Parallel Algorithms for Dandelion-Like Codes

Caminiti, Saverio; Petreschi, Rossella

doi:10.1007/978-3-642-01970-8_60

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…The tree corresponding to the Dandelion code C = (6, 2, 1, 7, 3, 7, 3, 8) is the tree given in Figure 1, where edge orientation has been provided for clarity. Linear-time encoding and decoding algorithms are common in literature for all Dandelion-like codes and [24] provided unique parallel encoding and decoding algorithms that when properly parametrized, can be utilized for all Dandelion-like mappings. All in all, both theoretical and experimental results have proven [23] that the Dandelion code positively satisfies all five properties enunciated by Palmer and Kershembaum, hence concluding that it is a suitable tree encoding choice for an efficient tree representation.…”

Section: A Dandelion Decodingmentioning

confidence: 99%

On the heritability of dandelion-encoded harmony search heuristics for tree optimization problems

Perfecto

Bilbao

Ser³

et al. 2015

2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)

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Tree based optimization problems stand for those paradigms where solutions can be arranged within a tree-like graph whose nodes represent the optimization variables of the problem at hand and their interconnecting edges topological and/or hierarchical relationships between such variables. In this context, a research line of increasing interest during the last decade focuses on the derivation of intelligent solution encoding strategies capable of 1) capturing all topological constraints of this particular class of graphs; and 2) preserving their connectivity properties when they undergo combination/mutation operations within approximative evolutionary solvers. This manuscript takes a step over the state of the art by shedding light on the heritability properties of the Dandelion tree encoding approach under avant-garde stochastically-controlled evolutionary operators. In particular we elaborate on the topological heritability of the socalled Harmony Memory Considering Rate (HMCR) exploitative operator of the Harmony Search algorithm, a population-based meta-heuristic algorithm that has so far shown to outperform other evolutionary schemes in a wide range of optimization scenarios. Results from extensive Monte Carlo simulations are discussed in terms of the preserved structural properties of the newly produced solutions with respect to the initial Dandelionencoded population.

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Section: A Dandelion Decodingmentioning

confidence: 99%

On the heritability of dandelion-encoded harmony search heuristics for tree optimization problems

Perfecto

Bilbao

Ser³

et al. 2015

2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)

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“…, C n−1 }. Both lineartime encoding and decoding algorithms have been widely utilized in the literature for all Dandelion-like codes [11]. The decoding procedure produces an output tree T ∈ n , with n denoting the set of possible trees interconnecting n nodes.…”

Section: Dandelion Codes For Tree Encodingmentioning

confidence: 99%

Dandelion-Encoded Harmony Search Heuristics for Opportunistic Traffic Offloading in Synthetically Modeled Mobile Networks

Perfecto

Bilbao

Ser³

et al. 2015

Advances in Intelligent Systems and Computing

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The high data volumes being managed by and transferred through mobile networks in the last few years are the main rationale for the upsurge of research aimed at finding efficient technical means to offload exceeding traffic to alternative communication infrastructures with higher transmission bandwidths. This idea is solidly buttressed by the proliferation of short-range wireless communication technologies (e.g. mobile devices with multiple radio interfaces), which can be conceived as available opportunistic hotspots to which the operator can reroute exceeding network traffic depending on the contractual clauses of the owner at hand. Furthermore, by offloading to such hotspots a higher effective coverage can be attained by those operators providing both mobile and fixed telecommunication services. In this context, the operator must decide if data generated by its users will be sent over conventional 4G+/4G/3G communication links, or if they will instead be offloaded to nearby opportunistic networks assuming a contractual cost penalty. Mathematically speaking, this problem can be formulated as a spanning tree optimization subject to cost-performance criteria and coverage constraints. This paper will elaborate on the efficient solving of this optimization paradigm by means of the Harmony Search meta-heuristic algorithm and the so-called Dandelion solution encoding, the latter allowing for the use of conventional meta-heuristic operators maximally preserving the locality of tree representations. The manuscript will discuss the obtained simulation results over different synthetically modeled setups of the underlying communication scenario and contractual clauses of the users.

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“…After each step we set g [v] = g[g [v]] and we stop after log n steps to avoid infinite recursion inside cycles. The procedure details are as follows: for v = 0 to n − 1 in parallel do 6. η(v) = max(η(v), g [v], η(g [v])) 7.…”

Section: Decoding Algorithmmentioning

confidence: 99%

“…Concerning parallel algorithms, studies have been performed and algorithms are known both for Prüfer-like codes [5] and for Dandelion-like codes [7]. The interested reader may found a complete survey on all these codes in [3].…”

Section: Introductionmentioning

confidence: 99%

Parallel Algorithms for Encoding and Decoding Blob Code

Caminiti

Petreschi

2010

WALCOM: Algorithms and Computation

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Abstract. A bijective code is a method for associating labeled n-trees to (n − 2)-strings of node labels in such a way that different trees yield different strings and vice versa. For all known bijective codes, optimal sequential encoding and decoding algorithms are presented in literature, while parallel algorithms are investigated only for some of these codes. In this paper we focus our attention on the Blob code: a code particularly considered in the field of Genetic Algorithms. To the best of our knowledge, here we present the first parallel encoding and decoding algorithms for this code. The encoding algorithm implementation is optimal on an EREW PRAM, while the decoding algorithm requires O(log n) time and O(n) processors on CREW PRAM.

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Parallel Algorithms for Dandelion-Like Codes

Cited by 5 publications

References 11 publications

On the heritability of dandelion-encoded harmony search heuristics for tree optimization problems

On the heritability of dandelion-encoded harmony search heuristics for tree optimization problems

Dandelion-Encoded Harmony Search Heuristics for Opportunistic Traffic Offloading in Synthetically Modeled Mobile Networks

Parallel Algorithms for Encoding and Decoding Blob Code

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