Early Experiences in Traffic Engineering Exploiting Path Diversity: A Practical Approach

Recent literature has proved that stable dynamic routing algorithms have solid theoretical foundation that makes them suitable to be implemented in a real protocol, and used in practice in many different operational network contexts. Such algorithms inherit much of the properties of congestion controllers implementing one of the possible combination of AQM/ECN schemes at nodes and flow control at sources. In this paper we propose a linear program formulation of the multi-commodity flow problem with congestion control, under max-min fairness, comprising demands with or without exogenous peak rates. Our evaluations of the gain, using path diversity, in scenarios as intra-domain traffic engineering and wireless mesh networks encourages real implementations, especially in presence of hot spots demands and non uniform traffic matrices. We propose a flow aware perspective of the subject by using a natural multi-path extension to current congestion controllers and show its performance with respect to current proposals. Since flow aware architectures exploiting path diversity are feasible, scalable, robust and nearly optimal in presence of flows with exogenous peak rates, we claim that our solution rethinked in the context of realistic traffic assumptions performs as better as an optimal approach with all the additional benefits of the flow aware paradigm

Green communication in energy renewable wireless mesh networks: routing, rate control, and power allocation

PublishedJournal Article© 2014 IEEE. The increasing demand for wireless services has led to a severe energy consumption problem with the rising of greenhouse gas emission. While the renewable energy can somehow alleviate this problem, the routing, flow rate, and power still have to be well investigated with the objective of minimizing energy consumption in multi-hop energy renewable wireless mesh networks (ER-WMNs). This paper formulates the problem of network-wide energy consumption minimization under the network throughput constraint as a mixed-integer nonlinear programming problem by jointly optimizing routing, rate control, and power allocation. Moreover, the min-max fairness model is applied to address the fairness issue because the uneven routing problem may incur the sharp reduction of network performance in multi-hop ER-WMNs. Due to the high computational complexity of the formulated mathematical programming problem, an energy-aware multi-path routing algorithm (EARA) is also proposed to deal with the joint control of routing, flow rate, and power allocation in practical multi-hop WMNs. To search the optimal routing, it applies a weighted Dijkstra's shortest path algorithm, where the weight is defined as a function of the power consumption and residual energy of a node. Extensive simulation results are presented to show the performance of the proposed schemes and the effects of energy replenishment rate and network throughput on the network lifetime

Fair and optimal resource allocation in wireless sensor networks

There is a large amount of research in wireless networks focuses on optimization of either network routing and power control alone. In contrast, this work aims at jointly optimizing the transmission power and routing path selection in order to optimize allocation of resources in interference constrained wireless environment. Moreover, we consider a multipath routing where multiple alternative paths are employed to transmit data between the end nodes. One of modern communication techniques that it applies to a network coding, though not explicitly implemented in this work. The proposed approach is first analyzed theoretically using Lagrangian optimization for a three-node scenario. We analyze this basic scenario, as it is essential for development of the overall multi-path routing schemes for multi-hop networks. The optimal solution for the three-node topology is replicated throughout the network to converge to a network-level solution. In contrast to existing studies, we explicitly consider interference from adjacent links, which varies with traffic flow thus optimizing the routing, and flow control decisions. The results and conclusions provide guidance as to the optimum routing decisions and a corresponding theoretical performance limits. The optimization of the throughput of the wireless network scenario is considered as a multi-variable optimization problem subject to flow and power constraints. Numerical analysis performed in Matlab-Simulink indicates that, given loose outage constraints, an optimal trade-off between the channel parameters renders optimum results even when the gain of the channel varies with time. The theoretical analysis and simulations demonstrate and validate that the channel capacity and efficiency are maximized when the routing decisions consider the network performance trade-offs. Next, the proposed routing and power control scheme is experimentally evaluated in hardware using universal software radio peripheral (USRP2). The USRP testbed utilizes the proposed multi-variable optimization algorithm. The communication system is implemented using GNU Radio software where the physical layer employs two direct-spread spectrum variants: (a) binary phase shift keying (DS-BPSK) and (b) orthogonal frequency division modulation (DS-OFDM) schemes. The experimental results are compared with the simulation results --Abstract, page iii

Multiflow Transmission in Delay Constrained Cooperative Wireless Networks

This paper considers the problem of energy-efficient transmission in multi-flow multihop cooperative wireless networks. Although the performance gains of cooperative approaches are well known, the combinatorial nature of these schemes makes it difficult to design efficient polynomial-time algorithms for joint routing, scheduling and power control. This becomes more so when there is more than one flow in the network. It has been conjectured by many authors, in the literature, that the multiflow problem in cooperative networks is an NP-hard problem. In this paper, we formulate the problem, as a combinatorial optimization problem, for a general setting of $k$-flows, and formally prove that the problem is not only NP-hard but it is $o(n^{1/7-\epsilon})$ inapproxmiable. To our knowledge*, these results provide the first such inapproxmiablity proof in the context of multiflow cooperative wireless networks. We further prove that for a special case of k = 1 the solution is a simple path, and devise a polynomial time algorithm for jointly optimizing routing, scheduling and power control. We then use this algorithm to establish analytical upper and lower bounds for the optimal performance for the general case of $k$ flows. Furthermore, we propose a polynomial time heuristic for calculating the solution for the general case and evaluate the performance of this heuristic under different channel conditions and against the analytical upper and lower bounds.Comment: 9 pages, 5 figure

Flow Allocation for Maximum Throughput and Bounded Delay on Multiple Disjoint Paths for Random Access Wireless Multihop Networks

In this paper, we consider random access, wireless, multi-hop networks, with multi-packet reception capabilities, where multiple flows are forwarded to the gateways through node disjoint paths. We explore the issue of allocating flow on multiple paths, exhibiting both intra- and inter-path interference, in order to maximize average aggregate flow throughput (AAT) and also provide bounded packet delay. A distributed flow allocation scheme is proposed where allocation of flow on paths is formulated as an optimization problem. Through an illustrative topology it is shown that the corresponding problem is non-convex. Furthermore, a simple, but accurate model is employed for the average aggregate throughput achieved by all flows, that captures both intra- and inter-path interference through the SINR model. The proposed scheme is evaluated through Ns2 simulations of several random wireless scenarios. Simulation results reveal that, the model employed, accurately captures the AAT observed in the simulated scenarios, even when the assumption of saturated queues is removed. Simulation results also show that the proposed scheme achieves significantly higher AAT, for the vast majority of the wireless scenarios explored, than the following flow allocation schemes: one that assigns flows on paths on a round-robin fashion, one that optimally utilizes the best path only, and another one that assigns the maximum possible flow on each path. Finally, a variant of the proposed scheme is explored, where interference for each link is approximated by considering its dominant interfering nodes only.Comment: IEEE Transactions on Vehicular Technolog

Space Shuffle: A Scalable, Flexible, and High-Bandwidth Data Center Network

Data center applications require the network to be scalable and bandwidth-rich. Current data center network architectures often use rigid topologies to increase network bandwidth. A major limitation is that they can hardly support incremental network growth. Recent work proposes to use random interconnects to provide growth flexibility. However routing on a random topology suffers from control and data plane scalability problems, because routing decisions require global information and forwarding state cannot be aggregated. In this paper we design a novel flexible data center network architecture, Space Shuffle (S2), which applies greedy routing on multiple ring spaces to achieve high-throughput, scalability, and flexibility. The proposed greedy routing protocol of S2 effectively exploits the path diversity of densely connected topologies and enables key-based routing. Extensive experimental studies show that S2 provides high bisectional bandwidth and throughput, near-optimal routing path lengths, extremely small forwarding state, fairness among concurrent data flows, and resiliency to network failures

Throughput Optimal Flow Allocation on Multiple Paths for Random Access Wireless Multi-hop Networks

In this paper we consider random access wireless multi-hop mesh networks with multi-packet reception capabilities where multiple flows are forwarded to the gateways through node disjoint paths. We address the issue of aggregate throughput-optimal flow rate allocation with bounded delay guarantees. We propose a distributed flow rate allocation scheme that formulates flow rate allocation as an optimization problem and derive the conditions for non-convexity for an illustrative topology. We also employ a simple model for the average aggregate throughput achieved by all flows that captures both intra- and inter-path interference. The proposed scheme is evaluated through NS-2 simulations. Our preliminary results are derived from a grid topology and show that the proposed flow allocation scheme slightly underestimates the average aggregate throughput observed in two simulated scenarios with two and three flows respectively. Moreover it achieves significantly higher average aggregate throughput than single path utilization in two different traffic scenarios examined.Comment: Accepted for publication at the 9th IEEE BROADBAND WIRELESS ACCESS WORKSHOP (BWA2013), IEEE Globecom 2013 Workshop