• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2258-2276
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• 2019

Resource sharing is one of the main goals achieved by network virtualization technology to enhance network resource utilization and enable resource customization. Though resource sharing can improve network efficiency by accommodating various users in a network, limited infrastructure capacity is still a challenge to ultra-low latency service operators. In this paper, we propose an inter-slice resource borrowing schema based on the device-to-device (D2D) potentiality especially for ultra-low latency transmission in cellular networks. An extended and modified Kuhn-Munkres bipartite matching algorithm is developed to optimally achieve inter-slice resource borrowing. Simulation results show that, proper D2D user matching can be achieved, satisfying ultra-low latency (ULL) users' quality of service (QoS) requirements and resource utilization in various scenarios.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2240-2254
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• 2021

We investigate the channel allocation problem in an ultra-dense device-to-device (D2D) enabled cellular network in underlaying mode where multiple D2D users are forced to share the same channel. Two kinds of low complexity solutions, which just require partial channel state information (CSI) exchange, are devised to resolve the combinatorial optimization problem with the quality of service (QoS) guaranteeing. We begin by sorting the cellular users equipment (CUEs) links in sequence in a matric of interference tolerance for ensuring the SINR requirement. Moreover, the interference quota of CUEs is regarded as one kind of communication resource. Multiple D2D candidates compete for the interference quota to establish spectrum sharing links. Then base station calculates the occupation of interference quota by D2D users with partial CSI such as the interference channel gain of D2D users and the channel gain of D2D themselves, and carries out the channel allocation by setting different access priorities distribution. In this paper, we proposed two novel fast matching algorithms utilize partial information rather than global CSI exchanging, which reduce the computation complexity. Numerical results reveal that, our proposed algorithms achieve outstanding performance than the contrast algorithms including Hungarian algorithm in terms of throughput, fairness and access rate. Specifically, the performance of our proposed channel allocation algorithm is more superior in ultra-dense D2D scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2204-2224
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• 2021

This paper studies secure wireless transmission from a multi-antenna transmitter to a single-antenna intended receiver overheard by multiple eavesdroppers with considering the imperfect channel state information (CSI) of wiretap channel. To enhance security of communication link, the artificial noise (AN) is generated at transmitter. We first design the robust joint optimal beamforming of secret signal and AN to minimize transmit power with constraints of security quality of service (QoS), i.e., minimum allowable signal-to-interference-and-noise ratio (SINR) at receiver and maximum tolerable SINR at eavesdroppers. The formulated design problem is shown to be nonconvex and we transfer it into linear matrix inequalities (LMIs). The semidefinite relaxation (SDR) technique is used and the approximated method is proved to solve the original problem exactly. To verify the robustness and tightness of proposed beamforming, we also provide a method to calculate the worst-case SINR at eavesdroppers for a designed transmit scheme using semidefinite programming (SDP). Additionally, the secrecy rate maximization is explored for fixed total transmit power. To tackle the nonconvexity of original formulation, we develop an iterative approach employing sequential parametric convex approximation (SPCA). The simulation results illustrate that the proposed robust transmit schemes can effectively improve the transmit performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.874-890
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• 2021

With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.275-280
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• 2010

Recently, This paper suggests that LED-ID technique applying positioning method for LED light. also, Authors in this paper has launched this investigation earnestly. However, there are various interferences such as MPI(Multi Path Interference) by reflected waves of the surface and interfere factors by their correlation properties of the ID in LED-ID wireless channel. Therefore, in this paper, we propose a novel OOK(On-Off Keying)-CDMA(Code Division Multiple Access) system using unipolar ZCD(Zero Correlation Duration) spreading code and verify the availability of the proposed system via the evaluation performance simulation.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.1-8
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• 2020

In order to reach Ultra-Reliable Low-Latency communication, one of 5G aims, Multi-access Edge Computing paradigm was born. The idea of this paradigm is to bring cloud computing technologies closer to the network edge. User services are hosted in multiple Edge Clouds, deployed at the edge of the network distributedly, to reduce the service latency. For mobile users, migrating their services to the most proper Edge Clouds for maintaining a Quality of Service is a non-convex problem. The service migration problem becomes more complex in high mobility scenarios. The goal of the study is to observe how user mobility affects the selection of Edge Cloud during a fixed mobility path. Mobility-Aware Service Migration (MASM) is proposed to optimize service migration based on two main parameters: routing cost and service migration cost, during a high mobility scenario. The performance of the proposed algorithm is compared with an existing greedy algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.9
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• pp.38-45
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• 2007

With the emergence of new applications, packet classification is essential for supporting advanced internet applications, such as network security and QoS provisioning. As the packet classification on multiple-fields is a difficult and time consuming problem, internet routers need to classify incoming packet quickly into flows. In this paper, we present multi-phase packet classification architecture using an internal buffer for fast packet processing. Using internal buffer between address pair searching phase and remained fields searching phases, we can hide latency from the characteristic that search times of source and destination header fields are different. Moreover we guarantee the improvement by using single entry caching. The proposed architecture is easy to apply to different needs owing to its simplicity and generality.

• Journal of Internet Computing and Services
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• v.11 no.3
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• pp.121-129
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• 2010

In recent years, Cloud computing is gaining much popularity as it can efficiently utilize the computing resources and hence can contribute to the issue of green IT. So to make the Cloud services commercialized, Cloud markets are necessary and are being developed. As the increasing numbers of various Cloud services are rapidly evolving in the Cloud market, how to select the best and optimal services will be a great challenge. In this paper we present a Cloud service selection framework in the Cloud market that uses a recommender system (RS) which helps a user to select the best services from different Cloud providers (CP) that matches his/her requirements. The RS recommends a service based on the QoS and Virtual Machine (VM) factors of difference CPs. The experimental results show that our Cloud service recommender system (CSRS) can effectively recommend a good combination of Cloud services to consumers.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.153-163
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• 2008

Almost literature has so far proposed the modifications to IEEE 802.11 DCF MAC protocol to improve system throughput and average delay. Jitter(variance in packet delays) is, however, considered as an important QoS parameter for real-time streaming service which is popularized increasingly. Unfortunately, legacy access protocol for WLAN can't support the jitter. This paper proposes two schemes modifying the DCF MAC protocol to reduce the average value of jitter for multimedia frames arrived at received nodes. The one scheme, referred to as DCW-DCF(Decreasing Contention Window-DCF), reduces CW(Contention Window) size by half whenever a transmitted frame collided against other frames and back-off happens. Also, it increase initial CW size according as the link utilization and the collision probability increase. The other scheme, referred to as D-DIFS(Differential-DIFS), assigns different values to DIFS. That is, the DIFS interval is deceased as the number of back-off for a frame increases. In this paper, the two schemes are evaluated through simulation using ns2 and simulation results show that the proposed schemes are effective for improving the jitter property of standard WLAN.