• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.8
• /
• pp.2140-2156
• /
• 2023

The Wireless Sensor Network (WSN), is constructed out of teeny-tiny sensor nodes that are very low-cost, have a low impact on the environment in terms of the amount of power they consume, and are able to successfully transmit data to the base station. The primary challenges that are presented by WSN are those that are posed by the distance between nodes, the amount of energy that is consumed, and the delay in time. The sensor node's source of power supply is a battery, and this particular battery is not capable of being recharged. In this scenario, the amount of energy that is consumed rises in direct proportion to the distance that separates the nodes. Here, we present a Hybrid Firefly Glow-Worm Swarm Optimization (HF-GSO) guided routing strategy for preserving WSNs' low power footprint. An efficient fitness function based on firefly optimization is used to select the Cluster Head (CH) in this procedure. It aids in minimising power consumption and the occurrence of dead sensor nodes. After a cluster head (CH) has been chosen, the Glow-Worm Swarm Optimization (GSO) algorithm is used to figure out the best path for sending data to the sink node. Power consumption, throughput, packet delivery ratio, and network lifetime are just some of the metrics measured and compared between the proposed method and methods that are conceptually similar to those already in use. Simulation results showed that the proposed method significantly reduced energy consumption compared to the state-of-the-art methods, while simultaneously increasing the number of functioning sensor nodes by 2.4%. Proposed method produces superior outcomes compared to alternative optimization-based methods.

• Journal of Internet Computing and Services
• /
• v.9 no.5
• /
• pp.165-173
• /
• 2008

Hybrid ad hoc networks are integrated networks referred to Home Networks, Telematics and Sensor networks can offer various services. Specially, in ad hoc network where each node is responsible for forwarding neighbor nodes' data packets, it should net only reduce the overall energy consumption but also balance individual battery power. Unbalanced energy usage will result in earlier node failure in overloaded nodes. it leads to network partitioning and reduces network lifetime. Therefore, this paper studied the routing protocol considering efficiency of energy. The suggested algorithm can predict the status of energy in each node using the energy prediction model. This can reduce the overload of establishing route path and balance individual battery power. The suggested algorithm can reduce power consumption as well as increase network lifetime.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.12
• /
• pp.9-16
• /
• 2009

Energy consumption as well as performance should be considered when designing up-to-date multicore processors. In this paper, we propose new design technique to reduce the energy consumption in the instruction cache for multicore processors by using modified filter cache. The filter cache has been recognized as one of the most energy-efficient design techniques for singlecore processors. The energy consumed in the instruction cache accounts for a significant portion of total processor energy consumption. Therefore, energy-aware instruction cache design techniques are essential to reduce the energy consumption in a multicore processor. The proposed technique reduces the energy consumption in the instruction cache for multicore processors by reducing the number of accesses to the level-1 instruction cache. We evaluate the proposed design using a simulation infrastructure based on SimpleScalar and CACTI. Simulation results show that the proposed architecture reduces the energy consumption in the instruction cache for multicore processors by up to 3.4% compared to the conventional filter cache architecture. Moreover, the proposed architecture shows better performance over the conventional filter cache architecture.

• Journal of Biosystems Engineering
• /
• v.37 no.6
• /
• pp.385-397
• /
• 2012

Purpose: Drying characteristics of sawdust was studied under batch mode using lab scale microwave dryer. The objective of this study was to investigate the effect of material load and microwave output power on drying characteristics of sawdust. Methods: Material load and microwave output power were varied from 23 to 186 g and 530 to 370 W respectively. Different kinetic models were tested to fit the drying rates of sawdust. Similarly, the activation energy was calculated by employing the Arrhenius equation. Results: The drying efficiency increased considerably, whereas the specific energy consumption significantly decreased with increase in material load and microwave output power. The cumulative energy efficiency increased by 9%, and the specific energy consumption decreased by 8% when the material load was increased from 23 to 186 g. The effective diffusivity increased with decrease in material load and increase in microwave output power. The previously published model gave the best fit for data points with $R^2$ and RMSE values of 0.999 and 0.01, respectively. Conclusions: The data obtained from this study could be used as a basis for modeling of large scale industrial microwave dryers for the pellet production.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1735-1754
• /
• 2022

The reliability and performance of WiFi need optimization because of the rising number of WiFi users day by day. A highlighted point is saving power while transmitting and receiving packets using WiFi devices. Wake-on-Wlan (WoW) is also implemented to improve energy consumption, but it also needs betterment. This paper will introduce universal ideas to transmit and receive packets using low-power technology like Bluetooth or BLE (Bluetooth low energy). While looking for power-saving ways in this research, WiFi connection and maintenance also take care using lesser power-consuming technology. Identifying different use-cases where low power technology can help save energy and maintain 802.11 connection is part of the research. In addition, the proposed method discuss energy saving with unicast and broadcast/multicast data. Calculation of power-saving and comparison with standalone WiFi usage clearly shows the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.6
• /
• pp.852-858
• /
• 2012

This paper describes evaluation results of the wind power penetration limit (WPPL) and the wind energy penetration (WEP) in the Mongolian central power system (MCPS). A wind power plant (WPP) in a power system possesses an output power limit because the power system must maintain a balance between the generation and consumption of electricity at all times in order to achieve an adequate level of quality. The instantaneous penetration limit (IPL) of wind generation at a load is determined as the minimum of the three technical constraints: the minimum output, the ramp rate capability, and the spinning reserve of the conventional generating units. In this paper, a WPPL is defined as the maximum IPL divided by the peak load. A maximal variation rate (VR) of wind power is a major factor in determining the IPL, WPPL, and WEP. This paper analyzes the effects of the maximal VR of wind power on the WPPL, WEP, and capacity factor (CF) in the MCPS. The results indicate that a small VR can facilitate a large amount of wind energy while maintaining a high CF with increased wind power penetration.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5343-5364
• /
• 2016

Considering the tradeoff between energy consumption and outage behavior in buffer-aided relay selection, a novel energy-efficient buffer-aided optimal relay selection scheme with power adaptation and Inter-Relay Interference (IRI) cancellation is proposed. In the proposed scheme, energy consumption minimization is the objective with the consideration of relay buffer state, outage probability and relay power control, in order to eliminate IRI. The proposed scheme selects a pair of optimal relays from multiple candidate relays, denoted as optimal receive relay and optimal transmit relay respectively. Source-relay and relay-destination communications can be performed within a time-slot, which performs as Full-Duplex (FD) relaying. Markov chain model is applied to analyze the evolution of relay buffer states. System steady state outage probability and achievable diversity order are derived respectively. In addition, packet transmission delay and power reduction performance are investigated with a specific analysis. Numerical results show that the proposed scheme outperforms other relay selection schemes in terms of outage behavior with power adaptation and IRI cancellation in the same relay number and buffer size scenario. Compared with Buffer State relay selection method, the proposed scheme reduces transmission delay significantly with the same amount of relays. Average transmit power reduction can be implemented to relays with the increasing of relay number and buffer size, which realizes the tradeoff between energy-efficiency, outage behavior and delay performance in green cooperative communications.

• Journal of Digital Convergence
• /
• v.12 no.2
• /
• pp.271-276
• /
• 2014

The life-time and performance of a wireless sensor network is closely related to energy-efficiency of sensor nodes. In this paper, to increase energy-efficiency, each sensor node operates in one of three operational modes which are normal, power-saving, and inactive. In normal mode sensor nodes sense and transmit data with normal period, whereas sensor nodes in power-saving mode have three-times longer period. In inactive mode, sensor nodes do not sense and transmit any data, which makes the energy consumption to be minimized. Plus, the proposed algorithm can avoid unnecessary energy consumption by preventing transmitting duplicate sensed data. We implemented and simulated the proposed algorithm using Tiny OS based ZigbeX platfom and NS-2, respectively. Performance evaluation results show that the proposed algorithm can prolong sensor networks' lifespan by efficiently reducing energy consumption and its standard deviation of all sensor nodes.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2005.05a
• /
• pp.331-336
• /
• 2005

It is increased electrical energy consumption with the development of intelligence society in the office buildings and thus an energy conservation through efficient use of electricity became more important. This paper shows a reasonable design demand factor in office buildings, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, peak power consumption, demand factor, etc., for 54 office buildings and 34 electrical design offices. In this dissertation, it is necessary to analyse the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried linear and nonlinear regression analysis.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2007.05a
• /
• pp.241-244
• /
• 2007

It is increased electrical energy consumption with the development of intelligence society in office buildings and thus an energy conservation through efficient use of electricity became more important. This paper shows a reasonable design demand factor in office buildings, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, peak power consumption, demand factor, etc., for 132 office buildings. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried linear and nonlinear regression analysis.