IPv6 tactical network management

Current and emerging technologies and equipment, such as unmanned aerial vehicles, ground sensors, networked radios, operator-worn sensor vests, and nanotechnology applications offer warfighters unprecedented command and control and information detection capabilities, yet the use of this technology has not been fully realized. The current protocol, IPv4, is incapable of providing enough addresses due to a depletion of IPv4 address space. IPv6, however, offers unprecedented network support for tactical-level sensor and communications assets in terms of increased address space, Quality of Service (QoS), flexibility, and security. The Department of Defense is transitioning from IPv4 to IPv6 in order to capitalize on IPv6's expanded capabilities. However, one unresolved area is proper IPv6 network management. Currently, the majority of the configuration and operational knowledge is in the mind of a very few individuals. The expertise currently available must be developed for application by the tactical network manager operating out on the edge of the network, in order to properly administer both an IPv4/IPv6 dual stacked network during the phased protocol transition and a purely native IPv6 network. Second, IPv6 features a robust Quality of Service (QoS) capability previously unavailable through IPv4, which requires research to determine the optimum configuration to support the warfighter's diverse requirements.http://archive.org/details/ipvtacticalnetwo109454574Outstanding ThesisUS Marine Corps (USMC) author.Approved for public release; distribution is unlimited

Adaptive Management of QoS Requirements for Wireless Multimedia Communications

We present a control model, which provides response time and bandwidth requirement adaptation in audio, video, and application sharing multipoint IP teleconferences for emerging wireless multimedia communications. The model is based on revealing feedback controls for multimedia call preparation and subsequent real time connection control. Case-based reasoning memory is used to associate real time congestion (connection) controls with call preparation controls and user QoS profiles. Web agents are used to capture user and application multimedia call profiles observed at the application layer and transfer them into the case memory. RTP statistics are used to identify the connection management feedback controls for the network layer. Real-time adaptation at the network layer and above is made possible by using hierarchical coding techniques. The proposed adaptive management architecture is illustrated by a case memory representation of call preparation feedback controls, RTP feedback control tests for providing audio stream bandwidth adaptation, and configuration of integrated experiments

An intelligent approach to quality of service for MPEG-4 video transmission in IEEE 802.15.1

Nowadays, wireless connectivity is becoming ubiquitous spreading to companies and in domestic areas. IEEE 802.15.1 commonly known as Bluetooth is high-quality, high-security, high-speed and low-cost radio signal technology. This wireless technology allows a maximum access range of 100 meters yet needs power as low as 1mW. Regrettably, IEEE 802.15.1 has a very limited bandwidth. This limitation can become a real problem If the user wishes to transmit a large amount of data in a very short time. The version 1.2 which is used in this project could only carry a maximum download rate of 724Kbps and an upload rate of 54Kbps In its asynchronous mode. But video needs a very large bandwidth to be transmitted with a sufficient level of quality. Video transmission over IEEE 802.15.1 networks would therefore be difficult to achieve, due to the limited bandwidth. Hence, a solution to transmit digital video with a sufficient quality of picture to arrive at the receiving end is required. A hybrid scheme has been developed in this thesis, comprises of a fuzzy logic set of rules and an artificial neural network algorithms. MPEG-4 video compression has been used in this work to optimise the transmission. This research further utilises an ‘added-buffer’ to prevent excessive data loss of MPEG-4 video over IEEE 802.15.1transmission and subsequently increase picture quality. The neural-fuzzy scheme regulates the output rate of the added-buffer to ensure that MPEG-4 video stream conforms to the traffic conditions of the IEEE 802.15.1 channel during the transmission period, that is to send more data when the bandwidth is not fully used and keep the data in the buffers if the bandwidth is overused. Computer simulation results confirm that intelligence techniques and added-buffer do improve quality of picture, reduce data loss and communication delay, as compared with conventional MPEG video transmission over IEEE 802.15.1