• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.23-29
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• 2015

Energy constraints of wireless sensor networks are an important challenge. Data Transmission requires energy. Distance between origin and destination has an important role in energy consumption. In addition, the location of base station has a large impact on energy consumption and a specific method not proposed for it. In addition, a obtain model for location of base station proposed. Also a model for distributed clustering is presented by cluster heads. Eventually, a combination of discussed ideas is proposed to improve the energy consumption. The proposed ideas have been implemented over the LEACH-C protocol. Evaluation results show that the proposed methods have a better performance in energy consumption and lifetime of the network in comparison with similar methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• International Journal of Quality Innovation
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• v.4 no.1
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• pp.205-212
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• 2003

Statistical Process Control (SPC) is recognized as one of the most important tool of quality control (QC), and is one research focus in order to implement SPC quickly and effectively using computer technology and network environments. This paper proposes the principle and topology of embedded SPC based on the Internet/lntranet, emphatically discusses the embedded data sampling block, embedded network interface and SPC strategy. An example of application is given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.819-837
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• 2014

Data centers, which implement cloud service, have been faced up with quick growth of energy consumption and low efficiency of energy. 60GHz wireless communication technology, as a new option to data centers, can provide feasible approach to alleviate the problems. Aiming at energy optimization in 60GHz wireless data centers (WDCs), we investigate virtualization technology to assign virtual resources to minimum number of servers, and turn off other servers or adjust them to the state of low power. By comprehensive analysis of wireless data centers, we model virtual network and physical network in WDCs firstly, and propose Virtual Resource Mapping Packing Algorithm (VRMPA) to solve energy management problems. According to VRMPA, we adopt packing algorithm and sort physical resource only once, which improves efficiency of virtual resource allocation. Simulation results show that, under the condition of guaranteeing network load, VPMPA algorithm can achieve better virtual request acceptance rate and higher utilization rate of energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2003-2021
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• 2020

Today's computer systems are widely integrated with CPU and GPU to achieve considerable performance, but energy consumption of such system directly affects operational cost, maintainability and environmental problem, which has been aroused wide concern by researchers, computer architects, and developers. To cope with energy problem, we propose a task-scheduling framework to reduce energy under performance constraint by rationally allocating the tasks across the CPU and GPU. The framework first collects the estimated energy consumption of programs and performance information. Next, we use above information to formalize the scheduling problem as the 0-1 knapsack problem. Then, we elaborate our experiment on typical platform to verify proposed scheduling framework. The experimental results show that our proposed algorithm saves 14.97% energy compared with that of the time-oriented policy and yields 37.23% performance improvement than that of energy-oriented scheme on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2017-2036
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• 2012

Based on the current solutions to the problem of energy hole, this paper proposed a nonuniform node distribution clustering algorithm, NNDC. Firstly, we divide the network into rings, and then have an analysis and calculation on nodes' energy consumption in each ring of the network when clustering algorithm is applied to collect data. We also put forward a scheme of nonuniform node distribution on the basis of the proportion of nodes' energy consumption in each ring, and change nodes' active/hibernating states under density control mechanism when network coverage is guaranteed. Simulation shows NNDC algorithm can satisfyingly balance nodes' energy consumption and effectively avoid the problem of energy hole.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4320-4333
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• 2017

Energy-efficient virtual resource allocation algorithm has become a hot research topic in cloud computing. However, most of the existing allocation schemes cannot ensure each type of resource be fully utilized. To solve the problem, this paper proposes a virtual machine (VM) allocation algorithm on the basis of multi-dimensional resource, considering the diversity of user's requests. First, we analyze the usage of each dimension resource of physical machines (PMs) and build a D-dimensional resource state model. Second, we introduce an energy-resource state metric (PAR) and then propose an energy-aware multi-dimensional resource allocation algorithm called MRBEA to allocate resources according to the resource state and energy consumption of PMs. Third, we validate the effectiveness of the proposed algorithm by real-world datasets. Experimental results show that MRBEA has a better performance in terms of energy consumption, SLA violations and the number of VM migrations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1692-1711
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• 2016

Energy is a scarce resource in wireless sensor networks (WSNs). A variety of clustering protocols for WSNs, such as the zone-based stable election protocol-enhanced (ZSEP-E), have been developed for energy optimization. The ZSEP-E is a heterogeneous zone-based clustering protocol that focuses on unbalanced energy consumption with parallel formation of clusters in zones and election of cluster heads (CHs). Most ZSEP-E research has assumed probabilistic election of CHs in the zones by considering the maximum residual energy of nodes. However, studies of the diverse CH election parameters are lacking. We investigated the performance of the ZSEP-E in such scenarios using a fuzzy logic approach based on three descriptors, i.e., energy, density, and the distance from the node to the base station. We proposed an efficient ZSEP-E scheme to adapt and elect CHs in zones using fuzzy variables and evaluated its performance for different energy levels in the zones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1604-1617
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• 2014

This paper proposes RIX-MAC (Receiver-Initiated X-MAC), a new energy-efficient MAC protocol based on an asynchronous duty cycling. RIX-MAC improves energy efficiency through utilizing short preambles and adopting the receiver-initiated approach, where RIX-MAC minimizes sender nodes' energy consumption by enabling transmitters to predict receiver nodes' wake-up times. It also reduces receiver nodes' energy consumption by decreasing the number of control frames. We use the network simulator to evaluate RIX-MAC's performance. Compared to the prior asynchronous duty cycling approaches of X-MAC and PW-MAC, the proposed protocol shows a remarkable improvement in energy-efficiency and end-to-end delay.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.49-56
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• 2015

As WSN is energy constraint so energy efficiency of nodes is important. Because avoiding long distance communication, clustering operating in rounds is an efficient algorithm for prolonging the lifetime of WSN and its performance depends on duration of a round. A short round time leads to frequent re-clustering while a long round time increases energy consume of cluster heads more. So existing clustering schemes determine proper round time, based on the parameters of initial WSN. But it is not appropriate to apply the round time according to initial value throughout the whole network time because WSN is very dynamic networks nodes can be added or vanished. In this paper we propose a new algorithm which calculates the round time relying on the alive node number to adapt the dynamic WSN. Simulation results validate the proposed algorithm has better performance in terms of energy consumption of nodes and loss rate of data.