring that the relevant device process takes place to improve network scalability, decrease energy consumption and maintain an extended network lifetime. Many researches have been developed on the numerous effective clustering algorithms to address this problem. Such algorithms almost dominate on the cluster head (CH) selection and cluster formation; using the intelligent type1 fuzzy-logic (T1-FL) scheme. In this paper, we suggest an interval type2 FL (IT2-FL) methodology that assumes uncertain levels of a decision to be more efficient than the T1-FL model. It is the so-called energy-efficient interval type2 fuzzy (EEIT2-F) low energy adaptive clustering hierarchical (LEACH) protocol. The IT2-FL system depends on three inputs of the residual energy of each node, the node distance from the base station (sink node), and the centrality of each node. Accordingly, the simulation results show that the suggested clustering protocol outperforms the other existing proposals in terms of energy consumption and network lifetime.
An energy efficient optimized cluster establishment methodology for sensor n...nooriasukmaningtyas
The compatibility of WSN is with various applications such as; healthcar eand environmental monitoring. Whereas nodes present in that network have limited ‘battery-life’ that cause difficulty to replace and recharge those batteries after deployment. Energy efficiency is a major problem in the present situation. In present, many algorithms based on energy efficiency have been introduced to improvise the conservation of energy in WSN. The LEACH algorithm improvises the network lifetime in comparison to direct transmission and multi-hop, but it has several limitations. The selection of CHs can be randomly done that doesn’t confirm the optimal solution, proper distribution and it lacks during complete network management. The centralized EE optimized cluster establishment approach (OCEA) for sensor nodes is proposed to decrease the average energy dissipation and provide significant improvement. The proposed EE WSN model with the sensor nodes is examined under a real-time scenario and it is compared with stateof-art techniques where it balances the energy consumption of the network and decreasing the cluster head number.
An energy optimization with improved QOS approach for adaptive cloud resources IJECEIAES
In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (퐴퐶푅푅) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model 퐴퐶푅푅 in terms of average run time, power consumption and average power required than any other state-of-art techniques.
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Net...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.
DESIGNING AN ENERGY EFFICIENT CLUSTERING IN HETEROGENEOUS WIRELESS SENSOR NET...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical
issue that degrades the network performance. Recharging and providing security to the sensor devices is
very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an
important and suitable approach to increase energy efficiency and transmitting secured data which in turn
enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC)
works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the
rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the
network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on
the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all
the cluster heads are formed at a time and selected on rotation based on considering the highest energy of
the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum
flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access
(CSMA), a contention window based protocol is used at the MAC layer for collision detection and to
provide channel access prioritization to HWSN of different traffic classes with reduction in End to End
delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the
cluster head for transmission without depleting the energy. Simulation parameters of the proposed system
such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing
system.
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
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A survey on dynamic energy management at virtualization level in cloud data c...csandit
Data centers have become indispensable infrastructure for data storage and facilitating the
development of diversified network services and applications offered by the cloud. Rapid
development of these applications and services imposes various resource demands that results
in increased energy consumption. This necessitates the development of efficient energy
management techniques in data center not only for operational cost but also to reduce the
amount of heat released from storage devices. Virtualization is a powerful tool for energy
management that achieves efficient utilization of data center resources. Though, energy
management at data centers can be static or dynamic, virtualization level energy management
techniques contributes more energy conservation than hardware level. This paper surveys
various issues related to dynamic energy management at virtualization level in cloud data
centers.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A LOW-ENERGY DATA AGGREGATION PROTOCOL USING AN EMERGENCY EFFICIENT HYBRID ME...IJCNCJournal
Recent wireless sensor network focused on developing communication networks with minimal power and cost. To achieve this, several techniques have been developed to monitor a completely wireless sensor network. Generally, in the WSN network, communication is established between the source nodes and the destination node with an abundant number of hops, an activity which consumes much energy. The node existing between source and destination nodes consumes energy for transmission of data and maximize network lifetime. To overcome this issue, a new Emergency Efficient Hybrid Medium Access Control (EEHMAC) protocol is presented to reduce consumption of energy among a specific group of WSNs which will increase the network lifetime. The proposed model makes a residual battery is utilized for effective transmission of data with minimal power consumption. Compared with other models, the experimental results strongly showed that our model is not only able to reduce network lifetime but also to increase the overall network performance.
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGSIJCNCJournal
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR
P LACEMENT O F E NERGY A WARE W IRELESS M ESH N ODES F OR E-L EARNING...IJCI JOURNAL
Energy efficiency solutions are more vital for Gree
n Mesh Network (GMN) campuses. Today students are
benefited using these e-learning methodologies. Ren
ewable energies such as solar, wind, hydro has
tremendous applications on energy efficient wireles
s networks for sustaining the ever growing traffic
demands. One of the major issues in designing a GMN
is minimizing the number of deployed mesh routers
and gateways and satisfying the sustainable QOS bas
ed energy constraints. During low traffic periods t
he
mesh routers are switched to power save or sleep mo
de. In this paper we have mathematically formulated
a
single objective function with multi constraints to
optimize the energy. The objective is to place min
imum
number of Mesh routers and gateways in a set of can
didate location. The mesh nodes are powered using
the solar energy to meet the traffic demands. Two g
lobal optimisation algorithms are compared in this
paper to optimize the energy sustainability, to gua
rantee seamless connectivity
Recent many works have concentrated on
dynamically turning on/off some base stations (BSs) in order to
improve energy efficiency in radio access networks (RANs). In
this survey, we broaden the research over BS switching
operations, which should competition up with traffic load
variations. The proposed method formulate the traffic variations
as a Markov decision process which should differ from dynamic
traffic loads which are still quite challenging to precisely forecast.
A reinforcement learning framework based BS switching
operation scheme was designed in order to minimize the energy
consumption of RANs. Furthermore a transfer actor-critic
algorithm (TACT) is used to speed up the ongoing learning
process, which utilizes the transferred learning expertise in
historical periods or neighboring regions. The proposed TACT
algorithm performs jumpstart and validates the feasibility of
significant energy efficiency increment.
Energy Splitting for SWIPT in QoS-constraint MTC Network: A Non-Cooperative G...IJCNCJournal
This paper studies the emerging wireless energy harvesting algorithm dedicated for machine type communication (MTC) in a typical cellular network where one transmitter (e.g. the base station, a hybrid access point) with constant power supply communicates with a set of users (e.g. wearable devices, sensors). In the downlink direction, the information transmission and power transfer are conducted simultaneously by the base station. Since MTC only transmits several bits control signal in the downlink direction, the received signal power can be split into two parts at the receiver side. One is used for information decoding and the other part is used for energy harvesting. Since we assume that the users are without power supply or battery, the uplink transmission power is totally from the energy harvesting. Then, the users are able to transmit their measured or collected data to the base station in the uplink direction. Game theory is used in this paper to exploit the optimal ratio for energy harvesting of each user since power splitting scheme is adopted. The results show that this proposed algorithm is capable of modifying dynamically to achieve the prescribed target downlink decoding signal-to-noise plus interference ratio (SINR) which ensures the high reliability of MTC while maximizing the uplink throughput.
EEIT2-F: energy-efficient aware IT2-fuzzy based clustering protocol in wirel...IJECEIAES
Improving the network lifetime is still a vital challenge because most wireless sensor networks (WSNs) run in an unreached environment and offer almost impossible human access and tracking. Clustering is one of the most effective methods for ensuring that the relevant device process takes place to improve network scalability, decrease energy consumption and maintain an extended network lifetime. Many researches have been developed on the numerous effective clustering algorithms to address this problem. Such algorithms almost dominate on the cluster head (CH) selection and cluster formation; using the intelligent type1 fuzzy-logic (T1-FL) scheme. In this paper, we suggest an interval type2 FL (IT2-FL) methodology that assumes uncertain levels of a decision to be more efficient than the T1-FL model. It is the so-called energy-efficient interval type2 fuzzy (EEIT2-F) low energy adaptive clustering hierarchical (LEACH) protocol. The IT2-FL system depends on three inputs of the residual energy of each node, the node distance from the base station (sink node), and the centrality of each node. Accordingly, the simulation results show that the suggested clustering protocol outperforms the other existing proposals in terms of energy consumption and network lifetime.
An energy efficient optimized cluster establishment methodology for sensor n...nooriasukmaningtyas
The compatibility of WSN is with various applications such as; healthcar eand environmental monitoring. Whereas nodes present in that network have limited ‘battery-life’ that cause difficulty to replace and recharge those batteries after deployment. Energy efficiency is a major problem in the present situation. In present, many algorithms based on energy efficiency have been introduced to improvise the conservation of energy in WSN. The LEACH algorithm improvises the network lifetime in comparison to direct transmission and multi-hop, but it has several limitations. The selection of CHs can be randomly done that doesn’t confirm the optimal solution, proper distribution and it lacks during complete network management. The centralized EE optimized cluster establishment approach (OCEA) for sensor nodes is proposed to decrease the average energy dissipation and provide significant improvement. The proposed EE WSN model with the sensor nodes is examined under a real-time scenario and it is compared with stateof-art techniques where it balances the energy consumption of the network and decreasing the cluster head number.
An energy optimization with improved QOS approach for adaptive cloud resources IJECEIAES
In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (퐴퐶푅푅) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model 퐴퐶푅푅 in terms of average run time, power consumption and average power required than any other state-of-art techniques.
Designing an Energy Efficient Clustering in Heterogeneous Wireless Sensor Net...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical issue that degrades the network performance. Recharging and providing security to the sensor devices is very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an important and suitable approach to increase energy efficiency and transmitting secured data which in turn enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC) works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all the cluster heads are formed at a time and selected on rotation based on considering the highest energy of the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access (CSMA), a contention window based protocol is used at the MAC layer for collision detection and to provide channel access prioritization to HWSN of different traffic classes with reduction in End to End delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the cluster head for transmission without depleting the energy. Simulation parameters of the proposed system such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing system.
DESIGNING AN ENERGY EFFICIENT CLUSTERING IN HETEROGENEOUS WIRELESS SENSOR NET...IJCNCJournal
Designing an energy-efficient scheme in a Heterogeneous Wireless Sensor Network (HWSN) is a critical
issue that degrades the network performance. Recharging and providing security to the sensor devices is
very difficult in an unattended environment once the energy is drained off. A Clustering scheme is an
important and suitable approach to increase energy efficiency and transmitting secured data which in turn
enhances the performance in the network. The proposed algorithm Energy Efficient Clustering (EEC)
works for optimum energy utilization in sensor nodes. The algorithm is proposed by combining the
rotation-based clustering and energy-saving mechanism for avoiding the node failure and prolonging the
network lifetime. This shows MAC layer scheduling is based on optimum energy utilization depending on
the residual energy. In the proposed work, a densely populated network is partitioned into clusters and all
the cluster heads are formed at a time and selected on rotation based on considering the highest energy of
the sensor nodes. Other cluster members are accommodated in a cluster based on Basic Cost Maximum
flow (BCMF) to allow the cluster head for transmitting the secured data. Carrier Sense Multiple Access
(CSMA), a contention window based protocol is used at the MAC layer for collision detection and to
provide channel access prioritization to HWSN of different traffic classes with reduction in End to End
delay, energy consumption, and improved throughput and Packet delivery ratio(PDR) and allowing the
cluster head for transmission without depleting the energy. Simulation parameters of the proposed system
such as Throughput, Energy, and Packet Delivery Ratio are obtained and compared with the existing
system.
Similar to Power consumption and energy management for edge computing: state of the art (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
TOP 10 B TECH COLLEGES IN JAIPUR 2024.pptxnikitacareer3
Looking for the best engineering colleges in Jaipur for 2024?
Check out our list of the top 10 B.Tech colleges to help you make the right choice for your future career!
1) MNIT
2) MANIPAL UNIV
3) LNMIIT
4) NIMS UNIV
5) JECRC
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7) BIT JAIPUR
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9) AMITY UNIV.
10) JNU
TO KNOW MORE ABOUT COLLEGES, FEES AND PLACEMENT, WATCH THE FULL VIDEO GIVEN BELOW ON "TOP 10 B TECH COLLEGES IN JAIPUR"
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Power consumption and energy management for edge computing: state of the art
1. TELKOMNIKA Telecommunication Computing Electronics and Control
Vol. 21, No. 4, August 2023, pp. 836~845
ISSN: 1693-6930, DOI: 10.12928/TELKOMNIKA.v21i4.24350 836
Journal homepage: http://telkomnika.uad.ac.id
Power consumption and energy management for edge
computing: state of the art
Tawfeeq E. Abdoulabbas1
, Sawsan M. Mahmoud2
1
Department of Electrical Engineering, Faculty of Engineering, University of Mustansiriyah, Baghdad, Iraq
2
Department of Computer Engineering, Faculty of Engineering, University of Mustansiriyah, Baghdad, Iraq
Article Info ABSTRACT
Article history:
Received Aug 04, 2022
Revised Dec 13, 2022
Accepted Feb 16, 2023
Edge computing aims to make internet-based services and remote computing
power close to the user by placing information technology (IT) infrastructure
at the network edges. This proximity provides data centers with low-latency
and context-aware services. Edge computing power consumption is mainly
caused by data centers, network equipment, and user equipment. With edge
computing (EC), energy management platforms for residential, industrial, and
commercial sectors are built. Energy efficiency is considered to be one of the
key aspects of edge power constraints. This paper provides the state of the art
of power consumption and energy management for edge computing, the
computation offloading methods, and more important highlights the power
efficiency of edge computing systems. Furthermore, renewable energy and
related concepts will also be explored and presented since no human
participation is required in replacing or recharging batteries when using such
energy sources. Based on such study, a recommendation is to develop a
dynamic system for energy management in real-time with the assessment of
local renewable energy so that the system be reliable with minimum power
consumption. Also, regarding energy management, we recommend providing
backup energy sources (or using more than one energy source) or (a hybrid
technique).
Keywords:
Edge computing
Energy efficiency
Offloading manager
Power management
This is an open access article under the CC BY-SA license.
Corresponding Author:
Sawsan M. Mahmoud
Department of Computer Engineering, Faculty of Engineering, University of Mustansiriyah
Baghdad, Iraq
Email: sawsan.mahmoud@uomustansiriyah.edu.iq
1. INTRODUCTION
Using edge computing (EC) over cloud computing (CC) provides some improvements and extension
capabilities and also there is ensuring of low latency within the service. The Internet of Things (IoT) uses a
variety of devices to collect real-time data, exchange information, store data, make computations, and provide
services. IoT technology is developing rapidly, but on the other hand, it is constrained by its limited power
sources with the devices of power demanded that must be reduced to ensure sustainable operation. It is good
to use special technologies such as compressed sensing and transmitting data to provide devices of low-power
consumption. From an architectural point of view, these devices must be energy efficient and require treatments
such as energy management with low energy [1]. Energy management can be viewed as a set of techniques for
controlling or managing multiple power sources to provide efficient power delivery in networked systems and
to ensure continuous operating conditions in spite of the available limited power sources. Power management
schemes can be divided into two aspects; energy supplying and energy consuming aspects. Energy supply
related to the characteristics of the sources required for supplying and transferring checks, e.g., sensor nodes are
often powered by connected batteries to ensure energy-efficient operation of the network, but these batteries have
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limited harvesting capacity and sometimes need to be replaced or recharged, so the management is required with
this situation to provide an alternative option for this power supply [2]. On the other hand, the energy consumption
should be determined so that a suitable energy management method could be specified. For example, smart
mobile devices (SMDs) typically have limited capacity processing and fixed battery energy. But there is a lot
of power consumption needed for tasks computing in the mobile edge computing (MEC) server [3]. For that
reason, a method like computation offloading is needed to minimize the overall energy consumption. Our
contributions to this paper are stated as:
− Studying and highlighting the performance of energy efficiency (EE) in EC and MEC to infer the
optimization of EC systems.
− Discuss various energy management mechanisms and make an overall insight classification upon them.
− Studying and explaining the offloading technique and the main computations of offloading techniques.
− Introducing the concepts of renewable energy and green energy as energy harvesting (EH) for mobile
along with challenges like resource allocation for green energy and computation offloading.
This paper is structured as: in the next section, we discuss the EE and its enhancement methods
according to different aspect layers involving the discussion of the green energy and renewable energy powered
MEC System. Section 3 will present the fundamentals of the offloading techniques in detail. Finally, section 5
concludes and lists some recommendations from the paper.
2. ENERGY EFFICIENCY
In general, EE is defined as the ability of a system to perform a specified task like transferring a bulk
of data traffic with saving power to meet the quality of services needed for a given service i.e., performing the
same task to produce the same result but with less energy needed. With the edge computing the total amount
of data traversing the network is reduced so the energy consumption is decreased which improve EE. An EE
metric is expressed as [4]:
𝜂 =
𝑜𝑢𝑡𝑝𝑢𝑡 𝑝𝑜𝑤𝑒𝑟
𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑 𝑝𝑜𝑤𝑒𝑟
; 𝑜𝑟 𝜂 =
𝑝𝑜𝑤𝑒𝑟
𝑡𝑟𝑎𝑓𝑓𝑖𝑐
; 𝑜𝑟 𝐸𝐸𝑈𝐸 =
𝑃𝑈𝐸
𝑇𝑈𝐸
[𝑊/𝑏𝑝𝑠]𝑜𝑟[𝐽/𝑏𝑖𝑡] (1)
The meaning of EE depends on the way of considering of the power of each part. For example, 𝑃𝑈𝐸
is the power of the mobile terminal(s) and 𝑇𝑈𝐸 is the power of traffic (at the user level). With the increasing
services required at the edge network of EC infrastructure, this will lead to the growth of energy demand.
For this reason, EE is one of the most important things in the designing of the EC system [5]. It can be seen
that the EE of a data center in the cloud is greater than that with the edge data centers (DCs). Also, in IoT
applications, sending computational tasks to the edge of the server have EE better than in the cloud. But on the
other side, the network latency of the cloud system is greater with any workloads assigned (far users from
DCs). These facts were investigated in [6] by introducing a way of edge/cloud energy management for wide
area network (WAN) using a network algorithm based on a software-defined network (SDN) with studying the
interchange of energy and the challenge for both types (edge/cloud). It has been shown that edge traffic can
handle the latency problem considering the short paths of the infrastructure of the edge network dependent.
2.1. Energy efficiency enhancement on EC
Much research is done to solve the difficulties associated with the limited battery capacity and enhance
the EE on EC. A survey in [1] presented a way of multiple batteries source-driven schemes of energy consumption
are used to ensure more EE network operation and get continuous energy preservation. EH can be used as a
conservation power source with battery supplying. From that sturdy, the wireless sensor network (WSN) is
classified to be a high level of energy management, and a wireless transferring energy is introduced as another
feeding to ordinary batteries [1]. EC can be studied as three-layers as shown in Figure 1 [2]. The figure illustrates
the layout of the process of EE enhancement on EC.
Figure 1. Energy efficiency enhancement layout
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2.1.1. Enhancing at the top cloud layer
The remote computation capacity at the edge of MEC networks is very close to the SMDs work nature
of bounded capacity processing and limited battery power. Many computations and jobs consume a lot of energy
so the solution is to offload these jobs to the MEC server especially when the battery is run out. The following
issues should be taken into account when the offloading is chosen [2]: wireless network state, the number of
SMDs, radio resources accessibility, and local battery power availability. A multi-user MEC system is
proposed in [3] where an increasing demand for computation offloading by multiple SMDs was well-noted.
The authors studied the overall energy consumption reduction by introducing an optimization criterion, taking
into account the battery’s lifetime. The optimization decision depends on some parameters such as offloading,
radio, and local resource computational allocation. Resource partitioning and a heuristic approach are
suggested to minimize the overall energy. In [7], it has been shown that the distribution of tasks and IoT devices
over multi-computation elements need more energy consumption compared with the centralized scheme.
A scheme which was proposed by Jalali et al. [8] studied the nano data centers (nDCs) models (or peer to peer
P2P scheme) energy consumption by dividing the network energy consumption according to the flow and time
of shared and unshared equipment usage. Energy analyzing has been done for applications that running over
DC either under cloud centralized DC or fog mode decentralized nano DCs. The results demonstrate that a
higher EE may be in the Fog mode. In addition, the applications which generate and distribute huge data near
users (i.e., edge networks) can facilitate the way for saving energy. Moreover, the number of hobs from the user
to the DC servers has less affecting on the whole energy demand. It has been shown that using nano servers can
give the best energy saving with the applications like video surveillance. For this case, it is preferred to allocate
data near the requested user because it needs a low rate of access data. So, in cloud applications, the centralized
DCs and nano servers together can give the best EE for content storage and distribution [8]. For the energy
consumed by equipment versus accessing data according to different locations, it is shown that the lower power
of (core/edge) will be for core-local DC than that of other types due to less distance from the user. Also, for the
energy consumption of IoT applications running from the cloud /fog with various computations, the IoT needs
more energy (transmission and device) where it will be lower for fog and edge of decentralized type. This
happened due to the centralized data center with the cloud system [9].
2.1.2. Enhancement at the edge server layer
Energy is considered to be an essential factor in this middle layer of the EC approach, servers might
be located in a private room or run on battery packs. Consequently, several power management systems have
been suggested to reduce the energy consumption of edge servers while still assuring their performance in
order to give a greater level of availability. We provide an overview of the following key tactics employed
recently in EC systems’ edge server layer.
a) The low-power management system strategies
The low-power management system strategies are mainly used at the edge servers in EC recently [2].
Such a system type is called cloudlets which are a small data center deployed usually away from mobile devices
at one wireless hop. For instance, small clouds at the edge called tactical cloudlet are proposed in [10] where
the energy consumption is analyzed via a virtual machine (VM) approach. Then it was appreciated the
provision of some cloudlet mechanisms. The maximum rate of energy depends on (VM compounding and the
provision of the on-demand VM). It was shown from the results that high EE can be found. Due to the
combination of a cloudlet pushed with a cached VM in a cloudlet environment, suitable resources can be
provided of offload computing tasks for multiple users [10]. Any IoT devices produce information that will be
processed in the extreme device, so the centralized servers will be released from the computational load, this
leads to decreasing overloading in the network traffic, and also minimizing the applications response time of
IoT devices. For wireless communication (which uses rechargeable sensor networks) there is a problem of high
energy consumption with these networks. Network utility maximization is another problem associated with the
dynamic-routing, so combined optimization is necessary to be done for routing and rate control with energy
management [11]. In a service-related to fog/edge architecture computing, enormous energy is saved by
performing data mining with an embedded system. Criteria of raw-data set orders so that the transmission data
will be reduced and eventually reduce the energy required [1].
b) Power management techniques with sustainable green energy power system
With the embedding of IoT technology, green energy management is developed with widespread
monitoring and reasonable communications in smart cities and sustainable energy. In [9] energy management
model based on IoT is implemented using deep reinforcement learning with EC. This model can improve the
performance of energy management and also decrease the execution time. The architecture includes mainly
three components: energy devices, energy edge servers, and energy cloud servers. The proposed model
supported with software contains four layers: sensing layer, network layer, cognition layer, and application
layer. Fog computing dual power sources are utilized in [12] to supply the system where the primary power
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source is solar energy to supply the fog nodes; the secondary power source is the backup battery. In that work,
a framework, which is involved with the overall analytical aspect, is proposed to get minimum energy
consumption of long-term cost. The framework can provide a high-quality service by using offloading data
with an energy-efficient mechanism for fog/cloud nodes. Also, in [13], a powered edge infrastructure is used
with a green energy of the rack-range type which is implemented with the help of “in-situ server systems using
renewable energy” InSURE system to pre-process data at the edge. InSURE source power is supplied by (solar
or wind) standalone power supply supported by a backup source like batteries. For this reason, efficient energy
flow control could be insured with the power supply of the edge server that is due to the buffering scheme of
energy, and a joint spatial-temporal power management mechanism is applied.
Green energy scheduling and other aspects such as task allocation, and VM migration joint are used in [14]
in minimizing the energy cost. To handle the complexity of the computation (with and transmission data) and
get the optimal solution, a heuristic algorithm approximating is proposed and attains a much more suitable
optimal solution and shows actively more reduction in energy consumption. In that algorithm, the energy
consumption might also be affected by the location of the VM by considering the location-related attenuation
ratio during transmission [14]. The distribution of the resources and devices (e.g., base stations (BS)) will be
managed at a network edge. In this pattern, the applications that need low latency can be implemented at the
network edge. Devices topology will make EC an ideal EE platform, so it has an impact on the green energy
distribution of EE computing. It is necessary to increase the available green energy so that to get minimum
brown energy consumption. This will need concentration job allocation and careful energy scheduling to
combine the energy provision with the required demand.
As we know, MEC servers have data centers that are small-scale compared with the data centers in
the cloud. So that, each server consumes less energy. Computation workload patterns may have a problem with
resource management and it needs some optimization and assessment approaches. So, to achieve green MEC,
different approaches are developed [15]. For example, dynamic right sizing, geographical load balancing, and
designing MEC use renewable energy.
c) Dynamic right-sizing
The energy consumption at MEC servers can be computed as [15]:
𝐸𝑠 = 𝛼. 𝐸𝑚𝑎𝑥 + (1 − 𝛼)𝑢 (2)
Where, 𝐸𝑚𝑎𝑥 is the peak demand server energy; 𝛼: the percentage of the inactive system energy; 𝑢: central
processing unit (CPU) utilization. It can be shown from the above equation when there is a light load; the servers
are worked in an inactive mode for EE in MEC. The computation loads are consolidated into a few numbers in
active servers. The design was forwarded to energy-proportional servers [16]. Thus, the energy consumption
would be proportional to the computation load. The dynamic right-sizing process is one of the methods that are
used to realize energy proportional servers by switching the speed of the servers at the edge and the computation
loads. The alternating server modes between the active and sleep could cause prejudice as long as potential energy
savings. It could tolerate the turning energy cost and application data transmission latency [15].
d) Geographical load balancing for MEC
Here, the idea of balance is coordinating MEC servers with user requisitions. Thus, the processes are
managed by the edge server with a high dataflow location to a nearby edge server with a low dataflow location.
Hence; the EE of the edge servers will be improved. In addition, the battery life of mobile devices will be
extended. For instance, the tasks can be offloaded to a closed server and the energy that is transferred could be
saved in this case. Generally, at edge servers, applications like VM management and dynamic right-sizing
require effective techniques for resource management [15].
e) Renewable energy-powered MEC systems
Renewable energy is an affirmative feature that can be beneficial for MEC. Mobile devices can use
renewable energy as EH can protract their battery life [15]. The use of renewable energy sources makes human
participation not required in replacing or recharging batteries. Some challenges are introduced like resource
allocation for green energy and computation offloading. One of the limitations in designing renewable
energy-powered MEC systems is the fulfilling performance, as renewable energy is mostly coming free. Also,
renewable energy has a randomness feature that may affect the offloading reliability and risks of failure.
The following possible solutions to handle the indicated issues can be considered [15]:
− Deploying the renewable energy-powered edge servers densely (more offloading will be available).
− It is conceivable to reduce the chance of energy shortage by choosing renewable energy sources.
− Hybrid energy sources are used to power MEC servers so reliability is improved. Harvested energy,
electric power and uninterrupted power are equipped to supply units at the edge servers [10].
− A technique of wireless power transfer (WPT) also is adopted, so the battery life will be longer the energy
harvested by each user 𝐸𝑢𝑖 in the download (DL) [17].
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𝐸𝑢𝑖 = 𝑖
𝑃𝐴ℎ𝑖𝜏𝑜 (3)
Where, 𝑖
= energy harvesting efficiency at each receiver; 𝑃𝐴 = transmit power at the hybrid access point
(H-AP); ℎ𝑖 = DL channel power gains; 𝜏𝑜 = time portions in each block allocated to the H-AP. The microgrid is
used to provide the renewable energy sources and supplying green energy to the edge computing. To achieve the
sustainable conditions operation the edge computing energy usage as well as the power supply of the system
should be minimized. So with suitable energy management [18] the power demand can be satisfied according
to the power supply from local or external energy sources through direct or indirect load control strategy as
shown in Figure 2, where four energy sources are provided i.e., renewable energy generation profile(s), storage
profiles (battery), available nearby renewable energy, and grid energy. To maximize the renewable energy
utilization with the edge computing side the scheduling techniques (time-sensitive decision) and application
programs (energy efficiency and IoT controlling) are used. Accordingly, the required renewable energy of
microgrid is provided according the load profiles demand from the edge computing. The red energy is supplied
from the traditional electricity supply network.
Figure 2. A renewable-energy-driven edge computing system
2.1.3. Enhancement at the device layer (end or bottom layer)
The energy-saving system is to be adopted at this end layer (edge device layer) of the EC diagram.
But the short life of the battery needed by IoT used with EC systems constitutes one of the constrained solutions
of power consumption, especially for a big operation scale. Cuervo et al. [19] propose an architecture named
mobile assistance using infrastructure (MAUI), to solve the battery life challenges using mobile code
offloading and remote execution. They proved that the energy consumption could be decreased when adopting
the MAUI program partitioning mechanism and minimizes. It should be necessary to remember that sometimes
power can be consumed by data transmission of user equipment (UE) which will be added to power server
consumption where it is shown that the power consumption is conversely proportional (trade-off) with
changing of average response time. Meanwhile, with all MECs, the processing times for the offloaded tasks
are reduced. The only way to increase the speed of the UE with a little decrease in the average response time
is by making a decrement in the energy consumption of data transferring [20]. The average power consumption
for computation (UE -server power 𝑃𝑆, switching dynamic power consumption 𝑃𝑑, an activity factor , loading
capacitance 𝐶, the supply voltage 𝑉, and the clock frequency 𝑓):
𝑃 = 𝑃𝑑 + 𝑃𝑆 = 𝐶 𝑉2
𝑓 + 𝑃𝑆 (4)
A new type of communication network had been described in [21] called data and energy integrated
communication networks (DEINs) which provide compromises wireless information transfer with wireless
energy transfer, to achieve the co-transmission of data and energy, especially for EH the energy transmission
using radio frequency instead of information decoding. The force side of the advent of DEINs is the big data,
which comes from sensors that produce a large number of small pieces of data. EH has arisen as a technology
for charging batteries in wireless communication. Huq et al. [22] develop a wireless system that treats the
energy efficient in an orthogonal frequency division multiple access. It has been performed to make
transmissions by coordinated multi-point between the small cell base stations (BSs) in a heterogeneous network
with a technique of 3rd
generation partnership project-long term evolution advanced to meet international
mobile telecommunications (IMT)-advanced targets. The power consumption in the network is confined to the
sum of all BS’s power consumption. The power consumption in mobile networks is usually causing overlooked
in comparison to radio network BSs [22]. Another model was proposed in [23] to improve EE in mobile
computing. In that model, a three-node MEC system is considered: a user node, a helper node, and an access
point node in contact with a MEC server. The optimization is made between the following aspects subject to
constraints related to the user’s computation latency (task partition to overcome most difficulties. Time
allocation that makes control for resource allocation, transmit power for the offloading system and CPU
frequencies of local processing or (local computing element) in the network at the user) [23].
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3. OFFLOADING MANAGER
Generally, implementing applications that require intensive calculation in terms of UE is restricted by
a battery capacity and energy-consuming of that equipment. Hence, making the battery life longer is demanded
to offload such applications to a common central cloud. However, the process of delivering and back causes a
considerable execution delay in addition to calculated time in the cloud. Such a delay is undesirable, especially
for real-time applications [24]. Offloading is the way of moving a resource-heavy task from the mobile devices
to a nearby device or network or any controller to complete this task and then retrieving the resulting task to
the mobile devices so that the energy consumption minimization, quality of service (QoS) guarantee, and
quality experiences enhancement [25].
3.1. Computation offloading division
The offloading decision relies on the application model to decide whether it is offloaded or not,
whether full or partial offload will be used, and what and how the calculation could be offloaded. Briefly, UE
needs to be collected from all aspects (i.e., network and management controller) to manage the offloading
process [26]. A computation offloading could be included in the four areas [27].
− The UE computation offloading determination is related to energy-consuming and running delay.
− Determining the computing resources allocation within MEC in terms of efficiency.
− Reducing the computation delay and managing the load distributed around resources and network nodes.
− The management of tasks offloaded should ensure the availability of supplemented service with all users.
A ternary decision maker (TDM) offloading framework was presented to reduce the response time
and energy consumption as well. The required execution task can be treated with local processors and the cloud
which are combined to provide multiple ways of application execution for mobile. A sophisticated decision
model was developed in [28]. Depending on the hierarchical structure and the elementary decision model which
face the offloading challenges in edge computing by using online scheduling to deal with the requests.
To reduce mobile energy consumption the offloading ratio joint optimization and the power transmission
should be reduced. A queening theory in [29] is utilized in MEC systems to investigate the energy consumption,
delay in execution, and payment cost of the offloading tasks. In [30], conduct an in-depth study of the power
consumption, execution latency, and payment cost of offloading processes in fog computing systems using
three queuing models to the MD, fog, and cloud centers, respectively, and explicitly consider the data rate and
power consumption of the wireless link. A multi-objective optimization problem is formulated with the
common goal of minimizing energy consumption, execution delay and payment cost by finding and delivering
optimal offloading probabilities vitality. The energy consumption to offload a task 𝑡𝑖 is [3]:
𝐸𝑖
𝑜
= 𝐸𝑖
𝑇
+ 𝐸𝑖
𝑠
=
𝑝𝑖𝑑𝑖
𝑅𝑖
+ 𝑘𝑖𝑓𝑖
2
𝑙𝑖 (5)
Where, 𝐸𝑖
𝑇
= the energy consumption of the communication process; 𝐸𝑖
𝑠
= the energy consumption at the MEC
server to execute task 𝑡𝑖 ; 𝑝𝑖 = the transmission undertaken power; 𝑑𝑖 = the amount of transfer bits (data + codes)
between the user’s device and the MEC server; 𝑅𝑖 = achievable uplink rate for SMDi; 𝑘𝑖 = the energy coefficient
depending on the chip architecture of 𝑆𝑀𝐷𝑖; 𝑓𝑖
2
= CPU frequency of 𝑆𝑀𝐷𝑖; 𝑙𝑖 = computation amount (cycles)
needed to execute the task. The computation offloading in edge computing faces many challenges: application
partitioning, task allocation, and task execution Figure 3 presents a summary of these challenges [30].
3.2. Offloading server strategy
The computation offloading can be classified into four categories [31]:
− Server-to-cloud server offloading: e.g., EC server offloads deliver computation tasks to a cloud server.
− Server-to-another EC server offloading: the process is similar for both CC and EC. It is more challenging
in EC due to the different features of EC, EH energy harvest, and EC server’s wireless link.
− From end device to EC server: (similar to cloud computing offloading), the computation tasks are
offloaded from end devices to cloud server, but offloading from end devices to the EC servers should
consider new factors, e.g., energy harvesting and mobility.
− End host-to-server1 offloading (3-tier): the end host decides the process whether it is locally using an EC
server or remotely using the cloud server.
The possible solution to the energy challenge is by enabling cooperation between the adjacent mobile
(or any controller) and offloading the higher energy-consuming tasks. Besides, it is conceivable to model the
offloading problem by investigating the management of energy-efficient resource consumption (e.g., multiuser
mobile edge computation offloading models). The study has made with data partition (scheduling) and time division
of communication then an optimal resource management is made. It has been found that optimal time-sharing
strategies tend to balance the effective computing power of multiple offloading devices by helping time-sharing
handsets [32].
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Multiple-input multiple-output (MIMO) multi-cell system was considered in [33] where multi-mobile
users make a query to offload the computation to a cloud server. Hence, the offloaded problem formed as the
linked optimization of the wireless resources assigned to each mobile user by the cloud to overcome consuming
energy. Meanwhile, the meeting latency is a constraint. So, the problem was modeled as non-convex in the
objective function and constraints. In [34], an algorithm has been performed for the offloading process
dynamically using the Lyapunov optimization. Thus, the offloaded parts of running the active program are
determined with changing rates along 3G network locations. The optimization is made for the offloading
assigning the related task, and the running time with the resource hardware needed. A heuristic broach was
applied in [35] using two stages. The first stage uses semi-definite relaxation and randomization techniques to
specify the offloading parts between users. The second stages optimize and manage the resource demands of
users. Meanwhile, a scenario of optimizing is offloaded from a single mobile device to multiple edge devices.
Thus, the total tasks’ running latency and the mobile device’s energy consumption were minimized by jointly
optimizing the task allocation decision and CPU frequency (network speed scaling) of the mobile device.
As a result, the improvement in performance is achieved.
3.2.1. Offloading device-to-device
Device-to-device (D2D) communication is proposed in [36], [37] links in MEC and corporate
computing sharing between multi-users so the mobility problems will be overcome. Also, the computation
offload is enabled for users to surrounding users exploiting powerful computation abilities. Due to the short
distance between the two devices, the transmission energy consumption of data will be minimized, but there
are new challenges are arising. These are [36]:
− Utilization way of D2D and cellular communications.
− The desertion of choosing surrounded users to ensure optimum offloading taking into account (users’
device information, dynamic links and computing power of heterogeneous users).
− Suffering from numerous D2D channels in terms of interference for a reliable link.
3.2.2. Device-to-MEC
The energy consumption and running time can be decreased by offloading computation from a UE to
a MEC server [38], the burden of the computation of mobile devices is lessened, the performance of
applications is increased, the energy consumption is minimized, and the lifetime of the battery of mobile UEs
is also increased. The power and time allocations were optimized in [18] to minimize offload power
consumption in non-orthogonal multiple access (NOMA) multi-user MEC networks. NOMA is applied to
multi-user MEC networks, where multiple users can simultaneously offload their tasks to the MEC server on
the same frequency band. Any user can split computing tasks into offload computing and local computing parts
by applying partial offloading. Thus, the energy consumption, offloading power, and task completion time
limitations were considered as non-convex problems. There is a method [26] in which the task type is
determined and then making partial offloading by dividing the program into local (mobile) and remote
execution (cloud), to overcome the resource needed and make energy serving, the task-input data is randomly
partitioned. Meanwhile, a system in [39] has been designed so that a server at the MEC and several applications
runs by a mobile device with considering three processes: computation offloading, task scheduling, and energy
consumption. Another offloading decision strategy was proposed in [40] for the multi-UE case. The strategy
reduces the energy consumption at the UE while allowing the maximum execution delay. In each time slot,
a decision on the computation offloading was often taken for the period where the most UE were divided into
two groups: in the first group, the computation is offloaded to the MEC while in the second group the
computation is locally achieved since the computation resources are inaccessible at the MEC. A systematic
optimization procedure was proposed in [41] using a mobile edge environment. Partition can be made with
running tasks and then, swapped out is processed (offloading) in parallel for distributing edge nodes. Therefore,
by simultaneously optimizing edge node selection, quality of results (QoR) level, and task assignment to all
edges, response time and power consumption can be reduced. Mainly there are two energy consumption types
for the computation offloading of mobile devices: task offloading and downloading computational energy
consumption. Sheng et al. [42] have considered the optimization of computation offloading strategy using
different servers in MEC. For UE, they use a queuing model and multiple servers. The average response time
(of offloaded and non-offloaded tasks for UE) and rate value of power consumption with the cost-performance
ratio were minimized. Furthermore, an efficient numerical method was developed using a variety of efficient
numerical algorithms [42]. The energy consumption by the mobile device (only that needed when the task is
uploaded) or (task is offloaded) [42] is:
𝐸𝑈𝑃 = 𝑇𝑢𝑝 × 𝑃𝑢𝑝 =
𝐷𝑛
𝑊 log2(1+
𝑃𝑢𝑝×𝐺𝑜𝑠
𝑁
)
× 𝑃𝑢𝑝 (6)
8. TELKOMNIKA Telecommun Comput El Control
Power consumption and energy management for edge computing: state of … (Tawfeeq E. Abdoulabbas)
843
Where 𝑇𝑢𝑝 = the transmission time required to upload a task; 𝑃𝑢𝑝 = upload power; 𝐷𝑛 = the amount
of data needed to upload tasks; 𝑁 = the Gauss noise power in the channel; 𝑊 = the channel bandwidth, and
𝐺𝑜𝑠 is the channel gain. The computations that are used in cloudlets with this approach can decrease the
overload of wearable devices by about 30% of energy [42]. The closer device will be the more tasks it can be
offloading (due to the lesser bandwidth loss of wireless transmissions). This also shows that EC is more suitable
for computation offloading than centralized cloud computing. The performing offloading computations show
that the offloading computation can save at least 50% of the power for mobile devices, which means that mobile
devices have longer endurance [42].
Figure 3. Challenges for computation offloading due to edge computing
3.3. Computation offloading of MEC
Different approaches were developed in relation to the efficient computation offloading mechanism of
MEC. For example, in MEC, a framework was introduced in [43] where the Markov decision is used based on a
sequential offloading decision to address the problem of dynamic service migration. Also, Zhang et al. [44], have
tried to trade-off between the tasks offloading computation of the cloud and keeping hold of them in the mobile
edge cloud. In [45] a small cell cluster formation and a scheme was used for load balancing on the edge of the
clouds in a 5G network where dense deployments were implemented. Regarding the feature of the MEC that
concerns the uniqueness of the wireless task offloading, network virtualization in the context of MEC networks
was presented in [46]. Two privacy issues are proposed named location privacy and usage pattern privacy.
There is a challenge to tackle the proposed privacy issues and at the same time preserve the best performance
of the delay and energy consumption. In [47], this challenge is handled by suggesting a scheme for the MEC
system to minimize the delay and the cost of energy consumption and even maintain the privacy of the user
above a specific level. The problem is considered a Markov decision process and an offloading scheme based
on privacy-aware tasks.
4. CONCLUSION
In this paper, different EE mechanisms in EC for MEC with their enhancement strategies for
performance consideration and technologies are studied and highlighted. It also discusses different energy
management techniques with their classification of each type. Moreover, some offloading approaches
according to different categories are explained and studied in detail. As mentioned earlier the EE of a data
center in the cloud is greater than that with the edge DCs. Also, in IoT applications, sending computational
tasks to the edge of the server have EE better than in the cloud. It can be concluded that, in EC systems,
to achieve minimum power consumption, some approaches cannot be simply applied because of the variability
and intermittency of renewable energy which adds other challenges to energy management. Also, as explained
earlier renewable energy is an affirmative feature that can be useful for MEC. It can be used by mobile devices
since EH can prolong their battery life.
It is recommended that designing a dynamic system for energy management in real-time is important
so as to respond to the availability of local renewable energy, and to the kind of IoT application. For edge
devices, it is recommended to use alternative ways for supply and not only depend on the single source but
also enabling using more than one energy source or a hybrid method to provide new energy sources. It is also
recommended to use an approach based on privacy-aware tasks for computation offloading tasks to minimize
the delay and the cost of energy consumption and even maintain the privacy of the user above a specific level
for the MEC system. Furthermore, we advocate making evaluations on the proposed management modeling to
be reliable for more than one system type with minimum power consumption.
9. ISSN: 1693-6930
TELKOMNIKA Telecommun Comput El Control, Vol. 21, No. 4, August 2023: 836-845
844
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BIOGRAPHIES OF AUTHORS
Tawfeeq E. Abdoulabbas received the B.Sc in Electrical Engineering from
University of Mustansiriyah /Baghdad, Iraq in 1992. In 1996, he obtained his M.Sc. from the
University of Technology/Baghdad, Iraq in Electrical and Engineering science. He joined the
academic staff of Mustansiriyah University/College of Engineering in 2012. His research
interests are on power management systems, smart homes, and smart grids. He can be
contacted: tawfikenad@uomustansiriyah.edu.iq.
Sawsan M. Mahmoud received her B.Sc. in Computer Science from University of
Technology/Baghdad, Iraq in 1994. She obtained her M.Sc. from University of Baghdad n 1998.
Her Ph.D. in Computational Intelligence is obtained from Nottingham Trent University,
Nottingham, UK in 2012. Sawsan joined the academic staff of Mustansiriyah
University/Engineering College in 1994. Her research interests include computational intelligence,
ambient intelligence (smart home and intelligent environment), wireless sensor network, data
mining, and health monitoring. She can be contacted: sawsan.mahmoud@uomustansiriyah.edu.iq.