Earticle

본 논문에서는 SAN(Storage Area Network)에 장착된 하드디스크를 단순히 고성능 저장장치로 교체하면 고성능 저장장치의 뛰어난 성능을 제대로 활용할 수 없음을 확인하고 원인 분석을 하여 고성능 저장장치를 위한 SAN의 성능 최적화기법들을 제안하였다. 먼저 고성능 저장장치에 맞지 않는 기존의 SAN 입출력경로에 존재하던 지연을 없애고, 저장장치 서버에서 입출력 요청들을 병렬 처리할 수 있게 하고, 소형 랜덤 입출력처리의 성능 향상을 위해 SAN에 연결된 초고속 네트워크에 사용되는 기존의 전송 프로토콜에 시간적 병합 기법을 추가하였다. 제안한 기법들의 우수성을 입증하는 방법으로 실제로 고성능 저장장치를 장착한 SAN에 최적화기법들을 구현하였으며, 다양한 입출력 데이터로 실험한 결과 30%이상의 입출력 지연시간 절감과 200%이상의 성능 향상을 확인하였다.

We noted that substituting hard disk with high-performance storage device on SAN did not immediately result in getting high performance. Investigating the reason behind this leaded us to propose optimization schemes for high-performance storage system. We first got rid of the latency in the I/O process which is unsuitable for the high-performance storage device, added parallelism on the storage server, and applied temporal merge to Superhigh speed network protocol for improving the performance with small random I/O. The proposed scheme was implemented on the SAN with high-performance storage device and we verified that there were about 30% reduction on the I/O delay latency and 200% improvement on the storage bandwidth.

Urban water supply schemes are studied with multi-attribute characteristics taken into consideration. This paper proposes an optimized urban water supply scheme based on grey system theory. In the model, optimized indicators are given and their weights are acquired through optimized grey related analysis. These indicators are subject to standardization and are calculated to get grey incidence degree. The optimal water supply scheme is determined by the grey incidence degree. Finally, empirical test on the water supply scheme of a city is conducted to prove its objectivity, feasibility and reliability.

Hadoop Distributed File System (HDFS) becomes a representative cloud platform, benefiting from its reliable, scalable and low-cost storage capability. However, HDFS does not present good storage and access performance when processing a huge number of small files, because massive small files bring heavy burden on NameNode of HDFS. Meanwhile, HDFS does not provide any optimization solution for storing and accessing small files, as well as no prefetching mechanism to reduce I/O operations. This paper proposes an optimized scheme, Structured Index File Merging-SIFM, using two level file indexes, the structured metadata storage, and prefetching and caching strategy, to reduce the I/O operations and improve the access efficiency. Extensive experiments demonstrate that the proposed SIFM can effectively achieve better performance in the terms of the storing and accessing for a large number of small files on HDFS, compared with native HDFS and HAR.

As a widely used programming model for the purposes of processing large data sets, MapReduce (MR) becomes inevitable in data clusters or grids, e.g. a Hadoop environment. Load balancing as a key factor affecting the performance of map resource distribution, has recently gained high concerns to optimize. Current MR processes in the realization of distributed tasks to clusters use hashing with random modulo operations, which can lead to uneven data distribution and inclined loads, thereby obstruct the performance of the entire distribution system. In this paper, a virtual partition consistent hashing (VPCH) algorithm is proposed for the reduce stage of MR processes, in order to achieve such a trade-off on job allocation. Besides, experienced programmers are needed to decide the number of reducers used during the reduce phase of the MR, which makes the quality of MR scripts differ. So, an extreme learning method is employed to recommend potential number of reducer a mapped task needs. Execution time is also predicted for user to better arrange their tasks. According to the results, VPCH can lead to load balancing and our prediction model can provide fast prediction than SVM with similar accuracy maintained.

With regard to the subject of sensor network node optimization, a strategy for wireless sensor network coverage optimization based on improved fish swarm algorithm is proposed in this paper. The improved algorithm is targeted on network coverage, node utilization rate and energy consumption balance, which makes use of the ergodic property of chaotic motion to overcome the disadvantage that artificial fish swarm algorithm may easily lead to regional optimization. As for this, the global searching ability of algorithm is improved and the solving efficiency is optimized. Moreover, the algorithm is able to adapt to complicated environment. Shown by related simulation experiment, the improved fish swarm algorithm could effectively optimize sensor network node deployment and improve network coverage rate. Compared with basic artificial fish swarm algorithm, improved fish swarm algorithm increases network coverage rate by 8.9%.

Proxy Mobile IPv6 (PMIPv6), a network-based localized mobility protocol, allows a mobile node (MN) to move around within the same PMIPv6 domain by keeping the same IP address. However, PMIPv6 does not support the global handover since it supports only an intra-domain handover. To support the global handover, MNs need to load the protocol stack for the global mobility. Our proposed scheme enables the MN’s session to be connected without any support of PMIPv6 protocol during the global handover. In addition, it reduces the packet transmission delay by performing the Route Optimization (RO) after the MN’s global handover. In this paper, we compare our proposed scheme with the existing Roaming scheme. As a result, the proposed scheme reduces the packet transmission delay by 25% and the packet loss by 78% compared with the existing one. In other words, our scheme supports the seamless and reliable handover for MN.

Design of complex mechanical equipment and scheme of manufacturing need a comprehensive consideration of constraints, and it embodies multiple layers, complexity, multiple types and uncertainty. This paper analyzes the question of scheme optimization for complex mechanical equipment and proposes a method of manufacturing scheme optimization for complex mechanical equipment based on multi -attribute fuzzy information measurement model. This method functions to build an indicator system of optimization scheme for manufacturing complex mechanical equipment. Three models are designed to evaluate all optimization indicators the system, namely model for computation of fuzzy interval indicator’s information quantity, model for computation of qualitative indicator information quantity and model for computation of fuzzy indicator’s information quantity with degree of membership. Weights are given to information quantity optimization indicators in different layers get total complex mechanical equipment scheme choose optimal strategy based on design manufacture.

The complex equipment design scheme assimilability is affected by many factors. The analyzing process of it is both qualitative and quantitative. The process is fuzzy and qualitatively uncertain. For the purpose of objectively analyzing the complex equipment design scheme assimilability, an optimization model of complex equipment scheme assimilability based on extension superiority is proposed in this paper. The model first analyzes the influential factors of assimilability, establishing an optimal index system to standardize different types of optimal indexes and construct ideal extension fields of optimal indexes of assimilability based on extension theory. After that an extension correlation function model and an extension optimization model are constructed respectively based on extension positive fields and negative fields of assimilability optimal indexes. The size of extension optimization of assimilability optimal index of complex equipment design scheme helps acquire the optimal assembling scheme. The model is tested taking an assembling design scheme for a type of complex equipment as example.

망이동성지원 프로토콜 (NEMO basic support protocol)은 이동망의 통신노드들에 대해 인터넷 연결을 제공하기 위한 확장된 MIPv6이다. 그러나, 망이동성지원 프로토콜은 중첩된 이동망의 경우에 다중 캡슐화와 함께 최적화되지 않은 경로 선택으로 인하여 데이터 전송 지연과 많은 비용을 요구한다. 본 논문에서는 계층적 MIPv6 (HMIPv6)와 계층적 프리픽스 할당 (HPD) 프로토콜을 결합한 제안 기법을 통해 핸드오프 발생시 효율적인 경로최적화와 더불어 패킷헤더비용과 위치등록부하를 감소시켰다. 제안 기법은 계층적 프리픽스할당과 트리기반 경로방법을 통하여 이동망 노드들에 대한 주소를 할당하고, 마이크로 이동성을 지원함과 동시에 도메인 내에서의 상호통신을 가능케 한다. 제안된 기법의 성능평가를 위해 NS-2로 모의실험을 하였다.

The Network Mobility (NEMO) basic support protocol extends the operation of Mobile IPv6 to provide uninterrupted Internet connectivity to the communicating nodes of mobile networks. The protocol is not efficient to offer delays in data delivery and higher overheads in the case of nested mobile networks because it uses fairly sub-optimal routing and multiple encapsulation of data packets. In this paper, our scheme combining Hierarchical Mobile IPv6 (HMIPv6) functionality and Hierarchical Prefix Delegation (HPD) protocol for IPv6, which provide more effective route optimization and reduce packet header overhead and the burden of location registration for handoff. The scheme also uses hierarchical mobile network prefix (HMNP) assignment and tree-based routing mechanism to allocate the location address of mobile network nodes (MNNs) and support micro-mobility and intra-domain data communication. The performance is evaluated using NS-2.

재난현장에서 신속한 애드혹 무선 백본망을 형성하기 위해서는 사전계획 없이 초동 대응요원들에 의하여 무선 애드혹 중계장치를 실시간으로 배치하는 기법이 필요하다. 그러나 이를 실현하기 위해서는 중계장치의 중복배치 최소화뿐만 아니라 통신권역 확장을 위한 중계장치의 최적 위치를 선정할 수 있어야 한다. 따라서 본 논문에서는 통신권역을 최적화하기 위한 새로운 중계장치 배치기법을 제안하고 모의실험을 통하여 알고리즘의 성능이 향상되었음을 보였다.

For rapid formed the ad hoc wireless backbone network in disaster scene, It is necessary for real-time deployment scheme of wireless ad hoc relay devices by first responders without pre-planning. However, in order to realize this scheme, redundant deployment should be minimized, as well as optimal location of relay devices should be selected to expand communication coverage. Therefore, in this paper, we propose a new deployment scheme of relay devices to optimize communication coverage and then through simulations showed that improved performance of algorithm.

The object of the present work is the numerical analysis of the computer hard disk slider. The pressure between slider and disk surfaces is calculated using the Boundary Fitted Coordinate System and Divergence Formulation for the nonlinear Reynolds' equation solution. The optimization scheme is applied to search for the steady state position of the slider. The simplified method is given for the case of the fixed inclined pad. The film thickness ratios and pitching and rolling angles are considered as alternative choice of the slider's coordinates. The behavior of the objective function for the Negative Pressure slider is studied in details. Methods of conjugate directions and feasible directions are applied.

The structural shape optimization is a useful tool for engineers to determine the shape of a structure. During the optimization process, relocations of nodes happen successively. However, excessive movement of nodes often results in the mesh distortion and eventually deteriorates the accuracy of the optimum solution. To overcome this problem, an efficient method for the shape optimization has been developed. The method starts from the design domain which is large enough to hold the possible shape of the structure. The design domain has pre-defined uniform fine meshes. At every cycle, the method judges whether all the elements are inside of the structure or not. Elements inside of the structure are assigned with real material properties, however elements outside of the structure are assigned with nearly zero values. The performance of the method is evaluated through various examples.

In many wireless sensor network (WSN) applications, the information transmitted by an individual entity or node is of limited use without the knowledge of its location. Research in node localization is mostly geared towards multi-hop range-free localization algorithms to achieve accuracy by minimizing localization errors between the node's actual and estimated position. The existing localization algorithms are focused on improving localization accuracy without considering efficiency in terms of energy costs and algorithm convergence time. In this work, we show that our proposed localization scheme, called DV-maxHop, can achieve good accuracy and efficiency. We formulate the multi-objective optimization functions to minimize localization errors as well as the number of transmission during localization phase. We evaluate the performance of our scheme using extensive simulation on several anisotropic and isotropic topologies. Our scheme can achieve dual objective of accuracy and efficiency for various scenarios. Furthermore, the recently proposed algorithms require random uniform distribution of anchors. We also utilized our proposed scheme to compare and study some practical anchor distribution schemes.

Out-of-Order Packet ($O^3P$) problem is an issue that significantly impacts to the QoS of service and network. Route optimization (RO) in PMIPv6 is proposed by P.Loureiro and M. Liebsch to reduce the load of LMAs and transmission delay. In RO scheme, at the time the optimal path is established, there exist two paths: optimal path and old path as non-optimal path for transmitting data between MN1 and MN2 that is the cause of $O^3P$ occurring. This paper proposes a scheme to prevent $O^3P$ problem by using packet buffering technique and a new mobility message, named End Traffic Marker (ETM) to mark the end of packet delivery through the old path.

Large amount of data is being generated in gaming servers due to the increase in the number of users and the variety of game services being provided. In particular, load balancing schemes for gaming servers are crucial consideration. The existing literature proposes algorithms that distribute loads in servers by mostly concentrating on load balancing and cooperative offloading. However, many proposed schemes impose heavy restrictions and assumptions, and such a limited service classification method is not enough to satisfy the wide range of service requirements. We propose a load balancing agent that combines the dynamic allocation programming method, a type of greedy algorithm, and proximal policy optimization, a reinforcement learning. Also, we compare performances of our proposed scheme and those of a scheme from previous literature, ProGreGA, by running a simulation.

Improving resource utilization has been a hot issue in heterogeneous wireless networks (HWNs). This paper proposes a radio resource management (RRM) method based on access proportion optimization. By considering two or more wireless networks in overlapping regions, users in these regions must select one of the networks to access when they engage in calls. Hence, the proportion of service arrival rate that accesses each network in the overlapping region can be treated as an optimized factor for the performance analysis of HWNs. Moreover, this study considers user mobility as an important factor that affects the performance of HWNs, and it is reflected by the handoff rate. The objective of this study is to maximize the total throughput of HWNs by choosing the most appropriate factors. The total throughput of HWNs can be derived on the basis of a Markov model, which is determined by the handoff rate analysis and distribution of service arrival rate in each network. The objective problem can actually be expressed as an optimization problem. Considering the convexity of the objective function, the optimization problem can be solved using the subgradient approach. Finally, an RRM optimization scheme for HWNs is proposed. The simulation results show that the proposed scheme can effectively enhance the throughput of HWNs, i.e., improve the radio resource utilization.

Future cellular networks will mainly be driven by, high quality channels, high band with utilization, low power consumption and efficient network management. For a given channel allocation, the capacity and quality of communication of cellular radio systems using CDMA(Code Division Multiple Access) can be increased by using a transmitter power control scheme to combat the near-far problem. Centralized power control schemes or distributed ones to maximize the minimum signal-to-interference in each user of CDMA wireless network have been investigated. This paper has proposed a distributed power control algorithm, which employs an adaptive search scheme, in order to solve quickly the linear systems of equations for power update in CDMA cellular radio systems. The simulation results show that the proposed scheme has faster convergence rate than the typical bang-bang type of distributed power control algorithm, which has been much used as a reference algorithm in IS-95A and W-CDMA communication network.

High frequency signal injection (HFI) is an alternative method for estimating rotor position of interior permanent magnet synchronous motor (IPMSM). The general method of frequency and amplitude selection is based on error tolerance and experiments, and is usually set with only one group of HF parameters, which is not efficient for different working modes. This paper proposes a novel rotor position estimation scheme by HFI with optimized frequency and amplitude, based on the mathematic model of IPMSM. The requirements for standstill and low-speed operational modes are met by applying this novel scheme. Additionally, the effects of the frequency and amplitude of the injected HF signal on the position estimation results under different operating conditions are analyzed. Furthermore, an optimization method for HF parameter selection is proposed to make the estimation process more efficient under different working conditions according to error tolerance. The effectiveness of the propose scheme is verified by the experiments on an IPMSM motor prototype.

Bit error rate (BER) monitoring is the ultimate goal of performance monitoring in all digital transmission systems as well as optical fiber transmission systems. To achieve this goal, optimization of the decision threshold must also be considered because BER is dependent on the level of decision threshold. In this paper, we analyze a pseudo-error counting scheme and propose an algorithm to achieve both BER monitoring and adaptive decision threshold optimization in optical fiber transmission systems. To verify the effectiveness of the proposed algorithm, we conduct computer simulations in both Gaussian and non-Gaussian distribution cases. According to the simulation results, BER and the optimum decision threshold can be estimated with the errors of < 20% and < 10 mV, respectively, within 0.1-s processing time in > 40-Gb/s transmission systems.

모바일 트래픽은 계속해서 폭발적으로 증가하고 있으며 이동통신 사업자들은 기지국의 추가 설치만으로 계속해서 증가하는 모바일 트래픽 요구량을 충족하는 것이 점점 어려워지고 있다. 이를 극복하기 위해 기존의 매크로 셀에 펨토셀과 같은 스몰 셀을 설치하여 공간 및 주파수의 재사용이 가능한 이기종 네트워크(Heterogeneous network) 개념이 도입되었다. 그러나 펨토 소유자의 협력 없이는 기존의 매크로셀 사용자가 펨토셀에 연결되어 전체 네트워크의 효율성을 증대시키기 어렵다. 펨토 소유자도 적절한 인센티브(incentive)를 받지 않고는 다른 단말들을 자신의 펨토 기지국에 수용할 필요성을 느끼지 못한다. 본 논문에서는 새로운 단말을 펨토 셀에 추가하기 위하여 펨토 소유자에 제시할 최적의 인센티브를 도출하는 방법을 제시한다. 단말의 전송률을 바탕으로 이득함수를 구성하였으며 네트워크 전체의 이득함수를 최대화 할 수 있는 인센티브를 계산한다.

Mobile traffic is increasing consistently, and mobile carriers are becoming more and more hard to meet this ever-increasing mobile traffic demand by means of additional installation of base stations. To overcome this problem, heterogeneous networks, which can reuse space and frequency by installing small cells such as femto cells in existing macro cells, were introduced. However, existing macro cell users are difficult to increase the spectral efficiency without the cooperation of femto owners. Femto owners are also reluctant to accommodate other mobile stations in their femto stations without proper incentive. In this paper, a method of obtaining the optimal incentive is proposed, which adopts a utility function based on the logarithm of throughput of mobile stations, and the incentive is calculated to maximize the utility of the entire network.