Best effort measurement based congestion control

Abstract available: p.

Internet Daemons: Digital Communications Possessed

We’re used to talking about how tech giants like Google, Facebook, and Amazon rule the internet, but what about daemons? Ubiquitous programs that have colonized the Net’s infrastructure—as well as the devices we use to access it—daemons are little known. Fenwick McKelvey weaves together history, theory, and policy to give a full account of where daemons come from and how they influence our lives—including their role in hot-button issues like network neutrality. Going back to Victorian times and the popular thought experiment Maxwell’s Demon, McKelvey charts how daemons evolved from concept to reality, eventually blossoming into the pandaemonium of code-based creatures that today orchestrates our internet. Digging into real-life examples like sluggish connection speeds, Comcast’s efforts to control peer-to-peer networking, and Pirate Bay’s attempts to elude daemonic control (and skirt copyright), McKelvey shows how daemons have been central to the internet, greatly influencing everyday users. Internet Daemons asks important questions about how much control is being handed over to these automated, autonomous programs, and the consequences for transparency and oversight. Table of Contents Abbreviations and Technical Terms Introduction 1. The Devil We Know: Maxwell’s Demon, Cyborg Sciences, and Flow Control 2. Possessing Infrastructure: Nonsynchronous Communication, IMPs, and Optimization 3. IMPs, OLIVERs, and Gateways: Internetworking before the Internet 4. Pandaemonium: The Internet as Daemons 5. Suffering from Buffering? Affects of Flow Control 6. The Disoptimized: The Ambiguous Tactics of the Pirate Bay 7. A Crescendo of Online Interactive Debugging? Gamers, Publics and Daemons Conclusion Acknowledgments Appendix: Internet Measurement and Mediators Notes Bibliography Index Reviews Beneath social media, beneath search, Internet Daemons reveals another layer of algorithms: deeper, burrowed into information networks. Fenwick McKelvey is the best kind of intellectual spelunker, taking us deep into the infrastructure and shining his light on these obscure but vital mechanisms. What he has delivered is a precise and provocative rethinking of how to conceive of power in and among networks. —Tarleton Gillespie, author of Custodians of the Internet Internet Daemons is an original and important contribution to the field of digital media studies. Fenwick McKelvey extensively maps and analyzes how daemons influence data exchanges across Internet infrastructures. This study insightfully demonstrates how daemons are transformative entities that enable particular ways of transferring information and connecting up communication, with significant social and political consequences. —Jennifer Gabrys, author of Program Eart

Traffic Profiles and Performance Modelling of Heterogeneous Networks

This thesis considers the analysis and study of short and long-term traffic patterns of heterogeneous networks. A large number of traffic profiles from different locations and network environments have been determined. The result of the analysis of these patterns has led to a new parameter, namely the 'application signature'. It was found that these signatures manifest themselves in various granularities over time, and are usually unique to an application, permanent virtual circuit (PVC), user or service. The differentiation of the application signatures into different categories creates a foundation for short and long-term management of networks. The thesis therefore looks from the micro and macro perspective on traffic management, covering both aspects. The long-term traffic patterns have been used to develop a novel methodology for network planning and design. As the size and complexity of interconnected systems grow steadily, usually covering different time zones, geographical and political areas, a new methodology has been developed as part of this thesis. A part of the methodology is a new overbooking mechanism, which stands in contrast to existing overbooking methods created by companies like Bell Labs. The new overbooking provides companies with cheaper network design and higher average throughput. In addition, new requirements like risk factors have been incorporated into the methodology, which lay historically outside the design process. A large network service provider has implemented the overbooking mechanism into their network planning process, enabling practical evaluation. The other aspect of the thesis looks at short-term traffic patterns, to analyse how congestion can be controlled. Reoccurring short-term traffic patterns, the application signatures, have been used for this research to develop the "packet train model" further. Through this research a new congestion control mechanism was created to investigate how the application signatures and the "extended packet train model" could be used. To validate the results, a software simulation has been written that executes the proprietary congestion mechanism and the new mechanism for comparison. Application signatures for the TCP/IP protocols have been applied in the simulation and the results are displayed and discussed in the thesis. The findings show the effects that frame relay congestion control mechanisms have on TCP/IP, where the re-sending of segments, buffer allocation, delay and throughput are compared. The results prove that application signatures can be used effectively to enhance existing congestion control mechanisms.AT&T (UK) Ltd, Englan

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

Simulation and analysis of adaptive routing and flow control in wide area communication networks

This thesis presents the development of new simulation and analytic models for the performance analysis of wide area communication networks. The models are used to analyse adaptive routing and flow control in fully connected circuit switched and sparsely connected packet switched networks. In particular the performance of routing algorithms derived from the L(_R-I) linear learning automata model are assessed for both types of network. A novel architecture using the INMOS Transputer is constructed for simulation of both circuit and packet switched networks in a loosely coupled multi- microprocessor environment. The network topology is mapped onto an identically configured array of processing centres to overcome the processing bottleneck of conventional Von Neumann architecture machines. Previous analytic work in circuit switched work is extended to include both asymmetrical networks and adaptive routing policies. In the analysis of packet switched networks analytic models of adaptive routing and flow control are integrated to produce a powerful, integrated environment for performance analysis The work concludes that routing algorithms based on linear learning automata have significant potential in both fully connected circuit switched networks and sparsely connected packet switched networks

Adaptive control of communication networks using learning automata.

This research investigates communications network routing procedures, based on distributed learning automata concepts for circuit and packet switched networks. For this application, the learning automaton is shown to be an ideal adaptive control mechanism, with simple feedback and updating strategies which allow extremely practical implementations and perform very close to the desired optimum. In this thesis, the nature of learning automata routing schemes are explored by analytical and computer simulation techniques, primarily developing an elementary understanding of the automata routing and adaption process. Using simple circuit and message switched networks the conditions for minimum blocking probability and average delay are established and compared with the equilibrium behaviour of learning automata operating under alternative reinforcement algorithms. Later, large scale simulations of real networks are used to demonstrate and relate the learning automata scheme to existing routing techniques. These experiments, which are performed on sophisticated simulation packages produced for this study, take as examples hierarchical and general structured telephone networks and packet switched communications networks configured with both virtual call and datagram protocols. In addition, studies under failure mode conditions, including link, node and focussed overloads, conclusively demonstrate the superior performance afforded by the learning automata routing approach

Traffic Re-engineering: Extending Resource Pooling Through the Application of Re-feedback

Parallelism pervades the Internet, yet efficiently pooling this increasing path diversity has remained elusive. With no holistic solution for resource pooling, each layer of the Internet architecture attempts to balance traffic according to its own needs, potentially at the expense of others. From the edges, traffic is implicitly pooled over multiple paths by retrieving content from different sources. Within the network, traffic is explicitly balanced across multiple links through the use of traffic engineering. This work explores how the current architecture can be realigned to facilitate resource pooling at both network and transport layers, where tension between stakeholders is strongest. The central theme of this thesis is that traffic engineering can be performed more efficiently, flexibly and robustly through the use of re-feedback. A cross-layer architecture is proposed for sharing the responsibility for resource pooling across both hosts and network. Building on this framework, two novel forms of traffic management are evaluated. Efficient pooling of traffic across paths is achieved through the development of an in-network congestion balancer, which can function in the absence of multipath transport. Network and transport mechanisms are then designed and implemented to facilitate path fail-over, greatly improving resilience without requiring receiver side cooperation. These contributions are framed by a longitudinal measurement study which provides evidence for many of the design choices taken. A methodology for scalably recovering flow metrics from passive traces is developed which in turn is systematically applied to over five years of interdomain traffic data. The resulting findings challenge traditional assumptions on the preponderance of congestion control on resource sharing, with over half of all traffic being constrained by limits other than network capacity. All of the above represent concerted attempts to rethink and reassert traffic engineering in an Internet where competing solutions for resource pooling proliferate. By delegating responsibilities currently overloading the routing architecture towards hosts and re-engineering traffic management around the core strengths of the network, the proposed architectural changes allow the tussle surrounding resource pooling to be drawn out without compromising the scalability and evolvability of the Internet

Simulated Annealing

The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production