Self organization based energy management techniques in mobile complex networks: a review

Fatima, Bahjat; Shah, Munam Ali

doi:10.1186/s40294-015-0008-1

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…Exchanging five control frames will not only consume more mobile energy but also CR nodes may miss the rare opportunity to transmit. Energy-efficient communication via wireless interfaces optimization usually requires some collaborative mechanism between operating system, applications, and network infrastructure (Fatima and Shah 2015). Moreover, F 2 -MAC does not specify whether the dedicated control channel is GCCC or non-GCCC.…”

Section: Non-gccc Cr Mac Protocolsmentioning

confidence: 99%

A survey on MAC protocols for complex self-organizing cognitive radio networks

Shah

Zhang

Kamran

et al. 2016

Complex Adapt Syst Model

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Complex self-organizing cognitive radio (CR) networks serve as a framework for accessing the spectrum allocation dynamically where the vacant channels can be used by CR nodes opportunistically. CR devices must be capable of exploiting spectrum opportunities and exchanging control information over a control channel. Moreover, CR nodes should intelligently coordinate their access between different cognitive radios to avoid collisions on the available spectrum channels and to vacate the channel for the licensed user in timely manner. Since inception of CR technology, several MAC protocols have been designed and developed. This paper surveys the state of the art on tools, technologies and taxonomy of complex self-organizing CR networks. A detailed analysis on CR MAC protocols form part of this paper. We group existing approaches for development of CR MAC protocols and classify them into different categories and provide performance analysis and comparison of different protocols. With our categorization, an easy and concise view of underlying models for development of a CR MAC protocol is provided.

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Section: Non-gccc Cr Mac Protocolsmentioning

confidence: 99%

A survey on MAC protocols for complex self-organizing cognitive radio networks

Shah

Zhang

Kamran

et al. 2016

Complex Adapt Syst Model

Self Cite

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“…Simulations capture the dynamics of various autonomous behaviors in CASs, and they can provide data output for analysis and processing. Since CASs exhibit nonlinear and emergent behaviors, simulations are the ideal choice for capturing such complexities 9 . As noted in Figure 2, steps 1‐3 must all occur in order to quantify CAS performance before moving to the last step.…”

Section: Introductionmentioning

confidence: 99%

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Douglas

Mazzuchi

Sarkani

2020

Systems Engineering

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Complex adaptive systems (CAS) exhibit emergent behaviors caused by the nonlinear actions between individual components within the system and their environment. These emergent behaviors are difficult to predict and measure making it very challenging to initially design from the start. Developing CASs, such as an autonomous swarming unmanned system, is a relevant key task today for solving hard problems with limited resources in a demanding economy. Swarming unmanned systems are valued by their unique capabilities, but how do stakeholders ensure their needs are considered during development? Certain stakeholders have interests that go beyond the initial delivery of the system, yet developers seem to focus efforts on designing autonomous behaviors to satisfy immediate mission needs. To close this gap, we propose a stakeholder focused framework for evaluating CASs over a full system life cycle for swarming unmanned systems. A goal‐oriented requirements engineering modeling methodology, Knowledge Acquisition in AutOmated Specification, is used to map requirements between stakeholder goals and autonomous behaviors. Behaviors are analyzed in an agent‐based simulation using NetLogo for quantifying stakeholder‐driven performance qualities (‐ilities). A case study was performed for a swarm of unmanned surface vessels called wave gliders to evaluate performance over the entire system life cycle.

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“…Out-of-equilibrium systems (non-linear dynamic processes), such as the Zhabotinsky-Belousov reaction [ 14 ] and other oscillating reactions, as well as convection phenomena [ 15 ] show self-organization of the pattern formation. Other examples of self-organization phenomena have been investigated, such as biological rithms [ 16 ], pattern formation and collective behaviour of neurons and in neuron networks [ 17 ], [ 18 ], [ 19 ], [ 20 ], patterns in excitable media [ 21 ], [ 22 ], [ 23 ], [ 24 ], quantum gravity [ 25 ], mobile networks [ 26 ]. Social systems also stem from self-organizing processes [ 27 ], e.g.…”

Section: Introductionmentioning

confidence: 99%

Self-organization in a diversity induced thermodynamics

Scire

Annovazzi-Lodi

2017

PLoS ONE

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In this work we show how global self-organized patterns can come out of a disordered ensemble of point oscillators, as a result of a deterministic, and not of a random, cooperative process. The resulting system dynamics has many characteristics of classical thermodynamics. To this end, a modified Kuramoto model is introduced, by including Euclidean degrees of freedom and particle polarity. The standard deviation of the frequency distribution is the disorder parameter, diversity, acting as temperature, which is both a source of motion and of disorder. For zero and low diversity, robust static phase-synchronized patterns (crystals) appear, and the problem reverts to a generic dissipative many-body problem. From small to moderate diversity crystals display vibrations followed by structure disintegration in a competition of smaller dynamic patterns, internally synchronized, each of which is capable to manage its internal diversity. In this process a huge variety of self-organized dynamic shapes is formed. Such patterns can be seen again as (more complex) oscillators, where the same description can be applied in turn, renormalizing the problem to a bigger scale, opening the possibility of pattern evolution. The interaction functions are kept local because our idea is to build a system able to produce global patterns when its constituents only interact at the bond scale. By further increasing the oscillator diversity, the dynamics becomes erratic, dynamic patterns show short lifetime, and finally disappear for high diversity. Results are neither qualitatively dependent on the specific choice of the interaction functions nor on the shape of the probability function assumed for the frequencies. The system shows a phase transition and a critical behaviour for a specific value of diversity.

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Self organization based energy management techniques in mobile complex networks: a review

Cited by 5 publications

References 36 publications

A survey on MAC protocols for complex self-organizing cognitive radio networks

A survey on MAC protocols for complex self-organizing cognitive radio networks

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Self-organization in a diversity induced thermodynamics

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