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The paper addresses the problem of massive content distribution in a network where multiple sessions coexist. In more traditional approaches, the sessions form separate overlay networks and operate independently from each other. In this case, some sessions may suffer from insufficient resources (e.g., aggregate upload bandwidth) even though other sessions have excessive resources. To cope with this...
In the following paper, we study the tradeoff between network utility and network lifetime for energy-constrained wireless sensor networks (WSNs). By introducing a parameter r, we combine these two objectives into a single weighted objective, and consider rate control and routing in this tradeoff framework simultaneously. First, using the dual decomposition method, we decompose the tradeoff model...
Subset problems are models for many important applications in the field of operational research. In this paper, we solve some benchmarks of the set partitioning problem with an ant-based algorithm using a transition rule with a lookahead mechanism. It was incorporated to check constraint consistency in each iteration. Computational results are presented showing the advantages to use this additional...
The study of the multicast routing protocol of multi-constrained is important for the development of the high performance network. The aims are the multi-constrained network model and the definition of the formula of every constrained characteristic measurement. However, it is a NP-complete problem. In order to gain the approximative solution, many heuristic algorithms have been designed by filling...
Test sequencing is a binary identification problem wherein one needs to develop a minimal expected cost testing procedure to determine which one of a finite number of possible failure sources, if any, is present. directed towards the test sequencing problem in the sequential fault diagnosis for systems, the test sequencing problem is converted to searching the minimal complete test sequencing based...
Revisiting an earlier examined multiple-input multiple-output (MIMO) radar waveform design problem which optimizes both minimum mean-square error estimation (MMSE) and mutual information (MI), we formulate a new waveform design problem and provide some further results in this paper, which complements the previous study. More specifically, we present an iterative optimization algorithm based on the...
A feedback arc set in a directed graph D is a set S of arcs in D such that D\ S is acyclic. The problem of determining a feedback arc set with least number of arcs is NP - complete for a general digraph. We define the strong feedback arc number ??s(G) for various orientations of an undirected graph G. The strong feedback arc problem of an undirected graph is to find a strong feedback arc set S of...
This paper copes with the approximate minimization of Markovian energy with pairwise interactions. We extend previous approaches that rely on graph-cuts and move making techniques. For this purpose, a new move is introduced that permits us to perform better approximate optimizations. Some experiments show that very good local minima are obtained while keeping the memory usage low.
We consider relay broadcast channels (RBCs) with multiple antennas at all nodes. A practical linear preceding, relaying and combining scheme is proposed. Under an overall power constraint, we derive the optimal power allocation solution in a closed form. A low complexity beamforming vector optimization algorithm is proposed to maximize the effective channel gains and improve the system performance...
In this paper, we consider the feature correspondence task as a graph matching problem. Our approach tends to maximize a similarity objective function, which consists of not only the feature vectors but also their corresponding constrained global spatial structures, by a new polynomial-time approximate optimization algorithm. This algorithm allows every node in a smaller graph to potentially be linked...
To reduce the computational burden of the nearest neighbor search (NNS) problem, most existing algorithms focus on `preprocessing' the data set to reduce the number of objects to be examined for each querying operation (e.g., efficient data structures, metric space transforms). In this paper we present a quantization based nearest-neighbor-preserving metric approximation algorithm (QNNM) that leads...
The problem of resource allocation (RA) in a downlink OFDMA system with minimum user rate requests is examined under the realistic scenario of partial (imperfect) channel state information (CSI) at the base station. The challenge in this setting is the non-zero probability of outage events which may lead to significant performance degradation if algorithms assuming perfect CSI are utilized. In this...
The problem of estimating the three-dimensional (3D) geometry of an object from a sequence of images obtained at different focus settings is called shape from focus (SFF). The conventional SFF methods apply focus measure operator at each pixel using neighboring pixels in the same image frame. However, for an object with complex geometry, such methods cannot compute accurate focus level of a pixel,...
We present a new mechanism to introduce diversity to a multiobjective algorithm based on ant colony optimization to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. Promising results are shown after applying the designed multiobjective ant colony optimization algorithm to ten real-like problem instances.
To avoid premature convergence and stagnation problems in classical ant colony system, a novel multi-behavior based multi-colony ant algorithm (MBMCAA) is proposed. The ant colony is divided into several sub-colonies; the sub-colonies have their own population evolved independently and in parallel according to four different behavior options, and update their local pheromone and global pheromone level...
Broadcasting/Multicasting problems have been well studied in wireless ad hoc networks. However, only a few approaches take into account the low interference and energy efficiency as the optimization objective simultaneously. In this paper, we study the interference and power constrained broadcast/multicast and the delay-bounded interference and power constrained broadcast/multicast routing problems...
The target of this paper is to propose a hybrid combination of the three main branches of Computational Intelligence, namely Fuzzy Systems, Neural Networks and Evolutionary Computing. The function approximation properties of fuzzy J-K and D flip-flops based feedforward neural network optimized and trained with a novel evolutionary algorithm based technique; the Bacterial Memetic Algorithm with Modified...
In cognitive radio cellular networks (CogCells), primary users (PUs) rarely utilize all the assigned frequency bands at a certain time and a location. The spectral inefficiency caused by the spectrum holes motivated cognitive radio technology (CR) that presents unlicensed secondary users (SUs) an opportunity for using spectrum holes. CR makes the SUs to find and use the spectrum holes without interrupting...
In the priority search phase of Wilderness Search and Rescue, a probability distribution map is created. Areas with higher probabilities are searched first in order to find the missing person in the shortest expected time. When using a UAV to support search, the onboard video camera should cover as much of the important areas as possible within a set time. We explore several algorithms (with and without...
Diversity maintenance of solutions is a crucial part in multi-objective optimization. However, most of existing studies show a good distribution with a large computational load or a comparative bad distribution quickly. In this paper, a method for pruning a set of non-dominated solutions using a spanning tree is proposed. This approach defines a density estimation metric - spanning tree crowding distance...
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