• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.5149-5167
• /
• 2017

Reducing energy consumption in a wireless video sensor network (WVSN) is a crucial problem because of the high video data volume and severe energy constraints of battery-powered WVSN nodes. In this paper, we present an adaptive dynamic resizing approach for a SRAM communication buffer in a WVSN node in order to reduce the energy consumption and thereby, to maximize the lifetime of the WVSN nodes. To reduce the power consumption of the communication part, which is typically the most energy-consuming component in the WVSN nodes, the radio needs to remain turned off during the data buffer-filling period as well as idle period. As the radio ON/OFF transition incurs extra energy consumption, we need to reduce the ON/OFF transition frequency, which requires a large-sized buffer. However, a large-sized SRAM buffer results in more energy consumption because SRAM power consumption is proportional to the memory size. We can dynamically adjust any active buffer memory size by utilizing a power-gating technique to reflect the optimal control on the buffer size. This paper aims at finding the optimal buffer size, based on the trade-off between the respective energy consumption ratios of the communication buffer and the radio part, respectively. We derive a formula showing the relationship between control variables, including active buffer size and total energy consumption, to mathematically determine the optimal buffer size for any given conditions to minimize total energy consumption. Simulation results show that the overall energy reduction, using our approach, is up to 40.48% (26.96% on average) compared to the conventional wireless communication scheme. In addition, the lifetime of the WVSN node has been extended by 22.17% on average, compared to the existing approaches.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.87-106
• /
• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.6
• /
• pp.29-36
• /
• 2016

A wireless passive sensor network is a network which, by letting separate RF sources supply energy to sensor nodes, is able to live an eternal life without batteries. Against expectations about an eternal life, however, a wireless passive sensor network still has many problems; scarcity of energy, non-simultaneity of energy reception and data transmission and inefficiency in resource allocation. In this paper, we focus on a wireless passive sensor network providing a packet service which is tolerable to packet losses but requires timely delivery of packets. Perceiving the practical constraints, we then consider a contending-type MAC scheme, rooted in framed and slotted ALOHA, for supporting many sensor nodes to deliver packets to a sink node. Next, we investigate the network-wide throughput achieved by the MAC scheme when the packets transmitted by geographically scattered sensor nodes experience path losses hence capture phenomena. Especially, we derive an exact formula of network-wide throughput in a closed form when 2 sensor nodes reside in the network. By controlling design parameters, we finally optimize the contending-type MAC scheme as to attain the maximum network-wide throughput.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.7 no.4
• /
• pp.118-129
• /
• 2008

This paper describes an IEEE 802.15.4-based hierarchical sensor network model for a VAWS(Vehicle Approach Warning System) which provides the drivers of vehicles approaching a sharp turn with the information about vehicles approaching the same turn from the opposite end. In the proposed network model, a tree-structured topology, that can prolong the lifetime of network is formed in a self-organizing manner by a topology control protocol. A simple but efficient routing protocol, that creates and maintains routing tables based on the network topology organized by the topology control protocol, transports data packets generated from the sensor nodes to the base station which then forwards it to a display processor. These protocols are designed as a network layer extension to the IEEE 802.15.4 MAC. In the simulation, which models a scenario with a sharp turn, it is shown that the proposed network model achieves a high-level performance in terms of both energy efficiency and throughput simultaneously.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.612-615
• /
• 2012

Energy efficiency in wireless sensor network is a principal issue because wireless sensor network uses limited energy. In wireless sensor network, because nodes are placed randomly, they may be concentrated in certain area. This dense area causes shortening the life of the concentrated area, and furthermore reducing the life of the entire network. In this paper, we suggest a additional cluster head selection algorithm for reducing the overload of head node in dense area and shows simulation result using our algorithm with LEACH algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.389-392
• /
• 2007

In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering technique. The sensed information in each cluster transfers to sink node through inter-cluster communications. Cluster head (CH) that nearby located in sink node much more spend own energy than far away CHs, because nearer CH forwards more data, so network lifetime is decreased. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster site, and improve CH lifetime by distributing transmission paths. As a result of analysis, the proposed algorithm shows longer network lifetime in WSN.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.11
• /
• pp.2550-2556
• /
• 2012

We proposed the energy-efficient routing algorithm ALPS (Ad hoc network Localized Positioning System) algorithm that is range-free based on the distance information. The routing coordinate method of ALPS algorithm consists of hierarchical cluster routing that provides immediately relative coordinate location using RSSI(Received Signal Strength Indication) information. Existing conventional DV-hop algorithm also to manage based on normalized the range free method, the proposed hierarchical cluster routing algorithm simulation results show more optimized energy consumption sustainable path routing technique to improve the network management.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.5
• /
• pp.482-486
• /
• 2008

When we design a sensor nodes, a energy-consumption of sensor nodes centers on design concerns to prolong lifetime of sensor network. In recent year, many researches have attempted to study this issue. One of that is TTDD(Two-Tier Data Dissemination approach) proposed to support a sensor network which includes several mobile sensor nodes. But it gives rise to a problem which increasing control packet for the formation and maintenance a grid structure. Therefore, we proposed a Energy-Efficient Routing Protocol used a permanent grid structure for reducing control packets in a sensor network.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.11
• /
• pp.1241-1248
• /
• 2014

An efficient battery usage of sensor nodes is main goal in a sensor network, which is the substructure of Internet of Things. Maximizing the battery usage of sensor nodes makes the lifetime of sensor network increase as well as the reliability of the network improved. The previous solutions to solve these problems are mainly focused on the cluster head selection based on the remaining energy. In this paper, we consider both the head selection and the replacement interval which is determined by a threshold that is based on the remaining energy, density of alive nodes, and location. Our simulation results show that the proposed scheme has outstanding contribution in terms of maximizing the life time of the network and balancing energy consumption of all nodes.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.2
• /
• pp.410-415
• /
• 2007

Recent advances in sensor network technology have open up challenges for its effective routing. Routing protocol receives most of the attention because routing protocols might differ depending on the application and network architecture. In the rapidly changing environment and dynamic nature of network formation efficient routing and energy consumption are very crucial. Sensor networks differ from the traditional networks in terms of energy consumption. Thus, data-centric technologies should be used to perform routing to yield an energy-efficient dissemination. By exploiting the advantages of both ant colony optimization techniques in network routing and the ability of data centric muting to organize data for delivery, our approach will cover features for building an efficient autonomous sensor network.