As the earth’s temperature increases, efficient heating, cooling, and lean building designs are critical to ensure environmental longevity for future generations. Reducing the usage of chemically involved mechanisms such as cooling units with hydrofluorocarbon refrigerants and improving natural absorption or reflection of sunlight is vital for sustainability and mandatory in any intelligent city design. This paper focuses on active temperature control utilizing novel intelligent window system designs that permit interior and external fixation. In addition to providing new smart home capabilities, the proposed system aims to reduce energy consumption, further providing benefits, including consumer cost savings and a reduction of fossil fuel usage. The paper provides the experimental test bed design and prototype of the intelligent system termed TRASS (Temperature Regulating Autonomous Solar Shade). TRASS is a self-sufficient product with communication capabilities and autonomous use. As the experimental results show, the autonomous control of the prototype allows accurate temperature regulation by managing the amount of sunlight. The model incorporates rechargeable batteries and alternative energy, allowing older generational homes and buildings to employ the system without needing external power. The system continuously maintains necessary environmental conditions indoors without user interaction. However, TRASS permits manual adjustments to ensure proper management at desired conditions.

Infrastructure limited zones like military environments differ from commercial and residential demands due to the sensitive applications and dynamic environments. Combative environments suffer from many challenges, including limited to no infrastructure access, rapid situational escalations, and possible adversarial attacks, both technological and physical. Regardless of the unstable situations, communication is a vital component necessary in any application. A lack of communication accessibility and private transmission can quickly become the adversary's advantages. In previous research, the authors designed a cooperative communication platform executing a different architecture than traditional models, such as the TCP/IP model [1] - thus, allowing custom communication implementations for additional cybersecurity advantages and more rapid deployment. This paper provides the passive link detection necessary for self-organizing mechanisms. The results depict useable links developed through passive discoveries and provide off-the-shelf hardware and software limitations and considerations.

Idle spectrum use and dynamic spectrum access are popular topics in academia and industry. Heterogenous networking is more popular than ever, with mobile offloading being the biggest motivator. Current communication implements several new protocols, such as 802.11u WiFi Certified Passpoint, multipath transmission control protocol (MPTCP), 5G Core Access Traffic Steering, Switching, and Splitting (ATSSS), and CoopNet. This paper introduces the primary methods and models included in the first two stages (Discovery and Decision) of the CoopNet multipath architecture defined in [1]. The discovery and decision stages are the fundamental stages necessary as proof of concept for experimental implementation. The results show that implementing just the first two stages improves the local communication throughput, delay, and utility, enabling new features, including introducing infrastructure as a service.

In Vehicular Ad-hoc Networks (VANETs), fast and reliable dissemination of safety messages is a key step toward improving the overall road safety. In a highly dynamic VANET environment, safety message dissemination in a multi-hop manner is a challenging and complex problem that has gained significant attention recently. Many protocols and schemes have been proposed to efficiently share safety messages among vehicles. However, most existing techniques do not perform well under real-world traffic conditions, or perform adequately only under very limited scenarios and traffic conditions. This research proposes a highly efficient and reliable multi-hop broadcasting protocol, Intelligent Forwarding Protocol (IFP), that exploits handshake-less communication, ACK Decoupling, and an efficient collision resolution mechanism. In this research, IFP has been extensively studied and evaluated to establish its robustness and superiority over existing schemes. A key contribution of this paper is to present an in-depth analysis and optimization of IFP using theoretical modeling, thorough simulations, and extensive real-world experimentation. With IFP, the message propagation delay is significantly reduced and packet delivery ratio is drastically improved.

Progress in modern communication technology is continuous and accelerated. Demand for higher bandwidth, lower latency, more reliable connectivity is ever-growing. With it, supporting a higher number of devices connected, deep network awareness, as well as a more accessible network is essential. The introduction of cloud/fog computing, cooperative communication architectures, and the Internet of Things (IoT) show that the capabilities of traditional network architectures and protocols are becoming obsolete. Therefore, new technologies, such as Software-Defined Networking, Network Function Virtualization, Content-Centric Networking, and Cooperative Networking are being introduced to sustain future demands. One primary limitation is the use of the conventional TCP/IP five-layer network model. More specifically, the redundant header overhead exiting in convention communication is an inefficient use of bandwidth increasing the overall communication latency. This paper proposes a new universal packetization standard that can be used to reduce the header overhead, and to prepare for next-gen communication, such as Cooperative Multipath Communication. Cooperative Multipath Communication provides an alternative communication standard to the TCP/IP five-layer model. The paper proposes shifting the responsibilities from the bottom layers to the application layer and end nodes to eliminate the dependency on conventional methods. The result section shows a significant improvement in latency, throughput, and packet reception.

Distributing high-quality 360 VR content to clients with modern networks using existing delivery techniques is economically challenging at scale. Despite the abundance of research in multihomed delivery and client-side adaptive bitrate (ABR) algorithms, current techniques continue to suffer from similar fundamental laws; namely the reliance on inflexible networks, inaccurate network models, and rigid control rules leading to suboptimal performance. This paper proposes a unique approach to address many of these limitations. First, through the implementation of a modified version of an MPEG initiative called Server and Network Assisted DASH (SAND) for use in multipath networks enabling opportunistic messaging between the client, server, and network. Secondly, through the optimization of ABR algorithms that were generated using reinforcement learning and finally, by active management of multipath enabled transport protocols. Testbed experimental results revealed that our technique outperformed many state-of-the- art ABR algorithms in multipath networks. The average multipath differential delay decreased by 30% or more and outperformed standard Multipath TCP (MPTCP) and Quick UDP Internet Connections (QUIC) in key quality of experience (QoE) metrics by up to 20%.

Omnidirectional streaming requirements can be an impediment to delivering virtual reality (VR) quality con- tent at scale. Leveraging multihomed device network options becomes a viable approach to ease congestion. Multipath TCP (MPTCP) has the ability to utilize multiple networks simultaneously, but its performance can suffer from excessive overhead due to its use of large reordering buffers. In this paper, we propose a unique approach to removing this limitation with a software-defined networking architecture. Using Mininet with Floodlight controllers to manage available paths, we designed a framework that actively manages Quick UDP Internet Connections (QUIC) and/or MPTCP network usage based on network characteristics. Testbed experiments reveal that the start- up buffering delay is decreased by up to 60% or more when using our algorithm in networks with packet loss rates above 2%. These results are favorable even when compared against another modern multipath algorithm that attempts to remedy this issue. Our analysis shows our framework outperforms standard MPTCP in network usage efficiency by up to 50% at packet loss rates above 1%.

In this work the Doppler effect is exploited for identifying a collision between two vehicles under Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions. A measurement campaign at 5.9GHz is conducted to observe the Doppler effect for Vehicle-to-Vehicle (V2V) networks. In our previous work, we developed a collision avoidance estimator based on tracking the LOS Doppler shift in the Doppler domain. We now report real-world captures of the Doppler phenomenon in terrestrial V2V networks during a collision and present a method for collision identification by tracking the NLOS Doppler spread in the channel. The classification method by Cepstral coefficients is shown to be reliable in NLOS and LOS conditions, allowing for 360-degree coverage of the vehicle using a single omni-antenna. Through machine learning, classification of collision feature observations is accurate with an accuracy of nearly 100% and reliable with a misclassification rate less than 1%.

This work presents a novel method we call: Frequency Injection Interfacing (FII), for OFDM communication systems. With FII, an external system or observer can communicate to an OFDM receiver through a frequency encoder that injects additional frequency content into the received signal. Specifically, the null subcarriers at the edges of the OFDM waveform are turned on or off to represent a binary code word which references a lookup table. OFDM transmitters do not broadcast wireless energy in the OFDM sidebands in order to comply with regulatory policies. To avoid violating transmission laws, FII uses a direct connection between the frequency encoder and OFDM receiver. Because FII can deliver a unique code word per packet in real time, FII could potentially allow new applications and optimizations for OFDM systems, without requiring a separate application program interface. The FII method is validated through experimentation using software defined radios, a GNU Radio IEEE 802.11 receiver, and a COTS vehicle-to-vehicle radio. A packet reception rate above 95% proves FII operates transparently within existing OFDM architectures, furthermore the non-optimized implementation of FII presented in this work reveals that FII could reliably deliver up to 2047 code words with 67% success and zero false alarms.

The IEEE 1609.4 standard allows a single radio device to utilize multiple channels by alternating control channel (CCH) and service channel (SCH). During the SCH interval, the RTS/CTS/data/ACK handshake can be triggered to transmit large size of data without the hidden node problem. However, it can cause the exposed node problem that hinders concurrent transmissions, which is fatal in highly dynamic VANETs. Even though judicious SCH selection in a multi-channel environment can mitigate the exposed node problem, IEEE 1609.4 does not specify how to select a SCH, which can cause the randomly selected SCHs to be biased. Conforming to the current standards, we therefore propose a novel scheme that enables the exposed vehicles to avoid selecting the same SCH by piggybacking a candidate SCH selection within the optional field of the basic safety message. Through extensive simulations, it is verified that the average throughput can be improved by up to 26%.

For human-driven as well as autonomous vehicles, one of the key requirements is continuous awareness of the surroundings to detect any potential threats (vehicles, pedestrians, wild-life etc.). This requires continuous cooperation between the vehicles by efficiently sharing safety information in a timely manner. However, this is a multi-dimensional and challenging problem due to the complex nature of the vehicular environment. To solve this problem, this paper proposes an elegant solution to efficiently share the safety information among vehicles by using only Basic Safety Messages (BSM), which are part of the existing V2V standards. Through this research, the vehicles are able to quickly and preemptively identify potential threats, not only in their close proximity, but also those which are further along the roadway by intelligently exchanging safety information between neighboring vehicles. Additionally, for the first time, the proposed architecture presents a practical approach of incorporating the onboard sensor data with the V2V communications. This leads to vehicles having improved visibility and situational awareness further outside of their one-hop coverage. Simulation results show that improved visibility of vehicles up to 2.6 km can be achieved while placing minimum overhead and complexity on the network.

Adaptive bitrate streaming is one of the most popular methods to deliver high definition video content for HTTP clients. Commonly used techniques rely primarily on the estimation of network bandwidth and/or buffer state client-side. Inaccurate estimation leads to performance degradation due to a lack of correct bitrate encoding per chunk, and poor network utilization as a result of inflexible transport protocols. In this paper, we propose a unique approach to removing the client-side estimation of network bandwidth and buffer state. Three modular HTTP/2 server push-based strategies leveraging Multipath TCP are designed to improve the delivery of the video content in lossy environments. The goal is to improve start-up delay and overall performance. Laboratory experiments reveal that the start-up buffering delay is decreased by 40% or more when using HTTP/2 over MPTCP in networks with packet loss rates above 2%.

The Doppler effect is typically an impairment for wireless communications in mobile-to-mobile environments. Multipath effects leading to delay dispersion at the receiver can create a challenging doubly selective time-frequency channel response. In Vehicle-to-Vehicle (V2V) communications, small-scale effects of the V2V channel over short durations are well understood. However, observing the Doppler response over longer durations can provide observations directly related to the vehicle dynamics. Understanding the channel contributions of the Doppler response in the macro could enable context aware Doppler sensing leading to enhanced collision avoidance or location based services. To model the large-scale Doppler channel response, geometry-based stochastic channel models (GSCM) provide the best representation of how the Doppler profile is changing with the vehicle motion (or lack of). In this novel work, we build upon an existing GSCM by including the double-bounced scattering off the participating vehicles themselves and validating these contributions through real-world experimentation. The model enables the study of a potentially new "sensor" in connected vehicle networks: the large-scale Doppler response, in which mobile scatters are observable and the V2V radio can be aware of the surrounding communication environment.

The current IEEE 1609.4 standard defines multi-channel operations to alternate control and service channel intervals during a period of 100ms. However, there is no mention of service channel selection for a service provider, which allows hidden service providers to select the same service channel. This limitation can cause the hidden terminal problem during the service channel intervals, leading to significant performance deterioration. Without modifying the existing standards, our proposed scheme enables hidden service providers to avoid selecting the same service channel by delivering their candidate service channel number in the optional field of the basic safety message (BSM). Through extensive simulations, it is verified that the packet reception ratio can be improved by up to 23% in typical broadcast scenarios.

Sharing emergency messages amongst vehicles on the road can greatly reduce traffic accidents. In Vehicular Ad Hoc Networks (VANETs) to share these emergency messages, fast and reliable message dissemination is the key objective in a highly dynamic VANET environment. This research proposes a novel broadcasting protocol to achieve these goals by introducing handshake-less broadcasting, ACK Decoupling and efficient collision resolution mechanism. A key contribution of this paper is to analyze and optimize the broadcasting algorithm using thorough mathematical modeling with extensive simulations. With the suggested optimization process, the message propagation delay can be significantly reduced.

Vehicle-to-Vehicle (V2V) communication is expected to make a global impact on improving driver safety by alerting motorists of potential collisions, but the full safety benefit can only be realized if every vehicle is equipped with a transceiver. Motivated to provide collision avoidance for drivers of vehicles only equipped with a V2V transceiver, we develop a framework for using the V2V communication signal simultaneously as a radar without suggesting any changes to the existing V2V standards or spectrum. The theoretical system treats the IEEE 802.11p waveform as a Multi-Frequency Continuous Wave signal to estimate the velocity and range of a vehicular threat not equipped with a V2V transceiver. While spectrum and upper layers of the protocol stack can vary depending on geographic region, the IEEE 802.11p physical layer protocol is adopted globally. Restrictions in waveform design due to IEEE 802.11p standardization are considered and leveraged for enhancing the radar operations. Through a rigorous simulation treatment, the V2V radar system would be capable of detecting a head-on collision with a 35.12% accuracy using only safety message packets. If non-safety packets are included in the detection operation, then up 100% accuracy is achievable.

The periodic broadcast of a safety message (SM) containing vehicle position and motion data is the salient mechanism for providing drivers pre-crash alerts in Vehicle-to-Vehicle (V2V) networks. However, if SMs are compromised or contain erroneous information, drivers may be unaware of impending danger. Even if vehicles were also equipped with active sensors, awareness may not be achievable in severe non-line-of-sight (NLOS) conditions where collision avoidance is needed most. In this work, a novel system for providing collision avoidance using the Received Signal Strength Indication (RSSI) in V2V networks is presented. Experimental observations of RSSI during collision and no-collision outcomes are analyzed to develop the system's prediction methodology, which is then rigorously tested through a simulation environment to assess the detection performance. The proposed system does not use traditional (Received Signal Strength) RSS distance estimation, fingerprinting, or cooperative methods, which depend heavily on a priori knowledge of path loss conditions. Instead, the decentralized system identifies specific trends in RSSI indicative of a collision. In comparison to RSS distance estimation methods, the proposed system is shown to detect over 35% more collisions in a variety of channel conditions, including NLOS.

Modeling large-scale fading effects in Vehicle-to-Vehicle communications (V2V) in the 5.9GHz Dedicated Short Range Communication band has received broad coverage in the literature over the last 15 years. The majority of V2V channel measurement campaigns have focused on describing the expected path loss of the V2V channel through empirical models. The path loss is a channel metric which describes how fast the received signal strength decays with distance. It is well known that the path loss exponent and reference path loss (y-intercept) varies for different environments, but it is not well understood how the channel changes in a given environment relative to lane separation or vehicle orientation. This paper presents an improved path loss model for line-of-sight (LOS) V2V communications at distances less than 100m. The path loss model removes the Gaussian random variable component, typically used to model shadowing in classic power law path loss model, and instead makes the y-intercept and path loss exponent Gaussian random variables. Derived from extensive empirical measurement campaigns in which vehicle orientation, approach direction, and lane separation are considered, the new channel model is compared to experimental data in which the vehicles move at different speeds. The improved path loss model performs a better fit to experimental data than existing path loss models, including two-ray ground reflection, dual-slope piecewise linear, and classic power law.

Vehicular Ad-hoc networks (VANETs) provide a way for a vehicle to deliver various types of information to users or drivers in other vehicles. Distributing a large amount of information such as multimedia messages in a single control channel makes the control channel easily congested. Transmitting multimedia messages through multi-channel to avoid this congestion becomes a feasible solution. However, low-connectivity in a low vehicle density in multi-channel poses unique challenges and can produce connection failure if this issue is not carefully addressed. In this paper, a network coding technique with divide-and-deliver is introduced to solve this unique challenge for delivering multimedia contents through multiple service channels in a low vehicle density. Through the rigorous analytical derivation and extensive simulation, we show the proposed scheme significantly improves reliability with minimum usage of the control channels in a typical VANETs environment.

Vehicular Ad Hoc Networks (VANETs) is an extension of Mobile Ad Hoc Networks (MANETs) to share traffic information and emergency alerts amongst vehicles on the road. To support many applications in VANETs, most studies use GPS to find the furthest node with ACK to ensure successful message reception. However, this ACK procedure can be removed if a channel between the sender and receiver is clear such that the sender can overhear the broadcasted messages from the receiver. If the sender fails, nodes closer to the sender inform the sender of successful rebroadcasting, which serves as an ACK to the sender. This process will either entirely remove costly ACKing processes or at least decouple the messages propagation from ACKing to the sender, which will significantly improve the speed of message propagation. In this paper, we use Signal-to-Noise Ratio (SNR) with ACK decoupling to ensure fast message propagation with reliable message recovery. Detailed simulation results show that the proposed SNR based approach with ACK decoupling outperforms the Smart Broadcast (SB) by 200% in average throughput and per hop delay, while ensuring the reliable dissemination of emergency messages in typical VANETs environments.

Providing tools to achieve a high level of safety transportation is the important objective in VANETs research. Hence, most of the works are devoted to developing safety-message dissemination algorithms. However, non-safety applications can also contribute to the network efficiency by exchanging traffic information. To support these applications, VANETs adopt the wireless access in the vehicular environment (WAVE) to guarantee the quality of service (QoS) using four different access categories. However, the WAVE could not provide the QoS to the users due to the collisions caused by the small contention-window size for the top priority traffic when top-priority traffic is dominant. Therefore, this small contention-window size setting for the prioritization induces severe performance degradation. In this paper, the Dynamic Service-Channels Allocation (DSCA) method is proposed to maximize throughput by dynamically assigning different service channels to the users. Theoretical analysis and extensive simulation works suggest that the DSCA improves the average throughput by 22% over the uniform channel allocation method. Moreover, the DSCA can be easily implemented in real devices without any protocol modifications.

A hidden-node problem is one of the major challenges that cause severe performance degradation in wireless ad-hoc networks. Even though RTS/CTS (Request To Send/Clear To Send) exchange can remove the hidden-node problem, the inefficiency of exchanging the RTS/CTS has brought attentions to many researchers. While most of these efforts have been focused on the theoretical analysis, very little efforts were given to the verification of proposed models through real-world experiments. Random-bit error is another important factor that deteriorates the network performance in wireless environments. Through rigorous real-world experiments, this paper demonstrates a feasible methodology to enhance network throughput in the existence of hidden nodes by using optimal fragments. Our previous analytical model that incorporates the impact by random-bit error and hidden nodes on the throughput is validated under various real-world environments. These experimental results will provide a solid foundation to the research communities in solving the hidden-node problem in noisy MANET environments.

Hidden nodes cause unexpected collisions and interferences in mobile ad-hoc networks (MANETs). However, little attention has been given to the behavior of hidden nodes, especially when channels are under random bit errors. Exchanging RTS/CTS can avoid hidden node problems. However, undesirable overheads in every packet cause performance degradation, and this motivates many researchers to design new algorithms with modification of the IEEE 802.11 standard. In this paper, the impact of hidden nodes is thoroughly modeled using Markov chains. This model incorporates critical network parameters (random bit errors, packet lengths, number of users) in noisy MANETs channels. Through rigorous analysis, the study suggests the optimal packet lengths to be used in various channel conditions with the existence of hidden nodes. These optimal fragments effectively reduce the number of retransmissions caused by collisions from hidden nodes and corrupted packets due to random bit errors, which significantly improves throughput in noisy MANETs channels without modification of the standards.

Reliability is a critical concern in disseminating safety messages in vehicular ad-hoc-networks (VANETs). Thus far, redundant broadcast (or next relay broadcast) has been used to ensure reliable transfer of safety messages. However, redundant broadcast fails to meet high-reliability requirement owing to lack of a feedback or acknowledgment (ACK) mechanism. In this work, a power controlled negative-acknowledgment (NACK) mechanism is introduced as a feedback technique to ensure reliable reception of safety messages. Significantly, this work also attempts to cover vehicles present in transmission holes in the broadcast region. Vehicles in the immediate neighborhood detect and recover safety message for a vehicle present in the transmission hole by estimating propagation loss for the vehicle. NACK together with hole detection and recovery mechanism nearly guarantees safety-message delivery in VANETs. Reliability of the proposed technique is formulated mathematically with packet reception ratio (PRR) as the reliability metric. Using theoretical analysis and simulation evaluation in ns-3 we establish that the proposed technique guarantees safety-message reception by mitigating packet loss caused by interference from hidden nodes, and at instances where vehicles are located in the transmission holes.

Vehicular Ad hoc Networks (VANETs) provide vehicle-to-vehicle and vehicle-to-infrastructure communication using Dedicated Short-Range Communications (DSRC). The core objective of VANETs is to provide safety message communication among vehicles. In dense urban traffic, safety message communication encounters severe packet collisions due to excessive number of nodes contending to access the control channel. In such a complex dense and mobile scenario, an ideal single vehicle per time slot has yet not been achieved. This paper introduces the use of lane level location information to achieve a single vehicle per time slot configuration. The transmission range of a message originator is divided into a grid using distance and lanes as the two variables. Each block within the grid houses a single vehicle at most that is assigned a unique time slot. The contention among nodes for the same time slot is virtually removed. Theory and ns-3 simulation justify the feasibility, and prove that the technique reduces packet collisions by 2%, and improves message dissemination speed by as much as 30% each hop.

Cognitive radio (CR) users are expected to be uncoordinated users that opportunistically seek the spectrum resource from primary users (PUs) in a competitive way. In most existing works, however, CR users are required to share the interference channel information and power strategies to conduct the game with pricing mechanisms that incur the frequent exchange of information. The requirement of significant communication overheads among CR users impedes fully distributed solutions for the deployment of CR networks, which is a challenging problem in the research communities. In this paper, a robust distributed power control algorithm is designed with low implementation complexity for CR networks through reinforcement learning, which does not require the interference channel and power strategy information among CR users (and from CR users to PUs). To the best of our knowledge, this research provides the solution for the first time for the incomplete-information power control game in CR networks. During the repeated game, CR users can control their power strategies by observing the interference from the feedback signals of PUs and transmission rates obtained in the previous step. This procedure allows achieving high spectrum efficiency while conforming to the interference constraint of PUs. This constrained repeated stochastic game with learning automaton is proved to be asymptotically equivalence to the traditional game with complete information. The properties of existence, diagonal concavity and uniqueness for the game are studied. A Bush-Mosteller reinforcement learning procedure is designed for the power control algorithm, and the properties of convergence and learning rate of the algorithm are analyzed. The performance of the learning-based power control algorithm is thoroughly investigated with simulation results, which demonstrates the effectiveness of the proposed algorithm in solving variety of practical CR network problems for real-world applications.

This study provides a general framework for distributed multi-user power control problems in cognitive radio (CR) networks over fading channels. Using a non-cooperative game with coupled constraints in CR and primary channel outages, the fundamental performance traits of power control for multiple CR users are analyzed in the present of multiple primary users (PUs) in fading environments for the first time. While the feasibility of target SINRs are always guaranteed in most studies for no-fading environments, the adopted channel outage model incorporates the probability that the SINR falls below a target threshold due to fast fading or interferences from other CR users. For the tractable analysis of the formulated problem, geometric programming approach is used to transfer it as a convex one. A dual decomposition approach is applied with layered structure for the constrained game, where each subproblem is full of economic interpretation. The properties of Nash Equilibrium (N.E.) for the proposed game are thoroughly investigated. An asynchronous distributed power control algorithm converging to the N.E. is designed, which ensures the robust implementation in fading environments. Finally, the simulation results and analysis are shown to enforce the effectiveness of the proposed algorithms for CR users over fading channels.

Vehicular ad hoc networks (VANETs) rely on multi-hop communication in order to disseminate information to locations beyond the transmission range. In this paper, the use of handshaking mechanism is evaluated against instant transmission for safety message routing in VANETs for the first time. It is argued that due to the small size of VANET safety message (mean payload size of 100 bytes), handshaking may not be advantageous to avoid hidden node problem and may incur overhead delay. The simplified instant broadcast routing without the use of handshake mechanism is recommended. Theoretical analysis of message propagation delay using instant broadcast routing is shown which can be easily extended for any broadcast method. Two prominent handshake based broadcast routing schemes are implemented in ns-3 along with instant broadcast scheme. The simulation results reveal that instant broadcast effectively lowers the message propagation delay by 100% each hop and guarantees reliable dissemination of safety messages to all endangered vehicles on the road.

The growing interest in vehicular ad hoc networks (VANETs) enables decentralized traveler information systems to become more feasible and effective in Intelligent Transportation Systems (ITS). Major challenges in such network environments include varying path characteristics and vulnerable channel quality resulting from dynamic traffic conditions and the design of the road. This paper demonstrates a feasible methodology that can enhance inter-vehicle information dissemination using dynamic optimal fragmentation with rate adaptation algorithm (DORA). DORA achieves maximum goodput in wireless mobile networks by computing a fragmentation threshold and transmitting optimal sized packets with maximum transfer rates. To estimate the SNR in the model, an adaptive on-demand UDP estimator is designed to reduce estimation overhead. Several test-beds were developed to evaluate the performance of DORA in channel estimation accuracy, ad hoc network goodput, and vehicle-to-vehicle network goodput along I-85 in Atlanta, Georgia. The proposed algorithm is an energy-efficient, generic CSMA/CA MAC protocol for wireless mobile computing applications, and enhances system goodput in ad hoc networks and vehicle-to-vehicle networks without modification of the base protocols.

This paper studies the repeated power control game in cognitive radio (CR) networks through reinforcement learning without channel and power strategy information exchange among CR users. Unlike traditional game-theoretical approaches on CR power control, this research solves the incomplete information power control problems for selfish and autonomous CR users for the first time. Each CR user in the problem only knows its own channel and power strategy while the information of primary users (PUs) and other different types of CR users are unknown. The formulated power control problem is a constrained repeated stochastic game with learning automaton. The objective of this repeated game is to maximize the average utility of each CR user under the interference power constraints of PUs. At each time step, the CR user only knows its own utility and the interference functions after the play but no further information. This power control game is proved to be asymptotically equivalent to the traditional game theory approaches. The properties of existence, diagonal concavity and uniqueness for this game are illustrated in detail. A Bush-Mosteller reinforcement learning procedure is designed for the power control algorithm. Finally, the learning based power control algorithm is implemented, and the simulation results with detailed analysis are shown to enforce the effectiveness of the proposed algorithms.

Cognitive radio ad hoc networks (CRAHNs) solve the problem of spectrum utilization when the licensed or primary user (PU) activity changes over time. This affects not only the spectrum availability, but also the network topology, making the analysis of scaling laws very challenging. Currently, the effect of PU activity on the network scaling laws has not been theoretically analyzed, to the best of our knowledge. In this paper, throughput capacity and delay scaling laws are introduced for CRAHNs by capturing the impact of PU activity in dense, and sparse PU deployment conditions. In the former case, it is observed that the scalability for the CRAHN is very low, with the capacity strongly related to the 'off' transmission times of the PU. Moreover, this is possible only under specific conditions of buffering, and queuing assumptions for the CRAHN. In the second case with sparse PUs, both the average throughput capacity and network delay of CRAHN are significantly improved. Interestingly, in both cases, the distribution of the PU locations does not impact the scalability in CRAHNs.

Various vehicular communication technologies have been proposed to provide reliable and seamless wireless communications. Short-range vehicular communications can be established using IEEE 802.11p, and the range of these protocols can be extended using mobile multi-hop ad hoc networks. To provide consistent quality of service (QoS) with maximum achievable transmission rate, many algorithms assume that the signal to noise ratio (SNR) of the receiver is known, or can be obtained by modifying protocols. In this paper, we present an efficient on-demand adaptive channel estimation technique. Using simple UDP messages without changing protocols, the estimator predicts the SNR with minimum signaling overheads. Extensive experiments in vehicular environments along the I-85 highway and residential areas in Atlanta, Georgia reinforce that the proposed algorithm is efficient and reliable channel estimation technique for next generation wireless mobile networks.

To support the quality of service in wireless multimedia communications, wireless systems should work well in typical wireless environments characterized by the path loss of the signals, multipath fading, interference to adjacent channels, and random errors. A variety of researches in the application-layer have been proposed to adapt the video encoder to the link quality by compressing the data with different rates. However, these approaches introduce additional overhead and are inefficient when the round-trip delays are long. This paper proposes an algorithm to prevent packet losses and skipped frames by using optimal fragmentation technique with rate adaptation. Using an adaptive SNR estimator, the sender estimates the SNR of the receiver, and shapes arbitrary sized packets into optimal length packets with rate adaptation. Through rigorous analysis and extensive experiments with an implemented test-bed, we show that the algorithm significantly enhances the visual quality of real-time multimedia streaming in noisy ad hoc networks. The experimental results reinforce the fact that the algorithm is a realistic approach that can be deployed without modifying existing standards.

Packet based wireless networks have provided high data rates, and the desire for ubiquitous wireless computing is growing rapidly. To accommodate these demands, wireless systems should work well in typical wireless environments. The most widely deployed WLAN technology, IEEE 802.11, uses the unlicensed ISM band, which is vulnerable to noise generated by electronic devices. This paper proposes a way to enhance system goodput in CSMA/CA MAC protocols using fragmentation. Our analytical model considers the number of contending stations, packet collisions, packet error probabilities, and fragmentation overheads. With extensive experiments in WLAN and ad hoc networks, we show the optimization improves the goodput approximately 18% in a typical WLAN and 48% in ad hoc networks. The proposed approach can be implemented to any CSMA/CA MAC protocol without modifying the standard.

This paper introduces a fast handoff mechanism, NeighborCasting, for use in wireless IP networks that utilize neighboring foreign agent (FA) information. NeighborCasting is based on the policy of utilizing, or perhaps even wasting, wired bandwidth between foreign agents, while minimizing RF (radio frequency) bandwidth exchanges, so that handoff latency is minimized. We demonstrate that the handoff latency is substantially reduced, while the typical overhead is minimally increased. Handoff latency is minimized by initiating data forwarding to the possible new foreign agent candidates (i.e., the neighbor foreign agents) at the time that the mobile node initiates the link-layer handoff procedure. NeighborCasting builds upon the Mobile IP handoff procedure by adding a small number of additional message types. The handoff mechanism is a unified procedure for inter-domain, intra-domain and inter-technology (e.g., LAN to WAN or TDMA to CDMA) handoffs and provides flexible choices to the network, while maintaining transparency to the mobile node. The neighbor FA discovery process is a distributed and dynamic mechanism, and the fast handoff schemes are scalable and reliable.