• Journal of the Korea Society of Computer and Information
• /
• v.16 no.3
• /
• pp.53-63
• /
• 2011

Many techniques have been proposed to store and query XML data efficiently. One way achieving this goal is using relational database by transforming XML data into relational format. It is important to transform schema to preserve the content, the structure and the constraints of the semantics information of the XML document. Especially, key constraints are an important part of database theory. Therefore, the proposal technique has considered the semantics of XML as expressed by primary keys and foreign keys. And, the proposal technique can preserve not only XML data constraints but also the content and the structure and the semantics of XML data thru transformation process. Transforming information is the content and the structure of the document(the parent-child relationship), the functional dependencies, semantics of the document as captured by XML key and keyref constraints. Because of XML schema transformation ensures that preserving semantic constraints, the advantages of these transformation techniques do not need to use the stored procedure or trigger which these data ensures data integrity in the relational database. In this paper, there is not chosen the ID/IDREF key which supported in DTD, the inheritance relationship, the implicit referential integrity.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.7
• /
• pp.2350-2364
• /
• 2014

This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

• Journal of Power Electronics
• /
• v.18 no.4
• /
• pp.1111-1126
• /
• 2018

In modern power systems, distributed generators (DGs) result in high stress on system frequency stability. Apart from the intermittent nature of DGs, most DGs do not contribute inertia or damping to systems. As a result, a new control method referred to as a virtual synchronous machine (VSM) has been proposed, which brought new characteristics to inverters such as synchronous machines (SM). DGs employing an energy storage system (ESS) provide inertia and damping through VSM control. Meanwhile, energy storage presents some physical constraints in the VSM implementation level. In this paper, a VSM mathematical model is built and analyzed. The dynamic responses of the output active power are presented when a step change in the frequency occurs. The influences of the inertia constant, damping factor and operating point on the ESS volume margins are investigated. In addition, physical constraints are proposed based on these analyses. The proposed physical constraints are simulated using PSCAD/EMTDC software and tested through RTDS experiment. Both simulation and RTDS test results verify the analysis.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.1
• /
• pp.34-39
• /
• 2008

Nash Equilibrium(NE) is essential to investigate a participant's bidding strategy in a competitive electricity market. Congestion on a transmission line makes it difficult to compute the NE due to causing a mixed strategy. In order to compute the NE of a multi-player game, some heuristics are proposed with concepts of a key player and power transfer distribution factor in other studies. However, generation capacity constraints are not considered and make it more difficult to compute the NE in the heuristics approach. This paper addresses an effect of generation capacity limits on the NE, and suggest a solution technique for the mixed strategy NE including generation capacity constraints as two heuristic rules. It is reported in this paper that a role of the key player who controls congestion in a NE can be transferred to other player depending on the generation capacity of the key player. The suggested heuristic rules are verified to compute the mixed strategy NE with a consideration of generation capacity constraints, and the effect of the generation constraints on the mixed strategy NE is analyzed in simulations of IEEE 30 bus systems.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.3
• /
• pp.1099-1109
• /
• 2018

For practical consideration, economic dispatch (ED) problems in power system have non-smooth cost functions with equality and inequality constraints that makes the problems complex constrained nonlinear optimization problems. This paper proposes a new constraint handling method for equality and inequality constraints which is employed to solve ED problems, where the incremental rate is employed to enhance the modification process. In order to prove the applicability of the proposed method, the study cases are tested based on the classical particle swarm optimization (PSO) and differential evolution (DE) algorithm. The proposed method is evaluated for ED problems using six different test systems: 6-, 15-, 20-, 38-, 110- and 140-generators system. Simulation results show that it can always find the satisfactory solutions while satisfying the constraints.

• Journal of Communications and Networks
• /
• v.6 no.4
• /
• pp.352-361
• /
• 2004

In this paper, we study how to achieve the maximum capacity under delay constraints for large mobile wireless networks. We develop a systematic methodology for studying this problem in the asymptotic region when the number of nodes n in the network is large. We first identify a number of key parameters for a large class of scheduling schemes, and investigate the inherent tradeoffs among the capacity, the delay, and these scheduling parameters. Based on these inherent tradeoffs, we are able to compute the upper bound on the maximum per-node capacity of a large mobile wireless network under given delay constraints. Further, in the process of proving the upper bound, we are able to identify the optimal values of the key scheduling parameters. Knowing these optimal values, we can then develop scheduling schemes that achieve the upper bound up to some logarithmic factor, which suggests that our upper bound is fairly tight. We have applied this methodology to both the i.i.d. mobility model and the random way-point mobility model. In both cases, our methodology allows us to develop new scheduling schemes that can achieve larger capacity than previous proposals under the same delay constraints. In particular, for the i.i.d. mobility model, our scheme can achieve (n-1/3/log3/2 n) per-node capacity with constant delay. This demonstrates that, under the i.i.d. mobility model, mobility increases the capacity even with constant delays. Our methodology can also be extended to incorporate additional scheduling constraints.

• Journal of Information Processing Systems
• /
• v.19 no.5
• /
• pp.563-575
• /
• 2023

Trajectory planning is a key technology for unmanned aerial vehicles (UAVs) to achieve complex flight missions. In this paper, a terminal constraints conversion-based Gauss pseudospectral trajectory planning optimization method is proposed. Firstly, the UAV trajectory planning mathematical model is established with considering the boundary conditions and dynamic constraints of UAV. Then, a terminal constraint handling strategy is presented to tackle terminal constraints by introducing new penalty parameters so as to improve the performance index. Combined with Gauss-Legendre collocation discretization, the improved Gauss pseudospectral method is given in detail. Finally, simulation tests are carried out on a four-quadrotor UAV model with different terminal constraints to verify the performance of the proposed method. Test studies indicate that the proposed method performances well in handling complex terminal constraints and the improvements are efficient to obtain better performance indexes when compared with the traditional Gauss pseudospectral method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.5
• /
• pp.1569-1586
• /
• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.4
• /
• pp.1106-1127
• /
• 2012

Service oriented architecture (SOA) lends itself to model the application components to coarse-grained services in such a way that the composition of different services could be feasible. Service composition fulfills numerous service requirements by constructing composite applications with various services. As it is the case in many real-world applications, different users have diverse QoS demands issuing for composite applications. In this paper, we present a service composition framework for a typical service overlay network (SON) considering both multiple QoS constraints and load balancing factors. Moreover, a service selection algorithm based on niching technique and particle swarm optimization (PSO) is proposed for the service composition problem. It supports optimization problems with multiple constraints and objective functions, whether linear or nonlinear. Simulation results show that the proposed algorithm results in an acceptable level of efficiency regarding the service composition objective under different circumstances.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.7 no.1
• /
• pp.142-156
• /
• 2015

A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.