• Journal of KIISE
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• v.43 no.3
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• pp.296-303
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• 2016

Mobile real-time systems with limited system resources and a limited power source need to fully utilize the system resources when the workload is heavy and reduce energy consumption when the workload is light. EDZL (Earliest Deadline until Zero Laxity), a multiprocessor real-time scheduling algorithm, can provide high system utilization, but little work has been done aimed at reducing its energy consumption. This paper tackles the problem of DVFS (Dynamic Voltage/Frequency Scaling) in EDZL scheduling. It proposes a technique to compute a uniform speed on full-chip DVFS platforms and individual speeds of tasks on per-core DVFS platforms. This technique, which is based on the EDZL schedulability test, is a simple but effective one for determining the speeds of tasks offline. We also show through simulation that the proposed technique is useful in reducing energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.665-683
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• 2011

Wireless sensor networks (WSN) consist of a large amount of sensor nodes distributed in a certain region. Due to the limited battery power of a sensor node, lots of energy-efficient schemes have been studied. Clustering is primarily used for energy efficiency purpose. However, clustering in WSNs faces several unattained issues, such as ensuring connectivity and scheduling inter-cluster transmissions. In this paper, we propose a location-based spiral clustering (LBSC) algorithm for improving connectivity and avoiding inter-cluster collisions. It also provides reliable location aware routing paths from all cluster heads to a sink node during cluster formation. Proposed algorithm can simultaneously make clusters in four spiral directions from the center of sensor field by using the location information and residual energy level of neighbor sensor nodes. Three logical addresses are used for categorizing the clusters into four global groups and scheduling the intra- and inter-cluster transmission time for each cluster. We evaluated the performance with simulations and compared it with other algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.6 s.324
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• pp.41-48
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• 2004

In an IP network, various types of traffics are statistically multiplexed to utilize efficiently the network resources. The DiffServ-aware-MPLS supports a wide variety of communication services with different QoS requirements. The DiffServ-aware-MPLS based on QoS architecture had become one of the most promising ways to guarantee QoS MulIti-service IP network. But how to manage IP network with QoS guarantee is still an open issue. In this paper, we propose DiffServ-aware-MPLS buffer management technique using the specified policing, queuing, and scheduling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.774-784
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• 2009

A wireless sensor network consisting of a large number of nodes with limited battery power should minimize energy consumption at each node to prolong the network lifetime. To improve the sensitivity of wireless sensor networks, an efficient scheduling algorithm and energy management technology for minimizing the energy consumption at each node is desired. ill this paper, we propose energy-aware routing mechanism for maximum lifetime and to optimize the solution quality for sensor network maintenance and to relay node from its adjacent cluster heads according to the node"s residual energy and its distance to the base station. Proposed protocol may minimize the energy consumption at each node, thus prolong the lifetime of the system regardless of where the sink is located outside or inside the cluster. Simulation results of proposed scheme show that our mechanism balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime. To verify propriety using NS-2, proposed scheme constructs sensor networks adapt to current model and evaluate consumption of total energy, energy consumption of cluster head, average energy dissipation over varying network areas with HEED and LEACH-C.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.130-139
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• 2010

Environmental issues and the need to reduce energy consumption for lowering operating costs have pushed power efficiency to become one of the major issues of current research in the field of wireless networks. This paper addresses a number of multiple input multiple output (MIMO) precoding and scheduling techniques across the PHY and MAC layers that can operate under a reduced link budget and collectively improve the transmit power efficiency of a base station, while maintaining the same levels of service. Different MIMO transmission and precoding schemes proposed for LTE, achieving varying degrees of multiuser diversity in both the time, frequency as well as the space domain, are examined. Several fairness-aware resource allocation algorithms are applied to the considered MIMO schemes and a detailed analysis of the tradeoffs between power efficiency and quality of service is presented. This paper explicitly examines the performance of a system serving real-time, VoIP traffic under different traffic loading conditions and transmit power levels. It is demonstrated that by use of efficient scheduling and resource allocation techniques significant savings in terms of consumed energy can be achieved, without compromising QoS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3603-3618
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• 2022

The offloading method is important when there are multiple mobile nodes and multiple edge servers. In the environment, those mobile nodes connect with edge servers with different bandwidths, thus taking different time and energy for offloading tasks. Considering the system load of edge servers and the attributes (the number of instructions, the size of files, deadlines, and so on) of tasks, the energy-aware offloading problem becomes difficult under our mobile edge environment (MCE). Most of the past work mainly offloads tasks by judging where the job consumes less energy. But sometimes, one task needs more energy because the preferred edge servers have been overloaded. Those methods always do not pay attention to the influence of the scheduling on the future tasks. In this paper, first, we try to execute the job locally when the job costs a lower energy consumption executed on the MD. We suppose that every task is submitted to the mobile server which has the highest bandwidth efficiency. Bandwidth efficiency is defined by the sending ratio, the receiving ratio, and their related power consumption. We sort the task in the descending order of the ratio between the energy consumption executed on the mobile server node and on the MD. Then, we give a "suffrage" definition for the energy consumption executed on different mobile servers for offloading tasks. The task selects the mobile server with the largest suffrage. Simulations show that our method reduces the execution time and the related energy consumption, while keeping a lower value in the number of uncompleted tasks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.10
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• pp.691-699
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• 2014

In order to increase network lifetime, duty-cycle MAC protocols which can reduce energy consumption caused by idle listening is proposed for WSNs. In common duty-cycle MAC protocols, each sensor node calculates its duty-cycle interval based on the current amount of residual energy. However, in WSNs with the capability of energy harvesting, existing duty-cycle intervals based on the residual energy may cause the sensor nodes which have high energy harvesting rate to suffer unnecessary sleep latency. Therefore, a duty-cycle scheduling scheme which adjust the duty-cycle interval based on both of the residual energy and the energy harvesting rate was proposed in our previous work. However, since this duty-cycle MAC protocol overlooked the performance variation according to the change of duty-cycle interval and adjusted the duty-cycle interval only linearly, the optimal duty-cycle interval could not be obtained to meet application requirements. In this paper, we propose three methods which calculate the duty-cycle interval and analyse their results. Through simulation study, we verify that network lifetime, end-to-end delay and packet delivery ratio can be improved up to 23%, 44% and 31% as compared to the existing linear duty-cycle scheduling method, respectively.

• Journal of Computing Science and Engineering
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• v.4 no.3
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• pp.189-206
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• 2010

It is generally accepted that dynamic voltage scaling (DVS) is one of the most effective techniques of energy minimization for real-time applications in embedded system design. The effectiveness comes from the fact that the amount of energy consumption is quadractically proportional to the voltage applied to the processor. The penalty is the execution delay, which is linearly and inversely proportional to the voltage. According to the granularity of tasks to which voltage scaling is applied, the DVS problem is divided into two subproblems: inter-task DVS problem, in which the determination of the voltage is carried out on a task-by-task basis and the voltage assigned to the task is unchanged during the whole execution of the task, and intra-task DVS problem, in which the operating voltage of a task is dynamically adjusted according to the execution behavior to reflect the changes of the required number of cycles to finish the task before the deadline. Frequent voltage transitions may cause an adverse effect on energy minimization due to the increase of the overhead of transition time and energy. In addition, DVS needs to be carefully applied so that the dynamically varying chip temperature should not exceed a certain threshold because a drastic increase of chip temperature is highly likely to cause system function failure. This paper reviews representative works on the theoretical solutions to DVS problems regarding inter-task DVS, intra-task DVS, voltage transition, and thermal-aware DVS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1313-1336
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• 2020

Cognitive radio (CR) is regarded as an effective approach to avoid the inefficient use of spectrum. However, CRNs have more special security problems compared with the traditional wireless communication systems due to its open and dynamic characteristics. Primary user emulation attack (PUEA) is a common method which can hinder secondary users (SUs) from accessing the spectrum by transmitting signals who has the similar characteristics of the primary users' (PUs) signals, and then the SUs' quality of service (QoS) cannot be guaranteed. To handle this issue, we first design a multiple-phase energy detection scheme based on the cooperation of multiple SUs to detect the PUEA more precisely. Second, a joint SUs scheduling and power allocation scheme is proposed to maximize the weighted effective capacity of multiple SUs with a constraint of the average interference to the PU. The simulation results show that the proposed method can effectively improve the effective capacity of the secondary users compared with the traditional overlay scheme which cannot be aware of the existence of PUEA. Also the good delay QoS guarantee for the secondary users is provided.