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This report deals with security in wireless sensor networks (WSNs), especially in network layer. Multiple secure routing protocols have been proposed in the literature. However, they often use the cryptography to secure routing functionalities. The cryptography alone is not enough to defend against multiple attacks due to the node compromise. Therefore, we need more algorithmic solutions. In this report, we focus on the behavior of routing protocols to determine which properties make them more resilient to attacks. Our aim is to find some answers to the following questions. Are there any existing protocols, not designed initially for security, but which already contain some inherently resilient properties against attacks under which some portion of the network nodes is compromised? If yes, which specific behaviors are making these protocols more resilient? We propose in this report an overview of security strategies for WSNs in general, including existing attacks and defensive measures. In this report we focus at the network layer in particular, and an analysis of the behavior of four particular routing protocols is provided to determine their inherent resiliency to insider attacks. The protocols considered are: Dynamic Source Routing (DSR), Gradient-Based Routing (GBR), Greedy Forwarding (GF) and Random Walk Routing (RWR).

Several approaches can be employed to counter pervasive monitoring at large scale on the Internet. One category of approaches aims to harden the current Internet architecture and to increase the security of high profile targets (data centers, exchange points etc.). Another category of approaches aims instead for target dispersal, i.e. disabling systematic mass surveillance via the elimination of existing vantage points, thus forcing surveillance efforts to be more specific and personalized. This paper argues how networking approaches that do not rely on central entities -- but rather on spontaneous interaction, as locally as possible, between autonomous peer entities -- can help realize target dispersal and thus counter pervasive monitoring.

Several approaches can be employed to counter pervasive monitoring at large scale on the Internet. One category of approaches aims to harden the current Internet architecture and to increase the security of high profile targets (data centers, exchange points etc.). Another category of approaches aims instead for target dispersal, i.e. disabling systematic mass surveillance via the elimination of existing vantage points, thus forcing surveillance efforts to be more specific and personalized. This paper argues how networking approaches that do not rely on central entities -- but rather on spontaneous interaction, as locally as possible, between autonomous peer entities -- can help realize target dispersal and thus counter pervasive monitoring.

Several approaches can be employed to counter pervasive monitoring at large scale on the Internet. One category of approaches aims to harden the current Internet architecture and to increase the security of high profile targets (data centers, exchange points etc.). Another category of approaches aims instead for target dispersal, i.e. disabling systematic mass surveillance via the elimination of existing vantage points, thus forcing surveillance efforts to be more specific and personalized. This paper argues how networking approaches that do not rely on central entities -- but rather on spontaneous interaction, as locally as possible, between autonomous peer entities -- can help realize target dispersal and thus counter pervasive monitoring.

This is lecture by ANDREW rOSS, uploaded for a course ISE241 'Wireless Networking' held for National College, South Bend, Indiana; 09 July 2014. Created by Gerard Arthus and released into the Public Domain under the Creative Commons License Non-Attribute. http://OpenEducation.org Go to the above site to find out more about the digitization of this item and the on-going attempt to help make 'Knowledge' and 'Information' available to everyone, anywhere, at any time, for no cost. There are many forces at work which are attempting to turn 'Public Domain' information into a commodity which some can milk for a profit. This parasitic use of information which should be freely available for all to access is an Intellectual Crime and should not be tolerated. Hi-resolution images included.

In recent times, wireless access technology is becoming increasingly commonplace due to the ease of operation and installation of untethered wireless media. The design of wireless networking is challenging due to the highly dynamic environmental condition that makes parameter optimization a complex task. Due to the dynamic, and often unknown, operating conditions, modern wireless networking standards increasingly rely on machine learning and artificial intelligence algorithms. Genetic algorithms (GAs) provide a well-established framework for implementing artificial intelligence tasks such as classification, learning, and optimization. GAs are well-known for their remarkable generality and versatility, and have been applied in a wide variety of settings in wireless networks. In this paper, we provide a comprehensive survey of the applications of GAs in wireless networks. We provide both an exposition of common GA models and configuration and provide a broad ranging survey of GA techniques in wireless networks. We also point out open research issues and define potential future work. While various surveys on GAs exist in literature, our paper is the first paper, to the best of our knowledge, which focuses on their application in wireless networks.

In recent times, wireless access technology is becoming increasingly commonplace due to the ease of operation and installation of untethered wireless media. The design of wireless networking is challenging due to the highly dynamic environmental condition that makes parameter optimization a complex task. Due to the dynamic, and often unknown, operating conditions, modern wireless networking standards increasingly rely on machine learning and artificial intelligence algorithms. Genetic algorithms (GAs) provide a well-established framework for implementing artificial intelligence tasks such as classification, learning, and optimization. GAs are well-known for their remarkable generality and versatility, and have been applied in a wide variety of settings in wireless networks. In this paper, we provide a comprehensive survey of the applications of GAs in wireless networks. We provide both an exposition of common GA models and configuration and provide a broad ranging survey of GA techniques in wireless networks. We also point out open research issues and define potential future work. While various surveys on GAs exist in literature, our paper is the first paper, to the best of our knowledge, which focuses on their application in wireless networks.

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Any practical WSN deployment must contend with a number of difficulties in its radio frequency (RF) environment. Multi-path reflections can distort signals, limit data rates, and cause signal fades that prevent nodes from having clear access to channels, especially in a closed environment such as a spacecraft. Other RF signal sources, such as wireless internet, voice, and data systems may contend with the sensor nodes for bandwidth. Finally, RF noise from electrical systems and periodic scattering from moving objects such as crew members will all combine to give an incredibly unpredictable, time-varying communication environment.

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Any practical WSN deployment must contend with a number of difficulties in its radio frequency (RF) environment. Multi-path reflections can distort signals, limit data rates, and cause signal fades that prevent nodes from having clear access to channels, especially in a closed environment such as a spacecraft. Other RF signal sources, such as wireless internet, voice, and data systems may contend with the sensor nodes for bandwidth. Finally, RF noise from electrical systems and periodic scattering from moving objects such as crew members will all combine to give an incredibly unpredictable, time-varying communication environment.

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Any practical WSN deployment must contend with a number of difficulties in its radio frequency (RF) environment. Multi-path reflections can distort signals, limit data rates, and cause signal fades that prevent nodes from having clear access to channels, especially in a closed environment such as a spacecraft. Other RF signal sources, such as wireless internet, voice, and data systems may contend with the sensor nodes for bandwidth. Finally, RF noise from electrical systems and periodic scattering from moving objects such as crew members will all combine to give an incredibly unpredictable, time-varying communication environment.

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Any practical WSN deployment must contend with a number of difficulties in its radio frequency (RF) environment. Multi-path reflections can distort signals, limit data rates, and cause signal fades that prevent nodes from having clear access to channels, especially in a closed environment such as a spacecraft. Other RF signal sources, such as wireless internet, voice, and data systems may contend with the sensor nodes for bandwidth. Finally, RF noise from electrical systems and periodic scattering from moving objects such as crew members will all combine to give an incredibly unpredictable, time-varying communication environment.

The purpose of this research is to investigate the use of commercial, off-the-shelf wireless networking technology in planetary exploration applications involving rovers and sensor webs. The three objectives of this research project are to: 1) simulate the radio frequency environment of proposed landing sites on Mars using actual topographic data, 2) analyze the performance of current wireless networking standards in the simulated radio frequency environment, and 3) propose modifications to the standards for more efficient utilization. In this annual report, we present our results for the second year of research. During this year, the effort has focussed on the second objective of analyzing the performance of the IEEE 802.11a and IEEE 802.1lb wireless networking standards in the simulated radio frequency environment of Mars. The approach builds upon our previous results which deterministically modelled the RF environment at selected sites on Mars using high-resolution topographical data. These results provide critical information regarding antenna coverage patterns, maximum link distances, effects of surface clutter, and multipath effects. Using these previous results, the physical layer of these wireless networking standards has now been simulated and analyzed in the Martian environment. We are looking to extending these results to the and medium access layer next. Our results give us critical information regarding the performance (data rates, packet error rates, link distances, etc.) of IEEE 802.1 la/b wireless networks. This information enables a critical examination of how these wireless networks may be utilized in future Mars missions and how they may be possibly modified for more optimal usage.

Nathaniel Lindley (@thanlindley) joins Jim Collison  https://twitter.com/jcollison and Mike Wieger from http://2980network.com/ for show #247 of Home Gadget Geeks brought to you by the Average Guy Network, part of http://thegeeksnetwork.com community. Please leave a REVIEW (iPhone or iPad) at https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewContentsUserReviews?id=457300409&type=Podcast&ls=1&mt=1 Support the Average Guy Tech Scholarship Fund: http://theAverageGuy.tv/amazon or if you are in Canada, use http://theAverageGuy.tv/amazonca WANT TO SUBSCRIBE? http://theAverageGuy.tv/subscribe Join us for the show live each Thursday at 8pmC/9E/1UTC at http://theAverageGuy.tv/live or call in your questions or comments to be played on the show at (402) 478-8450 Full show notes and video at http://theAverageGuy.tv/hgg247

Nathaniel Lindley (@thanlindley) joins Jim Collison  https://twitter.com/jcollison and Mike Wieger from http://2980network.com/ for show #247 of Home Gadget Geeks brought to you by the Average Guy Network, part of http://thegeeksnetwork.com community. Please leave a REVIEW (iPhone or iPad) at https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewContentsUserReviews?id=457300409&type=Podcast&ls=1&mt=1 Support the Average Guy Tech Scholarship Fund: http://theAverageGuy.tv/amazon or if you are in Canada, use http://theAverageGuy.tv/amazonca WANT TO SUBSCRIBE? http://theAverageGuy.tv/subscribe Join us for the show live each Thursday at 8pmC/9E/1UTC at http://theAverageGuy.tv/live or call in your questions or comments to be played on the show at (402) 478-8450 Full show notes and video at http://theAverageGuy.tv/hgg247

Nathaniel Lindley (@thanlindley) joins Jim Collison  https://twitter.com/jcollison and Mike Wieger from http://2980network.com/ for show #247 of Home Gadget Geeks brought to you by the Average Guy Network, part of http://thegeeksnetwork.com community. Please leave a REVIEW (iPhone or iPad) at https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewContentsUserReviews?id=457300409&type=Podcast&ls=1&mt=1 Support the Average Guy Tech Scholarship Fund: http://theAverageGuy.tv/amazon or if you are in Canada, use http://theAverageGuy.tv/amazonca WANT TO SUBSCRIBE? http://theAverageGuy.tv/subscribe Join us for the show live each Thursday at 8pmC/9E/1UTC at http://theAverageGuy.tv/live or call in your questions or comments to be played on the show at (402) 478-8450 Full show notes and video at http://theAverageGuy.tv/hgg247

Nathaniel Lindley (@thanlindley) joins Jim Collison  https://twitter.com/jcollison and Mike Wieger from http://2980network.com/ for show #247 of Home Gadget Geeks brought to you by the Average Guy Network, part of http://thegeeksnetwork.com community. Please leave a REVIEW (iPhone or iPad) at https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewContentsUserReviews?id=457300409&type=Podcast&ls=1&mt=1 Support the Average Guy Tech Scholarship Fund: http://theAverageGuy.tv/amazon or if you are in Canada, use http://theAverageGuy.tv/amazonca WANT TO SUBSCRIBE? http://theAverageGuy.tv/subscribe Join us for the show live each Thursday at 8pmC/9E/1UTC at http://theAverageGuy.tv/live or call in your questions or comments to be played on the show at (402) 478-8450 Full show notes and video at http://theAverageGuy.tv/hgg247

Networking For Beginners The Complete Guide To Computer Network Basics Wireless Technology And Network Security

This paper is concerned with the scaling of the number of hops in a large scale wireless ad-hoc network (WANET), a quantity we call network latency. A large network latency affects all aspects of data communication in a WANET, including an increase in delay, packet loss, required processing power and memory. We consider network management and data routing challenges in WANETs with scalable network latency. On the physical side, reducing network latency imposes a significantly higher power and bandwidth demand on nodes, as is reflected in a set of new bounds. On the protocol front, designing distributed routing protocols that can guarantee the delivery of data packets within scalable number of hops is a challenging task. To solve this, we introduce multi-resolution randomized hierarchy (MRRH), a novel power and bandwidth efficient WANET protocol with scalable network latency. MRRH uses a randomized algorithm for building and maintaining a random hierarchical network topology, which together with the proposed routing algorithm can guarantee efficient delivery of data packets in the wireless network. For a network of size $N$, MRRH can provide an average latency of only $O(\log^{3} N)$. The power and bandwidth consumption of MRRH are shown to be \emph{nearly} optimal for the latency it provides. Therefore, MRRH, is a provably efficient candidate for truly large scale wireless ad-hoc networking.

This paper is concerned with the scaling of the number of hops in a large scale wireless ad-hoc network (WANET), a quantity we call network latency. A large network latency affects all aspects of data communication in a WANET, including an increase in delay, packet loss, required processing power and memory. We consider network management and data routing challenges in WANETs with scalable network latency. On the physical side, reducing network latency imposes a significantly higher power and bandwidth demand on nodes, as is reflected in a set of new bounds. On the protocol front, designing distributed routing protocols that can guarantee the delivery of data packets within scalable number of hops is a challenging task. To solve this, we introduce multi-resolution randomized hierarchy (MRRH), a novel power and bandwidth efficient WANET protocol with scalable network latency. MRRH uses a randomized algorithm for building and maintaining a random hierarchical network topology, which together with the proposed routing algorithm can guarantee efficient delivery of data packets in the wireless network. For a network of size $N$, MRRH can provide an average latency of only $O(\log^{3} N)$. The power and bandwidth consumption of MRRH are shown to be \emph{nearly} optimal for the latency it provides. Therefore, MRRH, is a provably efficient candidate for truly large scale wireless ad-hoc networking.

A revolution has occurred in wireless communications over the last decade. Advances in processing power have enabled widespread deployment of radio networks as well as portable devices that can make use of such networks. Wireless networks have become more convenient and affordable and have spread to even fairly stationary applications such as home networking and community networking. Ad hoc networks can extend the range of such wireless networks: in an ad hoc network nodes cooperate to dynamically establish routing among themselves a packet sent by one node may be forwarded in turn by a sequence of other nodes allowing the packet to reach a destination beyond the sender wireless transmission range. This thesis discusses improvements to service in ad hoc network routing. Since different networks require different types of service, I propose several mechanisms to improve service in various network conditions. One example of service is Quality-of-Service (QoS ) since certain networks may desire some flows to have priority over other flows. Many of the mechanisms presented here make no distinction between lower and higher priority traffic and in may evaluation I only examine performance metrics aggregated over all flows rather than the performance of a few select flows. Another area encompassed by service is security. In particular when an attacker is present in the network a protocol that provides security against such an attacker should provide better service than one that does not. For example a secure protocol should deliver more packets incur less overhead or conserve overall network power usage better than in insecure protocol when the network is under attack. As a network experiences attack a secure network routing protocol may continue to provide some level of service whereas a traditional network routing protocol may fail completely.

Abstract We consider ad hoc wireless networks that use directional antennas and have limited energy resources. To explore quantitatively the advantage offered by the use of directional antennas over the case of omnidirectional antennas, we consider the case of connection-oriented multicast traffic. Building upon our prior work on multicasting algorithms, we introduce two protocols that exploit the use of directional antennas and evaluate their performance. We observe significant improvement with respect to the omnidirectional case, in terms of both energy efficiency and network lifetime. Additionally, we show that further substantial increase in the network's lifetime can be achieved by incorporating a simple measure of a node's residual energy into the node's cost function.

Abstract We consider ad hoc wireless networks that use directional antennas and have limited energy resources. To explore quantitatively the advantage offered by the use of directional antennas over the case of omnidirectional antennas, we consider the case of connection-oriented multicast traffic. Building upon our prior work on multicasting algorithms, we introduce two protocols that exploit the use of directional antennas and evaluate their performance. We observe significant improvement with respect to the omnidirectional case, in terms of both energy efficiency and network lifetime. Additionally, we show that further substantial increase in the network's lifetime can be achieved by incorporating a simple measure of a node's residual energy into the node's cost function.

Abstract We consider ad hoc wireless networks that use directional antennas and have limited energy resources. To explore quantitatively the advantage offered by the use of directional antennas over the case of omnidirectional antennas, we consider the case of connection-oriented multicast traffic. Building upon our prior work on multicasting algorithms, we introduce two protocols that exploit the use of directional antennas and evaluate their performance. We observe significant improvement with respect to the omnidirectional case, in terms of both energy efficiency and network lifetime. Additionally, we show that further substantial increase in the network's lifetime can be achieved by incorporating a simple measure of a node's residual energy into the node's cost function.

This paper reports on our testing the Doodle Labs DL435-30 and Xagyl Communications XC420M wireless networking miniPCI cards. They behave like IEEE 802.11 wireless networking cards but operate in the 420 MHz band. We have successfully tested these cards over 10 miles at about three Mbit/s data rate at a 5 MHz bandwidth in the 420 to 426 MHz ATV sub-band. Our test applications were a Webcam video streaming program and a file download server program that ran on inexpensive netbook computers.

This paper reports on our testing the Doodle Labs DL435-30 and Xagyl Communications XC420M wireless networking miniPCI cards. They behave like IEEE 802.11 wireless networking cards but operate in the 420 MHz band. We have successfully tested these cards over 10 miles at about three Mbit/s data rate at a 5 MHz bandwidth in the 420 to 426 MHz ATV sub-band. Our test applications were a Webcam video streaming program and a file download server program that ran on inexpensive netbook computers.

This thesis investigates the detection, classification, frame synchronization, and demodulation of wireless networking waveforms by a digital receiver. The approach is to develop detection thresholds for wireless networking signals based upon the probability density functions of the signal present or signal absent scenarios. A Neyman-Pearson test is applied to determine decision thresholds and the associated probabilities of detection. With a chosen threshold, MATLAB simulations are run utilizing models developed to generate and receive IEEE 802.11a, IEEE 802.16, and IEEE 802.11b signals in multipath channels characterized by Rayleigh fading. Algorithms are developed for frame synchronization for each of the three waveforms. The probability of signal detection, successful frame synchronization, and the bit error rates of the received packet header and data are calculated. The results show that, even in Rayleigh fading environments at low signal to noise levels, these three waveforms can be distinguished in a digital receiver. Further, the results show that significant signal information can be gathered on these wireless networking waveforms, even when the entire signal cannot be demodulated due to low signal to noise ratios.

This article is from Sensors (Basel, Switzerland) , volume 11 . Abstract This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

This article is from Sensors (Basel, Switzerland) , volume 11 . Abstract This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

This article is from Sensors (Basel, Switzerland) , volume 11 . Abstract This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

This article is from Sensors (Basel, Switzerland) , volume 11 . Abstract This work presents a localization scheme for use in wireless sensor networks (WSNs) that is based on a proposed connectivity-based RF localization strategy called the distributed Fermat-point location estimation algorithm (DFPLE). DFPLE applies triangle area of location estimation formed by intersections of three neighboring beacon nodes. The Fermat point is determined as the shortest path from three vertices of the triangle. The area of estimated location then refined using Fermat point to achieve minimum error in estimating sensor nodes location. DFPLE solves problems of large errors and poor performance encountered by localization schemes that are based on a bounding box algorithm. Performance analysis of a 200-node development environment reveals that, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error remains below 1% as the node density increases. Second, when the number of beacon nodes is less than 60, normal nodes lack sufficient beacon nodes to enable their locations to be estimated. However, the mean error changes slightly as the number of beacon nodes increases above 60. Simulation results revealed that the proposed algorithm for estimating sensor positions is more accurate than existing algorithms, and improves upon conventional bounding box strategies.

Motivated by the need of providing on-demand local computing resources over a wireless computing and communication infrastructure, we will begin to face over the next decade very large sensor-generated datasets on the order of zettabytes or even yottabytes. While centralized control and applications may still be needed, the bulk of the processing and storage must be distributed near the sensors. Motivated by results in compressive sampling, we obtain new results in rank deficient network coding, which is capable of addressing some of these challenges.

Motivated by the need of providing on-demand local computing resources over a wireless computing and communication infrastructure, we will begin to face over the next decade very large sensor-generated datasets on the order of zettabytes or even yottabytes. While centralized control and applications may still be needed, the bulk of the processing and storage must be distributed near the sensors. Motivated by results in compressive sampling, we obtain new results in rank deficient network coding, which is capable of addressing some of these challenges.

In Part I of this two-part paper [1], we proposed a new game, called Chinese restaurant game, to analyze the social learning problem with negative network externality. The best responses of agents in the Chinese restaurant game with imperfect signals are constructed through a recursive method, and the influence of both learning and network externality on the utilities of agents is studied. In Part II of this two-part paper, we illustrate three applications of Chinese restaurant game in wireless networking, cloud computing, and online social networking. For each application, we formulate the corresponding problem as a Chinese restaurant game and analyze how agents learn and make strategic decisions in the problem. The proposed method is compared with four common-sense methods in terms of agents' utilities and the overall system performance through simulations. We find that the proposed Chinese restaurant game theoretic approach indeed helps agents make better decisions and improves the overall system performance. Furthermore, agents with different decision orders have different advantages in terms of their utilities, which also verifies the conclusions drawn in Part I of this two-part paper.

In Part I of this two-part paper [1], we proposed a new game, called Chinese restaurant game, to analyze the social learning problem with negative network externality. The best responses of agents in the Chinese restaurant game with imperfect signals are constructed through a recursive method, and the influence of both learning and network externality on the utilities of agents is studied. In Part II of this two-part paper, we illustrate three applications of Chinese restaurant game in wireless networking, cloud computing, and online social networking. For each application, we formulate the corresponding problem as a Chinese restaurant game and analyze how agents learn and make strategic decisions in the problem. The proposed method is compared with four common-sense methods in terms of agents' utilities and the overall system performance through simulations. We find that the proposed Chinese restaurant game theoretic approach indeed helps agents make better decisions and improves the overall system performance. Furthermore, agents with different decision orders have different advantages in terms of their utilities, which also verifies the conclusions drawn in Part I of this two-part paper.

In Part I of this two-part paper [1], we proposed a new game, called Chinese restaurant game, to analyze the social learning problem with negative network externality. The best responses of agents in the Chinese restaurant game with imperfect signals are constructed through a recursive method, and the influence of both learning and network externality on the utilities of agents is studied. In Part II of this two-part paper, we illustrate three applications of Chinese restaurant game in wireless networking, cloud computing, and online social networking. For each application, we formulate the corresponding problem as a Chinese restaurant game and analyze how agents learn and make strategic decisions in the problem. The proposed method is compared with four common-sense methods in terms of agents' utilities and the overall system performance through simulations. We find that the proposed Chinese restaurant game theoretic approach indeed helps agents make better decisions and improves the overall system performance. Furthermore, agents with different decision orders have different advantages in terms of their utilities, which also verifies the conclusions drawn in Part I of this two-part paper.

Traditional networking solutions are unable to meet modern computing needs due to the expanding popularity of the internet, which requires increased agility and flexibility. To meet these objectives, software-defined networking (SDN) arises. A controller is a major element that will determine if SDN succeeds or fails. Various current SDN controllers in many sectors must be evaluated and compared. The performance of two well-known SDN controllers, POX and Ryu, is evaluated in this research. We used the Mininet-WiFi emulator to implement our work and the distributed internet traffic generator (D-ITG) to assess the aforementioned controllers using delay, jitter, packet loss, and throughput metrics. What is new in our research is the study of network performance in two different types of transmission media: wired and wireless. The speed of the wired medium was chosen to be fast ethernet, which was not previously studied. In addition, the size of the packet was varied among 128, 256, 512, and 1,024 bytes. The comparison was performed on three topologies (single, linear, and tree). The experimental results showed that Ryu offers significantly lower latency, jitter, and packet loss than POX in most scenarios. Also, the Ryu controller has higher throughput than POX, especially on wireless networks.

15 Wireless Networking

In this paper, we introduce a new networking architecture called Group Centric Networking (GCN) that is designed to support the large number of devices expected with the emergence of the Internet of Things. GCN is designed to enable these devices to operate collaboratively in a highly efficient and resilient fashion, while not sacrificing the users? ability to communicate with one another. We do a full protocol implementation of GCN in NS3, and verify GCN in emulation and on real hardware communicating over an RF channel. We show that GCN utilizes up to an order of magnitude fewer network resources than traditional wireless routing schemes, while providing superior connectivity and reliability.

In this paper, we introduce a new networking architecture called Group Centric Networking (GCN) that is designed to support the large number of devices expected with the emergence of the Internet of Things. GCN is designed to enable these devices to operate collaboratively in a highly efficient and resilient fashion, while not sacrificing the users? ability to communicate with one another. We do a full protocol implementation of GCN in NS3, and verify GCN in emulation and on real hardware communicating over an RF channel. We show that GCN utilizes up to an order of magnitude fewer network resources than traditional wireless routing schemes, while providing superior connectivity and reliability.

In this paper, we introduce a new networking architecture called Group Centric Networking (GCN) that is designed to support the large number of devices expected with the emergence of the Internet of Things. GCN is designed to enable these devices to operate collaboratively in a highly efficient and resilient fashion, while not sacrificing the users? ability to communicate with one another. We do a full protocol implementation of GCN in NS3, and verify GCN in emulation and on real hardware communicating over an RF channel. We show that GCN utilizes up to an order of magnitude fewer network resources than traditional wireless routing schemes, while providing superior connectivity and reliability.

Includes index

Includes index

In order to quantify any node's capacity to support optimal information flow within a distributed command and control network, a novel node capability value calculation is developed from first principles. The expression for the node capability value is developed using three fundamental building blocks: data throughput, bandwidth efficiency, and the link margin. The data throughput depends on the average packet arrival rate, the probability of not dropping a packet and the probability of correct receiving a packet at the queue. The bandwidth efficiency depends on the node data rate and the transmission bandwidth, while the link margin is a function of the received and required energy per bit to noise power density. The generalized connectivity integrates the computed node capability value by considering all the distributed network connections scaled by their route length and estimating the characteristic tempo, which is the maximum information exchange rate. The generalized connectivity results reflect the amount and quality of detectable information that the nodes can process and transmit about the network. The results also show how the power and bandwidth efficiency of any specific node compares the power and bandwidth efficiency of all the other nodes. A four-node dynamic scenario is simulated and used to numerically evaluate the expression for the node capability value. Command and control tradeoff issues facing battlespace managers and decision makers are examined by including the networks characteristic tempo into a single observe, orient, decide and act (OODA loop). Also, included in the OODA loop, are action tempos and the command and control speed. Consideration of the influence of three classic Sheridan levels of automation on decision making are used to model the operational impacts via three action tempo tiers: high, medium, and low-action. Input command and control information rates produced the strongest observed influences on aggregate network simulation outputs.

In order to quantify any node's capacity to support optimal information flow within a distributed command and control network, a novel node capability value calculation is developed from first principles. The expression for the node capability value is developed using three fundamental building blocks: data throughput, bandwidth efficiency, and the link margin. The data throughput depends on the average packet arrival rate, the probability of not dropping a packet and the probability of correct receiving a packet at the queue. The bandwidth efficiency depends on the node data rate and the transmission bandwidth, while the link margin is a function of the received and required energy per bit to noise power density. The generalized connectivity integrates the computed node capability value by considering all the distributed network connections scaled by their route length and estimating the characteristic tempo, which is the maximum information exchange rate. The generalized connectivity results reflect the amount and quality of detectable information that the nodes can process and transmit about the network. The results also show how the power and bandwidth efficiency of any specific node compares the power and bandwidth efficiency of all the other nodes. A four-node dynamic scenario is simulated and used to numerically evaluate the expression for the node capability value. Command and control tradeoff issues facing battlespace managers and decision makers are examined by including the networks characteristic tempo into a single observe, orient, decide and act (OODA loop). Also, included in the OODA loop, are action tempos and the command and control speed. Consideration of the influence of three classic Sheridan levels of automation on decision making are used to model the operational impacts via three action tempo tiers: high, medium, and low-action. Input command and control information rates produced the strongest observed influences on aggregate network simulation outputs.

This is a recording of a workshop in British Columbia Canada of how to set up a community wireless network. It is ten parts in QT and is about 2 hours.

Information centric networking (ICN) proposes to redesign the Internet by replacing its host-centric design with information-centric design. Communication among entities is established at the naming level, with the receiver side (referred to as the Consumer) acting as the driving force behind content delivery, by interacting with the network through Interest message transmissions. One of the proposed advantages for ICN is its support for mobility, by de-coupling applications from transport semantics. However, so far, little research has been conducted to understand the interaction between ICN and mobility of consuming and producing applications, in protocols purely based on information-centric principles, particularly in the case of NDN. In this paper, we present our findings on the mobility-based performance of Named Data Networking (NDN) in wireless access networks. Through simulations, we show that the current NDN architecture is not efficient in handling mobility and architectural enhancements needs to be done to fully support mobility of Consumers and Producers.

Information centric networking (ICN) proposes to redesign the Internet by replacing its host-centric design with information-centric design. Communication among entities is established at the naming level, with the receiver side (referred to as the Consumer) acting as the driving force behind content delivery, by interacting with the network through Interest message transmissions. One of the proposed advantages for ICN is its support for mobility, by de-coupling applications from transport semantics. However, so far, little research has been conducted to understand the interaction between ICN and mobility of consuming and producing applications, in protocols purely based on information-centric principles, particularly in the case of NDN. In this paper, we present our findings on the mobility-based performance of Named Data Networking (NDN) in wireless access networks. Through simulations, we show that the current NDN architecture is not efficient in handling mobility and architectural enhancements needs to be done to fully support mobility of Consumers and Producers.

Information centric networking (ICN) proposes to redesign the Internet by replacing its host-centric design with information-centric design. Communication among entities is established at the naming level, with the receiver side (referred to as the Consumer) acting as the driving force behind content delivery, by interacting with the network through Interest message transmissions. One of the proposed advantages for ICN is its support for mobility, by de-coupling applications from transport semantics. However, so far, little research has been conducted to understand the interaction between ICN and mobility of consuming and producing applications, in protocols purely based on information-centric principles, particularly in the case of NDN. In this paper, we present our findings on the mobility-based performance of Named Data Networking (NDN) in wireless access networks. Through simulations, we show that the current NDN architecture is not efficient in handling mobility and architectural enhancements needs to be done to fully support mobility of Consumers and Producers.