graph theoretic model for community wireless networks
TRANSCRIPT
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A Graph Theoretic Approach for Analysis and Design of Community Wireless
Networks
Abdelnasser M. Abdelaal and Hesham H. AliDepartment of Computer Science
College of Information Science and TechnologyUniversity of Nebraska at Omaha
Omaha, NE 68182{aabdelaal | hali}@mail.unomaha.edu
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Agenda
Introduction Graph Modeling Proposed Graph Theoretic Model Significance of Research Conclusion
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What are Community Wireless Networks
It is about “digital inclusion:” The world Internet penetration is 20.0 %.
Government solutions may not be applicable Commercial Internet solutions are not viable for communities that have:
Low income, limited population density, remote locations, harsh geography.
The overall objective is to improve the socio-economic well-being of the community at large.
A simple CWN: When two neighbors, friends, family members, or roommates share an
access point.
A citywide CWN: When a big community (or municipality) shares a few access points. It could grow, or concatenate with other WiFi hotspots, to form a city-wide
wireless network.
What are Community Wireless Networks, Cont.
Definition: CWNs are wireless networks owned, built and operated by the local
community for the purpose of providing affordable or free wireless access They are built by the shared resources of communities (e.g., times, effort,
money donations, skills, beliefs, values and computing resources. They are value networks where digital resources are brokered:
Commercial values Non-commercial values
Similar wireless networks: Municipal wireless WiFi hotspots Private wireless LANs
Private WLANs Municipal Wireless CWNs
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Issues of CWNs Issues of CWNs:
CWNs are complex systems with several social, economic, and technical variables.
There is a lack of theories and general models that describe and analyze these emerging networks
CWNs are mixed with municipal wireless networks, and public WiFi hotspots
Literature has been influenced by computer geeks and non academicians.
How can we measure the contributions and the benefits of stakeholders
The Objective: Using graph theory to describe and analyze CWNs and solve related
problems. We used a socio-technical approach is used to find the Internet
connectivity solution that fits a specific social group
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Developing a Wireless Network Suitable for a Specific Social Network
The social graph supported by the CWN The wireless graph that serves the community
Will the attributes of the community determine the suitable connectivity solution ?
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Why Graph Theory
Why graph concepts? We can tie the social resources with technical resources in a single artifact The distance between local residents and the connection between them is
important for coverage issues and antenna placement The properties ( social ties, trust, distance, density) of the social group
determine the most suitable solution and technology (ad-hoc, infrastructure BSS, extended service set).
In a classic village or neighborhood, “everyone knows everyone else” and it is easier for them to share a wireless network.
Actors are more likely to be connected with one another if they are geographically near to one another.
CWNs represent a new form of complex networks They represent collective actions in the digital domain similar to open source
software development
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What is a Graph?
A graph is a mathematical model G(V,E) comprises a set V of vertices and a set E of edges. The node set could be anything. The set of edges represent ties between nodes. If there is a tie between a and b, then {a,b} ⊆ E : a,b ∈V and a≠b}. then we say vertices a and b are adjacent and the edge {a, b} joins them or connects them or is
incident on them. Two edges that share one vertex, such as {a,b} and {b,c} with a≠c, are adjacent to each other. Edges could have weights, the weight of {a,b} is 5. Vertex {f} is isolated We have three components {f}, {h, g}, {a, b, c, d, e}
a
b
cd
e
f
h
g
5
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What can graphs model? Health Care
Health support systems, spread of diseases
Computer Science[ Cost of wiring computer networks Analyzing peer-to-peer networks Analyzing online social networks (e.g., emails, blogs, MySpace)
Management Science Corporate strategic alliances, organizational hierarchy Information flows, trade, partnerships
Social Science Neighboring behavior, community participation, civic engagement Children groups, friendship, high school cliques Work teams, voluntary associations, social movements Social contacts (kinship, terrorism, crime networks)
Economics and Finance Financial networks Good exchange, market contracts, and trade agreements
Many other applications in anthropology, transportation, biology
The world is composed of networks
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Community Wireless Community Wireless NetworksNetworks
Computer ScienceComputer Science
Management Management ScienceScience
Social ScienceSocial Science
EconomicsEconomics
and Financeand Finance
CWNs: A Multidisciplinary Approach
CWNs are socio-technical networks
There is a heavy confluence between social, economic, and technical variables
We can model them in a single artifact
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Proposed Graph Theoretic Model
.
Outputs
Inputs
Volunteerism, donations, partnerships, node hosting, OSS, frequency regulation, social ties and values
CWNsValue proposition, incentives, management, ownership, pricing, funding, acceptance
QoS, security, reliability, node placement, coverage, data rate, signal interference
Tech factors Social factors
Graph theory
Physical capital, social capital and human capital
Variables of CWNs
Implementation phase
Operation phase Educational, commercial, medical, municipal, societal, and personal services
Mobility, affordability, time and effort savings, resource sharing
Social and economic development
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A Graph Theoretic Model for CWNs, cont.
Each CWN is composed of a wireless graph ( or network) that serves a social graph
The wireless graph: The wireless network is a directed graph Gw = (Vw, Ew) Its nodes are workstations, routers, extenders, etc Its links are the wireless signals These links have attributes such as bit rate, packet delay, packet loss, security, etc
The social graph: The community is represented by a directed graph Gs (Vs, Es), Its set of nodes Vs represents actors or CWNs Its set of edges Es represent the social ties and interactions between these stakeholders. These ties could be kinship, neighborhood, collaboration, friendship, reciprocation, trust, etc. Vs has three categories of actors: beneficiaries, contributors, and isolated nodes. Edges are weighted by the contributions and the benefits of participants. Benefits include free Internet access, donated PCs, technical expertise, exposure, or spiritual benefits. Contributions include voluntary work or technical skills, donating money or old equipment, hosting a wireless
node.
The confluence and interaction between these two graphs determine the functionality of CWNs
Advantages of this Model It provides the vocabularies, concepts and the mathematical operations that could be
used to label, denote, quantify and measure variables of CWNs; It gives us the ability to prove theories and deduce testable statements related to
CWNs as complex networks. We can determine who are the main actors in the network? Who has control over what flows in the network? We can identify the location with best visibility to install the facilities We can cluster nodes in a way that provides better coverage and higher performance We can identify bottlenecks or central nodes that provide the only connection
between different parts of the network. We can measure the flows of tangible (e.g., donations) and intangibles (e.g., trust,
social cohesion, influence, knowledge) in the network We can identify isolated nodes It shows the importance of structural properties of communities while developing
CWNs
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Modeling Stakeholders of CWNs
Stakeholders of CWNs: Community members, Volunteers, municipalities, businesses, technology vendors, nonprofit
organizations, open source software developers, academic institutions, students, churches, etc. These stakeholders could be classified into beneficiaries, contributors, and isolates.
Their contributions: Donations, partnerships, volunteerism, technical skills, sharing a wireless signal with others. These contributions represent the role of social communities in building and sustaining their own
wireless networks
Their benefits: Providing free Internet access to bridge the digital divide; Improving the business opportunities in the area; Improving the civic engagement and political participation; Supporting municipal services Obtaining technical expertise Gaining publicity and exposure Improving the well-being of the community at large.
We can use concepts of graph theory to measure their contributions and benefits? This is important to empower them and engage them in building and maintaining these networks
Modeling The Omaha Wireless Network
Washington Library
Elmwood Park
UNO
Rosenblatt Stadium
PKI Students Omaha community
Vendors Municipalities
PKI - Experience , free internet
Free internet, old PCs, civic engagement
Publicity Reputation
Students Reputation - Technical skills 0
community Publicity Exposure - Publicity Reputation
Tech. vendors Access points 0 Access points - 0
Municipalities Access to public places
0 0 - -
Micro-Macro level of analysis
We view the Omaha wireless network as a value network
The columns represent benefits and the rows represent contributions of different actors
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Determining Where to Install the Access Point
A central actor is the one that is involved in many ties. The PKI is the graph center We installed access points at PKI because of its high centrality The administration unit is also hosted by PKI because of its high centrality
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Modeling Community Contributions to Build the Network
A matrix is a different way to represent a graph
If the cell value is “1”, the network receives this type of contribution and vis versa
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Modeling Community Contributions to Build the Network, Cont.
We can classify contributors of CWNs and measure their contributions
Green nods represent contributors and red nods represent IDs of CWNs
Main actors are volunteers, advocates, and money donors in different CWNs
The edges are weighted by the value of their contributions
This is important to reciprocate them and empower similar actors
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Modeling Community Contributions to Build the Network, Cont
time money Tech.support Sharing OSS Other
Time 1 0.06 0.46 0.59 0.3 0.22
Money 0.06 1 0.06 0.2 0.28 0.2
tech.support 0.46 0.06 1 0.23 0.3 0.22
Sharing 0.59 0.2 0.23 1 0.13 0.18
develop software 0.3 0.28 0.3 0.13 1 0.46
Other 0.22 0.2 0.22 0.18 0.46 1
The Similarity Matrix between Different Types of Community Contributions
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Significance of Research
For practitioners: This model expands the problem solving abilities of CWNs practitioners. It helps them to distinguish CWNs from municipal wireless networks
and commercial WiFi hotspots It helps communities to assess their potential resources that could be
mobilized to develop a community-centric wireless network For researchers:
This graph representation of CWNs provides a rich set of conceptual measures and insights to guide current and future research related to community and municipal wireless networks.
It helps us to solve a number of key problems using well defined algorithms such as identifying proper places for positioning access points using the concept of graph centers or finding the best grouping of nodes in the network using the concept of clustering in graphs.
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Significance of Research, Cont. The model limitations:
It is difficult to aggregate the tangible and intangible benefits and contributions of CWNs’ actors.
It is difficult to include all actors in the study. CWNs are networks not systems
Current and future work: Addressing the impact of the social variables (e.g., community size, density of the network,
and types of used applications) on the technical factors such as signal interference, QoS, throughput, and the optimal network size.
Measuring the role of CWNs in generating social capital and human capital. Measuring the trust in the domain of CWNs
The originality of our research : Modeling CWNs in a single artifact We consider the multidisciplinary nature of CWNs Economic flows, social networks, and computer networks are interrelated in CWNs The tangible and intangible contributions and benefits of CWNs stakeholders have
measurable economic value
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Conclusion We view a CWN as two graphs: a social graph and a wireless
graph. We used graph concepts to model and attribute CWNs CWNs are value networks where digital resources are brokered
among community members The attributes and the interactions between the components of these
two graphs determine different aspects of CWNs. This quantitative artifact helps us to study CWNs and measure their
related variables It helps us to decide where to install the access point or router It helps us to classify the stakeholders of CWNs and identify their
contributions and benefits. Future work will focus on measuring the role of CWNs in creating
social and human capital
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