At present, the probability of selecting "the peer next door" as an overlay neighbour in Kademlia is fairly small. Prior research has been concerned with reducing the lookup latency by means of proximity nei...
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At present, the probability of selecting "the peer next door" as an overlay neighbour in Kademlia is fairly small. Prior research has been concerned with reducing the lookup latency by means of proximity neighbour and route selection, but focused on recursive routing algorithms. This work leverages location data about peers and extends Kademlia's iterative routing algorithm to reduce cross-network traffic at the level of the distributed hash table. Evaluation with real-world measurement data gives evidence that locality of traffic tends to reduce lookup latencies as well. In turn, mechanisms that aim at reducing lookup latencies do not necessarily reduce cross-network traffic to the same extent.
In this paper we propose a linear shift register synthesis algorithm for a multisequence of varying length by modifying the lattice basis reduction multisequence synthesis (Wang-Zhu-Pei for short) algorithm (L.-P. Wan...
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ISBN:
(纸本)9781424422562
In this paper we propose a linear shift register synthesis algorithm for a multisequence of varying length by modifying the lattice basis reduction multisequence synthesis (Wang-Zhu-Pei for short) algorithm (L.-P. Wang et al., 2004). After a few simple modifications to it we can obtain the Schmidt-Sidorenko algorithm in (G. Schmidt and V.R. Sidorenko, 2006). In addition, we give the necessary and sufficient condition for the uniqueness of the minimal-length linear shift-register for generating a multisequence of varying length.
In this paper, an iterative high-resolution DOA algorithm is proposed for DOA estimation for CDMA systems. The algorithmiteratively removes detected signals from the received data and searches the residue spatial spe...
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In this paper, an iterative high-resolution DOA algorithm is proposed for DOA estimation for CDMA systems. The algorithmiteratively removes detected signals from the received data and searches the residue spatial spectrum for further signals. It does not require any computationally expensive eigen decomposition or spatial smoothing in coherent multipath scenarios. Results are presented illustrating highresolution at significantly lower SNR levels than those obtained by classical DOA algorithms such as MUSIC and MVM.
The author presents new algorithms for fixed-rate multiple description and multiresolution scalar quantizer design. The algorithms both run in time polynomial in the size of the source alphabet and guarantee globally ...
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The author presents new algorithms for fixed-rate multiple description and multiresolution scalar quantizer design. The algorithms both run in time polynomial in the size of the source alphabet and guarantee globally optimal solutions. To the authorpsilas knowledge, these are the first globally optimal design algorithms for multiple description and multiresolution quantizers.
Controlled-flooding algorithms are widely used in unstructured networks. Expanding ring (ER) achieves low response delay, while its traffic cost is huge; dynamic querying (DQ) is known for its desirable behavior in tr...
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ISBN:
(纸本)9781424432134
Controlled-flooding algorithms are widely used in unstructured networks. Expanding ring (ER) achieves low response delay, while its traffic cost is huge; dynamic querying (DQ) is known for its desirable behavior in traffic control, but it achieves lower search cost at the price of an undesirable latency performance; Enhanced dynamic querying (DQ+) can reduce the search latency too, while it is hard to determine a general optimum parameters set. In this paper, a novel algorithm named selective dynamic query (SDQ) is proposed. Unlike previous works that awkwardly processing floating TTL values, SDQ properly select an integer TTL value and a set of neighbors to narrow the scope of next query. Our experiments demonstrate that SDQ provides finer-grained control than other algorithms: its latency is close to the well-known minimum one via ER; in the mean time its traffic cost also close to the minimum. To our best knowledge, this is the first work capable of achieving best performance in terms of both response latency and traffic cost. In addition, our experiments also demonstrate that SDQ works well in various network topologies.
Based on the analysis of the basic particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to solve the problem with missile-target assignment in coordinated ...
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Based on the analysis of the basic particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to solve the problem with missile-target assignment in coordinated air combat (MTACAC). There were three improvements: 1. Adaptive adjustment of inertia weight; 2. Amelioration of particle velocity and position; 3. Better optimization strategy. Based on the principles of coordinated air combat efficiency and operational research, a missile-target assignment mathematical model was established. The IPSO algorithm was applied to seek the optimal missile assignment scheme for multi-target coordinated air-to-air combat. The simulation result indicated that the model of MTACAC was practical and feasible, and the IPSO algorithm was fast, simple, and more effective in finding out the global optimum assignment, when compared with the basic PSO algorithm and the genetic algorithm (GA).
Designing sensor networks with decentralized and autonomous decisions capabilities, i.e., without the need to send all the collected data to a fusion center, is a big challenge that is receiving considerable attention...
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Designing sensor networks with decentralized and autonomous decisions capabilities, i.e., without the need to send all the collected data to a fusion center, is a big challenge that is receiving considerable attention. One of the major drawbacks of distributed algorithms is their iterative nature. This makes them prone to an energy consumption that depends on the convergence time and on the power transmitted by each node to guarantee the network connectivity. Furthermore, in a realistic environment, the interaction among sensor is inevitably corrupted by noise which affects the final decision. In this work, we describe decentralized algorithms for implementing various processing tasks, from spatial smoothing to distributed decision, characterized by fast convergence properties, for a given network topology, and resilience against inter-sensor communication noise.
In this paper, we propose one grouped-iterative framework to generate a family of the MIMO detection algorithms. The presented framework not only includes the conventional iterative, grouped, and Chase detection algor...
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In this paper, we propose one grouped-iterative framework to generate a family of the MIMO detection algorithms. The presented framework not only includes the conventional iterative, grouped, and Chase detection algorithms, but also derives a new low-complexity MIMO detection algorithm. The proposed detection can adjust some parameters to achieve a range of trade-offs between performance and complexity. In (4,4) system with uncoded 16-QAM inputs, one instance of the proposed detection algorithm not only substantially reduces the multiplication complexity by 26.3% but also outperforms the BODF algorithm about 5 dB. Another instance of the proposed algorithm can save multiplication complexity by 34% at the penalty of 1 dB loss compared with the B-Chase detector.
In this paper, a new algorithm of image reconstruction for gamma ray tomography (GRT) systems is presented. There are several approaches to image reconstruction process. The most common algorithms in GRT are iterative...
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ISBN:
(纸本)9789665536789
In this paper, a new algorithm of image reconstruction for gamma ray tomography (GRT) systems is presented. There are several approaches to image reconstruction process. The most common algorithms in GRT are iterative algorithms. The proposed software is based on the iterative Least Square Techniques algorithm. The software generates automatically a weight matrix for the chosen setup. Experimental results are shown.
A coordinate function of criteria on the basis of intra- and inter-distances in the fuzzy C-means (FCM) is proposed. iterative self-organizing data analysis technique algorithm (ISODATA) and discrete particle swarm op...
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A coordinate function of criteria on the basis of intra- and inter-distances in the fuzzy C-means (FCM) is proposed. iterative self-organizing data analysis technique algorithm (ISODATA) and discrete particle swarm optimization (PSO) are combined to form a PSO self-organizing data analysis technique algorithm (PSO-ISODATA), which is used to conduct the optimal computing of FCM. Compared to other methods, our method can be used not only to do optimal clustering but also to yield the optimum coordinate number of clusters and the corresponding optimal clustering without artificial interference according to the clustering criteria, given a preset number of clustering. PSO-ISODATA has a wide application. When other cluster criteria are adopted, only the fitness function is needed to be modified.
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