Generalized load sharing for packet-switching networks

In this paper, we propose a framework to study how to effectively perform load sharing in multipath communication networks. A generalized load sharing (GLS) model has been developed to conceptualize how traffic is split ideally on a set of active paths. A simple traffic splitting algorithm, called weighted fair routing (WFR), has been developed at two different granularity level, namely, the packet level, and the call level, to approximate GLS with the given routing weight vector. The packet-by-packet WFR (PWFR) mimics GLS by transmitting each packet as a whole, whereas the call-by-call WFR (CWFR) imitates GLS so that all packets belonging to a single flow are sent on the same path. We have developed some performance bounds for PWFR and found that PWFR is a deterministically fair traffic splitting algorithm. This attractive property is useful in the provision of service with guaranteed performance when multiple paths can be used simultaneously to transmit packets which belong to the same flow. Our simulation studies, based on a collection of Internet backbone traces, reveal that WFR outperforms two other traffic splitting algorithms, namely, generalized round robin routing (GRR), and probabilistic routing (PRR). These promising results form a basis for designing future adaptive constraint-based multipath routing protocols.published_or_final_versio

Improving Real-Time Data Dissemination Performance by Multi Path Data Scheduling in Data Grids

The performance of data grids for data intensive, real-time applications is highly dependent on the data dissemination algorithm employed in the system. Motivated by this fact, this study first formally defines the real-time splittable data dissemination problem (RTS/DDP) where data transfer requests can be routed over multiple paths to maximize the number of data transfers to be completed before their deadlines. Since RTS/DDP is proved to be NP-hard, four different heuristic algorithms, namely kSP/ESMP, kSP/BSMP, kDP/ESMP, and kDP/BSMP are proposed. The performance of these heuristic algorithms is analyzed through an extensive set of data grid system simulation scenarios. The simulation results reveal that a performance increase up to 8 % as compared to a very competitive single path data dissemination algorithm is possible

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

Delay-constrained Routing Problems: Accurate Scheduling Models and Admission Control

As shown in [1], the problem of routing a flow subject to a worst-case end-to-end delay constraint in a packed-based network can be formulated as a Mixed-Integer Second-Order Cone Program, and solved with general-purpose tools in real time on realistic instances. However, that result only holds for one particular class of packet schedulers, Strictly Rate-Proportional ones, and implicitly considering each link to be fully loaded, so that the reserved rate of a flow coincides with its guaranteed rate. These assumptions make latency expressions simpler, and enforce perfect isolation between flows, i.e., admitting a new flow cannot increase the delay of existing ones. Other commonplace schedulers both yield more complex latency formulæ and do not enforce flow isolation. Furthermore, the delay actually depends on the guaranteed rate of the flow, which can be significantly larger than the reserved rate if the network is unloaded. In this paper we extend the result to other classes of schedulers and to a more accurate representation of the latency, showing that, even when admission control needs to be factored in, the problem is still efficiently solvable for realistic instances, provided that the right modeling choices are made. Keywords: Routing problems, maximum delay constraints, scheduling algorithms, admission control, Second-Order Cone Programs, Perspective Reformulatio

Delay-constrained shortest paths: approximation algorithms and second-order cone models

Routing real-time traffic with maximum packet delay in contemporary telecommunication networks requires not only choosing a path, but also reserving transmission capacity along its arcs, as the delay is a nonlinear function of both components. The problem is known to be solvable in polynomial time under quite restrictive assumptions, i.e., Equal Rate Allocations (all arcs are reserved the same capacity) and identical reservation costs, whereas the general problem is NP-hard. We first extend the approaches to the ERA version to a pseudo-polynomial Dynamic Programming one for integer arc costs, and a FPTAS for the case of general arc costs. We then show that the general problem can be formulated as a mixed-integer Second-Order Cone (SOCP) program, and therefore solved with off-the-shelf technology. We compare two formulations: one based on standard big-M constraints, and one where Perspective Reformulation techniques are used to tighten the continuous relaxation. Extensive computational experiments on both real-world networks and randomly-generated realistic ones show that the ERA approach is fast and provides an effective heuristic for the general problem whenever it manages to find a solution at all, but it fails for a significant fraction of the instances that the SOCP models can solve. We therefore propose a three-pronged approach that combines the fast running time of the ERA algorithm and the effectiveness of the SOCP models, and show that it is capable of solving realistic-sized instances with high accuracy at different levels of network load in a time compatible with real-time usage in an operating environment

Bursting the broadband bubble

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Broadband has revolutionised the way the Internet is used and has become the critical enabling infrastructure of our modem and knowledge-based economy. Its widespread introduction has not only greatly enhanced the speed at which information online can be accessed, but also the range and sophistication of the content available. It is still penetrating the telecommunication market and is seen by some as the most significant evolutionary step since the emergence of the Internet. However in the rush to achieve market share, there is a risk that insufficient attention may be paid to quality issues, the central theme of this research. The research addresses the issues of broadband quality with a stated objective of assessing broadband quality by means of an integrated framework that encompasses factors beyond strict technical characteristics of broadband networks. Indeed, the concept of quality is a multi-facetted one, for which various perspectives can be distinguished. In this work, broadband quality as perceived by users, ISP and Government in the United Kingdom (UK) is looked at and a survey report is given and analysed. The aim of this doctoral research was to provide much needed empirical broadband quality framework that would guide the service provider as well as the UK government in the provision of quality broadband to its consumers. It will also stand as a benchmark to countries wanting to provide quality broadband to its citizens. A survey research approach was employed to achieve the overall aim and objective of this research. This was conducted using the response of 133 participants located in various boroughs in the UK. The results of the survey show that quality, though desired by many, has been short-changed by the desire to have access to the Internet via broadband at the lowest cost possible. However, this has not encouraged some consumers to switch to broadband from dial-up service despite continuous low prices being offered by service providers. Furthermore, the results also indicated that focusing on broadband quality will improve and promote investment in broadband capacity and decrease the uncertainty in consumer demand for applications such as multi-media content delivery, enhanced electronic commerce and telecommuting that exploit broadband access

Delay-aware Link Scheduling and Routing in Wireless Mesh Networks

Resource allocation is a critical task in computer networks because of their capital-intensive nature. In this thesis we apply operations research tools and technologies to model, solve and analyze resource allocation problems in computer networks with real-time traffic. We first study Wireless Mesh Networks, addressing the problem of link scheduling with end-to-end delay constraints. Exploiting results obtained with the Network Calculus framework, we formulate the problem as an integer non-linear optimization problem. We show that the feasibility of a link schedule does depend on the aggregation framework. We also address the problem of jointly solving the routing and link scheduling problem optimally, taking into account end-to-end delay guarantees. We provide guidelines and heuristics. As a second contribution, we propose a time division approach in CSMA MAC protocols in the context of 802.11 WLANs. By grouping wireless clients and scheduling time slots to these groups, not only the delay of packet transmission can be decreased, but also the goodput of multiple WLANs can be largely increased. Finally, we address a resource allocation problem in wired networks for guaranteed-delay traffic engineering. We formulate and solve the problem under different latency models. Global optimization let feasible schedules to be computed with instances where local resource allocation schemes would fail. We show that this is the case even with a case-study network, and at surprisingly low average loads