• Journal of Communications and Networks
• /
• v.11 no.2
• /
• pp.166-174
• /
• 2009

In this paper, a distributed power and end-to-end rate control algorithm is proposed in the presence of licensed users. By Lagrangian duality theory, the optimal power and rate control solution is given for the unlicensed users while satisfying the interference temperature limits to licensed users. It is obtained that transmitting with either 0 or the maximum node power is the optimal scheme. The synchronous and asynchronous distributed algorithms are proposed to be implemented at the nodes and links. The convergence of the proposed algorithms are proved. Finally, further discussion on the utility-based fairness is provided for the proposed algorithms. Numerical results show that the proposed algorithm can limit the interference to licensed user under a predefined threshold.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.39 no.4
• /
• pp.180-187
• /
• 2002

Many real-time multimedia applications, such as video conferencing have stringent end-to-end delay constraints and consume large amount of network resources. In order to support these applications efficiently, multicast routing algorithms computing least cost multicast trees that satisfy a given end-to-end delay constraint are needed. However, finding such a tree is known to be computationally expensive. Therefore, we propose a heuristic distributed multicast routing algorithm that reduces a “finding multicast tree”that satisfies a given end-to-end delay constraint and minimizes the average resulting tree cost. Also, simulation results show that the proposed algorithm has much better average cost performance than other existing algorithms.

• Journal of Information Processing Systems
• /
• v.5 no.4
• /
• pp.175-186
• /
• 2009

Power consumed by modern computer systems, particularly servers in data centers has almost reached an unacceptable level. However, their energy consumption is often not justifiable when their utilization is considered; that is, they tend to consume more energy than needed for their computing related jobs. Task scheduling in distributed computing systems (DCSs) can play a crucial role in increasing utilization; this will lead to the reduction in energy consumption. In this paper, we address the problem of scheduling precedence-constrained parallel applications in DCSs, and present two energy- conscious scheduling algorithms. Our scheduling algorithms adopt dynamic voltage and frequency scaling (DVFS) to minimize energy consumption. DVFS, as an efficient power management technology, has been increasingly integrated into many recent commodity processors. DVFS enables these processors to operate with different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. Our algorithms effectively balance these two performance goals using a novel objective function and its variant, which take into account both goals; this claim is verified by the results obtained from our extensive comparative evaluation study.

• Journal of The Korean Association of Information Education
• /
• v.2 no.2
• /
• pp.269-277
• /
• 1998

In most of the distributed deadlock detection algorithms using messages called probes, only a portion of the generated messages are effectively used, and hence the wasted probes cause heavy communication traffic. In this paper, a distributed deadlock detection algorithm is proposed which can efficiently detect deadlocks making use of those residue probes. Our algorithm is complete in the sense that they detect not only those deadlocks in which the initiator is involved as most other algorithms do, but all the other deadlocks that are present anywhere in a connected wait-for-graph. To detect all the deadlocks, the algorithms known to be most efficient require O(ne) messages, where e and n are the number of edges and nodes in the graph, respectively. The single execution of the presented algorithm can accomplish the same task with O(e) messages.

• Journal of Korean Society for Quality Management
• /
• v.26 no.1
• /
• pp.192-200
• /
• 1998

The quickest path problem is one of the important things for quality of services in communication networks. It is to find a path to send a given amount of data from the source to the sink with minimum transmission time, where the transmission time is dependent on both the capacities and the traversal times of the arcs in the network. This is found under the networks that the capacity and the lead time of each ring are predetermined. It is general to solve the quickest path problem using shortest path algorithms. The relevant algorithms proposed till now are based on the capacity of rings in distributed environments. When the configuration of networks is changed, there can be two a, pp.oaches to find the quickest paths. The one is to find new quickest paths, and the other is to update the current quickest paths. As one of the algorithms for the latter, the distributed quickest path update algorithm was proposed. This paper aims to propose the distributed algorithm a, pp.icable to find the quickest path, when the configuration of networks is changed, using the quickest path tree update altorithm, and to verify its possibility of a, pp.ication by analyzing the transmission amount of data from one node to another from the theoretical point of view.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 1996.04a
• /
• pp.125-129
• /
• 1996

This paper deals with the problem of placement/sizing of distributed piezo actuators to achieve the control objective of vibration suppression. Using the mean square response as a performance index in optimization, we obtain optimal placement and sizing of the actuator. The use of genetic algorithms as a technique for solving optimization problems of placement and sizing is explored. Genetic algorithms are also used for the control strategy. The analysis of the system and response moment equations are carried out by using the Fokker-Planck equation. This paper presents the design and analysis of an active controller and optimal placement/sizing of distributed piezo actuators based on genetic algorithms for a flexible structure under random disturbance, shows numerical example and the result.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2002.10a
• /
• pp.203-210
• /
• 2002

The great advantages on the Genetic Algorithms(GAs) are ease of implementation, and robustness in solving a wide variety of problems, several GAs based optimization models for solving complex structural problems were proposed. However, there are two major disadvantages in GAs. The first disadvantage, implementation of GAs-based optimization is computationally too expensive for practical use in the field of structural optimization, particularly for large-scale problems. The second problem is too difficult to find proper parameter for particular problem. Therefore, in this paper, a Distributed Hybrid Genetic Algorithms(DHGAs) is developed for structural optimization on a cluster of personal computers. The algorithm is applied to the minimum weight design of steel structures.

• The KIPS Transactions:PartD
• /
• v.13D no.3 s.106
• /
• pp.391-398
• /
• 2006

This paper verifies deployment algorithms in wireless sensor networks using SPIN, a widely used model checking tool. In this paper, two deployment algorithms, DSSA(Distributed Self Spreading Algorithm) and TBDA(Tree Based Deployment Algorithm), are verified to check their stability against oscillation as well as energy consumption that is an important factor in wireless sensor networks.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.4 s.42
• /
• pp.119-125
• /
• 2006

Distributed Systems can be defined as set of computing resources connected by computer network. One of the most significant techniques in optimization problem domains is parallel genetic algorithms, which are based on distributed systems. Since the status of dynamic network environments such as Internet and mobile computing. can be changed continually, it must not be efficient on the dynamic environments to solve an optimization problem using previous parallel genetic algorithms themselves. In this paper, we propose the effective technique, in which the parallel genetic algorithm can be used efficiently on the dynamic network environments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.5
• /
• pp.2454-2468
• /
• 2019

The existing direct position determinations(DPD) for coherently distributed(CD) sources are mostly applicable for uniform linear array(ULA), which result in a low degree of freedom(DOF), and it is difficult for them to realize the effective positioning in underdetermined condition. In this paper, a novel DPD algorithm for coherently distributed sources based on compressed sensing with a moving nested array is present. In this algorithm, the nested array is introduced to DPD firstly, and a positioning model of signal moving station based on nested array is constructed. Owing to the features of coherently distributed sources, the cost function of compressed sensing is established based on vectorization. For the sake of convenience, unconstrained transformation and convex transformation of cost functions are carried out. Finally, the position coordinates of the distribution source signals are obtained according to the theory of optimization. At the same time, the complexity is analyzed, and the simulation results show that, in comparison with two-step positioning algorithms and subspace-based algorithms, the proposed algorithm effectively solves the positioning problem in underdetermined condition with the same physical element number.