• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2509-2528
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• 2012

Time division multiple access (TDMA) is a widely used media access control (MAC) technique that can provide collision-free and reliable communications, save energy and bound the delay of packets. In TDMA, energy saving is usually achieved by switching the nodes' radio off when such nodes are not engaged. However, the frequent switching of the radio's state not only wastes energy, but also increases end-to-end delay. To achieve high energy efficiency and low delay, as well as to further minimize the number of time slots, a multi-objective TDMA scheduling problem for industrial wireless mesh networks is presented. A hybrid algorithm that combines genetic algorithm (GA) and simulated annealing (SA) algorithm is then proposed to solve the TDMA scheduling problem effectively. A number of critical techniques are also adopted to reduce energy consumption and to shorten end-to-end delay further. Simulation results with different kinds of networks demonstrate that the proposed algorithm outperforms traditional scheduling algorithms in terms of addressing the problems of energy consumption and end-to-end delay, thus satisfying the demands of industrial wireless mesh networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1074-1086
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• 2015

We Relay-assisted cellular network architecture has been developed to cover cell-edge users and to improve capacity. However, the deployment of relay stations (RSs) in cellular networks may increase the total energy consumption. Though energy efficiency has become a major concern in cellular networks, little work has studied the energy efficiency of relay-assisted cellular networks by sleep scheduling. In this paper, a distributed base stations (BSs) sleep scheduling scheme in relay-assisted cellular networks is proposed. The goal is to maximize the energy efficiency under the spectral efficiency constraint. Firstly, whether the BSs should be sleeping or active is determined by the traffic profile. Then, the transmission powers of the active BSs are optimized within the game-theoretic framework, by using an interior-point method, so as to maximize the energy efficiency. Simulation results demonstrate that the effectiveness of the proposed scheme is superior to that turning on all the BSs without sleep scheduling.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9A
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• pp.884-891
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• 2006

A wireless sensor node is typically battery operated and energy constrained. Therefore it is critical to design efficient power management technique and scheduling technique. In this paper, we propose an OS-level power management technique for energy saving of wireless sensor node, it is called EA-SENTAS (Energy-Aware Sensor Node TAsk Scheduling). It can decrease the energy consumption of a wireless sensor node to use task scheduling technique that shut down components or use low power mode of each component when not needed. Simulation results show that EA-SENTAS saves energy up to 56 percent to compare with conventional duty cycle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.559-573
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• 2016

In this paper, we investigate the problem of achieving proportional fairness in hierarchical wireless sensor networks. Combining clustering formulation and scheduling, we maximize total bandwidth utility for proportional fairness while controlling the power consumption to a minimum value. This problem is decomposed into two sub-problems and solved in two stages, which are Clustering Formulation Stage and Scheduling Stage, respectively. The above algorithm, called CSPF_PC, runs in a network formulation sequence. In the Clustering Formulation Stage, we let the sensor nodes join to the cluster head nodes by adjusting transmit power in a greedy strategy; in the Scheduling Stage, the proportional fairness is achieved by scheduling the time-slot resource. Simulation results verify the superior performance of our algorithm over the compared algorithms on fairness index.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.116-124
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• 2015

Smart grids propose new solutions for electricity consumers as a means to help them use energy in an efficient way. In this paper, we consider the demand-side management issue that exists for a group of consumers (houses) that are equipped with renewable energy (wind turbines) and storage units (battery), and we try to find the optimal scheduling for their home appliances, in order to reduce their electricity bills. Our simulation results prove the effectiveness of our approach, as they show a significant reduction in electricity costs when using renewable energy and battery storage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.421-428
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• 2008

The DVS(Dynamic Voltage Scaling) technique is the method to reduce the dynamic energy consumption. As using slack times, it extends the execution time of the big load operations by changing the frequency and the voltage of variable voltage processors. Researches, that controlling the energy consumption of the processors and the data transmission among processors by controlling the bandwidth to reduce the energy consumption of the entire system, have been going on. Since operations in multiprocessor systems have the data dependency between processors, however, the DVS techniques devised for single processors are not suitable to improve the energy efficiency of multiprocessor systems. We propose the new scheduling algorithm based on DVS for increasing energy efficiency of multiprocessor systems. The proposed DVS algorithm can improve the energy efficiency of the entire system because it controls frequency and voltages having the data dependency among processors.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.92-100
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• 2018

In this paper, we propose a fault-tolerant scheduling scheme with energy efficiency for real-time periodic tasks on DVFS-enabled multicore processors. The scheme provides the tolerance of a permanent fault with the primary-backup task model. Also the scheme reduces the energy consumption of real-time tasks with the fully overlapped execution between each primary task and its backup task, whereas most of previous methods tried to minimize the overlapped execution between the two tasks. In order to the leakage energy loss of idle cores, the scheme activates a part of available cores with rarely used cores powered off. Evaluation results show that the proposed scheme saves up to 82% energy consumption of the previous method.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.61-66
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• 2015

We investigate rate scheduling and power allocation problem for a delay constrained CDMA systems. Specifically, we determine an energy efficient scheduling policy, while each user maintains the short term (n time slots) average throughput. More importantly, it is shown that the optimal transmission strategy for the uplink is same as that of the downlink, called uplink and downlink duality. We then examine the performance of the optimum transmission strategy for the uplink and the downlink for various system environments.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.3-9
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• 2015

We investigate rate scheduling and power allocation problem for a delay constrained CDMA systems. Specifically, we determine an energy efficient scheduling policy, while each user maintains the short term (n time slots) average throughput. We consider a multirate CDMA system where multirate is achieved by multiple codes. Each code can be interpreted as a virtual user. The aim is to schedule the virtual users into each time slot, such that the sum of transmit energy in n time slots is minimized. We then show that the total energy minimization problem can be solved by a shortest path algorithm. We compare the performance of the optimum scheduling with that of TDMA-type scheduling.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.506-516
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• 2015

Wireless sensor networks (WSNs) are generally comprised of densely deployed sensor nodes, which results in highly redundant sensor data transmissions and energy waste. Since the sensor nodes depend on batteries for energy, previous studies have focused on designing energy-efficient medium access control (MAC) protocols to extend the network lifetime. However, the energy-efficient protocols induce an extra end-to-end delay, and therefore recent increase in focus on WSNs has led to timely and reliable communication protocols for mission-critical applications. In this paper, we propose an energy efficient and delay guaranteeing node scheduling scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique.With the identification of analogies between cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired algorithm determines the state of the sensor node, as required by each application and as determined by the local environmental conditions and the states of the adjacent nodes. A control analysis shows that the proposed bio-inspired scheme guarantees the system stability by controlling the parameters of each node. Simulation results also indicate that the proposed scheme provides significant energy savings, as well as reliable delay guarantees by controlling the states of the sensor nodes.