Should QoS routing algorithms prefer shortest paths?

Multimedia traffic and real-time e-commerce applications can experience quality degradation in traditional networks such as the Internet. These difficulties can be overcome in networks which feature dynamically set up paths with bandwidth and delay guarantees. The problem of selecting such constrained paths is the task of quality of service (QoS) routing. This paper considers link-state routing, and the choice of cost metric used to implement QoS routing. There are two schools of thought regarding the choice of link cost. It is commonly assumed that QoS routing algorithms should limit hop count so as to conserve resources for future connections. Others advocate load balancing mechanisms so as to increase overall network utilisation. This paper investigates which of these approaches gives the better performance. We show that there is no one general answer to this question. We also point out the dangers of drawing general conclusions about routing algorithm performance based on the study of only a limited set of network topologies

Traffic engineering eye diagram

It is said that a picture is worth a thousand words - this statement also applies to networking topics. Thus, to effectively monitor network performance we need tools which present the performance metrics in a graphical way which is also clear and informative. We propose a tool for this purpose which we call the traffic engineering eye diagram (TEED). Eye diagrams are used in digital communications to analyse the quality of a digital signal; the TEED can similarly he used in the traffic engineering field to analyse the load balancing ability of a TE algorithm. In this paper we describe how to create such TEEDs and how to use them to analyse and compare various traffic engineering approaches

Connectivity aware routing - a method for finding bandwidth constrained paths over a variety of network topologies

Multimedia traffic and real-time e-commerce applications can experience quality degradation in traditional networks such as the Internet. These difficulties can be overcome in networks which feature dynamically set up paths with bandwidth and delay guarantees. The problem of selecting such constrained paths is the task of quality of service (QoS) routing. Researchers have proposed several ways of implementing QoS routing, preferring either mechanisms which distribute network load or algorithms which conserve resources. Our previous studies have shown that network connectivity is an important factor when deciding which of these two approaches gives the best performance. In this paper we propose an algorithm, which features both load distribution and resource conservation. It takes a hybrid approach which balances between these two extreme approaches, according to the level of network connectivity. Our simulations indicate that this algorithm offers excellent performance over a than existing algorithms

On-Line End-to-End Congestion Control

Congestion control in the current Internet is accomplished mainly by TCP/IP. To understand the macroscopic network behavior that results from TCP/IP and similar end-to-end protocols, one main analytic technique is to show that the the protocol maximizes some global objective function of the network traffic. Here we analyze a particular end-to-end, MIMD (multiplicative-increase, multiplicative-decrease) protocol. We show that if all users of the network use the protocol, and all connections last for at least logarithmically many rounds, then the total weighted throughput (value of all packets received) is near the maximum possible. Our analysis includes round-trip-times, and (in contrast to most previous analyses) gives explicit convergence rates, allows connections to start and stop, and allows capacities to change.Comment: Proceedings IEEE Symp. Foundations of Computer Science, 200

Admission Control to Minimize Rejections and Online Set Cover with Repetitions

We study the admission control problem in general networks. Communication requests arrive over time, and the online algorithm accepts or rejects each request while maintaining the capacity limitations of the network. The admission control problem has been usually analyzed as a benefit problem, where the goal is to devise an online algorithm that accepts the maximum number of requests possible. The problem with this objective function is that even algorithms with optimal competitive ratios may reject almost all of the requests, when it would have been possible to reject only a few. This could be inappropriate for settings in which rejections are intended to be rare events. In this paper, we consider preemptive online algorithms whose goal is to minimize the number of rejected requests. Each request arrives together with the path it should be routed on. We show an $O(\log^2 (mc))$-competitive randomized algorithm for the weighted case, where $m$ is the number of edges in the graph and $c$ is the maximum edge capacity. For the unweighted case, we give an $O(\log m \log c)$-competitive randomized algorithm. This settles an open question of Blum, Kalai and Kleinberg raised in \cite{BlKaKl01}. We note that allowing preemption and handling requests with given paths are essential for avoiding trivial lower bounds

Online Admission Control and Embedding of Service Chains

The virtualization and softwarization of modern computer networks enables the definition and fast deployment of novel network services called service chains: sequences of virtualized network functions (e.g., firewalls, caches, traffic optimizers) through which traffic is routed between source and destination. This paper attends to the problem of admitting and embedding a maximum number of service chains, i.e., a maximum number of source-destination pairs which are routed via a sequence of to-be-allocated, capacitated network functions. We consider an Online variant of this maximum Service Chain Embedding Problem, short OSCEP, where requests arrive over time, in a worst-case manner. Our main contribution is a deterministic O(log L)-competitive online algorithm, under the assumption that capacities are at least logarithmic in L. We show that this is asymptotically optimal within the class of deterministic and randomized online algorithms. We also explore lower bounds for offline approximation algorithms, and prove that the offline problem is APX-hard for unit capacities and small L > 2, and even Poly-APX-hard in general, when there is no bound on L. These approximation lower bounds may be of independent interest, as they also extend to other problems such as Virtual Circuit Routing. Finally, we present an exact algorithm based on 0-1 programming, implying that the general offline SCEP is in NP and by the above hardness results it is NP-complete for constant L.Comment: early version of SIROCCO 2015 pape