• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.113-117
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• 2021

The data gathering delay and the network lifetime are important indicators to measure the service quality of wireless sensor and actuator networks (WSANs). This study proposes a dynamically cluster head (CH) selection strategy and automatic scheduling scheme of collectors for prolonging the network lifetime and shorting data gathering delay in WSAN. First the monitoring region is equally divided into several subregions and each subregion dynamically selects a sensor node as CH. These can balance the energy consumption of sensor node thereby prolonging the network lifetime. Then a task allocation method based on genetic algorithm is proposed to uniformly assign tasks to actuators. Finally the trajectory of each actuator is optimized by ant colony optimization algorithm. Simulations are conducted to evaluate the effectiveness of the proposed method and the results show that the method performs better to extend network lifetime while also reducing data delay.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.1023-1033
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• 2007

This study considers a joint congestion control, routing and power control for energy-constrained wireless networks. A mathematical model is introduced which includes maximization of network utility, maximization of network lifetime, and trade-off between network utility and network lifetime. The framework would maximize the overall throughput of the network where the overall throughput depends on the data flow rates which in turn is dependent on the link capacities. The link capacity on the other hand is a function of transmit power levels and link Signal-to-Interference-plus-Noise-Ratio (SINR) which makes the power allocation problem inherently difficult to solve. Using dual decomposition techniques, subgradient method, and logarithmic transformations, a joint algorithm for rate and power allocation problems was formulated. Numerical examples for each optimization problem were also provided.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.227-237
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• 2016

Data collection is a key function for wireless sensor networks. There has been numerous data collection scheduling algorithms, but they fail to consider the deep and complex relationship among network lifetime, sink aggregated information and sample cycle for wireless sensor networks. This paper gives the upper bound on the sample period under the given network topology. An optimal schedule algorithm focusing on aggregated information named OSFAI is proposed. In the schedule algorithm, the nodes in hotspots would hold on transmission and accumulate their data before sending them to sink at once. This could realize the dual goals of improving the network lifetime and increasing the amount of information aggregated to sink. We formulate the optimization problem as to achieve trade-off among sample cycle, sink aggregated information and network lifetime by controlling the sample cycle. The results of simulation on the random generated wireless sensor networks show that when choosing the optimized sample cycle, the sink aggregated information quantity can be increased by 30.5%, and the network lifetime can be increased by 27.78%.

• Smart Media Journal
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• v.5 no.4
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• pp.41-48
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• 2016

In mobile ad hoc networks(MANETs), all the nodes in a network have limited resources. Therefore, communication topology which has long lifetime is suitable for nodes in MANETs. And MANETs are exposed to various threats because of a new node which can join the network at any time. There are various researches on security problems in MANETs and many researches have tried to make efficient schemes for reducing network power consumption. Power consumption is necessary to secure networks, however too much power consumption can be critical to network lifetime. This paper focuses on energy efficient monitoring node distribution for enhancing network lifetime in MANETs. Since MANETs cannot use centralized infrastructure such as security systems of wired networks, we propose an efficient IDS node distribution scheme using minimum spanning tree (MST) method to cover all the nodes in a network and enhance the network lifetime. Simulation results show that the proposed algorithm has better performance in comparison with the existing algorithms.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.139-144
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• 2022

Technological advancements taken the health care industry by a storm by embedding sensors in human body to measure their vitals. These smart solutions provide better and flexible health care to patients, and also easy monitoring for the medical practitioners. However, these innovative solutions provide their own set of challenges. The major challenge faced by embedding sensors in body is the issue of lack of infinite energy source. This work presents a meta-heuristic based routing model using modified PSO, and adopts an energy harvesting scheme to improve the network lifetime. The routing process is governed by modifying the fitness function of PSO to include charge, temperature and other vital factors required for node selection. A reactive routing model is adopted to ensure reliable packet delivery. Experiments have been performed and comparisons indicate that the proposed Energy Harvesting and Modified PSO (EHMP) model demonstrates low overhead, higher network lifetime and better network stability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1133-1151
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• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.592-598
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• 2018

In wireless sensor networks where there is no centralized base station, each node has limited transmission range and the multi-hop routing for transmitting data to the destination is the one of the important technical issues. In particular, the wireless sensor network is not powered by external power source but operates by its own battery, so it is required to maximize the network life through efficient use of energy. To balance the power consumption, the residual power based adaptive power control is required in routing protocol. In this paper, we propose a routing protocol that prolongs the network lifetime by balancing the power consumption among the nodes by controlling the transmit power according to the residual power. We evaluate the proposed routing protocol using extensive simulation, and the results show that the proposed routing scheme can balance the power consumption and prolong network lifetime.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.47-59
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• 2014

In this paper, I propose a new energy efficient clustering scheme to prolong the network lifetime by reducing energy consumption at the sensor node. It is possible that a node determines whether to participate in clustering with certain probability based on local density. This scheme is useful under the environment that sensor nodes are deployed unevenly within the sensing area. By adjusting the probability of participating in clustering dynamically with local density of nodes, the energy consumption of the network is reduced. So, the lifetime of the network is extended. In the region where nodes are densely deployed, it is possible to reduce the energy consumption of the network by limiting the number of node which is participated in clustering with probability which can be adjusted dynamically based on local density of the node. Through computer simulation, it is verified that the proposed scheme is more energy efficient than LEACH protocol under the environment where node are densely located in a specific area.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1238-1240
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• 2009

In the wireless sensor network, cooperative transmission is an effective technique to combat multi-path fading and reduce transmitted power. Relay selection and power allocation are important technical issues to determine the performance of cooperative transmission. In this paper, we proposed a new multi-relay selection and power allocation algorithm to increase network lifetime. The proposed relay selection scheme minimizes the transmitted power and increase the network lifetime by considering residual power as well as channel conditions. Simulation results show that proposed algorithm obtains much longer network lifetime than the conventional algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.795-798
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• 2007

In this paper, we proposed a simple power allocation scheme to maximize network lifetime. To maximize network lifetime, it is important to allocate power fairly among nodes in a network as well as to minimize total transmitted power. In the proposed scheme, the allocated power is proportional to the residual power and also satisfies the required SNR at destination node. In this paper, we calculate power allocation in "amplify and forward" (AF) model. We evaluated the proposed power allocation scheme using extensive simulation and simulation results show that proposed power allocation obtains much longer network lifetime than the equal power allocation.