Simulation Analysis of Routing Strategies in Multicasting Multiservice Loss Networks

SIMULATION ◽  
1997 ◽  
Vol 68 (1) ◽  
pp. 34-43
Author(s):  
Krzysztof Szarkowicz ◽  
Gábor Fodor ◽  
András Faragó ◽  
Tamás Henk
Keyword(s):  
Heuristic Algorithms ◽  
Simulation Analysis ◽  
Blocking Probability ◽  
Asynchronous Transfer Mode ◽  
Steiner Tree Problem ◽  
Weight Functions ◽  
Shortest Path Routing ◽  
Allocation Policy ◽  
Network Utilization ◽  
Multicast Algorithms

This paper begins with an overview of multicast algorithms, which are the most promising candidates to be in wide use in first generation Asynchronous Transfer Mode (ATM) based Broadband Integrated Services Digital Networks (B-ISDN). Since the Multiple Destination Routing (MDR) problem and the associated Steiner Tree problem are known to be NP-complete and therefore a number of heuristic algorithms have been proposed in the literature, we first need to establish which of these are the best candidates for the B-ISDN. We conclude that the weighted greedy -type algorithms are promising ones, and therefore we examine the behavior of these algorithms in terms of blocking probability and network utilization. In doing so, we use a B-ISDN call level simulation program, which proves to be an indispensable tool in the quest for efficient multicast algorithms. We find that shortest path routing with appropriate (adaptive) weight functions combined with the complete partitioning link allocation policy may give satisfactory blocking values and good network utilization in networks of different sizes.

Modelling and Simulation Analysis of Routing Algorithms in Multichannel Optical Communication Networks

2021 ◽  
Vol 1 (1) ◽  
pp. 29-33
Author(s):  
K. Angelov ◽  
S. Sadinov
Keyword(s):  
Optical Networks ◽  
Communication Networks ◽  
Optical Communication ◽  
Simulation Analysis ◽  
Blocking Probability ◽  
Optical Network ◽  
Optimal Path ◽  
Routing Algorithms ◽  
Weight Functions ◽  
Circuit Switching

In this paper, it is considered the broadband backbone optical networks with wavelength routing and circuit switching used to build long-range wide area networks. In this type of network, if there is an available and acknowledged connection request, it is necessary to determine the optimal path between the optical communication nodes in the network. This also requires the assignment of an optimal set of wavelengths along the selected route between these nodes. This paper takes into account the multichannel optical communication networks with spectral multiplexing. Four different routing algorithms are modeled and analyzed for which their weight functions are determined to take into account various factors, such as the total distance of the individual routes, the total number of available wavelengths for a given route and how many of them are available for use. It is studied and compared the performance of the proposed algorithms in a multichannel optical network in terms of blocking probability.

scholarly journals New Heuristic Algorithm for Dynamic Traffic in WDM Optical Networks

2015 ◽  
Vol 35 (3) ◽  
pp. 100-106 ◽  
Author(s):  
Arturo Benito Rodríguez Garcia ◽  
Leonardo Ramirez Lopez ◽  
Juan Carlos Travieso Torres
Keyword(s):  
Genetic Algorithms ◽  
Optical Networks ◽  
Heuristic Algorithm ◽  
Heuristic Algorithms ◽  
Blocking Probability ◽  
Wdm Optical Networks ◽  
Dynamic Traffic ◽  
Relative Growth ◽  
Traffic Conditions ◽  
Network Utilization

<p class="Abstractandkeywordscontent">The results and comparison of the simulation of a new heuristic algorithm called Snake One are presented. The comparison is made with three heuristic algorithms, Genetic Algorithms, Simulated Annealing, and Tabu Search, using blocking probability and network utilization as standard indicators. The simulation was made on the WDM NSFNET under dynamic traffic conditions. The results show a substantial decrease of blocking, but this causes a relative growth of network utilization. There are also load intervals at which its performance improves, decreasing the number of blocked requests.</p>

scholarly journals Blocking Probability in Pipeline Forwarding Networks

2014 ◽  
Vol 10 (1) ◽  
pp. 30
Author(s):  
Mario Baldi ◽  
Andrea Vesco
Keyword(s):  
Proper Time ◽  
Blocking Probability ◽  
Network Routing ◽  
Analytical Models ◽  
Network Resources ◽  
High Resource ◽  
Delay Sensitive ◽  
Network Utilization ◽  
Real Size ◽  
Time Frames

As multimedia communications continue to grow steadily on the Internet, pipeline forwarding (PF) of packets provides a scalable solution for engineering delay-sensitive traffic while guaranteeing deterministic Quality of Service (QoS) with high resource utilization. In PF networks resource reservation, while ensuring deterministic QoS on a per-flow basis, can result in a not null blocking probability. A reservation request may fails due to enough resources being available but not during the proper time frames. This work analyses blocking probability of reservation requests since it affects the capability of utilizing network resources to carry traffic with deterministic QoS. The blocking probability and, consequently, the achievable network utilization are analytically derived on general topology PF networks as function of the traffic intensity given the traffic matrix and the network routing. The correctness of the blocking models is also assessed by simulation in different scenarios. This work represent a valuable contribution over previous analytical models of the blocking probability as their application to real size scenarios is impractical due to their computation complexity.

scholarly journals Strategyproof auction mechanisms for network procurement

OR Spectrum ◽  
2020 ◽  
Vol 42 (4) ◽  
pp. 965-994
Author(s):  
Martin Bichler ◽  
Zhen Hao ◽  
Richard Littmann ◽  
Stefan Waldherr
Keyword(s):  
Heuristic Algorithms ◽  
Allocative Efficiency ◽  
Telecommunications Industry ◽  
Steiner Tree Problem ◽  
Solution Quality ◽  
Worst Case ◽  
Average Case ◽  
Auction Mechanisms ◽  
Deferred Acceptance ◽  
Minimum Steiner Tree Problem

Abstract Deferred-acceptance auctions can be seen as heuristic algorithms to solve $${{\mathcal {N}}}{{\mathcal {P}}}$$ N P -hard allocation problems. Such auctions have been used in the context of the Incentive Auction by the US Federal Communications Commission in 2017, and they have remarkable incentive properties. Besides being strategyproof, they also prevent collusion among participants. Unfortunately, the worst-case approximation ratio of these algorithms is very low in general, but it was observed that they lead to near-optimal solutions in experiments on the specific allocation problem of the Incentive Auction. In this work, which is inspired by the telecommunications industry, we focus on a strategic version of the minimum Steiner tree problem, where the edges are owned by bidders with private costs. We design several deferred-acceptance auctions (DAAs) and compare their performance to the Vickrey–Clarke–Groves (VCG) mechanism as well as several other approximation mechanisms. We observe that, even for medium-sized inputs, the VCG mechanisms experiences impractical runtimes and that the DAAs match the approximation ratios of even the best strategy-proof mechanisms in the average case. We thus provide another example of an important practical mechanism design problem, where empirics suggest that carefully designed deferred-acceptance auctions with their superior incentive properties need not come at a cost in terms of allocative efficiency. Our experiments provide insights into the trade-off between solution quality and runtime and into the additional premium to be paid in DAAs to gain weak group-strategyproofness rather than just strategyproofness.

Yen-BSR: A New Approach for the Choice of Routes in WDM Networks

2014 ◽  
Vol 35 (4) ◽  
Author(s):  
A. F. Santos ◽  
R. C. Almeida ◽  
K. D. R. Assis
Keyword(s):  
Optical Networks ◽  
Blocking Probability ◽  
Shortest Paths ◽  
Wavelength Assignment ◽  
Wdm Networks ◽  
Superior Performance ◽  
Wavelength Routing ◽  
Algorithm Performance ◽  
New Approach ◽  
Shortest Path Routing

AbstractIn this paper we propose to use an iterative algorithm for optimizing the fixed-alternate shortest path routing in the dynamic routing and wavelength assignment (RWA) problem in wavelength routing optical networks. The algorithm performance is compared, in terms of blocking probability, with the Dijkstra and Yen traditional algorithms, as well as with the recently proposed best among the shortest routes (BSR) algorithm. The results suggest that it is feasible to choose an appropriate set of routes for each pair of nodes (source, destination), among the shortest paths and efficiently balance the network load. For all studied scenarios, the proposed heuristic achieved superior performance.

scholarly journals A Powerful Bio-Inspired Optimization Algorithm Based PV Cells Diode Models Parameter Estimation

2021 ◽  
Vol 9 ◽  
Author(s):  
Liming Sun ◽  
Jingbo Wang ◽  
Lan Tang
Keyword(s):  
Heuristic Algorithms ◽  
Simulation Analysis ◽  
Dynamic Balance ◽  
Maximum Output Power ◽  
Optimization Methods ◽  
Maximum Output ◽  
Algorithm Optimization ◽  
Unknown Parameters ◽  
Cell Parameters ◽  
Pv Cell

Accurate and reliable photovoltaic (PV) cell parameter identification is critical to simulation analysis, maximum output power harvest, and optimal control of PV systems. However, inherent high-nonlinear and multi-modal characteristics usually result in thorny obstacles to hinder conventional optimization methods to obtain a fast and satisfactory performance. In this study, a novel bio-inspired grouped beetle antennae search (GBAS) algorithm is devised to effectively identify unknown parameters of three different PV models, i.e., single diode model (SDM), double diode model (DDM), and triple diode model (TDM). Compared against beetle antennae search (BAS) algorithm, optimization efficiency of GBAS algorithm is markedly enhanced based on a cooperative searching group that consists of multiple individuals rather than a single beetle. Besides, a dynamic balance mechanism between local exploitation and global exploration is designed to increase the probability for a higher quality optimum. Comprehensive case studies demonstrate that GBAS algorithm can outperform other advanced meta-heuristic algorithms in both optimization precision and stability for estimating PV cell parameters, e.g., standard deviation (SD) of root mean square error (RMSE) obtained by GBAS algorithm is 64.34% smaller than the best value obtained by other algorithms in SDM, 61.86% smaller than that in DDM.

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