Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

JTP, an energy-aware transport protocol for mobile ad hoc networks

Wireless ad-hoc networks are based on a cooperative communication model, where all nodes not only generate traffic but also help to route traffic from other nodes to its final destination. In such an environment where there is no infrastructure support the lifetime of the network is tightly coupled with the lifetime of individual nodes. Most of the devices that form such networks are battery-operated, and thus it becomes important to conserve energy so as to maximize the lifetime of a node. In this thesis, we present JTP, a new energy-aware transport protocol, whose goal is to reduce power consumption without compromising delivery requirements of applications. JTP has been implemented within the JAVeLEN system. JAVeLEN~\cite{javelen08redi}, is a new system architecture for ad hoc networks that has been developed to elevate energy efficiency as a first-class optimization metric at all protocol layers, from physical to transport. Thus, energy gains obtained in one layer would not be offset by incompatibilities and/or inefficiencies in other layers. To meet its goal of energy efficiency, JTP (1) contains mechanisms to balance end-to-end vs. local retransmissions; (2) minimizes acknowledgment traffic using receiver regulated rate-based flow control combined with selected acknowledgments and in-network caching of packets; and (3) aggressively seeks to avoid any congestion-based packet loss. Within this ultra low-power multi-hop wireless network system, simulations and experimental results demonstrate that our transport protocol meets its goal of preserving the energy efficiency of the underlying network. JTP has been implemented on the actual JAVeLEN nodes and its benefits have been demoed on a real system

JTP, an energy-aware transport protocol for mobile ad hoc networks (PhD thesis)

Wireless ad-hoc networks are based on a cooperative communication model, where all nodes not only generate traffic but also help to route traffic from other nodes to its final destination. In such an environment where there is no infrastructure support the lifetime of the network is tightly coupled with the lifetime of individual nodes. Most of the devices that form such networks are battery-operated, and thus it becomes important to conserve energy so as to maximize the lifetime of a node. In this thesis, we present JTP, a new energy-aware transport protocol, whose goal is to reduce power consumption without compromising delivery requirements of applications. JTP has been implemented within the JAVeLEN system. JAVeLEN [RKM+08], is a new system architecture for ad hoc networks that has been developed to elevate energy efficiency as a first-class optimization metric at all protocol layers, from physical to transport. Thus, energy gains obtained in one layer would not be offset by incompatibilities and/or inefficiencies in other layers. To meet its goal of energy efficiency, JTP (1) contains mechanisms to balance end-toend vs. local retransmissions; (2) minimizes acknowledgment traffic using receiver regulated rate-based flow control combined with selected acknowledgments and in-network caching of packets; and (3) aggressively seeks to avoid any congestion-based packet loss. Within this ultra low-power multi-hop wireless network system, simulations and experimental results demonstrate that our transport protocol meets its goal of preserving the energy efficiency of the underlying network. JTP has been implemented on the actual JAVeLEN nodes and its benefits have been demonstrated on a real system

Transport protocols for multi hop wireless networks

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

Reputation-Based Internet Protocol Security: A Multilayer Security Framework for Mobil Ad Hoc Networks

This research effort examines the theory, application, and results for a Reputation-based Internet Protocol Security (RIPSec) framework that provides security for an ad-hoc network operating in a hostile environment. In RIPSec, protection from external threats is provided in the form of encrypted communication links and encryption-wrapped nodes while internal threats are mitigated by behavior grading that assigns reputations to nodes based on their demonstrated participation in the routing process. Network availability is provided by behavior grading and round-robin multipath routing. If a node behaves faithfully, it earns a positive reputation over time. If a node misbehaves (for any number of reasons, not necessarily intentional), it earns a negative reputation. Each member of the MANET has its own unique and subjective set of Reputation Indexes (RI) that enumerates the perceived reputation of the other MANET nodes. Nodes that desire to send data will eliminate relay nodes they perceive to have a negative reputation during the formulation of a route. A 50-node MANET is simulated with streaming multimedia and varying levels of misbehavior to determine the impact of the framework on network performance. Results of this research were very favorable. Analysis of the simulation data shows the number of routing errors sent in a MANET is reduced by an average of 52% when using RIPSec. The network load is also reduced, decreasing the overall traffic introduced into the MANET and permitting individual nodes to perform more work without overtaxing their limited resources. Finally, throughput is decreased due to larger packet sizes and longer round trips for packets to traverse the MANET, but is still sufficient to pass traffic with high bandwidth requirements (i.e., video and imagery) that is of interest in military networks

An adaptable fuzzy-based model for predicting link quality in robot networks.

It is often essential for robots to maintain wireless connectivity with other systems so that commands, sensor data, and other situational information can be exchanged. Unfortunately, maintaining sufficient connection quality between these systems can be problematic. Robot mobility, combined with the attenuation and rapid dynamics associated with radio wave propagation, can cause frequent link quality (LQ) issues such as degraded throughput, temporary disconnects, or even link failure. In order to proactively mitigate such problems, robots must possess the capability, at the application layer, to gauge the quality of their wireless connections. However, many of the existing approaches lack adaptability or the framework necessary to rapidly build and sustain an accurate LQ prediction model. The primary contribution of this dissertation is the introduction of a novel way of blending machine learning with fuzzy logic so that an adaptable, yet intuitive LQ prediction model can be formed. Another significant contribution includes the evaluation of a unique active and incremental learning framework for quickly constructing and maintaining prediction models in robot networks with minimal sampling overhead