Traffic locality oriented route discovery algorithms for mobile ad hoc networks

There has been a growing interest in Mobile Ad hoc Networks (MANETs) motivated by the advances in wireless technology and the range of potential applications that might be realised with such technology. Due to the lack of an infrastructure and their dynamic nature, MANETs demand a new set of networking protocols to harness the full benefits of these versatile communication systems. Great deals of research activities have been devoted to develop on-demand routing algorithms for MANETs. The route discovery processes used in most on-demand routing algorithms, such as the Dynamic Source Routing (DSR) and Ad hoc On-demand Distance Vector (AODV), rely on simple flooding as a broadcasting technique for route discovery. Although simple flooding is simple to implement, it dominates the routing overhead, leading to the well-known broadcast storm problem that results in packet congestion and excessive collisions. A number of routing techniques have been proposed to alleviate this problem, some of which aim to improve the route discovery process by restricting the broadcast of route request packets to only the essential part of the network. Ideally, a route discovery should stop when a receiving node reports a route to the required destination. However, this cannot be achieved efficiently without the use of external resources; such as GPS location devices. In this thesis, a new locality-oriented route discovery approach is proposed and exploited to develop three new algorithms to improve the route discovery process in on-demand routing protocols. The proposal of our algorithms is motivated by the fact that various patterns of traffic locality occur quite naturally in MANETs since groups of nodes communicate frequently with each other to accomplish common tasks. Some of these algorithms manage to reduce end-to-end delay while incurring lower routing overhead compared to some of the existing algorithms such as simple flooding used in AODV. The three algorithms are based on a revised concept of traffic locality in MANETs which relies on identifying a dynamic zone around a source node where the zone radius depends on the distribution of the nodes with which that the source is “mostly” communicating. The traffic locality concept developed in this research form the basis of our Traffic Locality Route Discovery Approach (TLRDA) that aims to improve the routing discovery process in on-demand routing protocols. A neighbourhood region is generated for each active source node, containing “most” of its destinations, thus the whole network being divided into two non-overlapping regions, neighbourhood and beyond-neighbourhood, centred at the source node from that source node prospective. Route requests are processed normally in the neighbourhood region according to the routing algorithm used. However, outside this region various measures are taken to impede such broadcasts and, ultimately, stop them when they have outlived their usefulness. The approach is adaptive where the boundary of each source node’s neighbourhood is continuously updated to reflect the communication behaviour of the source node. TLRDA is the basis for the new three route discovery algorithms; notably: Traffic Locality Route Discovery Algorithm with Delay (TLRDA D), Traffic Locality Route Discovery Algorithm with Chase (TLRDA-C), and Traffic Locality Expanding Ring Search (TL-ERS). In TLRDA-D, any route request that is currently travelling in its source node’s beyond-neighbourhood region is deliberately delayed to give priority to unfulfilled route requests. In TLRDA-C, this approach is augmented by using chase packets to target the route requests associated with them after the requested route has been discovered. In TL-ERS, the search is conducted by covering three successive rings. The first ring covers the source node neighbourhood region and unsatisfied route requests in this ring trigger the generation of the second ring which is double that of the first. Otherwise, the third ring covers the whole network and the algorithm finally resorts to flooding. Detailed performance evaluations are provided using both mathematical and simulation modelling to investigate the performance behaviour of the TLRDA D, TLRDA-C, and TL-ERS algorithms and demonstrate their relative effectiveness against the existing approaches. Our results reveal that TLRDA D and TLRDA C manage to minimize end-to-end packet delays while TLRDA-C and TL-ERS exhibit low routing overhead. Moreover, the results indicate that equipping AODV with our new route discovery algorithms greatly enhance the performance of AODV in terms of end to end delay, routing overhead, and packet loss

Traffic locality oriented route discovery algorithms for mobile ad hoc networks

There has been a growing interest in Mobile Ad hoc Networks (MANETs) motivated by the advances in wireless technology and the range of potential applications that might be realised with such technology. Due to the lack of an infrastructure and their dynamic nature, MANETs demand a new set of networking protocols to harness the full benefits of these versatile communication systems. Great deals of research activities have been devoted to develop on-demand routing algorithms for MANETs. The route discovery processes used in most on-demand routing algorithms, such as the Dynamic Source Routing (DSR) and Ad hoc On-demand Distance Vector (AODV), rely on simple flooding as a broadcasting technique for route discovery. Although simple flooding is simple to implement, it dominates the routing overhead, leading to the well-known broadcast storm problem that results in packet congestion and excessive collisions. A number of routing techniques have been proposed to alleviate this problem, some of which aim to improve the route discovery process by restricting the broadcast of route request packets to only the essential part of the network. Ideally, a route discovery should stop when a receiving node reports a route to the required destination. However, this cannot be achieved efficiently without the use of external resources; such as GPS location devices. In this thesis, a new locality-oriented route discovery approach is proposed and exploited to develop three new algorithms to improve the route discovery process in on-demand routing protocols. The proposal of our algorithms is motivated by the fact that various patterns of traffic locality occur quite naturally in MANETs since groups of nodes communicate frequently with each other to accomplish common tasks. Some of these algorithms manage to reduce end-to-end delay while incurring lower routing overhead compared to some of the existing algorithms such as simple flooding used in AODV. The three algorithms are based on a revised concept of traffic locality in MANETs which relies on identifying a dynamic zone around a source node where the zone radius depends on the distribution of the nodes with which that the source is “mostly” communicating. The traffic locality concept developed in this research form the basis of our Traffic Locality Route Discovery Approach (TLRDA) that aims to improve the routing discovery process in on-demand routing protocols. A neighbourhood region is generated for each active source node, containing “most” of its destinations, thus the whole network being divided into two non-overlapping regions, neighbourhood and beyond-neighbourhood, centred at the source node from that source node prospective. Route requests are processed normally in the neighbourhood region according to the routing algorithm used. However, outside this region various measures are taken to impede such broadcasts and, ultimately, stop them when they have outlived their usefulness. The approach is adaptive where the boundary of each source node’s neighbourhood is continuously updated to reflect the communication behaviour of the source node. TLRDA is the basis for the new three route discovery algorithms; notably: Traffic Locality Route Discovery Algorithm with Delay (TLRDA D), Traffic Locality Route Discovery Algorithm with Chase (TLRDA-C), and Traffic Locality Expanding Ring Search (TL-ERS). In TLRDA-D, any route request that is currently travelling in its source node’s beyond-neighbourhood region is deliberately delayed to give priority to unfulfilled route requests. In TLRDA-C, this approach is augmented by using chase packets to target the route requests associated with them after the requested route has been discovered. In TL-ERS, the search is conducted by covering three successive rings. The first ring covers the source node neighbourhood region and unsatisfied route requests in this ring trigger the generation of the second ring which is double that of the first. Otherwise, the third ring covers the whole network and the algorithm finally resorts to flooding. Detailed performance evaluations are provided using both mathematical and simulation modelling to investigate the performance behaviour of the TLRDA D, TLRDA-C, and TL-ERS algorithms and demonstrate their relative effectiveness against the existing approaches. Our results reveal that TLRDA D and TLRDA C manage to minimize end-to-end packet delays while TLRDA-C and TL-ERS exhibit low routing overhead. Moreover, the results indicate that equipping AODV with our new route discovery algorithms greatly enhance the performance of AODV in terms of end to end delay, routing overhead, and packet loss.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Lifenet: a flexible ad hoc networking solution for transient environments

In the wake of major disasters, the failure of existing communications infrastructure and the subsequent lack of an effective communication solution results in increased risks, inefficiencies, damage and casualties. Currently available options such as satellite communication are expensive and have limited functionality. A robust communication solution should be affordable, easy to deploy, require little infrastructure, consume little power and facilitate Internet access. Researchers have long proposed the use of ad hoc wireless networks for such scenarios. However such networks have so far failed to create any impact, primarily because they are unable to handle network transience and have usability constraints such as static topologies and dependence on specific platforms. LifeNet is a WiFi-based ad hoc data communication solution designed for use in highly transient environments. After presenting the motivation, design principles and key insights from prior literature, the dissertation introduces a new routing metric called Reachability and a new routing protocol based on it, called Flexible Routing. Roughly speaking, reachability measures the end-to-end multi-path probability that a packet transmitted by a source reaches its final destination. Using experimental results, it is shown that even with high transience, the reachability metric - (1) accurately captures the effects of transience (2) provides a compact and eventually consistent global network view at individual nodes, (3) is easy to calculate and maintain and (4) captures availability. Flexible Routing trades throughput for availability and fault-tolerance and ensures successful packet delivery under varying degrees of transience. With the intent of deploying LifeNet on field we have been continuously interacting with field partners, one of which is Tata Institute of Social Sciences India. We have refined LifeNet iteratively refined base on their feedback. I conclude the thesis with lessons learned from our field trips so far and deployment plans for the near future.MSCommittee Chair: Santosh Vempala; Committee Member: Ashok Jhunjhunwala; Committee Member: Michael Best; Committee Member: Nick Feamste

Mobile Oriented Future Internet (MOFI)

This Special Issue consists of seven papers that discuss how to enhance mobility management and its associated performance in the mobile-oriented future Internet (MOFI) environment. The first two papers deal with the architectural design and experimentation of mobility management schemes, in which new schemes are proposed and real-world testbed experimentations are performed. The subsequent three papers focus on the use of software-defined networks (SDN) for effective service provisioning in the MOFI environment, together with real-world practices and testbed experimentations. The remaining two papers discuss the network engineering issues in newly emerging mobile networks, such as flying ad-hoc networks (FANET) and connected vehicular networks

Architectures for the Future Networks and the Next Generation Internet: A Survey

Networking research funding agencies in the USA, Europe, Japan, and other countries are encouraging research on revolutionary networking architectures that may or may not be bound by the restrictions of the current TCP/IP based Internet. We present a comprehensive survey of such research projects and activities. The topics covered include various testbeds for experimentations for new architectures, new security mechanisms, content delivery mechanisms, management and control frameworks, service architectures, and routing mechanisms. Delay/Disruption tolerant networks, which allow communications even when complete end-to-end path is not available, are also discussed

An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)

With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications

Position-Based Packet Forwarding for Vehicular Ad-Hoc Networks

Mobile Ad-Hoc Networks, or MANETs, are data communication networks between (potentially) mobile computer systems equipped with wireless communication devices and — in their purest form — in complete absence of communication infrastructure. Usage scenarios for these systems include communication during disaster recovery or battlefield communications. One of the great research challenges concerning MANETs is the Packet Forwarding Problem, i.e., the question to which neighbor node a data packet should be handed over to reach non-neighboring nodes. While this problem has been previously solved by the adaption of classic routing algorithms from wired networks, the availability of GPS enables to include information about the geographic position of nodes into the routing decision, by selecting forwarders that are geographically closest to the destination. While these algorithms have been shown to improve communication performance in networks with a high degree of node mobility, they require (a) a beaconing service that allows every node to build a table of its neighbors and (b) a so-called Location Service that allows to acquire the current position of non-neighboring nodes in the network. In this thesis, we propose Contention-Based Forwarding (or CBF), a greedy routing heuristic that is no longer in need of a beaconing service. Moreover, a forwarding node running CBF does not at all select the next forwarder explicitly but broadcasts the packet containing its own position and the position of the destination. The selection of the forwarding is now done in a contention period, where every possible forwarder, i.e., every receiver of the packet, considers its own suitability to forward by calculating the geographical progress for the packet if forwarded by itself. Then it waits for a time reciprocal to this suitability before simply retransmitting. If the retransmission of a packet is overheard, the own postponed retransmission process is canceled. In this thesis, we demonstrate that CBF outperforms beacon and position-based routing by delivering packets with constant overhead, almost ignorant of mobility. Also, we introduce two strategies to cope with the problem of packet duplication. A problem left open by greedy routing heuristics is routing in the presence of local optima, or voids. Voids are node placement situations, where — in spite of an existing route — no neighboring node is geographically closer to the destination than the current forwarder. In these situations, greedy forwarding fails and standard graph-based recovery well known from classical Position-Based Forwarding cannot be applied due to the lack of the beacon-based construction of neighbor tables. As a solution, we propagate Contention-Based Distance Vector Routing, a contention-based adaption of AODV that acquires topology information in the area of the void and does contention on the topological distance to the forwarder. Besides the forwarding algorithms, we extend position-based routing by two location services. The first, the Reactive Location Service or RLS is simple, purely on-demand and very robust to mobility, the second Hierarchical Location Service, is more complex but outperforms RLS in scalability. The second big column in this thesis is ad-hoc multi-hop communication in the context of Vehicular Ad-Hoc Networks , or VANET, i.e., networks where the communication system is carried by vehicles. These systems very elegantly fit into the propositions and requirements for our more general routing approaches since they have (a) easy access to position information an (b) "suffer" from high mobility. For VANETs, we separate the routing problem into highway and city scenarios and study various routing algorithms in both. In the end, we advocate the usage of position-based routing in both scenarios; moreover, the contention-based approaches are most promising. While a lot of ad-hoc research has been deemed to be theoretical, we have also built a multi-car communication system. For this system, we provided the network and system architecture and provided the communication software. In this thesis, we will describe these efforts as a proof-of-concept and provide measurement results

Learning for Cross-layer Resource Allocation in the Framework of Cognitive Wireless Networks

The framework of cognitive wireless networks is expected to endow wireless devices with a cognition-intelligence ability with which they can efficiently learn and respond to the dynamic wireless environment. In this dissertation, we focus on the problem of developing cognitive network control mechanisms without knowing in advance an accurate network model. We study a series of cross-layer resource allocation problems in cognitive wireless networks. Based on model-free learning, optimization and game theory, we propose a framework of self-organized, adaptive strategy learning for wireless devices to (implicitly) build the understanding of the network dynamics through trial-and-error. The work of this dissertation is divided into three parts. In the first part, we investigate a distributed, single-agent decision-making problem for real-time video streaming over a time-varying wireless channel between a single pair of transmitter and receiver. By modeling the joint source-channel resource allocation process for video streaming as a constrained Markov decision process, we propose a reinforcement learning scheme to search for the optimal transmission policy without the need to know in advance the details of network dynamics. In the second part of this work, we extend our study from the single-agent to a multi-agent decision-making scenario, and study the energy-efficient power allocation problems in a two-tier, underlay heterogeneous network and in a self-sustainable green network. For the heterogeneous network, we propose a stochastic learning algorithm based on repeated games to allow individual macro- or femto-users to find a Stackelberg equilibrium without flooding the network with local action information. For the self-sustainable green network, we propose a combinatorial auction mechanism that allows mobile stations to adaptively choose the optimal base station and sub-carrier group for transmission only from local payoff and transmission strategy information. In the third part of this work, we study a cross-layer routing problem in an interweaved Cognitive Radio Network (CRN), where an accurate network model is not available and the secondary users that are distributed within the CRN only have access to local action/utility information. In order to develop a spectrum-aware routing mechanism that is robust against potential insider attackers, we model the uncoordinated interaction between CRN nodes in the dynamic wireless environment as a stochastic game. Through decomposition of the stochastic routing game, we propose two stochastic learning algorithm based on a group of repeated stage games for the secondary users to learn the best-response strategies without the need of information flooding