Topology Control for Maintaining Network Connectivity and Maximizing Network Capacity Under the Physical Model

In this paper we study the issue of topology control under the physical Signal-to-Interference-Noise-Ratio (SINR) model, with the objective of maximizing network capacity. We show that existing graph-model-based topology control captures interference inadequately under the physical SINR model, and as a result, the interference in the topology thus induced is high and the network capacity attained is low. Towards bridging this gap, we propose a centralized approach, called Spatial Reuse Maximizer (MaxSR), that combines a power control algorithm T4P with a topology control algorithm P4T. T4P optimizes the assignment of transmit power given a fixed topology, where by optimality we mean that the transmit power is so assigned that it minimizes the average interference degree (defined as the number of interferencing nodes that may interfere with the on-going transmission on a link) in the topology. P4T, on the other hand, constructs, based on the power assignment made in T4P, a new topology by deriving a spanning tree that gives the minimal interference degree. By alternately invoking the two algorithms, the power assignment quickly converges to an operational point that maximizes the network capacity. We formally prove the convergence of MaxSR. We also show via simulation that the topology induced by MaxSR outperforms that derived from existing topology control algorithms by 50%-110% in terms of maximizing the network capacity

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

Measuring and Understanding Throughput of Network Topologies

High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst-case throughput performance is a subtle problem. In this paper, we develop a framework to benchmark the throughput of network topologies, using a two-pronged approach. First, we study performance on a variety of synthetic and experimentally-measured traffic matrices (TMs). Second, we show how to measure worst-case throughput by generating a near-worst-case TM for any given topology. We apply the framework to study the performance of these TMs in a wide range of network topologies, revealing insights into the performance of topologies with scaling, robustness of performance across TMs, and the effect of scattered workload placement. Our evaluation code is freely available

Receiver-Based Flow Control for Networks in Overload

We consider utility maximization in networks where the sources do not employ flow control and may consequently overload the network. In the absence of flow control at the sources, some packets will inevitably have to be dropped when the network is in overload. To that end, we first develop a distributed, threshold-based packet dropping policy that maximizes the weighted sum throughput. Next, we consider utility maximization and develop a receiver-based flow control scheme that, when combined with threshold-based packet dropping, achieves the optimal utility. The flow control scheme creates virtual queues at the receivers as a push-back mechanism to optimize the amount of data delivered to the destinations via back-pressure routing. A novel feature of our scheme is that a utility function can be assigned to a collection of flows, generalizing the traditional approach of optimizing per-flow utilities. Our control policies use finite-buffer queues and are independent of arrival statistics. Their near-optimal performance is proved and further supported by simulation results.Comment: 14 pages, 4 figures, 5 tables, preprint submitted to IEEE INFOCOM 201

Reliable routing scheme for indoor sensor networks

Indoor Wireless sensor networks require a highly dynamic, adaptive routing scheme to deal with the high rate of topology changes due to fading of indoor wireless channels. Besides that, energy consumption rate needs to be consistently distributed among sensor nodes and efficient utilization of battery power is essential. If only the link reliability metric is considered in the routing scheme, it may create long hops routes, and the high quality paths will be frequently used. This leads to shorter lifetime of such paths; thereby the entire network's lifetime will be significantly minimized. This paper briefly presents a reliable load-balanced routing (RLBR) scheme for indoor ad hoc wireless sensor networks, which integrates routing information from different layers. The proposed scheme aims to redistribute the relaying workload and the energy usage among relay sensor nodes to achieve balanced energy dissipation; thereby maximizing the functional network lifetime. RLBR scheme was tested and benchmarked against the TinyOS-2.x implementation of MintRoute on an indoor testbed comprising 20 Mica2 motes and low power listening (LPL) link layer provided by CC1000 radio. RLBR scheme consumes less energy for communications while reducing topology repair latency and achieves better connectivity and communication reliability in terms of end-to-end packets delivery performance

Towards a Queueing-Based Framework for In-Network Function Computation

We seek to develop network algorithms for function computation in sensor networks. Specifically, we want dynamic joint aggregation, routing, and scheduling algorithms that have analytically provable performance benefits due to in-network computation as compared to simple data forwarding. To this end, we define a class of functions, the Fully-Multiplexible functions, which includes several functions such as parity, MAX, and k th -order statistics. For such functions we exactly characterize the maximum achievable refresh rate of the network in terms of an underlying graph primitive, the min-mincut. In acyclic wireline networks, we show that the maximum refresh rate is achievable by a simple algorithm that is dynamic, distributed, and only dependent on local information. In the case of wireless networks, we provide a MaxWeight-like algorithm with dynamic flow splitting, which is shown to be throughput-optimal

Wireless network coding for multi-hop relay channels

Future wireless communication systems are required to meet growing demands for high spectral e�ciency, low energy consumption and high mobility. The advent of wireless network coding (WNC) has o�ered a new opportunity to improve network throughput and transmission reliability by exploiting interference in intermediate relays. Combined with network coding and self-information cancelation, WNC for two-way relay channels (TWRCs) has come to the forefront. This dissertation focuses on exploiting WNC in multi-hop two-way relay channels (MH-TRCs). Particularly, a multi-hop wireless network coding (MH-WNC) scheme is designed for the generalized L-node K-message MH-TRC. Theoretical studies on the network throughput and performance bounds achieved by the MH-WNC scheme with di�erent relaying strategies (i.e., amplify-and-forward (AF) and compute-and-forward (CPF)) are carried out. Furthermore, by introducing di�erent numbers of transmission time intervals into the MH-WNC, a multiple-time-interval (Multi-TI) MH-WNC is proposed to determine an optimal MH-WNC which can achieve the best outage performance for all-scale MH-TRCs. Finally, this study extends the research on WNC one step forward from two-user networks to multi-user networks. An extended CPF joint with a dominated solution for maximizing the overall computation rate is proposed for the multi-way relay channel (mRC) in the last chapter. The contributions of this dissertation are multifold. First, the proposed MHWNC scheme with fixed two transmission time intervals can achieve a significantly improved network throughput compared to the non-network coding (Non-NC) scheme in the generalized L-node K-message MH-TRC. Theoretical results are derived for both multi-hop analog network coding (MH-ANC) and multi-hop compute-and-forward (MH-CPF). Moreover, both theoretical and numerical results demonstrate that the two MH-WNC schemes can be applied to different scale MH-TRCs to achieve a better outage performance compared to the conventional Non-NC scheme (i.e., MH-ANC for the non-regenerative MH-TRC with a small number of nodes, and MH-CPF for the regenerative MH-TRC with a large number of nodes.). Furthermore, a Multi-TI MH-WNC scheme is generalized with a special binary-tree model and characteristic matrix. The determined optimal MH-WNC scheme is able to provide the best outage performance and outperform the Non-NC scheme in all scale MH-TRCs. Last but not least, this dissertation provides a preliminary investigation of WNC in mRCs. The proposed dominated solution for maximizing the overall computation rate can ensure that all the nodes in the mRC successfully recover their required messages. Moreover, the extended CPF strategy is proven superior to Non-NC in the mRC with a small number of users