Deriving network topologies from real world constraints

2010 ◽  
Author(s):  
Mahmood A. Hameed ◽  
Abdul Jabbar ◽  
Egemen K. Cetinkaya ◽  
James P.G. Sterbenz
Keyword(s):  
Real World ◽  
Network Topologies

scholarly journals MISSING DATA AS PART OF THE SOCIAL BEHAVIOR IN REAL-WORLD FINANCIAL COMPLEX SYSTEMS

2018 ◽  
Vol 21 (01) ◽  
pp. 1850002 ◽  
Author(s):  
GUY KELMAN ◽  
ERAN MANES ◽  
MARCO LAMIERI ◽  
DAVID S. BRÉE
Keyword(s):  
Complex Systems ◽  
Real World ◽  
Missing At Random ◽  
Strategic Information ◽  
The Social ◽  
Network Topologies ◽  
Not Missing At Random ◽  
Information Withholding ◽  
Data Collection Procedure

Many real-world networks are known to exhibit facts that counter our knowledge prescribed by the theories on network creation and communication patterns. A common prerequisite in network analysis is that information on nodes and links will be complete because network topologies are extremely sensitive to missing information of this kind. Therefore, many real-world networks that fail to meet this criterion under random sampling may be discarded.In this paper, we offer a framework for interpreting the missing observations in network data under the hypothesis that these observations are not missing at random. We demonstrate the methodology with a case study of a financial trade network, where the awareness of agents to the data collection procedure by a self-interested observer may result in strategic revealing or withholding of information. The non-random missingness has been overlooked despite the possibility of this being an important feature of the processes by which the network is generated. The analysis demonstrates that strategic information withholding may be a valid general phenomenon in complex systems. The evidence is sufficient to support the existence of an influential observer and to offer a compelling dynamic mechanism for the creation of the network.

Fair Caching Networks

2021 ◽  
Vol 48 (3) ◽  
pp. 89-90
Author(s):  
Yuezhou Liu ◽  
Yuanyuan Li ◽  
Qian Ma ◽  
Stratis Ioannidis ◽  
Edmund Yeh
Keyword(s):  
Real World ◽  
Np Hard ◽  
Allocation Strategy ◽  
Gain Rate ◽  
Network Topologies ◽  
Allocation Strategies

We study fair content allocation strategies in caching networks through a utility-driven framework, where each request achieves a utility of its caching gain rate. The resulting problem is NP-hard. Submodularity allows us to devise a deterministic allocation strategy with an optimality guarantee factor arbitrarily close to 1-1/e. When 0 < α ≤ 1, we further propose a randomized strategy that attains an improved optimality guarantee, (1 - 1/e)1-α, in expectation. Through extensive simulations over synthetic and real-world network topologies, we evaluate the performance of our proposed strategies and discuss the effect of fairness.

scholarly journals An Optimal Rewiring Strategy for Cooperative Multiagent Social Learning

2019 ◽  
Vol 33 ◽  
pp. 10049-10050
Author(s):  
Hongyao Tang ◽  
Jianye Hao ◽  
Li Wang ◽  
Tim Baarslag ◽  
Zan Wang
Keyword(s):  
Social Learning ◽  
Multiagent Systems ◽  
Real World ◽  
Large Scale ◽  
Dynamic Environment ◽  
Multiagent Coordination ◽  
Learning Framework ◽  
Repeated Interaction ◽  
Long Run ◽  
Network Topologies

Multiagent coordination in cooperative multiagent systems (MASs) has been widely studied in both fixed-agent repeated interaction setting and static social learning framework. However, two aspects of dynamics in real-world MASs are currently missing. First, the network topologies can dynamically change during the course of interaction. Second, the interaction utilities between each pair of agents may not be identical and not known as a prior. Both issues mentioned above increase the difficulty of coordination. In this paper, we consider the multiagent social learning in a dynamic environment in which agents can alter their connections and interact with randomly chosen neighbors with unknown utilities beforehand. We propose an optimal rewiring strategy to select most beneficial peers to maximize the accumulated payoffs in long-run interactions. We empirically demonstrate the effects of our approach in large-scale MASs.

scholarly journals Ripple-Spreading Network Model Optimization by Genetic Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Xiao-Bing Hu ◽  
Ming Wang ◽  
Mark S. Leeson
Keyword(s):  
Genetic Algorithm ◽  
Complex Network ◽  
Network Model ◽  
Real World ◽  
Network Models ◽  
Small World ◽  
Network Systems ◽  
Scale Free ◽  
Apply Genetic ◽  
Network Topologies

Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM) is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs) of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA) to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

A Diffusion Model for Communication Standards in Supply Networks

2008 ◽  
pp. 504-520
Author(s):  
Tim Stockheim ◽  
Michael Schwind ◽  
Kilian Weiss
Keyword(s):  
Communication Network ◽  
Market Power ◽  
Real World ◽  
Value Chain ◽  
Potential Cost ◽  
Supply Networks ◽  
Local Communication ◽  
Implementation Costs ◽  
Network Topologies ◽  
The Impact

This article presents a simulation framework that analyzes the diffusion of communication standards in different supply networks. We show that agents’ decisions depend on potential cost reduction, pressure from members of their communication network, and implementation costs of their communication standards. Besides focusing on process-specific market power distributions, the impact of relationship stability and process connectivity is analyzed as determinants of the diffusion of communication standards within different supply network topologies. In this context, two real-world scenarios from the automotive and paper/publishing industries are used as examples for different network topologies. The results support the thesis that increasing relationship dynamics and process connectivity lead to decreasing competition of communication standards. In certain circumstances, local communication clusters appear along the value chain, enabling these clusters to preserve their globally inferior standardization decision.

A Diffusion Model for Communication Standards in Supply Networks

2011 ◽  
pp. 105-121
Author(s):  
Michael Schwind ◽  
Tim Stockheim ◽  
Kilian Weiss
Keyword(s):  
Communication Network ◽  
Market Power ◽  
Real World ◽  
Value Chain ◽  
Potential Cost ◽  
Supply Networks ◽  
Local Communication ◽  
Implementation Costs ◽  
Network Topologies ◽  
The Impact

This chapter presents a simulation framework that analyzes the diffusion of communication standards in different supply networks. We show that agents’ decisions depend on potential cost reduction, pressure from members of their communication network, and implementation costs of their communication standards. Besides focusing on process-specific market power distributions, the impact of relationship stability and process connectivity are analyzed as determinants of the diffusion of communication standards within different supply network topologies. In this context, two real-world scenarios, from the automotive and paper and publishing industries, are used as examples for different network topologies. The results support the thesis that increasing relationship dynamics and process connectivity lead to decreasing competition of communication standards. In certain circumstances, local communication clusters appear along the value chain, enabling these clusters to preserve their globally inferior standardization decision.

scholarly journals A Methodology to Select Topology Generators for Ad Hoc Mesh Network Simulations

2020 ◽  
pp. 741-746
Author(s):  
Michael O’Sullivan ◽  
◽  
Leonardo Aniello ◽  
Vladimiro Sassone
Keyword(s):  
Wireless Communications ◽  
Real World ◽  
Ad Hoc ◽  
Industrial Research ◽  
Mesh Network ◽  
The Real ◽  
Preliminary Results ◽  
Network Topologies ◽  
Initial Placement ◽  
Network Simulations

Many academic and industrial research working on Wireless Communications and Networking rely on simulations, at least in the first stages, to obtain preliminary results to be subsequently validated in real settings. Topology generators (TG) are commonly used to generate the initial placement of nodes in artificial Ad Hoc Mesh Network topologies, where those simulations take place. The significance of these experiments heavily depends on the representativeness of artificial topologies. Indeed, if they were not drawn fairly, obtained results would apply only to a subset of possible configurations, hence they would lack of the appropriate generality required to port them to the real world. Although using many TGs could mitigate this issue by generating topologies in several different ways, that would entail a significant additional effort. Hence, the problem arises of what TGs to choose, among a number of available generators, to maximise the representativeness of generated topologies and reduce the number of TGs to use. In this paper, we address that problem by investigating the presence of bias in the initial placement of nodes in artificial Ad Hoc Mesh Network topologies produced by different TGs. We propose a methodology to assess such bias and introduce a metric to quantify the diversity of the topologies generated by a TG with respect to all the available TGs, which can be used to select what TGs to use. We carry out experiments on three well-known TGs, namely BRITE, NPART and GT-ITM. Obtained results show that using the artificial networks produced by a single TG can introduce bias.

Replications can cause distorted belief in scientific progress

2018 ◽  
Vol 41 ◽  
Author(s):  
Michał Białek
Keyword(s):  
Real World ◽  
Scientific Progress ◽  
The Public ◽  
Psychological Science

AbstractIf we want psychological science to have a meaningful real-world impact, it has to be trusted by the public. Scientific progress is noisy; accordingly, replications sometimes fail even for true findings. We need to communicate the acceptability of uncertainty to the public and our peers, to prevent psychology from being perceived as having nothing to say about reality.

Current Issues: Evidence-Based Practice for the Real World: Thoughts on Clinical Education in Communication Disorders

2010 ◽  
Vol 20 (3) ◽  
pp. 100-105 ◽  
Author(s):  
Anne K. Bothe
Keyword(s):  
Clinical Education ◽  
Real World ◽  
Evidence Based Practice ◽  
Communication Disorders ◽  
University Faculty ◽  
Evidence Based ◽  
Speech Language Pathology ◽  
Basic Principles ◽  
The Real ◽  
Language Pathology

This article presents some streamlined and intentionally oversimplified ideas about educating future communication disorders professionals to use some of the most basic principles of evidence-based practice. Working from a popular five-step approach, modifications are suggested that may make the ideas more accessible, and therefore more useful, for university faculty, other supervisors, and future professionals in speech-language pathology, audiology, and related fields.

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