Dynamic Adjustment Algorithm Research Articles

An Effective RAID Data Layout for Object‐Based De‐duplication Backup System

We propose an alternative Redundant array of independent disks (RAID) data layout, Asymmetrical grouping data organization (AGDO), for object-based data de-duplication backup system. Object-based data deduplication is an effective solution for detecting duplicate data for compound files. We designed an asymmetrical grouping strategy, the disk in the array are partitioned into different groups, and in each group parallelism data access scheme is adopted, different types of objects are stored in different groups with maybe different group size, it can set and manage dynamic group size by using dynamic disk group adjustment algorithms. The performance of AGDO is evaluated and proved to be sufficient for the continuous storage application. The result is that disk accesses are concentrated in a part of the disks over a long time period and reduces the power consumption to 25% in a 10 disk configuration. Moreover, object-based de-duplication combined with AGDO has great potential in increasing data restoration speed for compound files. We have shown that this combination makes average restoration speed improved 11%.

A robust power control scheme for femtocell networks with probability constraint of channel gains

In this paper, a robust power control algorithm is proposed in two-tier femtocell network system in order to address the uncertain channel gains of the interference links. In the algorithm, an outage probability is used to guarantee the communication qualities of users. As the deterministic form of the outage probability constraint is not convex of power, a novel and simple method is utilized to solve the power allocation problem. The allocation solution can be determined based on the average channel gains which are engaged with a dynamic factor with average signal-to-interference-plus-noise ratio. In the scheme, a dynamic power adjustment algorithm is developed. The algorithm attempts to guarantee the outage probability requirement of the macrocell user, and to achieve the optimal power allocation of femtocell users. Apart from the appropriate resource for the network, an admission control algorithm is adopted to remove the femtocell user whose communication quality can not be ensured. Numerical results demonstrate the effectiveness of the robust power control algorithm and also explain the admission control algorithm.

Survey of Dynamic Super-Frame Adjustment Schemes in Beacon-Enabled IEEE 802.15.4 Networks: An Application’s Perspective

IEEE 802.15.4 targets low data rate communication with limited power devices and cheap wireless networking solutions. In recent years both industry and academia are attracted to IEEE 802.15.4 because of its applicability in wireless sensor networks and wireless body area networks. An important feature of IEEE 802.15.4 is its very low duty cycle operation for conserving energy consumption of sensor device. Super-frame structure of IEEE 802.15.4 defines the duty cycle of nodes. The super-frame structure is based on two parameters: beacon order (BO) and super-frame order (SO). The performance of an IEEE 802.15.4 network depends on the values of BO and SO. These values depict the energy consumption, throughput, node discovery and latency of communication. IEEE 802.15.4 uses fixed BO and SO values which can be carefully chosen to meet the network requirements. In this paper, an extensive survey of dynamic super-frame adjustment algorithms is presented. The survey focuses on beacon-enabled star topology of IEEE 802.15.4 and studies the impact of aforementioned algorithms for various applications. Also, the survey categorizes common IEEE 802.15.4 applications based on their requirements for super-frame adjustment. A brief simulation analysis is included in this survey to highlight the impact of BO and SO on the network performance.

Reducing the complexity of an adaptive radial basis function network with a histogram algorithm

In this paper, a constructive training technique known as the dynamic decay adjustment (DDA) algorithm is combined with an information density estimation method to develop a new variant of the radial basis function (RBF) network. The RBF network trained with the DDA algorithm (i.e. RBFNDDA) is able to learn information incrementally by creating new hidden units whenever it is necessary. However, RBFNDDA exhibits a greedy insertion behaviour that absorbs both useful and non-useful information during its learning process, therefore increasing its network complexity unnecessarily. As such, we propose to integrate RBFNDDA with a histogram (HIST) algorithm to reduce the network complexity. The HIST algorithm is used to compute distribution of information in the trained RBFNDDA network. Then, hidden nodes with non-useful information are identified and pruned. The effectiveness of the proposed model, namely RBFNDDA-HIST, is evaluated using a number of benchmark data sets. A performance comparison study between RBFNDDA-HIST and other classification methods is conducted. The proposed RBFNDDA-HIST model is also applied to a real-world condition monitoring problem in a power generation plant. The results are analysed and discussed. The outcome indicates that RBFNDDA-HIST not only can reduce the number of hidden nodes significantly without requiring a long training time but also can produce promising accuracy rates.

Forming a dynamic adjustment algorithm for the radio-optical system of a large terrestrial fully steerable radio telescope

This article discusses the problem of forming a dynamic adjustment algorithm for the radio-optical system of a large terrestrial fully steerable radio telescope that can be carried out in its operating regime under conditions of deformation of the elements of the metallic structures of the radio telescope, generated by external effects. The adjustment algorithm is based on the concept of an equivalent radio lens whose optical parameters are formed by the methods of matrix optics in Kogel’nik’s basis. These results are illustrated, using as an example a terrestrial fully steerable radio telescope with a primary reflector 64 m in diameter, produced in this country.

A Dynamic Water-Filling Method for Real-Time HVAC Load Control Based on Model Predictive Control

Heating ventilation and air-conditioning (HVAC) system can be viewed as elastic load to provide demand response. Existing work usually used HVAC to do the load following or load shaping based on given control signals or objectives. However, optimal external control signals may not always be available. Without such control signals, how to make a tradeoff between the fluctuation of non-renewable power generation and the limited demand response potential of the elastic load, while still guaranteeing user comfort level, is still an open problem. To solve this problem, we first model the temperature evolution process of a room and propose an approach to estimate the key parameters of the model. Second, based on the model predictive control, a centralized and a distributed algorithm are proposed to minimize the fluctuation and maximize user comfort level. In addition, we propose a dynamic water level adjustment algorithm to make the demand response always available in two directions. Extensive simulations based on practical data sets show that the proposed algorithms can effectively reduce the load fluctuation.

Utility-driven relay for hybrid access femtocells based on cognitive radio spectrum auction

Femtocells promisingly improve coverage and spectrum efficiency at the edge of macrocell. However, macro users may suffer dead-zone trouble due to strong interference coming from closed access femtocell, or compete spectrum resource with femto users in the open access model. In this paper, we propose a novel utility-driven relay scheme adopted by hybrid access femtocell (HAF) to address the above two issues, wherein the macrocell maximizes the usage of its idle spectrum bands, bided by femtocells, via cognitive radio spectrum auction; and recompense relay expense to stimulate selfish femtocells undertaking HAFs to relay the signal to the vicinal macro user, meanwhile avoiding two-tier interference. Spectrum competition among femtocells is formulated as a static Cournot game provided with global information; then necessarily considered as a dynamic Cournot game of the strategy adapting distributively according to the players previous actions. Furthermore, we introduce a protocol and propose refund factor, spectrum price dynamic adjustment algorithms to achieve the Stackelberg equilibrium, i.e., the solution of the non-cooperative game between macrocell and femtocells. We also prove the existence of equilibrium and the convergence of algorithms. Extensive simulation results show the details of games, which indicate they can match the win-win hybrid access mechanism, benefiting cell-edge macro users for better QoS and higher access opportunities for femto users.

Optimal allocation of distributed generation and energy storage system in microgrids

This study presents a new approach for optimal allocation of distributed generation (DG) and energy storage system (ESS) in microgrids (MGs). The practical optimal allocation problems have non-smooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. A dynamic capacity adjustment algorithm is incorporated in the matrix real-coded genetic algorithm (MRCGA) framework to deal with the non-smooth cost functions. The proposed cost function takes into consideration operation cost minimisation as well as investment cost minimisation at the same time for the MG. Moreover, an energy storage equality constraint is applied to manage the state of charge of EES in MGs. The MRCGA is used to minimise the cost function of the system while constraining it to meet the customer demand and security of the system. For each studied case, sets of optimal capacities and economic operation strategies of ESS and DG sources are determined. The computational simulation results are presented to verify the effectiveness of the proposed method.

Research on the Key Technologies of Resource Dynamic Management in Cloud Computing Environment

For the "hot spots" problem caused by the number of replica could not satisfy the soaring request from users, we present a Cloud Computing storage resource replica dynamic scheduling scheme based on HDFS. There are two sub algorithms which is the number of replica dynamic adjustment algorithm and replica placement algorithm. This scheme could improve system stability and file access through put. The experiment result shows this optimized scheme lower the access delay obviously than the original scheme with some cost of storage resource and network workload. For the problem of metadata management, this paper introduced a distributed metadata management scheme. This scheme distributed metadata into several name node according to their ability, and provides an efficient inquiry algorithm for metadata to improve system availability and reliability. The experiment result shows the multi-name nodes system with this metadata management scheme could improve the performance than the original system facing the huge metadata operation requests.

A Dynamic Adjustment Algorithm of Slow-Start Threshold Based on RTT

The slow-start threshold in the current TCP Reno algorithm is a fixed value, and it does not change with the current network congestion status, which is prone to end the slow-start course too early or too late. Round-trip time (RTT) can reflect the current network status better. The paper presents a dynamic adjustment algorithm of slow-start threshold based on RTT, by which the value of slow-start threshold is dynamically adjusted according to the current RTT. Simulation results show that it effectively reduces congestion collapse in congestion state, and throughput is further improved under ideal network status.

Neural Network Adaptive Control for X-Y Position Platform with Uncertainty

An improvement neural network adaptive control strategy is put forward for X-Y position platform with uncertainty by the paper. Firstly, dynamics model of X-Y position platform is established. Then, RBF neural network with good learning ability is used to approach non-linear system. The early period control accuracy of the problem is considered by the paper, because good precision in the early period is difficult to be obtained by neural network controller, so PID controller is designed to compensate control. An improvement dynamic optimization adjustment algorithm of network weights is designed to speed up the learning speed. Simulation results show that the control method is more effective to improve the control precision and real-time and has a good application value.

Balanced Binary Tree Adjustment Algorithm Visualization Teaching Research and Practice

Data structure teaching difficulty is not to show a variety of data structures and algorithms of dynamic process. Balanced binary tree insert and delete balance adjustment process is also so. In order to show the dynamic rebalancing process, by using object oriented method to achieve AVL tree visualization. On the left side of the window shows the minimum unbalanced subtree dynamic adjustment algorithm, on the right side real-time call in relative rebalancing graphic, and at each node upper real-time display every subtree's balance factor, shows various shapes balance binary tree insert and delete operation of all balance adjustment.

A hybrid intelligent approach for modeling brand choice and constructing a market response simulator

Brand choice models, used for describing the process of choosing mutually exclusive alternatives, attracted a large amount of attention from researchers in the early of the recent decade. These models can be used as a market response simulator for simulating marketing strategies and assessing how changes in marketing variables such as pricing and promotions will influence consumer behavior and thus perform ‘what-if’ simulations. So a reliable and relevant brand choice model can be very useful and effective, which, in fact, represents a worthwhile opportunity to improve the efficiency of the marketing decisions. In this paper we offer a new approach by integrating of Probabilistic Neural Network (PNN) and Data preprocessing for brand choice modeling and constructing a market response simulator. This approach, called Preprocessed-Probabilistic Neural Network (PPNN), consists of two main stages. First, a robust Genetic Based Instance Selection Model (GBIS) employed to look for a representative data subset of instances in training data set. The second stage ends up with a relevant brand choice model, using a probabilistic neural network trained by Dynamic Decay Adjustment Algorithm (DDA). The evaluation process is carried out using the same data set been used in literature for modeling individual consumer choices in a retail coffee market. The evaluation results show that the offered approach outperforms all previous methods, so it can be considered as an effective tool for consumer behavior modeling and simulation.

An Effective Load Balancing Algorithm for Structured P2P Networks

In DHT based P2P systems, various issues such as peer heterogeneity,network topology, and diverse file popularity, may affect the DHT system efficiency. A new load balance algorithm, static load distribution algorithm and dynamic load adjustment algorithm (SDDA) is proposed, SDDA is designed based on the concept of virtual server, The new algorithm can dynamically adjusts Address-Space and fairness workload for each node after measured it’s capacity. Through research and simulation analysis, compared with the traditional virtual server load balancing algorithm, the SDDA algorithm is with better load balance, faster velocity of load balancing, less load movement cost, and more excellent stability of P2P system.

Code division multiple access/pulse position modulation ultra‐wideband radio frequency identification for Internet of Things: concept and analysis

SUMMARYRadio frequency identification (RFID) is a compelling technology for Internet of Things (IoT). Ultra‐wideband (UWB) technology is one promising wireless technique for future RFID, especially for high‐throughput sensing applications. On‐off keying UWB RFID system provides high pulse rate but suffers severe collisions that limit the system throughput. This paper proposes to utilize low pulse rate code division multiple access/pulse position modulation UWB in the tag‐to‐reader link to provide multiple tag access capability and build a high‐throughput RFID system for IoT. We analyze asynchronous matched filter receiver and decorrelating receiver for multi‐tag detection and design an effective medium access control scheme to optimize the network throughput. We propose an effective dynamic frame size adjustment algorithm on the basis of theoretical analysis and determine the preferable length of Gold codes. With a similar data rate, the throughput of the proposed system using the decorrelating receiver is 8.6 times higher than that of the electronic product code class 1 generation 2 system. Only using 1/10 pulse rate and 1/15 data rate, the proposed system outperforms the on‐off keying UWB RFID system 1.4 times in terms of throughput. Copyright © 2012 John Wiley & Sons, Ltd.

An Adaptive and Dynamic Load Balancing Algorithm for Structured P2P Systems

One important issue in the DHT design is how to balance the load across the nodes in the system. To achieve load balance, existing DHT-based P2P systems simply resort to the hash function to map objects to nodes randomly. However, the use of DHT and the heterogeneity of nodes capacities may give rise to load imbalance problems, and affect the DHT system efficiency as well. A new load balance algorithm, static load distribution algorithm and dynamic load adjustment algorithm (SDDA) is proposed, SDDA is designed based on the concept of virtual server, The new algorithm can dynamically adjusts Address-Space and fairness workload for each node after measured it’s capacity. Through research and simulation analysis, compared with the traditional virtual server load balancing algorithm, the SDDA algorithm is with better load balance, faster velocity of load balancing, less load movement cost, and more excellent stability of P2P system.

IEEE 802.16m에서 이동 단말의 전력 절감 방안

다양한 서비스의 활성화로 인한 이동 단말의 사용 시간 및 트래픽의 증가로 인해 배터리로 구동되는 이동 단말의 전력 절감 기술이 주목받고 있다. 본 논문은 4G 기술 중의 하나인 Mobile WiMAX라 불리는 IEEE 802.16m의 전력 절감 기술에 대해서 기술한다. 먼저 IEEE 802.16m의 기초가 되는 IEEE 802.16e 전력 절감 방안과의 차이점 및 기술적 특정을 살펴본다. 이동 단말의 효율적인 전력 관리를 위해 패킷들의 도착 분포 정보를 기반으로 동적 수면 사이클 조절 방안을 제안한다. 제안한 방안을 에너지 절감 측면과 패킷 대기 지연 시간 측면에서 살펴본다. As the usage of mobile stations increases thanks to various services, power saving mechanisms of mobile station operated by battery power have been gained much attention. This paper presents a power saving mechanism(PSM) of IEEE 802.16m, called Mobile WiMAX, for 4G mobile technology. This paper first presents different points of the PSM of IEEE 802.16m from IEEE 802.16e, which is a basis of IEEE 802.16m. This paper proposes a dynamic sleep cycle adjustment algorithm for improving the performance of IEEE 802.16m PSM by considering the arrival pattern of incoming packets from base station. Performance of the algorithm is analyzed in terms of energy consumption as well as waiting time of packets.

An Adaptive and Dynamic Load Balancing Algorithm for Structured P2P Systems

One important issue in the DHT design is how to balance the load across the nodes in the system. To achieve load balance, existing DHT-based P2P systems simply resort to the hash function to map objects to nodes randomly. However, the use of DHT and the heterogeneity of nodes capacities may give rise to load imbalance problems, and affect the DHT system efficiency as well. A new load balance algorithm, static load distribution algorithm and dynamic load adjustment algorithm (SDDA) is proposed, SDDA is designed based on the concept of virtual server, The new algorithm can dynamically adjusts Address-Space and fairness workload for each node after measured it’s capacity. Through research and simulation analysis, compared with the traditional virtual server load balancing algorithm, the SDDA algorithm is with better load balance, faster velocity of load balancing, less load movement cost, and more excellent stability of P2P system.

Distributed Optimal Resource Allocation Algorithm Based on Mission of Cooperative Multi-Flows in Ad Hoc Network

Flexibility of Ad Hoc network flourishes many network applications,such as video surveillance and so on,with multiple flows and joint collaboration characteristics.However,existing algorithms rely on an independent data stream utility function,the result of competition for resources often does not meet the mission requirements of the joint distribution of bandwidth, causing the joint task inefficient.It is an important constraint to improve the quality of network services.We are the first to quantify the perception of mission-resource relationship,improving the precision of original model.A mission-based dynamic resource utilization adjustment algorithm (Based-on mission utility resource dynamic algorithm MRD) is proposed.The paper proved the global optimum of the algorithm.Simulation shows that this method can improve the Ad Hoc network efficiency.

Dynamic slot assignment protocol for QoS support on TDMA-based mobile networks

An efficient bandwidth allocation scheme in wireless networks should not only guarantee successful data transmission without collisions but also enhance the channel spatial reuse to maximize the system throughput. The design of high-performance wireless Local Area Network (LAN) technologies making use of TDMA/FDD MAC (Time Division Multiple Access/Frequency Division Duplex – Medium Access Control) is a very active area of research and development. Several protocols have been proposed in the literature as TDMA-based bandwidth allocation schemes. However, they do not have a convenient generic parameters or suitable frame repartition for dynamic adjustment. In this work, we undertake the design and performance evaluation of a QoS (Quality of Service)-aware scheme built on top of the underlying signaling and bandwidth allocation mechanisms provided by most wireless LANs standards. The main contribution of this study is the new guarantee-based dynamic adjustment algorithm used in MAC level to provide the required QoS for all traffic types in wireless medium especially Wireless ATM (Asynchronous Transfer Mode). Performance evaluation of this approach consists of improving the bandwidth utilization, supporting different QoS requirements and reducing call reject probability and packet latency.