Towards Internet QoS Provisioning Based on Generic Distributed QoS Adaptive Routing Engine

Increasing efficiency and quality demands of modern Internet technologies drive today’s network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature

Weighted-DESYNC and Its Application to End-to-End Throughput Fairness in Wireless Multihop Network

The end-to-end throughput of a routing path in wireless multihop network is restricted by a bottleneck node that has the smallest bandwidth among the nodes on the routing path. In this study, we propose a method for resolving the bottleneck-node problem in multihop networks, which is based on multihop DESYNC (MH-DESYNC) algorithm that is a bioinspired resource allocation method developed for use in multihop environments and enables fair resource allocation among nearby (up to two hops) neighbors. Based on MH-DESYNC, we newly propose weighted-DESYNC (W-DESYNC) as a tool artificially to control the amount of resource allocated to the specific user and thus to achieve throughput fairness over a routing path. Proposed W-DESYNC employs the weight factor of a link to determine the amount of bandwidth allocated to a node. By letting the weight factor be the link quality of a routing path and making it the same across a routing path via Cucker-Smale flocking model, we can obtain throughput fairness over a routing path. The simulation results show that the proposed algorithm achieves throughput fairness over a routing path and can increase total end-to-end throughput in wireless multihop networks

Joint Power-Efficient Traffic Shaping and Service Provisioning for Metro Elastic Optical Networks

Considering the time-averaged behavior of a metro elastic optical network, we develop a joint procedure for resource allocation and traffic shaping to exploit the inherent service diversity among the requests for power-efficient network operation. To support the quality of service diversity, we consider minimum transmission rate, average transmission rate, maximum burst size, and average transmission delay as the adjustable parameters of a general service profile. The work evolves from a stochastic optimization problem, which minimizes the power consumption subject to stability, physical, and service constraints. The optimal solution of the problem is obtained using a complex dynamic programming method. To provide a near-optimal fast-achievable solution, we propose a sequential heuristic with a scalable and causal software implementation, according to the basic Lyapunov iterations of an integer linear program. The heuristic method has a negligible optimality gap and a considerably shorter runtime compared to the optimal dynamic programming, and reduces the consumed power by 72% for an offered traffic with a unit variation coefficient. The adjustable trade-offs of the proposed scheme offer a typical 10% power saving for an acceptable amount of excess transmission delay or drop rate

QoS Routing with worst-case delay constraints: models, algorithms and performance analysis

In a network where weighted fair-queueing schedulers are used at each link, a flow is guaranteed an end-to-end worst-case delays which depends on the rate reserved for it at each link it traverses. Therefore, it is possible to compute resource-constrained paths that meet target delay constraints, and optimize some key performance metrics (e.g., minimize the overall reserved rate, maximize the remaining capacity at bottleneck links, etc.). Despite the large amount of literature that has appeared on weighted fair-queueing schedulers since the mid '90s, this has so far been done only for a single type of scheduler, probably because the complexity of solving the problem in general appeared forbidding. In this paper, we formulate and solve the optimal path computation and resource allocation problem for a broad category of weighted fair-queueing schedulers, from those emulating a Generalized Processor Sharing fluid server to variants of Deficit Round Robin. We classify schedulers according to their latency expressions, and show that a significant divide exists between those where routing a new flow affects the performance of existing flows, and those for which this do not happen. For the former, explicit admission control constraints are required to ensure that existing flows still meet their deadline afterwards. However, despite this major difference and the differences among categories of schedulers, the problem can always be formulated as a Mixed-Integer Second-Order Cone problem (MI-SOCP), and be solved at optimality in split-second times even in fairly large networks

Quality-of-service provisioning in high speed networks : routing perspectives

The continuous growth in both commercial and public network traffic with various quality-of-service (QoS) requirements is calling for better service than the current Internet\u27s best effort mechanism. One of the challenging issues is to select feasible paths that satisfy the different requirements of various applications. This problem is known as QoS routing. In general, two issues are related to QoS routing: state distribution and routing strategy. Routing strategy is used to find a feasible path that meets the QoS requirements. State distribution addresses the issue of exchanging the state information throughout the network, and can be further divided into two sub-problems: when to update and how to disseminate the state information. In this dissertation, the issue of when to update link state information from the perspective of information theory is addressed. Based on the rate-distortion analysis, an efficient scheme, which outperforms the state of the art in terms of both protocol overhead and accuracy of link state information, is presented. Second, a reliable scheme is proposed so that, when a link is broken, link state information is still reachable to all network nodes as long as the network is connected. Meanwhile, the protocol overhead is low enough to be implemented in real networks. Third, QoS routing is NP-complete. Hence, tackling this problem requires heuristics. A common approach is to convert this problem into a shortest path or k-shortest path problem and solve it by using existing algorithms such as Bellman-Ford and Dijkstra algorithms. However, this approach suffers from either high computational complexity or low success ratio in finding the feasible paths. Hence, a new problem, All Hops k-shortest Path (AHKP), is introduced and investigated. Based on the solution to AHKP, an efficient self-adaptive routing algorithm is presented, which can guarantee in finding feasible paths with fairly low average computational complexity. One of its most distinguished properties is its progressive property, which is very useful in practice: it can self-adaptively minimize its computational complexity without sacrificing its performance. In addition, routing without considering the staleness of link state information may generate a significant percentage of false routing. Our proposed routing algorithm is capable of minimizing the impact of stale link state information without stochastic link state knowledge. Fourth, the computational complexities of existing s-approximation algorithms are linearly proportional to the adopted linear scaling factors. Therefore, two efficient algorithms are proposed for finding the optimal (the smallest) linear scaling factor such that the computational complexities are reduced. Finally, an efficient algorithm is proposed for finding the least hop(s) multiple additive constrained path for the purpose of saving network resources

Advance Reservations of Bandwidth in Computer Networks

In dieser Arbeit wurden die unterschiedlichen Aspekte untersucht, die die Leistungsfähigkeit eines Systems zur Vorausreservierung in Computer-Netzwerken bestimmen. Basierend auf einer Architektur, welche den Basisdienst für Vorausreservierungen mittels Multiprotocol Label Switching (MPLS) zur Verfügung stellt, wurden innerhalb eines Netzwerkmanagementsystems unterschiedliche Dienste implementiert und simulativ auf ihre Auswirkungen auf die Leistungsfähigkeit des Netzwerks in Bezug auf Anzahl zugelassener Datenströme sowie transportierte Datenmenge untersucht. Diese Dienste erweitern in entscheidendem Maße auch die Breite des Dienstangebots in Netzwerken im Vergleich zu bisherigen Implementierungen. So ist es möglich bei Angabe einer festen Datenmenge vom Netzwerkmanagement geeignete Übertragungszeiten und raten bestimmen zu lassen. Diese Parameter werden dann, zum Beispiel in Form von Service Level Agreements (SLA), vom Netzwerkmanagement garantiert und sind insbesondere in Umgebungen wichtig, in denen die Übertragung sehr großer Datenmengen notwendig ist, beispielsweise in Grid-Computing- Systemen. Die erweiterten Dienste dienen jedoch nicht nur den Nutzern, sondern sind auch für Betreiber interessant, da sie es ermöglichen die Leistungsfähigkeit des Netzwerkes zu erhöhen. Dies ist insbesondere zusammen mit weiteren Verfahren möglich, die die zusätzlich zur Verfügung stehenden Informationen über zeitliche Aspekte, wie die Dauer von Übertragungen, nutzen. Im Vergleich zu den heute hauptsächlich betrachteten Systemen zur sog. unmittelbaren Reservierung, kann bei geschicktem Einsatz der hier implementierten Dienste und Verfahren eine deutliche Verbesserung der Leistung erzielt werden. Hinzu kommen bei Vorausreservierungen die erheblichen Vorteile für die Nutzer eines Netzwerkes, wie z.B. der oben beschriebene Datentransfer. Die Leistung eines Netzwerkes bemisst sich jedoch nicht nur an der transportierten Datenmenge, sondern auch am Verhalten im Fehlerfall und der Geschwindigkeit des Managementsystems. Dazu wurden im Rahmen dieser Arbeit mögliche Strategien zur Reaktion von Vorausreservierungssystemen im Fall von Link-Ausfällen entwickelt und untersucht. Auch hier kommt dem zeitlichen Aspekt eine wichtige Bedeutung zu. Es erwies sich als erfolgreich, nicht nur unmittelbar betroffene Datenströme sondern auch solche, die zwar bereits bekannt, jedoch noch nicht aktiv waren, in die Fehlerbehandlungsstrategie mit einzubeziehen. Datenstrukturen, die von der Zugangskontrolle des Managementsystems benötigt werden und dort die Geschwindigkeit maßgeblich bestimmen, wurden unter den Aspekten der Zugriffsgeschwindigkeit und des Speicherverbrauchs untersucht. Hierbei wurde gezeigt, dass Arrays erhebliche Vorteile im Hinblick auf beide Aspekte haben und in den meisten Fällen einer Baumstruktur, die speziell für die Aufgabe innerhalb der Zugangskontrolle entwickelt wurde, überlegen sind. Die Nutzung von Vorausreservierungen in Computer-Netzwerken ist damit eine nützliche und wichtige Erweiterung der Funktionalität eines Netzwerkes sowohl in Bezug auf das zur Verfügung stehende Angebot an Diensten, als auch im Hinblick auf die Leistungsfähigkeit des Netzwerkes.In this thesis, the impact of using advance reservations of bandwidth in a computer network on the performance for both clients and operators of the network is examined. Based on an architecture that uses multi-protocol label switching (MPLS) controlled by bandwidth brokers, a number of services that - compared to todays best-effort or immediate reservation networks - provide an enhanced functionality for clients were developed. These services allow clients to specify requests in a less stringent way than currently necessary, for example, it is possible to define only the amount of data to be transmitted between two network endpoints and the management system then determines suitable transmission parameters such as start and stop time and transmission rate. This functionality provides reliable feedback to clients and can serve as a foundation for providing service-level agreements, e.g., guaranteeing deadlines for the transmission of a certain amount of data. The additional services can also be used by network operators to improve the overall utilization of the network. In addition, the various opportunities of using the additional temporal dimension of the advance reservation service are suitable to improve the network performance. It can be shown that the amount of blocked requests and bandwidth can be considerably decreased making use of both services and the additional information available in the given environment. Besides the achievable throughout and amount of admitted requests, the term performance in the context of advance reservation systems also covers other aspects such as failure recovery strategies and the processing time required by the network management system. In the thesis, several strategies to be applied in case of link failures are outlined and examined with respect to their applicability and achievable performance. For example, it can be shown that it is worthwhile to consider not only flows which are active at the time a failure occurs but also to take inactive but already admitted flows into account in order to achieve the best possible performance. In addition to failure recovery, also the processing speed of the management system is of importance. For that purpose, in particular the data structures used to store the current and future network status need to be examined since they dominate the processing time of the management system. Two data structures, arrays and a tree which was especially designed for this purpose were examined, showing that arrays are superior with respect to processing speed and memory consumption in almost any environment

Software-Driven and Virtualized Architectures for Scalable 5G Networks

In this dissertation, we argue that it is essential to rearchitect 4G cellular core networks–sitting between the Internet and the radio access network–to meet the scalability, performance, and flexibility requirements of 5G networks. Today, there is a growing consensus among operators and research community that software-defined networking (SDN), network function virtualization (NFV), and mobile edge computing (MEC) paradigms will be the key ingredients of the next-generation cellular networks. Motivated by these trends, we design and optimize three core network architectures, SoftMoW, SoftBox, and SkyCore, for different network scales, objectives, and conditions. SoftMoW provides global control over nationwide core networks with the ultimate goal of enabling new routing and mobility optimizations. SoftBox attempts to enhance policy enforcement in statewide core networks to enable low-latency, signaling-efficient, and customized services for mobile devices. Sky- Core is aimed at realizing a compact core network for citywide UAV-based radio networks that are going to serve first responders in the future. Network slicing techniques make it possible to deploy these solutions on the same infrastructure in parallel. To better support mobility and provide verifiable security, these architectures can use an addressing scheme that separates network locations and identities with self-certifying, flat and non-aggregatable address components. To benefit the proposed architectures, we designed a high-speed and memory-efficient router, called Caesar, for this type of addressing schemePHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146130/1/moradi_1.pd

Analysis of bandwidth allocation on end-to-end QoS networks under budget control

AbstractThis paper considers the problem of bandwidth allocation on communication networks with multiple classes of traffic, where bandwidth is determined under the budget constraint. Due to the limited budget, there is a risk that the network service providers can not assert a 100% guaranteed availability for the stochastic traffic demand at all times. We derive the blocking probabilities of connections as a function of bandwidth, traffic demand and the available number of virtual paths based on the Erlang loss formula for all service classes. A revenue/profit function is studied through the monotonicity and convexity of the blocking probability and expected path occupancy. We present the optimality conditions and develop a solution algorithm for optimal bandwidth of revenue management schemes. The sensitivity analysis and three economic elasticity notions are also proposed to investigate the marginal revenue for a given traffic class by changing bandwidth, traffic demand and the number of virtual paths, respectively. By analysis of those monotone and convex properties, it significantly facilitates the operational process in the efficient design and provision of a core network under the budget constraint

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

Media Flow Rate Allocation in Multipath Networks

We address the problem of joint path selection and video source rate allocation in multipath streaming in order to optimize a media specific quality of service. An optimization problem is proposed, which aims at minimizing a video distortion metric based on sequence-dependent parameters, and transmission channel characteristics, for a given network infrastructure.An in-depth analysis of the media distortion evolution allows us to define a low complexity algorithm for an optimal rate allocation in multipath network scenarios. In particular, we show that a greedy allocation of rate along paths with increasing error probability leads to an optimal solution. We argue that a network path shall not be chosen for transmission, unless all other available paths with lower error probability have been chosen. Moreover, the chosen paths should be used at their maximum available end-to-end bandwidth. Simulation results show that the optimal rate allocation carefully trades off total encoding/transmission rate, with the end-to-end transmission error probability and the number of chosen paths. In many cases, the optimal rate allocation provides more than 2