9882029
The Group Search Optimizer and its Application on Truss Structure Design
This paper introduces a novel optimization algorithm, group search optimization (GSO) algorithm and its implementation method is presented in detail. The GSO is used to investigate the planar and space truss structures with continuous variables and is tested by two truss optimization problems. The optimization results are compared with that of the particle swarm optimization (PSO) algorithm, the particle swarm optimization with passive congregation (PSOPC) and the heuristic particle swarm optimizer (HPSO) algorithm. Results from the two tested cases illustrate the ability of the GSO algorithm to find the optimal results, which are better than that of the PSO and PSOPC, while are at the same level of that of HPSO optimization method. Meanwhile, the results also show that the GSO algorithm maintains a preferable convergence accuracy among these four algorithms.
14281509
A Quick Group Search Optimizer with Passive Congregation and its Convergence Analysis
This paper presents a quick group search optimizer with passive congregation (QGSOPC) for optimum design of pin connected structure. The algorithm is based on the quick group search optimizer (QGSO). The QGSOPC algorithm is verified and compared with the HPSO, GSO and QGSO algorithm used for the designs of two planar and spatial truss structures. The results show that the QGSOPC algorithm not only has preferable convergence rate and accuracy, but also it has the best stability of convergence rate and accuracy. It is desired for QGSOPC to be used more effectively for practical structural optimal design problems.
1036059
Neighbor Relationship and Optimization in Mesh Overlay Multicast
Nodes in mesh overlay multicast system don't have fixed parent-children relationship like that in trees and form neighbors. But in data-driven mesh and based on pulling method, for each packet, it still follows a certain tree and the parent-children relationship does exist. While having the powerful peers stay closer to the source may improve the performance, we make the peers of high out bandwidth preempt the neighbor of the peers near the source. In our paper, we describe the delivery trees set and construct the main distribution tree, which carries most of the data, to construct the signaling path and relay priority preemption message to reduce the cost. We model the neighbor relationship to decide which neighbor to be preempted based on the capacity of the node and the contribution it makes to the probed nodes. Our simulations show that after a temporary reduction in performance at the beginning, which for the optimization chaos of optimization procedure, the system converges to a stable state and gains better performance, especially for playback delay, and meanwhile the control overhead is in reasonable range.
26148023
Constant Modulus Based Blind Channel Estimation for OFDM Systems
A novel blind channel estimation scheme is proposed for OFDM systems employing PSK modulation. This scheme minimizes the number of possible channels by exploiting the constant modulus property, chooses a best fit over the possible channels by exploiting the finite alphabet property of information signals, and achieves competitive performance with low computational complexity. Results comparing the new scheme with the finite-alphabet based channel estimation are presented.
35120658
Max-Relevance and Min-Redundancy Greedy Bayesian Network Learning on High Dimensional Data
Existing algorithms for learning Bayesian network require a lot of computation on high dimensional itemsets which affects accuracy especially on limited datasets and takes up a large amount of time. To address the above problem, we propose a novel Bayesian network learning algorithm MRMRG, Max Relevance-Min Redundancy Greedy. MRMRG algorithm is a variant of K2 which is a well- known BN learning algorithm. We also analyze the time complexity of MRMRG. The experimental results show that MRMRG algorithm has much better efficiency and accuracy than most of existing algorithms on limited datasets.
46240388
An Efficient Heuristic Algorithm for Constructing Delay- and Degree-Bounded Application-Level Multicast Tree
In this paper we first investigate the problem of finding a delay- and degree-bounded maximum sum of nodes ALMT. We proved the problem is NP-hard, and testify its relationship with the well-studied degree-bounded minimum maximum-delay ALMT problem. We proposed a greedy algorithm FindOverlayTree with SRPF heuristic. The simulation results show that our design solution is a valid and cost-effective approach where compared to other three modified classic heuristics under several performance metrics.
13519541
WS-SLA: A Framework for Web Services Oriented Service Level Agreements
Service level agreements (SLA) becomes the prevailing business model for delivery of a large number of products and services in telecommunication and IT arenas. We presents an integrated service level agreement model applied to operating supporting system (OSS), on the basis of WfMC workflow reference model and service oriented architecture (SOA). And an application scenario instance of SLA system architecture is described by a set of operations models by Business Process Execution Language (BPEL)