Queuing delays in randomized load balanced networks

Valiant’s concept of Randomized Load Balancing (RLB), also promoted under the name ‘two-phase routing’, has previously been shown to provide a cost-effective way of implementing overlay networks that are robust to dynamically changing demand patterns. RLB is accomplished in two steps; in the first step, traffic is randomly distributed across the network, and in the second step traffic is routed to the final destination. One of the benefits of RLB is that packets experience only a single stage of routing, thus reducing queueing delays associated with multi-hop architectures. In this paper, we study the queuing performance of RLB, both through analytical methods and packet-level simulations using ns2 on three representative carrier networks. We show that purely random traffic splitting in the randomization step of RLB leads to higher queuing delays than pseudo-random splitting using, e.g., a round-robin schedule. Furthermore, we show that, for pseudo-random scheduling, queuing delays depend significantly on the degree of uniformity of the offered demand patterns, with uniform demand matrices representing a provably worst-case scenario. These results are independent of whether RLB employs priority mechanisms between traffic from step one over step two. A comparison with multi-hop shortest-path routing reveals that RLB eliminates the occurrence of demand-specific hot spots in the network

Algorithmic Implementation of Load Balancing –in Wireless LAN

Intra domain traffic engineering (TE) has become an indispensable tool for Internet service providers (ISPs) to Optimize network performance and utilize network resources efficiently . Various explicitrouting TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires large ternary content addressable memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this paper, we present an approach, called generalized destination-based multipath routing (GDMR), to achieve the same high performance as explicit routing. The main contribution of this paper is that we prove that an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR

Algorithmic Implementation of Load Balancing �in Wireless LAN

Intra domain traffic engineering (TE) has become an indispensable tool for Internet Service Providers (ISPs) to optimize network performance and utilize network resources efficiently. Various explicit routing TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires Large Ternary Content Addressable Memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this project, we present an approach, called Generalized Destination-Based Multipath Routing (GDMR), to achieve the high performance as explicit routing. The main contribution of this project is to enhance an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR

Auto-bandwidth control in dynamically reconfigured hybrid-SDN MPLS networks

The proposition of this work is based on the steady evolution of bandwidth demanding technology, which currently and more so in future, requires operators to use expensive infrastructure capability smartly to maximise its use in a very competitive environment. In this thesis, a traffic engineering control loop is proposed that dynamically adjusts the bandwidth and route of flows of Multi-Protocol Label Switching (MPLS) tunnels in response to changes in traffic demand. Available bandwidth is shifted to where the demand is, and where the demand requirement has dropped, unused allocated bandwidth is returned to the network. An MPLS network enhanced with Software-defined Networking (SDN) features is implemented. The technology known as hybrid SDN combines the programmability features of SDN with the robust MPLS label switched path features along with traffic engineering enhancements introduced by routing protocols such as Border Gateway Patrol-Traffic Engineering (BGP-TE) and Open Shortest Path First-Traffic Engineering (OSPF-TE). The implemented mixed-integer linear programming formulation using the minimisation of maximum link utilisation and minimum link cost objective functions, combined with the programmability of the hybrid SDN network allows for source to destination demand fluctuations. A key driver to this research is the programmability of the MPLS network, enhanced by the contributions that the SDN controller technology introduced. The centralised view of the network provides the network state information needed to drive the mathematical modelling of the network. The path computation element further enables control of the label switched path's bandwidths, which is adjusted based on current demand and optimisation method used. The hose model is used to specify a range of traffic conditions. The most important benefit of the hose model is the flexibility that is allowed in how the traffic matrix can change if the aggregate traffic demand does not exceed the hose maximum bandwidth specification. To this end, reserved hose bandwidth can now be released to the core network to service demands from other sites

Design Issues of Reserved Delivery Subnetworks

In this proposal, we introduce the reserved delivery subnetwork (RDS), a mechanism that can al-low information service providers to deliver more consistent service to their customers without perflow resource reservation. In addition to service performance improvements, reserved delivery sub-networks can also provide protection against network resource attacks. Many applications such asweb content delivery services and virtual private networks can benefit from reserved delivery sub-networks. We address a number of issues with the deployment of RDSs. First, we formulate theconfiguration problem of an RDS as a minimum concave cost network flow problem, where the perunit flow cost decreases as the current flow increases. An approximation heuristic is presented andstudied to solve this configuration problem. Second, we extend our study to the configuration prob-lem of RDSs with multiple sources. We also investigate the configuration problem for subnetworksthat allow load redistribution and load balancing among the sources. In addition, we plan to studyhow to use RDS proxies to regulate the flow of traffic to end users, so as to minimize network delay

Robust routing under dynamic traffic demands

In order to provide service reliability with reasonable quality, it is essential for the network operator to manage the traffic flows in the core network. Managing traffic in the network is performed as routing function. In the traditional traffic management, network operator can tune routing parameters to simply manage the traffic. But traditional routing methods are not designed to handle the sudden fluctuations in the traffic. As a result, this may apparently lead to the traffic congestions in some parts of the core network, leaving other part underutilized. In this thesis we explore issues related to the routing robustness in the face of traffic demand variations. We investigate different routing methods for efficient routing using maximum link utilization (MLU) as a performance metric. The primary advantage of using link utilization is its ease to compute the network performance on real network data and synthetic data. Overloaded links might result in Quality of Service degradation (e.g. larger packet delay, packet losses etc.), so MLU might be a useful measure of network performance. For the experimentation, we have used unique data from the real operational network available in the public domain and the random data for large network topology instances. Furthermore, we propose a simple routing algorithm called Robust Routing Technique (RRT) to implement a robust routing mechanism. This mechanism allows network operator to satisfy the networking goals such as load balancing, routing robustness to the range of traffic demand matrices, link failures or to the traffic changes caused by uncertain traffic demands. Simulation experiments with real network topologies and random topologies demonstrate that our routing solution is simple (for routing) and flexible (for forwarding). K-Shortest path implementation in RRT can be extended for Multi Protocol Label Switching. Finally, we evaluate the performance of robust routing under dynamic traffic demands. We formulate the problem as a multi commodity flow problem using linear programming. We use congestion ratio to define the robust routing performance. We provide a variant to the existing robust routing mechanisms by modelling traffic demand due to Distributed Denial of service attacks or worms. Simulation results are compared with the popular OSPF traffic engineering algorithm to provide effectiveness to the proposed routing scheme. Simulation results are compared with the popular OSPF traffic engineering algorithm to provide effectiveness to the proposed routing scheme

Robust network design under polyhedral traffic uncertainty

Ankara : The Department of Industrial Engineering and The Institute of Engineering and Science of Bilkent Univ., 2007.Thesis (Ph.D.) -- Bilkent University, 2007.Includes bibliographical references leaves 160-166.In this thesis, we study the design of networks robust to changes in demand estimates. We consider the case where the set of feasible demands is defined by an arbitrary polyhedron. Our motivation is to determine link capacity or routing configurations, which remain feasible for any realization in the corresponding demand polyhedron. We consider three well-known problems under polyhedral demand uncertainty all of which are posed as semi-infinite mixed integer programming problems. We develop explicit, compact formulations for all three problems as well as alternative formulations and exact solution methods. The first problem arises in the Virtual Private Network (VPN) design field. We present compact linear mixed-integer programming formulations for the problem with the classical hose traffic model and for a new, less conservative, robust variant relying on accessible traffic statistics. Although we can solve these formulations for medium-to-large instances in reasonable times using off-the-shelf MIP solvers, we develop a combined branch-and-price and cutting plane algorithm to handle larger instances. We also provide an extensive discussion of our numerical results. Next, we study the Open Shortest Path First (OSPF) routing enhanced with traffic engineering tools under general demand uncertainty with the motivation to discuss if OSPF could be made comparable to the general unconstrained routing (MPLS) when it is provided with a less restrictive operating environment. To the best of our knowledge, these two routing mechanisms are compared for the first time under such a general setting. We provide compact formulations for both routing types and show that MPLS routing for polyhedral demands can be computed in polynomial time. Moreover, we present a specialized branchand-price algorithm strengthened with the inclusion of cuts as an exact solution tool. Subsequently, we compare the new and more flexible OSPF routing with MPLS as well as the traditional OSPF on several network instances. We observe that the management tools we use in OSPF make it significantly better than the generic OSPF. Moreover, we show that OSPF performance can get closer to that of MPLS in some cases. Finally, we consider the Network Loading Problem (NLP) under a polyhedral uncertainty description of traffic demands. After giving a compact multicommodity formulation of the problem, we prove an unexpected decomposition property obtained from projecting out the flow variables, considerably simplifying the resulting polyhedral analysis and computations by doing away with metric inequalities, an attendant feature of most successful algorithms on NLP. Under the hose model of feasible demands, we study the polyhedral aspects of NLP, used as the basis of an efficient branch-and-cut algorithm supported by a simple heuristic for generating upper bounds. We provide the results of extensive computational experiments on well-known network design instances.Altın, AyşegülPh.D

Congestion avoidance in overlay networks through multipath routing

Overlay networks relying on traditional multicast routing approaches use only a single path between a sender and a receiver. This path is selected based on latency, with the goal of achieving fast delivery. Content is routed through links with low latency, ignoring slower links of the network which remain unused. With the increasing size of content on the Internet, this leads to congestion, messages are dropped and have to be retransmitted. A multicast multipath congestion-avoidance routing scheme which uses multiple bottleneck-disjoint paths between senders and receivers was developed, as was a linear programming model of the network to distribute messages intelligently across these paths according to two goals: minimum network usage and load-balancing. The former aims to use as few links as possible to perform routing, while the latter spreads messages across as many links as possible, evenly distributing the traffic. Another technique, called message splitting, was also used. This allows nodes to send a single copy of a message with multiple receivers, which will then be duplicated by a node closer to the receivers and sent along separate paths only when required. The model considers all of the messages in the network and is a global optimisation. Nevertheless, it can be solved quickly for large networks and workloads, with the cost of routing remaining almost entirely the cost of finding multiple paths between senders and receivers. The Gurobi linear programming solver was used to find solutions to the model. This routing approach was implemented in the NS-3 network simulator. The work is presented as a messaging middleware scheme, which can be applied to any overlay messaging network.Open Acces

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