A Complex Adaptive Network System (CANS) is a social network system that is decentralised and can evolve to achieve its goals (or purposes), based on its own narratives; a set of evolved rules; and these are related to a history of past circumstances. CANS respond to their environment and themselves be “nested” within other network systems such as group; groups within an organisation; a group that strategically plans projects related to other network systems such as markets, or communities, or environmental ecosystems. Each are forms of interrelated and interacting system networks.
EXPOSURE AND AVOIDANCE MECHANISM OF BLACK HOLE AND JAMMING ATTACK IN MOBILE A...ijcseit
Mobile ad hoc network (MANETs) is an infrastructure-less/self-configurable system in which every node
carries on as host or router and every node can participate in the transmission of packets. Because of its
dynamic behaviour such system is more susceptible against various sorts of security threats, for example,
Black hole, Wormhole , Jamming , Sybil, Byzantine attack and so on which may block the transmission of
the system. Black hole attack and Jamming attack is one of them which promote itself has shortest or new
fresh route to the destination while jamming attack which make activity over the system. This paper
introduces the thorough literature study for the Black hole attack and jamming attack of both the attack by
various researchers.
THE NASH’S BALANCE IN THE THEORY OF GAMES FOR A SECURE MODEL MECHANISM IN ROU...ijcisjournal
The present work is dedicated to study attacks and countermeasure in MANET. After a short introduction to what the Mobile Ad hoc Networks (MANETs) are and network security we present a survey of various attacks in MANETs pertaining to fail routing protocols. We present the different tools used by these attacks and the mechanisms used by the secured routing protocols to counter them. We also study a mechanism of security, named the reputation, proposed for the MANETs and the protocol which implements it. We also propose a secure mechanism which is based on the reputation. Our work ends with a proposal analytical model to the modules of our mechanism and the equilibrium states of our model.
EXPOSURE AND AVOIDANCE MECHANISM OF BLACK HOLE AND JAMMING ATTACK IN MOBILE A...ijcseit
Mobile ad hoc network (MANETs) is an infrastructure-less/self-configurable system in which every node
carries on as host or router and every node can participate in the transmission of packets. Because of its
dynamic behaviour such system is more susceptible against various sorts of security threats, for example,
Black hole, Wormhole , Jamming , Sybil, Byzantine attack and so on which may block the transmission of
the system. Black hole attack and Jamming attack is one of them which promote itself has shortest or new
fresh route to the destination while jamming attack which make activity over the system. This paper
introduces the thorough literature study for the Black hole attack and jamming attack of both the attack by
various researchers.
THE NASH’S BALANCE IN THE THEORY OF GAMES FOR A SECURE MODEL MECHANISM IN ROU...ijcisjournal
The present work is dedicated to study attacks and countermeasure in MANET. After a short introduction to what the Mobile Ad hoc Networks (MANETs) are and network security we present a survey of various attacks in MANETs pertaining to fail routing protocols. We present the different tools used by these attacks and the mechanisms used by the secured routing protocols to counter them. We also study a mechanism of security, named the reputation, proposed for the MANETs and the protocol which implements it. We also propose a secure mechanism which is based on the reputation. Our work ends with a proposal analytical model to the modules of our mechanism and the equilibrium states of our model.
Power Aware Cluster to Minimize Load In Mobile Ad Hoc NetworksIJRES Journal
Mobile ad hoc networks (MANETs) are popularly known to their mobility and ease of usage. These networks are a set of identical nodes that move freely to communicate among networks and they are represented as a set of clusters. However, their wireless and active natures cause them to be more susceptible to various types of security attacks and transmission energy consumption so that they drop out of the network easily. Now-a-days the major challenge of MANETS is to endow with the assurance to the secure network services and also to provide a nearby balance of load for the cluster-heads. To meet this confront, certificate revocation with load balancing is an important central component to provide security and energy conservation in the network communications. In this paper, we focus on load balancing clustering to widen the lifetime of the cluster-head for a maximum time before allowing it to withdraw so as to distribute the responsibility to other legitimate nodes in the cluster to act as a cluster-head along with the issue of certificate revocation process. For quick, accurate, secure certificate revocation and to conserve energy, we propose the CCRV with Load Balancing Clustering scheme where we can reduce the burden of the cluster along with secure certificate revocation. In particular, to minimize the transmission energy consumption, we use the master slave model to operate the network with longer lifetime and we propose load balancing mechanism to enhance the lifetime of the cluster-head.
CAMP: cluster aided multi-path routing protocol for the wireless sensor, according to an article written by "Mohit Sajwan1 • Devashish Gosain2 • Ajay K. Sharma1
Network clustering is an important technique used in many large-scale distributed systems. Given good design and implementation, network clustering can significantly enhance the system\'s scalability and efficiency. However, it is very challenging to design a good clustering protocol for networks that scale fast and change continuously. In this paper, we propose a distributed network clustering protocol SDC targeting large-scale decentralized systems. In SDC, clusters are dynamically formed and adjusted based on SCM, a practical clustering accuracy measure. Based on SCM, each node can join or leave a cluster such that the clustering accuracy of the whole network can be improved. A big advantage of SDC is it can recover accurate clusters from node dynamics with very small message overhead. Through extensive simulations, we conclude that SDC is able to discover good quality clusters very efficiently.
A Proposed Algorithm to Detect the Largest Community Based On Depth LevelEswar Publications
The incredible rising of online networks show that these networks are complex and involving massive data.Giving a very strong interest to set of techniques developed for mining these networks. The clique problem is a well known NP-Hard problem in graph mining. One of the fundamental applications for it is the community detection. It helps to understand and model the network structure which has been a fundamental problem in several fields. In literature, the exponentially increasing computation time of this problem make the quality of these solutions is limited and infeasible for massive graphs. Furthermore, most of the proposed approaches are able to detect only disjoint communities. In this paper, we present a new clique based approach for fast and efficient overlapping
community detection. The work overcomes the short falls of clique percolation method (CPM), one of most popular and commonly used methods in this area. The shortfalls occur due to brute force algorithm for enumerating maximal cliques and also the missing out many vertices thatleads to poor node coverage. The proposed work overcome these shortfalls producing NMC method for enumerating maximal cliques then detects overlapping communities using three different community scales based on three different depth levels to assure high nodes coverage and detects the largest communities. The clustering coefficient and cluster density are used to measure the quality. The work also provide experimental results on benchmark real world network to
demonstrate the efficiency and compare the new proposed algorithm with CPM method, The proposed algorithm is able to quickly discover the maximal cliques and detects overlapping community with interesting remarks and findings.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
The popularity of Wireless Sensor Networks (WSN) have increased rapidly and tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since sensor devices rely on battery power and node energy and may be placed in hostile environments, so replacing them becomes a difficult task. Thus, improving the energy of these networks i.e. network lifetime becomes important. The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency using fuzzy logic controller. It presents a comparison between the different methods on the basis of the network lifetime. It compares existing ABC optimization method with BFO algorithm for different size of networks and different scenario. It provides cluster head selection method with good performance and reduced computational complexity. In addition it also proposes BFO as an algorithm for clustering of WSN which would result in improved performance with faster convergence.
Distribution of maximal clique size underijfcstjournal
In this paper, we analyze the evolution of a small-world network and its subsequent transformation to a
random network using the idea of link rewiring under the well-known Watts-Strogatz model for complex
networks. Every link u-v in the regular network is considered for rewiring with a certain probability and if
chosen for rewiring, the link u-v is removed from the network and the node u is connected to a randomly
chosen node w (other than nodes u and v). Our objective in this paper is to analyze the distribution of the
maximal clique size per node by varying the probability of link rewiring and the degree per node (number
of links incident on a node) in the initial regular network. For a given probability of rewiring and initial
number of links per node, we observe the distribution of the maximal clique per node to follow a Poisson
distribution. We also observe the maximal clique size per node in the small-world network to be very close
to that of the average value and close to that of the maximal clique size in a regular network. There is no
appreciable decrease in the maximal clique size per node when the network transforms from a regular
network to a small-world network. On the other hand, when the network transforms from a small-world
network to a random network, the average maximal clique size value decreases significantly.
DISTRIBUTION OF MAXIMAL CLIQUE SIZE UNDER THE WATTS-STROGATZ MODEL OF EVOLUTI...ijfcstjournal
In this paper, we analyze the evolution of a small-world network and its subsequent transformation to a
random network using the idea of link rewiring under the well-known Watts-Strogatz model for complex
networks. Every link u-v in the regular network is considered for rewiring with a certain probability and if
chosen for rewiring, the link u-v is removed from the network and the node u is connected to a randomly
chosen node w (other than nodes u and v). Our objective in this paper is to analyze the distribution of the
maximal clique size per node by varying the probability of link rewiring and the degree per node (number
of links incident on a node) in the initial regular network. For a given probability of rewiring and initial
number of links per node, we observe the distribution of the maximal clique per node to follow a Poisson
distribution. We also observe the maximal clique size per node in the small-world network to be very close
to that of the average value and close to that of the maximal clique size in a regular network. There is no
appreciable decrease in the maximal clique size per node when the network transforms from a regular
network to a small-world network. On the other hand, when the network transforms from a small-world
network to a random network, the average maximal clique size value decreases significantly
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
A SECURE CLUSTER BASED COMMUNICATION IN WIRELESS NETWORK USING CRYPTOGRAPHIC ...IJNSA Journal
Mobile Adhoc Networks are becoming very popular in current Wireless Technology, which is been
associated to business, socially and in some critical applications like Military etc, The network which is
formed by self configuring wireless links which are connected to each other. These applications are
categorized by hostile environment that they serve while communicating between nodes. However in such
Wireless Network will be more exposed to different types of security attacks. The challenge is to meet
secure network communication. In this paper we focus on cluster based secure communication to improve
the reliability between clusters. In this scheme the Cluster Members (CM) submits a report to the Cluster
Head (CH) and temporarily stores Evidences as a security tokens. The reports contain digital signatures.
The CH will verify the consistency of the CM report and updates to Accounting Centre (AC). AC will verify
the uniformity of reports and clears the cryptographic operations. For attacker nodes, the security tokens
are requested to classify and expel the attacker nodes which submit wrong reports.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
Guide to Human Activity System (HAS) MappingDavid Alman
The Guide to Human Activity System (HAS) Mapping is a summary that explains what a HAS Map is; how to develop a HAS Map as a flow map to assess a problem situation; how to review conflicting issues, and how to develop an improved HAS Map to address the problem situation.
Power Aware Cluster to Minimize Load In Mobile Ad Hoc NetworksIJRES Journal
Mobile ad hoc networks (MANETs) are popularly known to their mobility and ease of usage. These networks are a set of identical nodes that move freely to communicate among networks and they are represented as a set of clusters. However, their wireless and active natures cause them to be more susceptible to various types of security attacks and transmission energy consumption so that they drop out of the network easily. Now-a-days the major challenge of MANETS is to endow with the assurance to the secure network services and also to provide a nearby balance of load for the cluster-heads. To meet this confront, certificate revocation with load balancing is an important central component to provide security and energy conservation in the network communications. In this paper, we focus on load balancing clustering to widen the lifetime of the cluster-head for a maximum time before allowing it to withdraw so as to distribute the responsibility to other legitimate nodes in the cluster to act as a cluster-head along with the issue of certificate revocation process. For quick, accurate, secure certificate revocation and to conserve energy, we propose the CCRV with Load Balancing Clustering scheme where we can reduce the burden of the cluster along with secure certificate revocation. In particular, to minimize the transmission energy consumption, we use the master slave model to operate the network with longer lifetime and we propose load balancing mechanism to enhance the lifetime of the cluster-head.
CAMP: cluster aided multi-path routing protocol for the wireless sensor, according to an article written by "Mohit Sajwan1 • Devashish Gosain2 • Ajay K. Sharma1
Network clustering is an important technique used in many large-scale distributed systems. Given good design and implementation, network clustering can significantly enhance the system\'s scalability and efficiency. However, it is very challenging to design a good clustering protocol for networks that scale fast and change continuously. In this paper, we propose a distributed network clustering protocol SDC targeting large-scale decentralized systems. In SDC, clusters are dynamically formed and adjusted based on SCM, a practical clustering accuracy measure. Based on SCM, each node can join or leave a cluster such that the clustering accuracy of the whole network can be improved. A big advantage of SDC is it can recover accurate clusters from node dynamics with very small message overhead. Through extensive simulations, we conclude that SDC is able to discover good quality clusters very efficiently.
A Proposed Algorithm to Detect the Largest Community Based On Depth LevelEswar Publications
The incredible rising of online networks show that these networks are complex and involving massive data.Giving a very strong interest to set of techniques developed for mining these networks. The clique problem is a well known NP-Hard problem in graph mining. One of the fundamental applications for it is the community detection. It helps to understand and model the network structure which has been a fundamental problem in several fields. In literature, the exponentially increasing computation time of this problem make the quality of these solutions is limited and infeasible for massive graphs. Furthermore, most of the proposed approaches are able to detect only disjoint communities. In this paper, we present a new clique based approach for fast and efficient overlapping
community detection. The work overcomes the short falls of clique percolation method (CPM), one of most popular and commonly used methods in this area. The shortfalls occur due to brute force algorithm for enumerating maximal cliques and also the missing out many vertices thatleads to poor node coverage. The proposed work overcome these shortfalls producing NMC method for enumerating maximal cliques then detects overlapping communities using three different community scales based on three different depth levels to assure high nodes coverage and detects the largest communities. The clustering coefficient and cluster density are used to measure the quality. The work also provide experimental results on benchmark real world network to
demonstrate the efficiency and compare the new proposed algorithm with CPM method, The proposed algorithm is able to quickly discover the maximal cliques and detects overlapping community with interesting remarks and findings.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
The popularity of Wireless Sensor Networks (WSN) have increased rapidly and tremendously due to the vast potential of the sensor networks to connect the physical world with the virtual world. Since sensor devices rely on battery power and node energy and may be placed in hostile environments, so replacing them becomes a difficult task. Thus, improving the energy of these networks i.e. network lifetime becomes important. The thesis provides methods for clustering and cluster head selection to WSN to improve energy efficiency using fuzzy logic controller. It presents a comparison between the different methods on the basis of the network lifetime. It compares existing ABC optimization method with BFO algorithm for different size of networks and different scenario. It provides cluster head selection method with good performance and reduced computational complexity. In addition it also proposes BFO as an algorithm for clustering of WSN which would result in improved performance with faster convergence.
Distribution of maximal clique size underijfcstjournal
In this paper, we analyze the evolution of a small-world network and its subsequent transformation to a
random network using the idea of link rewiring under the well-known Watts-Strogatz model for complex
networks. Every link u-v in the regular network is considered for rewiring with a certain probability and if
chosen for rewiring, the link u-v is removed from the network and the node u is connected to a randomly
chosen node w (other than nodes u and v). Our objective in this paper is to analyze the distribution of the
maximal clique size per node by varying the probability of link rewiring and the degree per node (number
of links incident on a node) in the initial regular network. For a given probability of rewiring and initial
number of links per node, we observe the distribution of the maximal clique per node to follow a Poisson
distribution. We also observe the maximal clique size per node in the small-world network to be very close
to that of the average value and close to that of the maximal clique size in a regular network. There is no
appreciable decrease in the maximal clique size per node when the network transforms from a regular
network to a small-world network. On the other hand, when the network transforms from a small-world
network to a random network, the average maximal clique size value decreases significantly.
DISTRIBUTION OF MAXIMAL CLIQUE SIZE UNDER THE WATTS-STROGATZ MODEL OF EVOLUTI...ijfcstjournal
In this paper, we analyze the evolution of a small-world network and its subsequent transformation to a
random network using the idea of link rewiring under the well-known Watts-Strogatz model for complex
networks. Every link u-v in the regular network is considered for rewiring with a certain probability and if
chosen for rewiring, the link u-v is removed from the network and the node u is connected to a randomly
chosen node w (other than nodes u and v). Our objective in this paper is to analyze the distribution of the
maximal clique size per node by varying the probability of link rewiring and the degree per node (number
of links incident on a node) in the initial regular network. For a given probability of rewiring and initial
number of links per node, we observe the distribution of the maximal clique per node to follow a Poisson
distribution. We also observe the maximal clique size per node in the small-world network to be very close
to that of the average value and close to that of the maximal clique size in a regular network. There is no
appreciable decrease in the maximal clique size per node when the network transforms from a regular
network to a small-world network. On the other hand, when the network transforms from a small-world
network to a random network, the average maximal clique size value decreases significantly
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
A SECURE CLUSTER BASED COMMUNICATION IN WIRELESS NETWORK USING CRYPTOGRAPHIC ...IJNSA Journal
Mobile Adhoc Networks are becoming very popular in current Wireless Technology, which is been
associated to business, socially and in some critical applications like Military etc, The network which is
formed by self configuring wireless links which are connected to each other. These applications are
categorized by hostile environment that they serve while communicating between nodes. However in such
Wireless Network will be more exposed to different types of security attacks. The challenge is to meet
secure network communication. In this paper we focus on cluster based secure communication to improve
the reliability between clusters. In this scheme the Cluster Members (CM) submits a report to the Cluster
Head (CH) and temporarily stores Evidences as a security tokens. The reports contain digital signatures.
The CH will verify the consistency of the CM report and updates to Accounting Centre (AC). AC will verify
the uniformity of reports and clears the cryptographic operations. For attacker nodes, the security tokens
are requested to classify and expel the attacker nodes which submit wrong reports.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
Similar to Complex Adaptive Network Systems (CANS) draft 2 (20)
Guide to Human Activity System (HAS) MappingDavid Alman
The Guide to Human Activity System (HAS) Mapping is a summary that explains what a HAS Map is; how to develop a HAS Map as a flow map to assess a problem situation; how to review conflicting issues, and how to develop an improved HAS Map to address the problem situation.
Capability and organizational health v1 pdfDavid Alman
Capability is increasingly important to organizations, relevant to how employees’ carry out their roles; to improving productivity; and to organisations achieving sought after goals.
Capability refers to the ability to act quickly, effectively, and innovatively to a changing environment and customer needs. Without the application of capability, employees demonstrate limited performance, processes are inefficient, and organizations do not deliver what they should or could.
Capability is central to Organizational Health to improve organizational performance, and satisfy employee and customer needs
Using systems thinking to improve organisationsDavid Alman
Systems Thinking has been described as an approach to problem solving where "problems" are viewed as symptoms of an underlying system. If the underlying cause of a system problem is not addressed, problems can repeat and grow and cause unexpected consequences. This blog introduces a System Thinking Maturity Model, an ST Maturity Model, to help assess the underlying cause of problems and select a Systems Thinking Approach to resolve them.
This is about using user experiences at points of interaction –touchpoints- to understand how to achieve better outcomes from:
> Services to customers, patients, community groups;
> Roles (either job or team/group) carried out;
> Employee competence within a role;
> Employee well-being: Health & safety, and satisfaction.
While these are widely different areas, we can improve the way organisations perform and provide services to users through the use of Touchpoint Value Mapping.
The purpose of Open Surveys is to help understand and improve the effectiveness of an organisational change or some aspect of organisational performance based on respondent comments.
Open Surveys and their analysis are based on, and developed from, respondents’ thoughts and feelings expressed in their own words. • In an Open Survey respondents answer a few questions in detail by expressing themselves in their own words. Responses are grouped into categories, and from these categories broader patterns are built showing how comments are linked. Such patterns are, or can be fitted together, into a model covering and representing the collective views of respondents.
Organisational productivity is about assessing and improving the efficiency and effectiveness of public and private sector organisations. Four productivity models are explained and linked to a wide range of productivity improvement methodologies.
Systems are deeply embedded in the way an organisation manages health and safety (H&S). Over the last century there are recognizable shifts in the approaches taken toward H&S systems. Four Health and Safety System Approaches are identified and covered showing how the perspective taken by each of H&S and related accident analysis differ. These Health and Safety System Approaches are not substitutable options, rather they can be viewed as progressively adding to ways in which H&S is improved by organisations, in a sense reflecting a progression in the level of maturity of organisational H&S. The multi-level perspectives reflected in Health & Safety System Approaches can be similarly reflected in the law of tort and in Commissions of Inquiry into H&S failures.
Human Activity System (HAS) Maps visually illustrate and capture the “flow” of causes and outcomes in a problem situation.
In HAS Mapping a problem situation is viewed as occurring within a “system”, a Human Activity System (HAS), where the “system” allows a problem situation’s causes and effects to be identified and shaped into a causal relationship flow map, so underlying issues and their interrelationships can be better recognised and addressed.
The flow of causes to outcomes within a problem situation can be developed, for example, based on using, for example, “but-for” analysis (i.e. “but for an act or omission of X, Y would not have occurred”), and “Why- Because” analysis.
HAS Maps are versatile and can be applied to investigating, assessing, and addressing a wide range of problem situations.
Multilevel System Analysis - An Introduction to Systems Thinking David Alman
With the myriad of problem situations organisations face and the wide range of options in techniques, methodologies, and models available, how do we select a “best fit” between a problem situation and a means to its solution?
The purpose of this paper is to explain Multilevel System Analysis (MSA) as an introduction to Systems Thinking, and a means to match problem situations with Systems Thinking methodologies and models for their resolution.
Conflict analysis using an organizational justice model.v1David Alman
This paper relates to applying conflict analysis and diagnostic models to grievance and complaint processes. Conflict analysis is critical in achieving successful outcomes within an organization’s grievance or complaint process, and involves two steps: Diagnosing the conflict; and then developing a program to fit and address the conflict.
Conflict models are an effective way of diagnosing conflict, and an Organizational Justice Model is used to example their application within an organisational setting.
Organizational Health refers to an organization’s ability to achieve its goals based on an environment that seeks to improve organizational performance and support employee well-being. While these two perspectives are very different, a nexus between them means issues in one affect the other.
Improving organizational performance involves applying a systems thinking approach at organization, process, and role levels, and supporting employee well-being involves addressing both employee satisfaction and employee health (physical, mental, and social). Organizational health and employee well-being audits provide the means whereby an organization can continuously learn how to improve itself.
The purpose of the Organisational Sustainability slide show is to present a way organisations, both private and public sector, can :
a) Improve theirs and others sustainability, and in doing so also
b) Show how their progress can be measured in economic, community, and environmental terms .
Productivity is about adding value to outcomes achieved and in the way work is done. Productivity can be measured in terms of Cost and Benefit
through both tangible and intangible measures. The concept of productivity continues to evolve and is relevant to all forms of organisation, whether in the public or private sector, or NGO.
There are also a wide range of productivity methods available to add value at the:
Organisational Level
Process Level, and
Role Level
Because Proventive Solutions uses a Human Activity System (HAS) as the foundation for all its productivity methodologies, these productivity methodologies go beyond a focus on "hard" system activities to include "soft" social interactions that also affect the value of what is done and outcomes.
Workplace stress can be identified and addressed through a Stress Risk Management Audit, sometimes referred to as a Stress Risk Management Assessment. In a number of Australian States, and in the UK through the Safety Executive (UK), workplace stress risk factors have been identified and considered in a risk assessment process. This powerpoint is intended to fit into recommended practices rather be considered as an alternative. It also aligns with other Organisational Health methodologies, such as the Organisational Health Audit and Complaints Management, by using an underlying Human Activity System model. This allows for the identification stress risk factors to be identified when addressing other workplace issues.
Organisational Health Audits assess through a collaborative process ways organisational and employee performance and well-being can be improved based on Human Activity System (HAS) criteria.
The approach taken recognizes that organisational performance and employee well-being are interconnected, and uses a Human Activity Systems (HAS) model to identify interdependent and interacting factors.
Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
B2B payments are rapidly changing. Find out the 5 key questions you need to be asking yourself to be sure you are mastering B2B payments today. Learn more at www.BlueSnap.com.
Recruiting in the Digital Age: A Social Media MasterclassLuanWise
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
LA HUG - Video Testimonials with Chynna Morgan - June 2024Lital Barkan
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
We will dig deeper into:
1. How to capture video testimonials that convert from your audience 🎥
2. How to leverage your testimonials to boost your sales 💲
3. How you can capture more CRM data to understand your audience better through video testimonials. 📊
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
Know more: https://www.synapseindia.com/technology/mean-stack-development-company.html
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
In the Adani-Hindenburg case, what is SEBI investigating.pptxAdani case
Adani SEBI investigation revealed that the latter had sought information from five foreign jurisdictions concerning the holdings of the firm’s foreign portfolio investors (FPIs) in relation to the alleged violations of the MPS Regulations. Nevertheless, the economic interest of the twelve FPIs based in tax haven jurisdictions still needs to be determined. The Adani Group firms classed these FPIs as public shareholders. According to Hindenburg, FPIs were used to get around regulatory standards.
2. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 2
Contents
1 A CANS are Network Systems.................................................................................................3
1.1 Definition .........................................................................................................................3
2. CANS Characteristics..........................................................................................................3
3. Network Model Examples......................................................................................................5
3.1 Multileveled/Multilayered System Networks..................................................................5
3.2 Distributive Networks ......................................................................................................6
3.3 Area Grouping Network...................................................................................................7
7 Conflict Analysis ......................................................................................................................8
7.1 Conflict Network Analysis ................................................................................................8
7.2 Reframing Conflict Networks...........................................................................................9
8 Agent Based Modelling (ABM)..............................................................................................10
Conclusion................................................................................................................................11
References ...............................................................................................................................12
About the author .....................................................................................................................13
3. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 3
Complex Adaptive Network Systems (CANS)
1 CANS are Network Systems.
1.1 Definition
A Complex Adaptive Network System (CANS) is a network of social interacting agents that,
as a whole, represent a system. In this respect CANS include:
Humans referred to as Agents;
A social network, of which there are different forms;
A social network demonstrating human characteristics such as interrelationships
(e.g. conflict, cooperative, and competitive relationships); ideological narratives;
rules; and purposes;
A boundary that characterises what is inside and outside of the network system.
2. CANS Characteristics
CANS are dynamic network systems able to adapt to and evolve (i.e. co-evolve) in
their changing environment: There is no separation between a CANS and its
environment as CANS respond and adapt to their changing environment.
CANS has a number of characteristics such as:
A “Distributed” Network where there is no single centralised control mechanism
that governs social system network behaviour. Rather control of a CANS tends
to be highly dispersed. In this respect there is no hierarchy of command and
control in a CANS. There is no planning or managing, but there is a constant re-
organising to find the best fit with the environment, where the CANS is
continually self organising through the process of emergence and feedback.
Any coherent behaviour in a system arises from competition and cooperation
among the agents themselves. Some system networks tend toward order not
disorder through a process of spontaneous self organisation (based on evolved
simple rules).
4. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 4
Network “Connectivity” where a decision or action by one part within a CANS will
influence all other related parts but not in any uniform manner.
CANS interact in networks and form patterns of behaviour that could not have
been predicted from understanding each particular agent, and continuously
improves its efficiency to achieve its aims and objectives.
Network “Co-evolution” where network behaviour can change based on their
interactions with one another and with the environment. Additionally, patterns
of network behaviour can change over time.
Most CANS are “nested network systems”: Systems within other systems and
many are systems of smaller systems. CANS is part of many different network
systems most of which are themselves part of other network systems.
Chaos does have a place in CANS in that systems exist on a spectrum ranging
from equilibrium to chaos. A system in equilibrium does not have the internal
dynamics to respond to its environment (and slowly or quickly die). On the other
hand a system network in chaos ceases to function. The most productive state
to be in is at the edge of chaos where there is maximum variety and creativity,
leading to new possibilities.
CANS history grows from their own evolutionary environment. CANS evolve and
form a narrative about what they are about. While these system networks
evolve they constantly assess their past and present in order to inform their
future. History in terms of how they are rooted and evolved gives CANS a self-
generated “learning loop” from which it can increase its rate of emergence.
The future is unpredictable. As a CANS organises, it creates a multitude of
competing, complimentary and counter intuitive “alternatives” from which it will
derive its ‘future’. This allows the network system to employ the maximum
amount of variety and creativity in securing its future, whatever that may be. An
optimal network system exists on the edge of “chaos” where a CANS has the
ability to choose alternative futures is optimised, informed by network
knowledge that is generating a wide range of possibilities and alternatives.
5. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 5
3. Network Model Examples
3.1 Multileveled/Multilayered System Networks
CANS are decentralised networks of interacting humans (Agents) who frame and reframe
their purpose and react and respond to feedback from their external environment.
CANS networks can be multileveled/multilayered where agents at one level can
competitively or cooperatively interact with agents at another network level. A CANS can
also be part of another CANS, as exampled in Diagram 1.
Diagram 1 A Multileveled CANS Example
A work group CANS
An organisation CANS
A market CANS
A community CANS
An eco system CANS
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3.2 Distributive Networks
Where each “node” is connected to neighbouring nodes within a decentralised network. A
node can represent agents, groups, communities, and so on as exampled in Diagram 1.
Diagram 2. Distributive Network
A Distributive network can also reflect layers or levels as shown in Diagram 3.
Diagram 3. Distributive Lattice Network
7. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 7
3.3 Area Grouping Network
A group of nodes, such as teams, who are in the same layer or level of a network. This is
analogous to peer groups relying on equal rather than on hierarchical arrangements, as
exampled in Diagram 4.
Diagram 4. Area Grouping Network
3.4 Ramification Network
Where control in the network is highly dispersed and decentralised, where the network is
split into related agent networks, as exampled in Diagram 5.
Diagram 5 Ramification Network
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7 Conflict Analysis
7.1 Conflict Network Analysis
Conflict, and competition, between CANS agents, irrespective of the form of network they
are in, can be resolved and collaboration assisted by carrying out a Conflict Network Analysis
and applying a process that improves relationships, cooperation, and meaningful
understanding.
A Conflict Network Analysis uses types of conflict issues as a means of assessment as shown
in Table 1.
Types of Agent Conflict issues CANS Conflict Issue Examples
Structural issues e.g.what are the rule
sets affecting agent behaviour
Value based issues e.g. What is the
history of the conflict, and reinforcing
Narratives?
Relationship based issues e.g.
competition, cooperation
Information based issues
Interest based issues e.g. what are the
interests underlying conflicts?
Needs based issues e.g. What are the
agent Network’s needs?
Table 1
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7.2 Reframing Conflict Networks
CANS agent conflicts can be resolved by the network agents working through and
addressing their issues. Diagram 6 is a shortened and amended version of Tuckman’s theory
of group development applied to groups as CANS, and extended to broader CANS
applications.
Diagram 6. Stages in Network Development
A Conflict Network Map is exampled is Diagram 7 that are based on conflict issues referred
to in Table 1. In terms of addressing System Network conflict a conflict resolution process
can explore:
Alternatives: What actions are possible”
Expectations: What future consequences might follow from each alternative? How
likely are possible consequences, assuming that alternatives are chosen?
Preferences: How valuable (to agents) are the consequences associated with each of
the alternatives?
Decision rule: How is a choice made among alternatives in terms of the values of
their consequences?
Network
Forming
Network Storming
Network Norming
Network break up
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Diagram 7. A Conflict Network Map
8 Agent Based Modelling (ABM)
Agent-based models consist of dynamically interacting rule-based agents that interact to
create real-world-like scenarios. ABMs are software systems that can simulate the
evolution of a CANS by, for example, explaining the emergence of social network patterns
such as in community behaviour, market performance; impact on ecosystem sustainability.
11. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 11
Conclusion
A Complex Adaptive Network System (CANS) is a social network system that is decentralised
and can evolve to achieve its goals (or purposes), based on its own narratives; a set of
evolved rules; and these are related to a history of past circumstances. CANS respond to
their environment and themselves be “nested” within other network systems such as group;
group within an organisation; a group that strategically plans projects related to other
network systems such as markets, or communities, or environmental ecosystems. Each are
forms of interrelated and interacting system networks.
In developing CANS material three related areas are considered to explain what is, and what
is involved in, Complex Adaptive Network Systems:
Conflict Adaptive Systems (CAS);
Network models relevant to CAS
Conflict Networks
12. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 12
References
Complex Adaptive Systems. Serena Chan. Downloaded on 13/4/14 from
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What are Fractal Systems? Peter Fryer and Jules Ruis. Downloaded on 13/4/14 from
http://www.fractal.org/Bewustzijns-Besturings-Model/Fractal-systems.htm
Understanding and defeating a complex adaptive system. Lieutenant Colonel Ian Langford.
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publications/~/media/Files/Our%20future/DARA%20Publications/AAJ/2012Summer/Compl
ex-Adaptive-System-AAJ-Vol9-No3-Summer-2012.pdf
Navigating Complexity by Arthur Battram. First published by The Industrial Society, London
in 1998, and by Stylus Publishing inc, Sterling USA.
The Conflict Mapping Chart. L. Shay Bright Downloaded on 13/4/14
http://www.cmsupport.org/ConflictMapping/ConflictMappingChart_ShayBright.pdf
Field guide to conflict analysis. Downloaded on 14/4/14
http://www.fao.org/docrep/008/a0032e/a0032e0d.htm
Analysing actor networks while assuming "frame rationality". Pieter Bots Downloaded on
14/4/14
http://www.hks.harvard.edu/netgov/files/NIPS/PWG_BOTS_Analyzing_actor_networks_14_
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Systemic Conflict Transformation: Reflections on the Conflict and Peace Process in Sri Lanka
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handbook.net/documents/publications/dialogue6_ropers_lead.pdf
Group Dynamics Donelson Forsyth Downloaded on 13/4/14
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df
13. Complex Adaptive Network System (CANS) David Alman Draft 1 Page 13
About the author
David Alman lives in Brisbane, Queensland, Australia, and is the business owner of
Proventive Solutions, which offers services in Organisational Health.
Organisational Health is a broad overview term that refers to assessing and improving
performance and well being of both an organisation and its employees, recognising there is
a nexus between the two.
David writes blogs, articles and PowerPoints on subjects related to organisational health,
productivity, conflict management, and systems thinking. These can be accessed through a
Google website and Word Press website. Please refer to:
https://sites.google.com/site/proventivesolutions/ and
http://davidalman.wordpress.com/home-page-welcome/