On the performance of ACO-based methods in p2p resource discovery

Krynicki, Kamil; Jaén, Javier; Mocholi, Jose A.

doi:10.1016/j.asoc.2013.07.022

Cited by 13 publications

(26 citation statements)

References 24 publications

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“…1. In chapter 2 we present the paper On the performance of ACO-based methods in P2P resource discovery [12]. The main focus of this preliminary work was to formally define what prerequisites must an algorithm fulfill in order to be considered acceptable for P2P resources queries.…”

Section: Contributionsmentioning

confidence: 99%

“…As many works before [12] [15] [31] we decided to adopt the Hop per Hit (HpH, dimensionless) measure. It can be read as: how many steps a single ant must take to obtain a single resource during a given iteration.…”

Section: Quality Measurementioning

confidence: 99%

“…Due to the lengthy process of pheromone deposition and evaporation ACO algorithms cope only to an acceptable degree with dynamic graphs and dynamically distributed resources [8] [9] [10] [11]. In addition, and perhaps more importantly, they are not suitable for class-based or semantic searches [12] [13].…”

Section: Challengesmentioning

confidence: 99%

“…Nevertheless, the dynamic issue has remained largely unaddressed. In various papers [12] [29] [15] it has also been shown that ACO-based algorithms are more than an adequate base for a P2P search engine. However, P2P networks are innately and unpredictably dynamic which makes the mentioned problem relevant.…”

Section: Introductionmentioning

confidence: 99%

“…The period between consecutive resource distributions is set at nM od = 10 3 , therefore the resource distribution will be executed 99 times within a single experiment. The two above statements are concluded from [12].…”

mentioning

confidence: 99%

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Ant Colony Algorithms for the Resolution of Semantic Searches in P2P Networks

Krynicki¹

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SummaryThe long-lasting trend in the field of computation of stress and resource distribution has found its way into computer networks via the concept of peer-to-peer (P2P ) connectivity. P2P is a symmetrical model, where each network node is enabled a comparable range of capacities and resources. It stands in a stark contrast to the classical, strongly asymmetrical client-server approach. P2P, originally considered only a complimentary, server-side structure to the straightforward client-server model, has been shown to have the substantial potential on its own, with multiple, widely known benefits: good fault tolerance and recovery, satisfactory scalability and intrinsic load distribution. However, contrary to client-server, P2P networks require sophisticated solutions on all levels, ranging from network organization, to resource location and managing.In this thesis we address one of the key issues of P2P networks: performing efficient resource searches of semantic nature under realistic, dynamic conditions. There have been numerous solutions to this matter, with evolutionary, stigmergybased, and simple computational foci, but few attempt to resolve the full range of challenges this problem entails. To name a few: real-life P2P networks are rarely static, nodes disconnect, reconnect and change their content. In addition, a trivial incorporation of semantic searches into well-known algorithms causes significant decrease in search efficiency.In our research we build a solution incrementally, starting with the classic Ant Colony System (ACS ) within the Ant Colony Optimization metaheuristic (ACO). ACO is an algorithmic framework used for solving combinatorial optimization problems that fits contractually the problem very well, albeit not providing an immediate solution to any of the aforementioned problems.First, we propose an efficient ACS variant in structured (hypercube structured) P2P networks, by enabling a path-post processing algorithm, which called Tabu Route Optimization (TRO). Next, we proceed to resolve the issue of network dynamism with an ACO-compatible information diffusion approach. Consequently, we attempt to incorporate the semantic component of the searches. This initial approximation to the problem was achieved by allowing ACS to differentiate between iii search types with the pheromone-per-concept idea. We called the outcome of this merger Routing Concept ACS (RC-ACS ). RC-ACS is a robust, static multipheromone implementation of ACS. However, we were able to conclude from it that the pheromone-per-concept approach offers only limited scalability and cannot be considered a global solution.Thus, further progress was made in this respect when we introduced to RC-ACS our novel idea: dynamic pheromone creation, which replaces the static one-to-one assignment. We called the resulting algorithm Angry Ant Framework (AAF ). In AAF new pheromone levels are created as needed and during the search, rather than prior to it. The final step was to enable AAF, not only to create pheromone levels, but to reassi...

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Section: Contributionsmentioning

confidence: 99%

Section: Quality Measurementioning

confidence: 99%