This document presents a mathematical framework for analyzing systems of interacting networks. The key points are:
1) The framework allows calculating the percolation threshold and component size distributions for systems of l interacting networks, taking into account connectivity both within and between networks.
2) Exact expressions are derived for the percolation threshold and applied to different degree distributions for two interacting networks.
3) The framework is applied to real-world systems involving communications networks and software networks to better understand their structure and function.
A Survey on Clustering Techniques for Wireless Sensor Network IJORCS
Wireless sensor networks have been used in various fields like battle feilds, surveillance, schools, colleges, etc. It has been used in our day-to-day life. Its growth increases day by day. Sensor node normally senses the physical event from the environment such as temperature, sound, vibration, pressure etc. Sensor nodes are connected with each other through wireless medium such as infrared or radio waves it depends on applications. Each node has its internal memory to store the information regarding the event packets. In this paper we will come to know the various algorithms in clustering techniques for wireless sensor networks and discuss them. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption .It can also increase network scalability. Sensor nodes are considered to be homogeneous since the researches in the feild of WSNs have been evolved but in reality homogeneous sensor networks hardly exist. Here we will discuss some of the impact of heterogeneous sensor networks on WSN and various clustering algorithms used in HWSN.
Dear Students
Ingenious techno Solution offers an expertise guidance on you Final Year IEEE & Non- IEEE Projects on the following domain
JAVA
.NET
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ROBOTICS
MECHANICAL
MATLAB etc
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enquiry@ingenioustech.in
044-42046028 or 8428302179.
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A Framework for Routing Misbehavior Recognition in MANETSEECJOURNAL
Mobile Ad-hoc Networks (MANETs) operate on the basic underlying assumption that all participating nodes fully collaborate in self-organizing functions. However, performing network functions consumes energy and other resources. Therefore, some network nodes may decide against cooperating with others. These nodes are called selfish / misbehaving nodes. Misbehavior of suspicious nodes in MANETs is detected, and the information is propagated throughout the network, so that the misbehaving node will be cut off from the rest of the network. We propose a network-layer acknowledgment-based scheme, termed the 2ACK scheme, which can be simply added-on to any source routing protocol. The proposed scheme detects misbehaving nodes, and then seeks to alleviate the problem by notifying the routing protocol to avoid them in future routes. Our results show that proposed scheme reasonably improves the packet delivery ratio, with some additional routing overhead.
Characterization of directed diffusion protocol in wireless sensor networkijwmn
Wireless sensor network (WSN) has enormous applications in many places for monitoring the environments
of importance. Sensor nodes are capable of sensing, computing, and communicating. These sensor nodes
are energy constraint and operated by batteries. Since energy consumption is an important issue of WSN,
there have been many energy-efficient protocols proposed for the WSN. Directed diffusion (DD) is a datacentric
protocol that focuses on the energy efficiency of the networks. Since the first proposal of DD
protocol by Deborah, there have been various versions of DD protocols proposed by many scientists across
the globe. These upgraded versions of DD protocols add on various features to the original DD protocol
such as energy, scalability, network lifetime, security, reliability, and mobility. In this paper, we discuss
and classify various characteristics of themost populardirected diffusion protocols that have been proposed
over couple of years.
A Survey on Clustering Techniques for Wireless Sensor Network IJORCS
Wireless sensor networks have been used in various fields like battle feilds, surveillance, schools, colleges, etc. It has been used in our day-to-day life. Its growth increases day by day. Sensor node normally senses the physical event from the environment such as temperature, sound, vibration, pressure etc. Sensor nodes are connected with each other through wireless medium such as infrared or radio waves it depends on applications. Each node has its internal memory to store the information regarding the event packets. In this paper we will come to know the various algorithms in clustering techniques for wireless sensor networks and discuss them. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption .It can also increase network scalability. Sensor nodes are considered to be homogeneous since the researches in the feild of WSNs have been evolved but in reality homogeneous sensor networks hardly exist. Here we will discuss some of the impact of heterogeneous sensor networks on WSN and various clustering algorithms used in HWSN.
Dear Students
Ingenious techno Solution offers an expertise guidance on you Final Year IEEE & Non- IEEE Projects on the following domain
JAVA
.NET
EMBEDDED SYSTEMS
ROBOTICS
MECHANICAL
MATLAB etc
For further details contact us:
enquiry@ingenioustech.in
044-42046028 or 8428302179.
Ingenious Techno Solution
#241/85, 4th floor
Rangarajapuram main road,
Kodambakkam (Power House)
http://www.ingenioustech.in/
A Framework for Routing Misbehavior Recognition in MANETSEECJOURNAL
Mobile Ad-hoc Networks (MANETs) operate on the basic underlying assumption that all participating nodes fully collaborate in self-organizing functions. However, performing network functions consumes energy and other resources. Therefore, some network nodes may decide against cooperating with others. These nodes are called selfish / misbehaving nodes. Misbehavior of suspicious nodes in MANETs is detected, and the information is propagated throughout the network, so that the misbehaving node will be cut off from the rest of the network. We propose a network-layer acknowledgment-based scheme, termed the 2ACK scheme, which can be simply added-on to any source routing protocol. The proposed scheme detects misbehaving nodes, and then seeks to alleviate the problem by notifying the routing protocol to avoid them in future routes. Our results show that proposed scheme reasonably improves the packet delivery ratio, with some additional routing overhead.
Characterization of directed diffusion protocol in wireless sensor networkijwmn
Wireless sensor network (WSN) has enormous applications in many places for monitoring the environments
of importance. Sensor nodes are capable of sensing, computing, and communicating. These sensor nodes
are energy constraint and operated by batteries. Since energy consumption is an important issue of WSN,
there have been many energy-efficient protocols proposed for the WSN. Directed diffusion (DD) is a datacentric
protocol that focuses on the energy efficiency of the networks. Since the first proposal of DD
protocol by Deborah, there have been various versions of DD protocols proposed by many scientists across
the globe. These upgraded versions of DD protocols add on various features to the original DD protocol
such as energy, scalability, network lifetime, security, reliability, and mobility. In this paper, we discuss
and classify various characteristics of themost populardirected diffusion protocols that have been proposed
over couple of years.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
AN EFFICIENT ROUTING PROTOCOL FOR DELAY TOLERANT NETWORKS (DTNs)cscpconf
Delay-Tolerant Networks are those which lacks continuous communications among mobile
nodes . Distributed clustering scheme and cluster-based routing protocol are used for DelayTolerant
Mobile Networks (DTMNs). The basic idea is to distributive group mobile nodes with
similar mobility pattern into a cluster, which can then interchangeably share their resources for
overhead reduction and load balancing, aiming to achieve efficient and scalable routing in DTMN. Load balancing is carried out in two ways, Intra cluster load balancing and Inter cluster load balancing. The Convergence and stability become major challenges in distributed clustering in DTMN. An efficient routing protocol will be provided for the delay tolerant networks through which the stability of the network is maintained .Based on nodal contact probabilities, a set of functions including Sync(), Leave(), and Join() are devised for cluster formation and gateway selection. Finally, the gateway nodes exchange network information and perform routing
PERFORMANCE COMPARISON OF QOS METRICS FOR A DISTRIBUTED PRICING SCHEMEijasuc
De-centralized nature of nodes, in ad-hoc networks, results in the users adapting their operations
independently. Such operations are mostly biased upon the figures and data available for the parameters
which are imperative for superior performance or, in other words, improved Quality of Performance (QoS)
of the nodes. In centrally controlled networks following cooperative game theory principles, collective
operations are performed by the nodes for better QoS of the network. Although nodes in decentralized
networks undertake individual operations, the final outcome of the whole network and thus the performance
of the nodes in the network are influenced by the operations of other nodes. Hence, a distributed resource
allocation approach in such a scenario can be modeled as a non-cooperative game. Asynchronous
Distributed Pricing (ADP) is one such virtual pricing algorithm in which a user’s payoff is determined by
the difference between how much a given performance metric is valued and how much is paid for it. User
service demands and priorities are modeled using numerically emulated QoS metrics termed as utility
functions. The network objective is to maximize the sum of all users’ payoff. However, for convergence of
the sum of all users’ payoff to a global maximum, the determination of the QoS metric’s utility function
with sufficient concavity is essential. Although supermodularity conditions have been previously defined
and determined to obtain suitable utility functions, we have numerically and analytically illustrated that the
convergence performance characteristics fluctuates with the choice of QoS metrics in the algorithm for
similar utility functions as well. We have assessed the optimality of utility functions under Signal-toInterference-plus-Noise ratio and Signal-to-Interference ratio based calculations. This paper also explores
into the difference in performance characteristics obtained by the addition of a significant value noise
variance in the ADP algorithm.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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.
Replica Placement In Unstable Radio LinksCSCJournals
In this paper, proposed a solution for replica placement onto mobile hosts which are continuously moving and disconnections occur by unstable radio links, which are likely to be disconnected after a short time. Consider an Ad Hoc network in which mobile hosts are entered and communicate with other mobile hosts in the network and get replicas from the neighbors, while accessing the data items disconnections may occur due to unstable radio links. In this way accessing the data items is difficult. In this paper, develop a mechanism to access the data items from the mobile hosts after disconnection occur for short time. The proposed mechanism works efficiently in mosaic networks also. The technique incorporates the access frequency from mobile hosts to each data object, the status of the network connectivity by exhibit an adjacent matrix, and communication costs, which are very low by accessing data items from nearest neighbors. The derived mechanism is general, flexible and adaptable to cater for various applications in ad hoc networks. This approach is efficient in both execution time and solution quality.
Dynamic Hybrid Topology Design for Integrated Traffic Support in WDM Mesh Net...CSCJournals
The future Internet will require the transport of a wide range of services including high bandwidth one-to-many applications, with a dynamic interconnection of devices. WDM layer support realizes such services in a transparent, reliable and efficient way. Most of the recent studies have been focused on efficiently building and configuring light-paths for unicast or light-trees for multicast in isolation, and do not take existing traffic demands and configuration into consideration. In this paper we consider a dynamic design problem of integrated traffic in a realistic WDM mesh network. In such a network, new traffic demands of either multicast and/or unicast are supported dynamically in the presence of an existing mixture of traffic. The amount of bandwidth per wavelength is abundant, while the wavelengths and light splitting capabilities on WDM switches are limited. Using subwavelength sharing among traffic demands of unicast and multicast, we build a hybrid virtual topology that exploits both existing light-trees and light-paths. By optimizing WDM resources in addition to resource sharing with existing unicast and multicast demands, we truly maximize the WDM layer capability and efficiently support more traffic demands. We validate the efficiency of our approach with extensive simulations on various network topologies.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Achieving Transmission Fairness in Distributed Medium Access Wireless Mesh Ne...ijwmn
Wireless mesh networking gained an international interest over the years as a result to high recognition in
the wireless industry as a cost effective, scalable, wider coverage and capacity capable wireless technology.
The contention based distributed medium access in wireless networks has advanced not only in supporting
the quality of multimedia but also achieving high throughput and to minimize packet delay overheads in
legacy systems. Unfortunately, the impact of such enhancement has not been fully justified with mesh
network environments yet. The medium access frames are required to be contended over multi-hops to
overcome the challenges of improving overall system performance through concurrent transmissions. The
goal of this paper is to discuss the issues and challenges of transmission fairness and the effect of
concurrent transmission on system performance. To mitigate transmission fairness issues, we review
existing open literature on mesh networking and provide guidelines for better system design and
deployment. Finally, we conclude the paper with future research directions. This study may help network
designer and planner to overcome the remaining challenging issues in the design and deployment of WMNs
worldwide.
A Novel Approach for Detection of Routes with Misbehaving Nodes in MANETsIDES Editor
Network nodes in MANET’s are free to move randomly.
Therefore, the network topology may change rapidly.
Routing protocol for MANET’s are used for delivery of data
packets from source to the desired destination, Routing protocols
are also designed based on the assumption that all the
participating nodes are fully cooperative. However, due to the
scarcely available battery based energy, node behaviours may
exist. One such routing misbehaviours is that some nodes may
be selfish by participating in route discovery and maintenance
process, but refuse to forward the packet in order to save its
energy. To solve this problem we propose a reputation based
scheme where the watch dog uses a passive overhearing of
nodes and assign a value to it as an appreciation or add nuggets
to them. In this proposal, nodes with highest value are
highly recommended for data forwarding and allow nodes to
avoid the use of misbehaving nodes in future route selection.
AdHoc On Demand Distance vector routing protocol may be
used to get the recommendation details of the node intended
to forward the packet from the neighbouring nodes. This paper
proposes a novel method to mitigate the route with misbehaving
nodes and also suggests a way to find if any intruder is
present in the cluster of participating nodes using security
aware AODV protocol.
Complexity Número especial da Nature Physics Insight sobre complexidadeaugustodefranco .
Albert-László Barabási, James P. Crutchfield, M. E. J. Newman, Alessandro Vespignani, Jianxi Gao, Sergey V. Buldyrev, Eugene Stanley and Shlomo Havlin Janeiro 2012
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
AN EFFICIENT ROUTING PROTOCOL FOR DELAY TOLERANT NETWORKS (DTNs)cscpconf
Delay-Tolerant Networks are those which lacks continuous communications among mobile
nodes . Distributed clustering scheme and cluster-based routing protocol are used for DelayTolerant
Mobile Networks (DTMNs). The basic idea is to distributive group mobile nodes with
similar mobility pattern into a cluster, which can then interchangeably share their resources for
overhead reduction and load balancing, aiming to achieve efficient and scalable routing in DTMN. Load balancing is carried out in two ways, Intra cluster load balancing and Inter cluster load balancing. The Convergence and stability become major challenges in distributed clustering in DTMN. An efficient routing protocol will be provided for the delay tolerant networks through which the stability of the network is maintained .Based on nodal contact probabilities, a set of functions including Sync(), Leave(), and Join() are devised for cluster formation and gateway selection. Finally, the gateway nodes exchange network information and perform routing
PERFORMANCE COMPARISON OF QOS METRICS FOR A DISTRIBUTED PRICING SCHEMEijasuc
De-centralized nature of nodes, in ad-hoc networks, results in the users adapting their operations
independently. Such operations are mostly biased upon the figures and data available for the parameters
which are imperative for superior performance or, in other words, improved Quality of Performance (QoS)
of the nodes. In centrally controlled networks following cooperative game theory principles, collective
operations are performed by the nodes for better QoS of the network. Although nodes in decentralized
networks undertake individual operations, the final outcome of the whole network and thus the performance
of the nodes in the network are influenced by the operations of other nodes. Hence, a distributed resource
allocation approach in such a scenario can be modeled as a non-cooperative game. Asynchronous
Distributed Pricing (ADP) is one such virtual pricing algorithm in which a user’s payoff is determined by
the difference between how much a given performance metric is valued and how much is paid for it. User
service demands and priorities are modeled using numerically emulated QoS metrics termed as utility
functions. The network objective is to maximize the sum of all users’ payoff. However, for convergence of
the sum of all users’ payoff to a global maximum, the determination of the QoS metric’s utility function
with sufficient concavity is essential. Although supermodularity conditions have been previously defined
and determined to obtain suitable utility functions, we have numerically and analytically illustrated that the
convergence performance characteristics fluctuates with the choice of QoS metrics in the algorithm for
similar utility functions as well. We have assessed the optimality of utility functions under Signal-toInterference-plus-Noise ratio and Signal-to-Interference ratio based calculations. This paper also explores
into the difference in performance characteristics obtained by the addition of a significant value noise
variance in the ADP algorithm.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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.
Replica Placement In Unstable Radio LinksCSCJournals
In this paper, proposed a solution for replica placement onto mobile hosts which are continuously moving and disconnections occur by unstable radio links, which are likely to be disconnected after a short time. Consider an Ad Hoc network in which mobile hosts are entered and communicate with other mobile hosts in the network and get replicas from the neighbors, while accessing the data items disconnections may occur due to unstable radio links. In this way accessing the data items is difficult. In this paper, develop a mechanism to access the data items from the mobile hosts after disconnection occur for short time. The proposed mechanism works efficiently in mosaic networks also. The technique incorporates the access frequency from mobile hosts to each data object, the status of the network connectivity by exhibit an adjacent matrix, and communication costs, which are very low by accessing data items from nearest neighbors. The derived mechanism is general, flexible and adaptable to cater for various applications in ad hoc networks. This approach is efficient in both execution time and solution quality.
Dynamic Hybrid Topology Design for Integrated Traffic Support in WDM Mesh Net...CSCJournals
The future Internet will require the transport of a wide range of services including high bandwidth one-to-many applications, with a dynamic interconnection of devices. WDM layer support realizes such services in a transparent, reliable and efficient way. Most of the recent studies have been focused on efficiently building and configuring light-paths for unicast or light-trees for multicast in isolation, and do not take existing traffic demands and configuration into consideration. In this paper we consider a dynamic design problem of integrated traffic in a realistic WDM mesh network. In such a network, new traffic demands of either multicast and/or unicast are supported dynamically in the presence of an existing mixture of traffic. The amount of bandwidth per wavelength is abundant, while the wavelengths and light splitting capabilities on WDM switches are limited. Using subwavelength sharing among traffic demands of unicast and multicast, we build a hybrid virtual topology that exploits both existing light-trees and light-paths. By optimizing WDM resources in addition to resource sharing with existing unicast and multicast demands, we truly maximize the WDM layer capability and efficiently support more traffic demands. We validate the efficiency of our approach with extensive simulations on various network topologies.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Achieving Transmission Fairness in Distributed Medium Access Wireless Mesh Ne...ijwmn
Wireless mesh networking gained an international interest over the years as a result to high recognition in
the wireless industry as a cost effective, scalable, wider coverage and capacity capable wireless technology.
The contention based distributed medium access in wireless networks has advanced not only in supporting
the quality of multimedia but also achieving high throughput and to minimize packet delay overheads in
legacy systems. Unfortunately, the impact of such enhancement has not been fully justified with mesh
network environments yet. The medium access frames are required to be contended over multi-hops to
overcome the challenges of improving overall system performance through concurrent transmissions. The
goal of this paper is to discuss the issues and challenges of transmission fairness and the effect of
concurrent transmission on system performance. To mitigate transmission fairness issues, we review
existing open literature on mesh networking and provide guidelines for better system design and
deployment. Finally, we conclude the paper with future research directions. This study may help network
designer and planner to overcome the remaining challenging issues in the design and deployment of WMNs
worldwide.
A Novel Approach for Detection of Routes with Misbehaving Nodes in MANETsIDES Editor
Network nodes in MANET’s are free to move randomly.
Therefore, the network topology may change rapidly.
Routing protocol for MANET’s are used for delivery of data
packets from source to the desired destination, Routing protocols
are also designed based on the assumption that all the
participating nodes are fully cooperative. However, due to the
scarcely available battery based energy, node behaviours may
exist. One such routing misbehaviours is that some nodes may
be selfish by participating in route discovery and maintenance
process, but refuse to forward the packet in order to save its
energy. To solve this problem we propose a reputation based
scheme where the watch dog uses a passive overhearing of
nodes and assign a value to it as an appreciation or add nuggets
to them. In this proposal, nodes with highest value are
highly recommended for data forwarding and allow nodes to
avoid the use of misbehaving nodes in future route selection.
AdHoc On Demand Distance vector routing protocol may be
used to get the recommendation details of the node intended
to forward the packet from the neighbouring nodes. This paper
proposes a novel method to mitigate the route with misbehaving
nodes and also suggests a way to find if any intruder is
present in the cluster of participating nodes using security
aware AODV protocol.
Complexity Número especial da Nature Physics Insight sobre complexidadeaugustodefranco .
Albert-László Barabási, James P. Crutchfield, M. E. J. Newman, Alessandro Vespignani, Jianxi Gao, Sergey V. Buldyrev, Eugene Stanley and Shlomo Havlin Janeiro 2012
Dynamic spread of hapiness in a large social networkaugustodefranco .
Dynamic spread of happiness in a large social network:
longitudinal analysis over 20 years in the Framingham Heart Stud by James Fowler & Nicholas Christakis (2008)
To have the ability to “think outside the box” is generally regarded as something positive. At a moment in time when resources are scarce, and the problems facing us are many, innovation and professional excellence becomes a requirement, rather than a matter of choice. At the core of our attempts to come up with new, and better solutions are the digital technologies. Within the structural engineering context, the different types of off-the-shelf packages for finite element analysis play a central role. These “black-box” types of software packages exemplify how user-friendliness may have harmful consequences within a field where knowledge and the successful mastery of relevant skills is key, and consequently- ignorance may lead to fatal results. These tools make any effort “venturing outside” difficult to achieve. A technical paradigm shift is called for- that places learning and creative, informed exploration at the heart of the user experience. Presented during the Knowledge Based Engineering session of the 19th IABSE congress entitled "Challenges in Design and Construction of an Innovative and Sustainable Built Environment" held in Stockholm, September 21-23, 2016.
To have the ability to “think outside the box” is generally regarded as something positive. At a moment in time when resources are scarce, and the problems facing us are many, innovation and professional excellence becomes a requirement, rather than a matter of choice. At the core of our attempts to come up with new, and better solutions are the digital technologies. Within the structural engineering context, the different types of off-the-shelf packages for finite element analysis play a central role. These “black-box” types of software packages exemplify how user-friendliness may have harmful consequences within a field where knowledge and the successful mastery of relevant skills is key, and consequently- ignorance may lead to fatal results. These tools make any effort “venturing outside” difficult to achieve. A technical paradigm shift is called for- that places learning and creative, informed exploration at the heart of the user experience. Presented during the Knowledge Based Engineering session of the 19th IABSE congress held in Stockholm, September 21-23, 2016.
In this paper the design of an experiment is presented. An experiment was designed to select relevant and not redundant features or characterization functions, which allow quantitatively discriminating among different types of complex networks. As well there exist researchers given to the task of classifying some networks of the real world through characterization functions inside a type of complex network, they do not give enough evidences of detailed analysis of the functions that allow to determine if all of them are necessary to carry out an efficient discrimination or which are better functions for discriminating. Our results show that with a reduced number of characterization functions such as the degree dispersion coefficient can discriminate efficiently among the types of complex networks treated here.
COMMUNICATIONS OF THE ACM November 2004Vol. 47, No. 11 15.docxmonicafrancis71118
COMMUNICATIONS OF THE ACM November 2004/Vol. 47, No. 11 15
N
etworks are hot. The
Internet has made it pos-
sible to observe and mea-
sure linkages
representing relationships of
all kinds. We now recognize
networks everywhere: air
traffic, banking, chemical
bonds, data communications,
ecosystems, finite element
grids, fractals, interstate
highways, journal citations,
material structures, nervous
systems, oil pipelines, orga-
nizational networks, power
grids, social structures, trans-
portation, voice communica-
tion, water supply, Web
URLs, and more.
Several fields are collabo-
rating on the development of
network theory, measurement,
and mapping: mathematics
(graph theory), sociology (net-
works of influence and communi-
cation), computing (Internet), and
business (organizational net-
works). This convergence has pro-
duced useful results for risk
assessment and reduction in com-
plex infrastructure networks,
attacking and defending networks,
protecting against network con-
nectivity failures, operating busi-
nesses, spreading epidemics
(pathogens as well as computer
viruses), and spreading innova-
tion. Here, I will survey the fun-
damental laws of networks that
enable these results.
Defining a Network
A network is usually defined as a
set of nodes and links. The nodes
represent entities such as persons,
machines, molecules, documents,
or businesses; the links represent
relationships between pairs of
entities. A link can be directed
(one-way relationship) or undi-
rected (mutual relationship). A
hop is a transition from one node
to another across a single link
separating them. A path is a series
of hops. Networks are very gen-
eral: they can represent any kind
of relation among entities.
Some common network
topologies (interconnection pat-
terns) have their own names:
clique or island (a connected sub-
network that may be isolated
from other cliques), hierarchical
network (tree structured), hub-
and-spoke network (a special
node, the hub, connected directly
to every other node), and multi-
hub network (several hubs con-
nected directly to many nodes).
Some network topologies are
planned, such as the electric grid,
the interstate highway system, or
Network Laws
M
IC
H
A
EL
S
LO
A
N
Peter J. Denning
Many networks, physical and social, are complex and scale-invariant.
This has important implications from the spread of epidemics and
innovations to protection from attack.
The Profession of IT
16 November 2004/Vol. 47, No. 11 COMMUNICATIONS OF THE ACM
the air traffic system; others are
unplanned. In his seminal papers
about the Internet, Paul Baran
proposed that a planned, distrib-
uted network would be more
resilient to failures than a hub-
and-spoke network.
A host of physical systems eas-
ily fit a network model. Perhaps
less obvious is that human social
networks also fit the model. The
individuals of an organization are
linked by their relationships—
who emails whom, who seeks
advice from whom, or who influ-
ences w.
FAST AND ACCURATE MINING THE COMMUNITY STRUCTURE: INTEGRATING CENTER LOCATING...Nexgen Technology
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The Majority Rule is applied to a topology that consists of two coupled
random networks, thereby mimicking the modular structure observed in social
networks. We calculate analytically the asymptotic behaviour of the model and derive a
phase diagram that depends on the frequency of random opinion flips and on the inter-
connectivity between the two communities. It is shown that three regimes may take
place: a disordered regime, where no collective phenomena takes place; a symmetric
regime, where the nodes in both communities reach the same average opinion; an
asymmetric regime, where the nodes in each community reach an opposite average
opinion. The transition from the asymmetric regime to the symmetric regime is shown
to be discontinuous.
Simulator for Energy Efficient Clustering in Mobile Ad Hoc Networkscscpconf
The research on various issues in Mobile ad hoc networks is getting popular because of its
challenging nature and all time connectivity to communicate. Network simulators provide the
platform to analyse and imitate the working of the nodes in the networks along with the traffic
and other entities. The current work proposes the design of a simulator for the mobile ad hoc
networks that provides a test bed for the energy efficient clustering in the dynamic network.
Node parameters like degree of connectivity and average transmission power are considered for
calculating the energy consumption of the mobile devices. Nodes that consume minimum energy among their 1-hop neighbours are selected as the cluster heads.
REFLEXÕES: APRENDIZAGEM OU DERIVA ONTOGÊNICA pelo Dr. Humberto Maturana (1982), Departamento de Biologia da Faculdade de Ciências Básicas e Farmacêuticas. Universidade do Chile, Santiago, Chile. Traduzido por Júlia Eugênia Gonçalves.
CONDORCET, Marquês de (1792). Relatório de projeto de decreto sobre a organiz...augustodefranco .
CONDORCET, Marquês de (1792). Relatório de projeto de decreto sobre a organização geral da instrução pública in Hippeau: A Instrução Pública na França durante a Revolução.
NIETZSCHE, Friederich (1888). Os "melhoradores" da humanidade, Parte 2 e O qu...augustodefranco .
NIETZSCHE, Friederich (1888). Os "melhoradores" da humanidade, Parte 2 e O que falta aos alemães, Parte 5 in O crepúsculo dos ídolos, ou Como filosofar com o martelo.
Book completo do programa de investigação-aprendizagem democrática pelo exercício do reconhecimento de padrões autocráticos em 10 romances e 10 filmes clássicos. O programa é totalmente à distância e foi desenhado para poder ser feito nas férias (daí o nome fantasia 100 DIAS DE VERÃO). Inscrições https://www.sympla.com.br/100-dias-de-verao__23054
Textos de Augusto de Franco publicados no Facebook, entre maio e setembro de 2014, sobre o Decreto 8.243/2014 que institui a Política Nacional de Participação Social - PNPS e o Sistema Nacional de Participação Social - SNPS, e dá outras providências
Por que os democratas não podem apostar todas as fichas no processo eleitoral. Artigo de Augusto de Franco, publicado originalmente no Facebook em 9 de setembro de 2014.
Um programa de aprendizagem democrática pelo exercício do reconhecimento de padrões autocráticos em romances e filmes clássicos. Trata-se de um programa ofertado pelo LABE=R de 10 de janeiro a 20 de abril de 2015
Democracia cooperativa: escritos políticos escolhidos de John Deweyaugustodefranco .
FRANCO, Augusto e POGREBINSCHI, Thamy (editores) (2008) Democracia Cooperativa - Escritos Políticos Escolhidos de John Dewey. A versão final desta obra foi impressa em papel. Porto Alegre: ediPUCRS, 2008.
Como configurar um ambiente de investigação-aprendizagem openscience em sua escola. Capacitação teórica e opção de programa prático para educadores e gestores escolares e extraescolares.Programa intensivo de aprendizagem para agentes de educação que desejam configurar novos ambientes inovadores de pesquisa ou investigação em escolas e outras organizações. Programa presencial ofertado pelo LABE=R em São Paulo.
Programa de Aprendizagem Política a distância, ofertado pelo LABE=R (Laboratório da Escola-de-Redes), com 80 horas (estimadas) de duração, realizado totalmente pelo Facebook, de junho a setembro de 2014.
“Punished for Protesting:Rights Violations in Venezuela’s Streets, Detention Centers, and Justice System” (Punidos por Protestar: Violações de Direitos nas Ruas, Centros de Detenção e Sistema de Justiça na Venezuela) da organização Human Rights Watch, publicado em 5 de maio de 2014
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
1. Percolation on interacting networks
E. A. Leicht1 and Raissa M. D’Souza1, 2
1
Department of Mechanical and Aeronautical Engineering, University of California, Davis, CA 95616
2
The Santa Fe Institute, Santa Fe, NM 87501
(Dated: July 6, 2009)
Most networks of interest do not live in isolation. Instead they form components of larger systems
in which multiple networks with distinct topologies coexist and where elements distributed amongst
different networks may interact directly. Here we develop a mathematical framework based on
generating functions for analyzing a system of l interacting networks given the connectivity within
and between networks. We derive exact expressions for the percolation threshold describing the onset
of large-scale connectivity in the system of networks and each network individually. These general
expressions apply to networks with arbitrary degree distributions and we explicitly evaluate them for
arXiv:0907.0894v1 [cond-mat.dis-nn] 6 Jul 2009
l = 2 interacting networks with a few choices of degree distributions. We show that the percolation
threshold in an individual network can be significantly lowered once “hidden” connections to other
networks are considered. We show applications of the framework to two real-world systems involving
communications networks and socio-tecnical congruence in software systems.
PACS numbers: 64.60.aq, 89.75.Fb
In the past decade there has been a significant advance works was introduced with the layered network frame-
in understanding the structure and function of networks. work of [4]. Yet, the networks in the distinct layers must
Mathematical models of networks are now widely used to be composed of the identical nodes (modeling essentially
describe a broad range of complex systems, from spread physical connectivity and logical connectivity or flow).
of disease on networks of human contacts to interactions Herein we consider systems of l ≥ 2 distinct interact-
amongst proteins [1, 2, 3]. However, current methods ing networks and calculate explicitly how the connectiv-
deal almost exclusively with individual networks treated ity within and between networks determines the onset of
as isolated systems. In reality an individual network is large scale connectivity in the system and in each net-
often just one component in a much larger complex sys- work individually. Our mathematical formulation has
tem; a system that can bring together multiple networks some overlap with recent works calculating connectivity
with distinct topologies and functions. For instance, a properties in a single network accounting for a diversity
pathogen spreads on a network of human contacts abet- of node attributes [5, 6] or interactions between modules
ted by global and regional transportation networks. Like- within a network [7, 8]. Here we present our formalism
wise, email and e-commerce networks rely on the Internet and also applications to real-world systems of interacting
which in turn relies on the electric grid. In biological sys- networks coming from telecommunications and software.
tems, activated genes give rise to proteins some of which The onset of large-scale connectivity (i.e., the percola-
go back to the genetic level and activate or inhibit other tion threshold) corresponding to the emergence of a giant
genes. Results obtained in the context of a single isolated connected component in an isolated network has been
network can change dramatically once interactions with
other networks are incorporated.
Consider a system formed by two interacting networks,
α and β, Fig 1(a). Network α could be a human contact k1 edges to
α network 1
network for one geographic region and network β that for
a separated region. When viewed as individual systems,
kν t
ed wo
··
only small clusters of connected nodes exist, hence, a dis-
ne
ge rk
·
sb ν
ease spreading in either network should stay contained
ac
edge traversed
within clusters. In reality, a disease can hop from α to β,
k
µ
from ν to µ
···
for instance, by an infected person flying on a airplane,
spread in the β network and eventually hop back to the kl edges to
α network into new clusters, causing an epidemic out- network l
break. Next consider interacting networks that contain β
completely different types of nodes. Network α can be
(a) (b)
a social network, such as an email communication net-
work of software developers, while network β can be a FIG. 1: a) Two networks α and β. Nodes interact directly
technological network, such as the network of calls be- with other nodes in their immediate network, yet also with
tween functions in software code. Here, bi-partite edges nodes in the second network. b) An illustration of the re-
connect developers on α to code they author on β. maining edges incident to a node in a network µ reached by
An important step towards modeling interacting net- following a random edge between networks ν and µ.
2. 2
studied extensively, first for random networks with Pois- Consider selecting uniformly at random an edge falling
son degree distributions [9] and later for random networks between a node in network ν and a node in network
with arbitrary degree distributions [10]. Similar results µ (i.e., a ν-µ edge). The µ node attached to the edge
were then derived using generating functions [11, 12], the is kν times more likely to have ν-degree kν than de-
approach we employ herein. Generating functions, simi- gree 1. We can also account for the remaining local
lar to the network configuration model [10, 13], evaluate connectivity, to nodes in other networks as shown in
the ensemble of all possible random networks consistent Fig. 1(b). In single isolated networks remaining con-
with a specified degree distribution, {pk }, and are most nectivity is called the excess degree of a node [11]. Let
µν
accurate in the sparse regime where networks are approx- qk1 ···kν ···kl denote the probability of following a randomly
imately tree-like. Thus in the regime before the emer- chosen ν-µ edge to a node with excess ν degree as shown
gence of the giant component, generating functions can in Fig. 1(b) (which has total ν-degree of kν + 1). Then
be used to calculate the distribution of component sizes. qk1 ···kν ···kl ∝ (kν + 1)pµ1 ···(kν +1)···kl , and the generating
µν
k
In the supercritical regime they can be used to calculate µν
function for the distribution, {qk1 ···kl } is,
the distribution in sizes of components that are not part
of the giant component. ∞
µν
For our purposes, a system with l ≥ 2 interacting net- Gµν (x) = qk1 ···kl xk1 · · · xkl
1 l (2)
works is described by a set of degree distributions. Each k1 ,...,kl =0
individual network µ is characterized by a multi-degree ∞ (kν + 1)pµ1 ···(kν +1)···kl
k
distribution, {pµ1 k2 ···kl }, where pµ1 k2 ···kl is the fraction
k k = ∞ µ xk1 · · · xkl
1 l
of all nodes in network µ that have k1 edges to nodes k1 ,···kl =0 j1 ,...,jl =0 (jν+1 )pj1 ···(jν +1)···jl
in network 1, k2 edges to nodes in network 2, etc. The −1
∞ ∞
multi-degree distribution for each network may be writ- ∂
ten in the form of a generating function: = jν pµ1 ···jl
j pµ1 ···kl xk1 · · · xkl
k 1 l
j1 ,··· ,jl =0
∂xν
k1 ,...,kl =0
∞
ν
Gµ (x1 , . . . , xl ) = pµ1 ···kl xk1 · · · xkl . (1) Gµ (x)
k 1 l =
k1 ,...,kl =0 ν
Gµ (1)
To simplify notation in what follows, we now define two ν
where Gµ (x) denotes the first derivative of Gµ (x) with
l-tuple’s, x = (x1 , . . . , xl ) and 1 = (1, . . . , 1).
respect to xν and the denominator is a normalization
Our interest is in calculating the distribution of compo- ν ν
constant so that Gµν (1) = 1. Also note that Gµ (1) ≡ k µ
nent sizes, where a component is a set of nodes connected
is the average ν-degree for a node in network µ.
to one another either directly or indirectly by travers-
The distribution of second nearest neighbors for
ing a path along edges. Clearly such components can
that µ node via the ν layer is calculated by us-
be composed of nodes distributed among the l different
ing Eq. 2 as the argument to Eq. 1, namely
networks, and our formulation allows us to calculate the
Gµ (1, 1, ..., Gνµ (x)|xλ =1,λ=µ , ..., 1). Comparing this dis-
distribution of such system-wide components, yet also to
refine the focus and calculate the contribution coming tribution calculated via generating functions to that
from nodes contained in only one of the l networks. found in real-world interacting networks can reveal in-
We begin by deriving the distribution of connectiv- teresting statistical features. Returning to the software
ity forGeneral Availability release randomly chosen edge. example, we have a network of email communication be-
First a node at the end of a tween developers, a network of relations between code,
Bug and security fix
and bipartite edges connecting developers to the code
6 they edit. We would expect that the real system does not
5 resemble a random network, but instead reflects a struc-
JSD (norm)
4 ture conducive to project development. For instance, if
3 two developers edit the same code we would like for them
2 to directly communicate via email and thus be first neigh-
1 bors. In a sparse random network these developers would
0
2001 2002 2003 2004 typically be second neighbors, connected indirectly via
Time the code they both edit.
We analyze the evolution of the Apache 2.0 Open
FIG. 2: Comparison over time of the distribution of the num- Source Software project from mid-2000 thru 2004, with
ber of developers connected indirectly via co-editing code in data aggregated over three month windows. From this we
the Apache project with the distribution expected in a ran- extracted the multi-degree distribution of the system for
dom network with the same multi-degree distribution. Verti- each time-shot, which we then plug into our generating
cal lines mark the first generally available release in 2002, and functions to calculate the expected distribution of second
a significant deviation from random in 2003, when the com- neighbors found by following first a developer-to-code
munication network shrinks and the project seems to become edge then a code-to-developer edge. We then compare
more efficiently organized. this distribution to the real distribution of such devel-
3. 3
We recognize the form of this equation from Eq. 2, thus
µ λ ! ! µ λ µ γ Hµν (x) = xµ Gµν [H1µ (x), . . . , Hlµ (x)]. (5)
!
= µ + µ + µ +... We now consider starting from a randomly chosen µ-
!"# !"# $"# node, rather than a random ν-µ edge. A topology such as
ν µ ν µ ν µ ν µ
one from Fig. 3 exists a the end of each edge incident to
the µ-node. The generating function for the probability
FIG. 3: A diagramatical representation of the topological con- distribution of component sizes is,
straints placed on the generating function Hµν (x) for the dis-
Hµ (x) = xµ Gµ [H1µ (x), . . . , Hlµ (x)]. (6)
tribution of sizes of components reachable by following a ran-
domly chosen ν-µ edge. The labels attached to each edge While in theory it is possible to solve Eq. 5 for Hµν (x)
indicate type or flavor of the edge and summation notation and use that solution in Eq. 6 to solve for Hµ (x), in
indicates that we are summing over all possible flavors.
practice, even for the case of a single isolated network, as
noted in [11] the equations are typically quite difficult to
solve. Yet, Eq. 6 allows calculation of average component
oper second nearest neighbors using the Jensen-Shannon
size. A component may include multiple node flavors, but
divergence [14], a symmetric measure based on Kullback-
we can distinguish between the average number of each
Leibler divergence. The results are shown in Fig. 2 with
type. For example, the average number of ν-nodes in the
the JS-score of the real networks normalized by the JS-
component of a randomly chosen µ-node is
scores from the ensemble of random networks. Values
greater or less than unity indicate networks more or less ∂
random than average. We indicate two vertical bars sµ ν = Hµ (x)
∂xν x=1
where significant difference between the random and real
= δµν Gµ [H1µ (1), . . . , Hlµ (1)]
networks occurs. The first, in mid-2002 marks the first
l
general availability release of Apache 2.0, the second, at λ ν
the start of 2003, is a bug and security fix [15]. This lat- + Gµ [H1µ (1), . . . , Hlµ (1)]Hλµ (1)
ter point, moreover, marks when a substantial purging λ=1
of developers from the communication network occurs. l
λ ν
In any three-month window we observe that only about = δµν + Gµ (1)Hλµ (1) (7)
25 developers edit code, yet prior to 2003 the number λ=1
of developers in the email network is significantly larger. ν
Intuitively Eq. 7 is reasonable because Hγλ (1) represents
Thus this time seems to indicate when the Apache project
the average number of ν-nodes in the component found
becomes more efficiently organized, eliminating noise of
by following a µ-λ edge towards a λ-node, and the ex-
spurious emails to inactive developers.
pected number of µ-λ edges incident to an initial µ-node
We are now in position to consider component sizes. λ
λ λ
Assume we follow a randomly chosen ν-µ edge to a µ node is Gµ (1) (recall, Gµ (1) = k µ ). The product of the two
(Fig. 1(b)), and consider the distribution in sizes of the terms summed over all λ networks produces the num-
component found by following the additional outgoing ber of ν-nodes in a component connected to a randomly
edges. Let Hµν (x) denote the associated generating func- chosen µ-node, sµ ν .
tion. Fig. 3 illustrates all the types of connectivity possi- The preceding results regarding components hold in
ble for the µ-node, and summing over all these possibili- the sub-critical regime where no giant connected compo-
ties leads to the self-consistency equation for Hµν (x): nent exists. Once a giant component emerges, generating
functions allow us to calculate properties of components
µν
Hµν (x) = xµ q0···0 (3) not belonging to it. The giant component will span mul-
1 l tiple networks and calculating its size requires accounting
+ xµ δ1,Pl µν
Hγµ (x)kγ for the contribution from each network. Let Sµ be the
kλ qk1 ···kl
k1 ...kl =0
λ=1
γ=1 fraction of µ-nodes belonging to the giant component.
2 l
The probability that a randomly chosen µ-node is not
µν part of the giant component must then satisfy the fol-
+ xµ δ2,Pl q Hγµ (x)kγ + ···
λ=1 kλ k1 ···kl lowing equation,
k1 ,...,kl =0 γ=1
∞
δij denotes the Kronecker delta, used here to account for 1 − Sµ = pµ1 ,...,kl uk1 · · · ukl = Gµ (u1µ , . . . , ulµ ), (8)
k 1µ lµ
all combinations of flavors of edges connected to the µ- k1 ,...,kl =0
node leading to specified excess degree i. Reordering the
terms, Eq. 3 becomes where uνµ is the probability that an µ-ν edge is not part
of the giant component. In addition, for all µ, ν ∈ l, uνµ
∞ must satisfy,
µν
Hµν (x) = xµ qk1 ···kl H1µ (x)k1 · · · Hlµ (x)kl . (4)
k1 ...kl =0 uνµ = Gνµ (u1ν , . . . , ulν ), (9)
4. 4
derived using the same self-consistency arguments that 1
resulted in Eq. 5.
Though all the equations above hold for a system of
l ≥ 2 interacting networks, we now give a concrete ex- 0.8
Fraction of nodes
ample for l = 2, with the networks indexed as α and β.
Consider first the simplest of systems, where the inter-
0.6
nal connectivity of α and β each has a distinct Poisson
degree distribution, and the inter-network connectivity
0.7
is described by a third Poisson degree distribution, for 0.4
α α β β 0.6
instance, pαα kβ = (k α )kα e−kα /kα ! (k α )kβ e−kα /kβ ! .
k
0.5
0.4
ν
(Recall k µ denotes the average ν-degree for a node in 0.2 0.3
0.2
network µ.) Then, from Eq. 1, 0.1
01
α β 10 κ 100
Gα (xα , xβ ) = ekα (xα −1) ekα (xβ −1) (10) 00 1 2 3 4 5
β
α β
Gβ (xα , xβ ) = ekβ (xα −1) ekβ (xβ −1) . (11) kβ
Using Eq. 7, the average number of α-nodes in a compo- FIG. 4: Numerical simulations of connectivity in a system
nent reachable from a randomly chosen α-node is, of two interacting Poisson degree distributed networks, α and
α β α α β
β, with inter-network connectivity also Poisson distributed, as
kα + kα kβ − kα kβ connectivity on β increases. Each network has 100,00 nodes,
sα α =1+ α β β α
. (12) α β α
with kα = 0.4 and kα = kβ = 0.5. Shown are the fraction of
(1 − k α )(1 − k β ) − k α k β
α nodes, Sα (circles), β nodes, Sβ (squares), and all nodes,
S (triangles) in the system-wide giant component, with the
The average component size diverges for
α β β α dashed curves giving the analytic results, Eqns. (13) and (14).
( 1 − k α ) ( 1 − k β ) = k α k β ; the point at The horizontal dashed line is the asymptotic value to which
which the giant component emerges. (Ref. [8] recently Sα approaches. (Inset) Analogous results when α has Poisson
α
presented an alternate method for deriving similar per- distribution with kα = 0.5, inter-network edges follow a Pois-
β α
colation thresholds and connectivity properties, but in a son distribution with kα = kβ = 0.4, but β has a power-law
single network with multiple interacting communities.) distribution with exponent τ = 2.5 and an exponential cutoff
Note, following Eq. 7, we can show sβ α , sα β , and that we vary between 1 ≤ κ ≤ 300. The solid curve is the
sβ β also all diverge at this point, marking when a giant result for network β when viewed in isolation.
component emerges in each network and throughout
the system. Further simplifying, by assuming the two β α α β
−1
interacting networks have the same degree distribution, shown that as k β increases Sα → α W
kα
−k α e−kα −kα +1
α β β α
k α = k β = k intra and k α = k β = k inter , then the giant (dashed horizontal line in Fig. 4), where W is the Lam-
component emerges when, k inter + k intra = 1, recovering bert W function, also known as the product log.
the standard result for a single network (which, by We next consider more complex degree distribu-
definition, has k inter = 0) that emergence occurs for tions, where α is still described by a Poisson dis-
k intra = 1. tribution, but the internal connectivity of β is de-
Once the giant component emerges the uνµ which sat- scribed by a power-law distribution with an exponen-
isfy Eq. 9 are uαα = uαβ = 1 − Sα and uββ = uβα = tial cutoff. While power-law degree distributions have
1 − Sβ , while Sα and Sβ , respectively, the number of α- attracted considerable attention as a model for node
nodes and β-nodes in the giant component of the system, degree distributions in many types of networks [16],
satisfy a power-law with an exponential cutoff may be a
better model for real-world networks [17]. Here
α β α α
Sα = 1 − e−(kα Sα +kα Sβ ) (13) pβα kβ
k = (k β )kα e−kβ /kα ! (kβ )τ e−kβ /κ /Liτ (e−1/κ )
α β
Sβ = 1 − e−(kβ Sα +kβ Sβ ) . (14) where Lin (x) is the nth polylogarithm of x and serves
as a normalizing factor for the distribution. Thus, we
To observe the change in connectivity of one network can write our basic generating function for network β,
precipitated by an increase in connectivity of a second
network attached to the first, we simulated a system of α Liτ (xβ e−1/κ )
Gβ (xα , xβ ) = ekβ (xα −1) . (15)
α β α
two interacting networks and fixed k α , k α , and k β while Liτ (e−1/κ )
β β
varying k β from 0 to 5 (Fig. 4). As k β increases the The generating function for α is still given by Eq. 10.
β-network becomes a single connected component (the We simulate the impact on the connectivity of the α-
traditional behavior for a single network) and Sβ → 1. network as the exponential cutoff and hence the average
However, the connectivity of α remains limited. It can be degree of network β increases, inset of Fig. 4. Again
5. 5
1 tooth connectivity between individuals from raw data of
Bluetooth sightings by 41 attendees at the 25th IEEEE
International Conference on Computer Communications
Fraction of nodes (S)
0.8
(INFOCOM) [19]. We initially partition the raw data
into discrete 20 minute windows and consider that a
0.6 communication edge exists between any two devices so
α
long as they are within contact for at least 120 seconds.
0.4 Each network has approximately a Poisson degree dis-
tribution of connectivity. We choose two arbitrary 20
minute snapshots as proxies for two distinct networks,
0.2
β
α and β, representing, for instance, two separate rooms
at the conference. We calculate how adding long-range
0 0.2 0.4 0.6 0.8 1 connections between α and β (for instance via text mes-
β α sages or email) enhances overall connectivity in the sys-
kα and kβ ] tem. In other words, we calculate how many long-range
FIG. 5: Inset are two sample networks of Bluetooth connec- connections would be needed between two isolated local
tivity. The main figure shows the increase in participation Bluetooth networks to create the desired large scale con-
in the giant component as connectivity between α and β in- nectivity, potentially allowing many users to share infor-
β α
creases, starting from kα = kβ = 0.1. Points are obtained by mation. Figure 5 shows the size of the giant component
taking the empirical data and simulating inter-network edges obtained via numerical simulations using the real data
β α
with the appropriate kα and kβ , averaged over 100 realiza- (points) and the analytic calculations obtained via gen-
tions. The solid line is from analytic calculations. erating functions (dashed line). The analytic calculations
slightly overestimate connectivity, yet there is remarkable
agreement with empirical data even though the actually
the dashed curves are the analytic results obtained by networks are quite small.
solving Eqns. 8 and 9. The solid red line is the behavior In summary, we have introduced a formalism for cal-
for the β network considered in isolation, showing that culating connectivity properties in a system of l interact-
even the percolation threshold for β is lowered through ing networks. We demonstrate the extreme lowering of
connectivity with network α. the percolation threshold possible once interactions with
Finally we consider an application of connectivity to other networks are taken into account. This framework
communications networks, building on the increasing in- for calculating connectivity and statistics of interacting
terest in using Bluetooth connectivity between individ- networks should be broadly applicable, and we show po-
uals to transmit data [18]. For instance, rather than tential applications to software and communications sys-
downloading a webpage (such as the CNN homepage) tems.
by connecting to the Internet, a copy could be obtained Acknowledgements We thank Christian Bird for
from a close-by individual already in possession of this providing data on the Apache project and for useful con-
data. We construct prototypical networks of local Blue- versations.
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