Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods

Copyright @ 2010 Elsevier B.V. All rights reserved.In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the channel assignment. Therefore they bear severe drawback, that is, channel assignment cannot work well with the determined multicast tree. In this paper, we integrate them together and solve it by intelligent computational methods. First, we develop a unified framework which consists of the problem formulation, the solution representation, the fitness function, and the channel assignment algorithm. Then, we propose three separate algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and tabu search). These three algorithms aim to search minimum-interference multicast trees which also satisfy the end-to-end delay constraint and optimize the usage of the scarce radio network resource in wireless mesh networks. To achieve this goal, the optimization techniques based on state of the art genetic algorithm and the techniques to control the annealing process and the tabu search procedure are well developed separately. Simulation results show that the proposed three intelligent computational methods based multicast algorithms all achieve better performance in terms of both the total channel conflict and the tree cost than those comparative references.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

Traffic and Resource Management in Robust Cloud Data Center Networks

Cloud Computing is becoming the mainstream paradigm, as organizations, both large and small, begin to harness its benefits. Cloud computing gained its success for giving IT exactly what it needed: The ability to grow and shrink computing resources, on the go, in a cost-effective manner, without the anguish of infrastructure design and setup. The ability to adapt computing demands to market fluctuations is just one of the many benefits that cloud computing has to offer, this is why this new paradigm is rising rapidly. According to a Gartner report, the total sales of the various cloud services will be worth 204 billion dollars worldwide in 2016. With this massive growth, the performance of the underlying infrastructure is crucial to its success and sustainability. Currently, cloud computing heavily depends on data centers for its daily business needs. In fact, it is through the virtualization of data centers that the concept of "computing as a utility" emerged. However, data center virtualization is still in its infancy; and there exists a plethora of open research issues and challenges related to data center virtualization, including but not limited to, optimized topologies and protocols, embedding design methods and online algorithms, resource provisioning and allocation, data center energy efficiency, fault tolerance issues and fault tolerant design, improving service availability under failure conditions, enabling network programmability, etc. This dissertation will attempt to elaborate and address key research challenges and problems related to the design and operation of efficient virtualized data centers and data center infrastructure for cloud services. In particular, we investigate the problem of scalable traffic management and traffic engineering methods in data center networks and present a decomposition method to exactly solve the problem with considerable runtime improvement over mathematical-based formulations. To maximize the network's admissibility and increase its revenue, cloud providers must make efficient use of their's network resources. This goal is highly correlated with the employed resource allocation/placement schemes; formally known as the virtual network embedding problem. This thesis looks at multi-facets of this latter problem; in particular, we study the embedding problem for services with one-to-many communication mode; or what we denote as the multicast virtual network embedding problem. Then, we tackle the survivable virtual network embedding problem by proposing a fault-tolerance design that provides guaranteed service continuity in the event of server failure. Furthermore, we consider the embedding problem for elastic services in the event of heterogeneous node failures. Finally, in the effort to enable and support data center network programmability, we study the placement problem of softwarized network functions (e.g., load balancers, firewalls, etc.), formally known as the virtual network function assignment problem. Owing to its combinatorial complexity, we propose a novel decomposition method, and we numerically show that it is hundred times faster than mathematical formulations from recent existing literature

Improving Multicast Communications Over Wireless Mesh Networks

In wireless mesh networks (WMNs) the traditional approach to shortest path tree based multicasting is to cater for the needs of the poorest performingnode i.e. the maximum permitted multicast line rate is limited to the lowest line rate used by the individual Child nodes on a branch. In general, this meansfixing the line rate to its minimum value and fixing the transmit power to its maximum permitted value. This simplistic approach of applying a single multicast rate for all nodes in the multicast group results in a sub-optimal trade-off between the mean network throughput and coverage area that does not allow for high bandwidth multimedia applications to be supported. By relaxing this constraint and allowing multiple line rates to be used, the mean network throughput can be improved. This thesis presents two methods that aim to increase the mean network throughput through the use of multiple line rates by the forwarding nodes. This is achieved by identifying the Child nodes responsible for reducing the multicast group rate. The first method identifies specific locations for the placement of relay nodes which allows for higher multicast branch line rates to be used. The second method uses a power control algorithm to tune the transmit power to allow for higher multicast branch line rates. The use of power control also helps to reduce the interference caused to neighbouring nodes.Through extensive computer simulation it can be shown that these two methods can lead to a four-fold gain in the mean network throughput undertypical WMN operating conditions compared with the single line rate case

A Survey of Scheduling in Time-Sensitive Networking (TSN)

TSN is an enhancement of Ethernet which provides various mechanisms for real-time communication. Time-triggered (TT) traffic represents periodic data streams with strict real-time requirements. Amongst others, TSN supports scheduled transmission of TT streams, i.e., the transmission of their packets by edge nodes is coordinated in such a way that none or very little queuing delay occurs in intermediate nodes. TSN supports multiple priority queues per egress port. The TAS uses so-called gates to explicitly allow and block these queues for transmission on a short periodic timescale. The TAS is utilized to protect scheduled traffic from other traffic to minimize its queuing delay. In this work, we consider scheduling in TSN which comprises the computation of periodic transmission instants at edge nodes and the periodic opening and closing of queue gates. In this paper, we first give a brief overview of TSN features and standards. We state the TSN scheduling problem and explain common extensions which also include optimization problems. We review scheduling and optimization methods that have been used in this context. Then, the contribution of currently available research work is surveyed. We extract and compile optimization objectives, solved problem instances, and evaluation results. Research domains are identified, and specific contributions are analyzed. Finally, we discuss potential research directions and open problems.Comment: 34 pages, 19 figures, 9 tables 110 reference

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

On Near Optimal Time and Dynamic Delay and Delay Variation Multicast Algorithms

Multicast is one of the most prevalent communication modes in computer networks. A plethora of systems and applications today rely on multicast communication to disseminate traffic including but not limited to teleconferencing, videoconferencing, stock exchanges, supercomputers, software update distribution, distributed database systems, and gaming. This dissertation elaborates and addresses key research challenges and problems related to the design and implementation of multicast algorithms. In particular, it investigates the problems of (1) Designing near optimal multicast time algorithms for mesh and torus connected systems and (2) Designing efficient algorithms for Delay and Delay Variation Bounded Multicast (DVBM). To achieve the first goal, improvements on four tree based multicast algorithms are made: Modified PAIR (MPAIR), Modified DIAG (MDIAG), Modified MIN (MMIN), and Modified DIST (MDIST). The proof that MDIAG generates optimal or optimal plus one multicast time in 2-Dimensional (2D) mesh networks is provided. The hybrid version of MDIAG (HMDIAG) is designed, that gives a 3-additive approximation algorithm on multicast time in 2D torus networks. To make HMDIAG applicable on systems using higher dimensional meshes and tori, it is extended and the proof that it gives a (2n-1)-additive approximation algorithm on multicast time in nD torus networks is given. To address the second goal, Directional Core Selection (DCS) algorithm for core selection and DVBM Tree generation is designed. To further reduce the delay variation of trees generated by DCS, a k-shortest-path based algorithm, Build Lower Variation Tree (BLVT) is designed. To tackle dynamic join/leave requests to the ongoing multicast session, the dynamic version of both algorithms is given that responds to requests by reorganizing the tree and avoiding session disruption. To solve cases where single-core based algorithms fail to construct a DVBM tree, a dynamic three-phase algorithm, Multi-core DVBM Trees (MCDVBMT) is designed, that semi-matches group members to core nodes

Optimization Methods for Optical Long-Haul and Access Networks

Optical communications based on fiber optics and the associated technologies have seen remarkable progress over the past two decades. Widespread deployment of optical fiber has been witnessed in backbone and metro networks as well as access segments connecting to customer premises and homes. Designing and developing a reliable, robust and efficient end-to-end optical communication system have thus emerged as topics of utmost importance both to researchers and network operators. To fulfill these requirements, various problems have surfaced and received attention, such as network planning, capacity placement, traffic grooming, traffic scheduling, and bandwidth allocation. The optimal network design aims at addressing (one or more of) these problems based on some optimization objectives. In this thesis, we consider two of the most important problems in optical networks; namely the survivability in optical long-haul networks and the problem of bandwidth allocation and scheduling in optical access networks. For the former, we present efficient and accurate models for availability-aware design and service provisioning in p-cycle based survivable networks. We also derive optimization models for survivable network design based on p-trail, a more general protection structure, and compare its performance with p-cycles. Indeed, major cost savings can be obtained when the optical access and long-haul subnetworks become closer to each other by means of consolidation of access and metro networks. As this distance between long-haul and access networks reduces, and the need and expectations from passive optical access networks (PONs) soar, it becomes crucial to efficiently manage bandwidth in the access while providing the desired level of service availability in the long-haul backbone. We therefore address in this thesis the problem of bandwidth management and scheduling in passive optical networks; we design efficient joint and non-joint scheduling and bandwidth allocation methods for multichannel PON as well as next generation 10Gbps Ethernet PON (10G-EPON) while addressing the problem of coexistence between 10G-EPONs and multichannel PONs

Design and provisioning of WDM networks for traffic grooming

Wavelength Division Multiplexing (WDM) is the most viable technique for utilizing the enormous amounts of bandwidth inherently available in optical fibers. However, the bandwidth offered by a single wavelength in WDM networks is on the order of tens of Gigabits per second, while most of the applications\u27 bandwidth requirements are still subwavelength. Therefore, cost-effective design and provisioning of WDM networks require that traffic from different sessions share bandwidth of a single wavelength by employing electronic multiplexing at higher layers. This is known as traffic grooming. Optical networks supporting traffic grooming are usually designed in a way such that the cost of the higher layer equipment used to support a given traffic matrix is reduced. In this thesis, we propose a number of optimal and heuristic solutions for the design and provisioning of optical networks for traffic grooming with an objective of network cost reduction. In doing so, we address several practical issues. Specifically, we address the design and provisioning of WDM networks on unidirectional and bidirectional rings for arbitrary unicast traffic grooming, and on mesh topologies for arbitrary multipoint traffic grooming. In multipoint traffic grooming, we address both multicast and many-to-one traffic grooming problems. We provide a unified frame work for optimal and approximate network dimensioning and channel provisioning for the generic multicast traffic grooming problem, as well as some variants of the problem. For many-to-one traffic grooming we propose optimal as well as heuristic solutions. Optimal formulations which are inherently non-linear are mapped to an optimal linear formulation. In the heuristic solutions, we employ different problem specific search strategies to explore the solution space. We provide a number of experimental results to show the efficacy of our proposed techniques for the traffic grooming problem in WDM networks