Medium access control, error control and routing in underwater acoustic networks: a discussion on protocol design and implementation

The journey of underwater communication which began from Leonardo’s era took four and a half centuries to find practical applications for military purposes during World War II. However, over the last three decades, underwater acoustic communications witnessed a massive development due to the advancements in the design of underwater communicating peripherals and their supporting protocols. Successively, doors are opened for a wide range of applications to employ in the underwater environment, such as oceanography, pollution monitoring, offshore exploration, disaster prevention, navigation assistance, monitoring, coastal patrol and surveillance. Different applications may have different characteristics and hence, may require different network architectures. For instance, routing protocols designed for unpartitioned multi-hop networks are not suitable for Delay-Tolerant Networks. Furthermore, single-hop networks do not need routing protocols at all. Therefore, before developing a protocol one must study the network architecture properly and design it accordingly. There are several other factors which should also be considered with the network architecture while designing an efficient protocol for underwater networks, such as long propagation delay, limited bandwidth, limited battery power, high bit error rate of the channel and several other adverse properties of the channel, such as, multi-path, fading and refractive behaviors. Moreover, the environment also has an impact on the performance of the protocols designed for underwater networks. Even temperature changes in a single day have an impact on the performance of the protocols. A good protocol designed for any network should consider some or all of these characteristics to achieve better performance. In this thesis, we first discuss the impact of the environment on the performance of MAC and routing protocols. From our investigation, we discover that even temperature changes within a day may affect the sound speed profile and hence, the channel changes and the protocol performance vary. After that we discuss several protocols which are specifically designed for underwater acoustic networks to serve different purposes and for different network architectures. Underwater Selective Repeat (USR) is an error control protocol designed to assure reliable data transmission in the MAC layer. One may suspect that employing an error control technique over a channel which already suffers from long propagation delays is a burden. However, USR utilizes long propagation by transmitting multiple packets in a single RTT using an interlacing technique. After USR, a routing protocol for surveillance networks is discussed where some sensors are laid down at the bottom of the sea and some sinks are placed outside the area. If a sensor detects an asset within its detection range, it announces the presence of intruders by transmitting packets to the sinks. It may happen that the discovered asset is an enemy ship or an enemy submarine which creates noise to jam the network. Therefore, in surveillance networks, it is necessary that the protocols have jamming resistance capabilities. Moreover, since the network supports multiple sinks with similar anycast address, we propose a Jamming Resistance multi-path Multi-Sink Routing Protocol (MSRP) using a source routing technique. However, the problem of source routing is that it suffers from large overhead (every packet includes the whole path information) with respect to other routing techniques, and also suffers from the unidirectional link problem. Therefore, another routing protocol based on a distance vector technique, called Multi-path Routing with Limited Cross-Path Interference (L-CROP) protocol is proposed, which employs a neighbor-aware multi-path discovery algorithm to support low interference multiple paths between each source-destination pair. Following that, another routing protocol is discussed for next generation coastal patrol and surveillance network, called Underwater Delay-Tolerant Network (UDTN) routing where some AUVs carry out the patrolling work of a given area and report to a shore based control-center. Since the area to be patrolled is large, AUVs experience intermittent connectivity. In our proposed protocol, two nodes that understand to be in contact with each other calculate and divide their contact duration equally so that every node gets a fair share of the contact duration to exchange data. Moreover, a probabilistic spray technique is employed to restrict the number of packet transmissions and for error correction a modified version of USR is employed. In the appendix, we discuss a framework which was designed by our research group to realize underwater communication through simulation which is used in most of the simulations in this thesis, called DESERT Underwater (short for DEsign, Simulate, Emulate and Realize Test-beds for Underwater network protocols). It is an underwater extension of the NS-Miracle simulator to support the design and implementation of underwater network protocols. Its creation assists the researchers in to utilizing the same codes designed for the simulator to employ in actual hardware devices and test in the real underwater scenario

Congestion Control and Routing over Challenged Networks

This dissertation is a study on the design and analysis of novel, optimal routing and rate control algorithms in wireless, mobile communication networks. Congestion control and routing algorithms upto now have been designed and optimized for wired or wireless mesh networks. In those networks, optimal algorithms (optimal in the sense that either the throughput is maximized or delay is minimized, or the network operation cost is minimized) can be engineered based on the classic time scale decomposition assumption that the dynamics of the network are either fast enough so that these algorithms essentially see the average or slow enough that any changes can be tracked to allow the algorithms to adapt over time. However, as technological advancements enable integration of ever more mobile nodes into communication networks, any rate control or routing algorithms based, for example, on averaging out the capacity of the wireless mobile link or tracking the instantaneous capacity will perform poorly. The common element in our solution to engineering efficient routing and rate control algorithms for mobile wireless networks is to make the wireless mobile links seem as if they are wired or wireless links to all but few nodes that directly see the mobile links (either the mobiles or nodes that can transmit to or receive from the mobiles) through an appropriate use of queuing structures at these selected nodes. This approach allows us to design end-to-end rate control or routing algorithms for wireless mobile networks so that neither averaging nor instantaneous tracking is necessary

Multi-constrained mechanism for intra-body area network quality-of-service aware routing in wireless body sensor networks

Wireless Body Sensor Networks (WBSNs) have witnessed tremendous research interests in a wide range of medical and non-medical fields. In the delaysensitive application scenarios, the critical data packets are highly delay-sensitive which require some Quality-of-Service (QoS) to reach the intended destinations. The categorization of data packets and selection of poor links may have detrimental impacts on overall performance of the network. In WBSN, various biosensors transmit the sensed data towards a destination for further analysis. However, for an efficient data transmission, it is very important to transmit the sensed data towards the base station by satisfying the QoS multi-constrained requirements of the healthcare applications in terms of least end-to-end delay and high reliability, throughput, Packet Delivery Ratio (PDR), and route stability performance. Most of the existing WBSN routing schemes consider traffic prioritization to solve the slot allocation problem. Consequently, the data transmission may face high delays, packet losses, retransmissions, lack of bandwidth, and insufficient buffer space. On the other hand, an end-to-end route is discovered either using a single or composite metric for the data transmission. Thus, it affects the delivery of the critical data through a less privileged manner. Furthermore, a conventional route repair method is considered for the reporting of broken links which does not include surrounding interference. As such, this thesis presents the Multi-constrained mechanism for Intra- Body Area Network QoS aware routing (MIQoS) with Low Latency Traffic Prioritization (LLTP), Optimized Route Discovery (ORD), and Interference Adaptive Route Repair (IARR) schemes for the healthcare application of WBSN with an objective of improving performance in terms of end-to-end delay, route stability, and throughput. The proposed LLTP scheme considers various priority queues with an optimized scheduling mechanism that dynamically identifies and prioritizes the critical data traffic in an emergency situation to enhance the critical data transmission. Consequently, this will avoid unnecessary queuing delay. The ORD scheme incorporates an improved and multi-facet routing metric, Link Quality Metric (LQM) optimizes the route selection by considering link delay, link delivery ratio, and link interference ratio. The IARR scheme identifies the links experiencing transmission issues due to channel interference and makes a coherent decision about route breakage based on the long term link performance to avoid unnecessary route discovery notifications. The simulation results verified the improved performance in terms of reducing the end-to-end delay by 29%, increasing the throughput by 22% and route stability by 26% as compared to the existing routing schemes such as TTRP, PA-AODV and standard AODV. In conclusion, MIQoS proves to be a suitable routing mechanism for a wide range of interesting applications of WBSN that require fast, reliable and multi-hop communication in heavily loaded network traffic scenarios

Application Platforms, Routing Algorithms and Mobility Behavior in Mobile Disruption-Tolerant Networks

Mobile disruption-tolerant networks (DTNs), experience frequent and long duration partitions due to the low density of mobile nodes. In these networks, traditional networking models relying on end-to-end communication cease to work. The topological characteristics of mobile DTNs impose unique challenges for the design and validation of routing protocols and applications. We investigate challenges of mobile DTNs from three different viewpoints: the application layer, a routing perspective, and by studying mobility patterns. In the application layer, we have built 7DS (7th Degree of Separation) as a modular platform to develop mobile disruption-tolerant applications. 7DS offers a class of disruption-tolerant applications to exchange data with other mobile users in the mobile DTN or with the global Internet. In the routing layer, we have designed and implemented PEEP as an interest-aware and energy efficient routing protocol which automatically extracts individual interests of mobile users and estimates the global popularity of data items throughout the network. PEEP considers mobile users' interests and global popularity of data items in its routing decisions to route data toward the community of mobile users who are interested in that data content. Mobility of mobile users impacts the conditions in which routing protocols for mobile DTNs must operate and types of applications that could be provided for mobile networks in general. The current synthetic mobility models do not reflect real-world mobile users' behavior. Trace-based mobility models, also, are based on traces that either represent a specific population of mobile users or do not have enough granularities in representing mobility of mobile users for example cell tower traces. We use Sense Networks' GPS traces that are being collected by monitoring a broad spectrum of mobile users. Using these traces, we employ a Markovian approach to extract inherent patterns in human mobility. We design and implement a new routing algorithm for mobile DTNs based on our Markovian analysis of the human mobility. We explore how the knowledge of the mobility improves the performance of our Markov based routing algorithm. We show that that our Markov based routing algorithm increases the rate of data delivery to popular destinations with consuming less energy than legacy algorithms

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour