Toward PTNET Network Topology Analysis and Routing Algorithm Design

Data centers often hold tens to hundreds of thousands of servers in order to offer cloud computing services at scale. Ethernet switching and IP routing have their own advantages and limitations in building data center networks. Recent research, such as PortLand and BCube, has proposed scalable data center network designs. A common feature of these designs is that their addressing and routing are customized to specific topologies. In this paper, we propose a generic addressing, routing and forwarding protocol for data center networks, which works on arbitrarily layered'' network topologies. We first form the network as a multi-rooted tree. Each network node (i.e., hosts and switches) is then assigned one or more locators, and each locator encodes a downward path from the roots to this node. Data center networks often have rich path diversity, so tracking all locators of a destination node will cause switches to have very large forwarding tables. We further use a new forwarding model to reduce the forwarding states. In addition, the multiple-locator mechanism brings built-in support for multi-path routing, load balancing and fault tolerance. Evaluations based on simulations and prototype experiments demonstrate that our proposal achieves our design goals.

Two intrinsic features of Named Data Networking(NDN), in-network caching and multipath communication, offer the potential for fast and reliable big data transmissions via multisource content delivery. Network coding has recently been utilized to achieve efficient multisource content delivery in NDN. On the other hand, request pipelining is essential for efficient multisource content delivery in network coding enabled NDN. However, it is a challenge to simultaneously support network coding and request pipelining in NDN in a cost-effective way. To address this problem, we propose NCP-NDN, a network coding and request pipelining enabled named data networking architecture. NCP-NDN supports reasonably efficient Interest aggregation when enabling request pipelining without undermining the privacy of content retrieval by extending each Interest with a session and generation oriented requester identifier. Besides, NCP-NDN provides consumers with linearly independent blocks while request pipelining is enabled by combining rank-based matching, one forwarding of each block for per requester and face, and recoding the matching cached blocks before replying an Interest. Our experimental studies illustrate that NCP-NDN improves the performance of content delivery and reduces the overhead of big data transmissions as compared to the existing schemes.

The data center network is an important infrastructure for the cloud service. With the rapid development of cloud computing, data center network scale exponentially, and the traditional tree network topology have not accommodate this growth model for a single point of failure and bottlenecks. DCell is a decentralized, fault-tolerant data center network topology. Although DCell has good fault tolerance, it does not implement the strategy of the data object placemen and query. This paper proposes an efficient, fault-tolerant, self-organizing model NetCloud for data placement and query in DCN based on DCell. The key of data is be mapped to a binary string by the NetCloud_hash algorithms. Accordingly, we presented a data placement algorithm PRLCP and a replicate strategy for NetCloud with DNB algorithm. The simulation shows that it has better query performance and fault tolerance.

Data centers (DCs), owing to the exponential growth of Internet services, have emerged as an irreplaceable and crucial infrastructure to power this ever-growing trend. A DC typically houses a large number of computing and storage nodes, interconnected by a specially designed network, namely, DC network (DCN). The DCN serves as a communication backbone and plays a pivotal role in optimizing DC operations. However, compared to the traditional network, the unique requirements in the DCN, for example, large scale, vast application diversity, high power density, and high reliability, pose significant challenges to its infrastructure and operations. We have observed from the premium publication venues (e.g., journals and system conferences) that increasing research efforts are being devoted to optimize the design and operations of the DCN. In this paper, we aim to present a systematic taxonomy and survey of recent research efforts on the DCN. Specifically, we propose to classify these research efforts into two areas: 1) DCN infrastructure and 2) DCN operations. For the former aspect, we review and compare the list of transmission technologies and network topologies used or proposed in the DCN infrastructure. For the latter aspect, we summarize the existing traffic control techniques in the DCN operations, and survey optimization methods to achieve diverse operational objectives, including high network utilization, fair bandwidth sharing, low service latency, low energy consumption, high resiliency, and etc., for efficient DC operations. We finally conclude this survey by envisioning a few open research opportunities in DCN infrastructure and operations.

A theory for the design of deadlock-free adaptive routing algorithms for wormhole networks, proposed by the author (1991, 1993), supplies sufficient conditions for an adaptive routing algorithm to be deadlock-free, even when there are cyclic dependencies between channels. Also, two design methodologies were proposed. Multicast communication refers to the delivery of the same message from one source node to an arbitrary number of destination nodes. A tree-like routing scheme is not suitable for hardware-supported multicast in wormhole networks because it produces many headers for each message, drastically increasing the probability of a message being blocked. A path-based multicast routing model was proposed by Lin and Ni (1991) for multicomputers with 2D-mesh and hypercube topologies. In this model, messages are not replicated at intermediate nodes. This paper develops the theoretical background for the design of deadlock-free adaptive multicast routing algorithms. This theory is valid for wormhole networks using the path-based routing model. It is also valid when messages with a single destination and multiple destinations are mixed together. The new channel dependencies produced by messages with several destinations are studied. Also, two theorems are proposed, developing conditions to verify that an adaptive multicast routing algorithm is deadlock-free, even when there are cyclic dependencies between channels. As an example, the multicast routing algorithms of Lin and Ni are extended, so that they can take advantage of the alternative paths offered by the network.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Compressionless Routing (GR) is a new adaptive routing framework which provides a unified framework for efficient deadlock-free adaptive routing and fault-tolerance. CR exploits the tight-coupling between wormhole routers for flow control to detect potential deadlock situations and recover from them. Fault-tolerant Compressionless Routing (FCR) extends Compressionless Routing to support end-to-end fault-tolerant delivery. Detailed routing algorithms, implementation complexity and performance simulation results for CR and FCR are presented.CR has the following advantages: deadlock-free adaptive routing in torus networks with no virtual channels, simple router designs, order-preserving message transmission, applicability to a wide variety of network topologies, and elimination of the need for buffer allocation messages. FCR has the following advantages: tolerates transient faults while maintaining data integrity (nonstop fault-tolerance), tolerates permanent faults, can be applied to a wide variety of network topologies, and eliminates the need for software buffering and retry for reliability. These advantages of CR and FCR not only simplify hardware support for adaptive routing and fault-tolerance, they also can simplify communication software layers.

Given the current expansion of cloud computing, the expected advent of the Internet of Things, and the requirements of future fifth‐generation network infrastructures, significantly larger pools of computational and storage resources will soon be required. This emphasizes the need for more scalable data centers that are capable of providing such an amount of resources in a cost‐effective way. A quick look into today's commercial data centers shows that they tend to rely on variations of well‐defined leaf‐spine/Clos data center network (DCN) topologies, offering low latency, ultrahigh bisectional bandwidth, and enhanced reliability against concurrent failures. However, DCNs are typically restricted by the use of the Transmission Control Protocol/Internet Protocol (TCP/IP) suite, thus suffering limited routing scalability. In this work, we study the benefits that replacing TCP/IP with the recursive internetwork architecture (RINA) can bring into commercial DCNs, focusing on forwarding and routing scalability. We quantitatively evaluate the benefits that RINA solutions can yield against those based on TCP/IP and highlight how, by deploying RINA, topological routing solutions can improve even more the efficiency of the network. To this goal, we propose a rule‐and‐exception forwarding policy tailored to the characteristics of several DCN variants, enabling fast forwarding decisions with merely neighbors' information. Upon failures, few exceptions are necessary, whose computation can also profit from the known topology. Extensive numerical results show that the proposed policy requirements depend mainly on the number of neighbors and concurrent failures in the DCN rather than its size, dramatically reducing the amount of forwarding and routing information stored at DCN nodes.

The information and communication technology nowadays more than ever depends on the Internet and cloud computing, so that the data centers (DCs) have been converted to a constitutive unit of the cloud computing. A DC is composed of two primary parts: servers and Data Center Networks (DCNs). Robustness and scalability are two major challenges of the DCNs that are expanded based on two strategies, scale-out, and scale-up. This paper is distinctive from the related studies in two aspects. The first one is to simultaneously focus on both the scalability and the robustness challenges of the DCNs. For this purpose, we will concentrate on the comparison of robustness in the scalable models of these networks. The second one is, despite the previous work that only evaluated the DCN robustness under topological changes, we evaluated the robustness and fault tolerance against three types of unexpected changes in topology, traffic, and COI (community of interest) in the present work. Hence, we have chosen the network criticality (NC) as a graph-theoretic metric for analyzing DCN robustness. Afterward, we compare some structural and spectral graph metrics with NC among some well-known DCNs, and their scale-out and scale-up. Our results are useful to select the appropriate scaling strategy with the goal of maximizing the robustness of existing DCNs and provide a guideline for designing the new robust and scalable DCN.

A reconfigurable interconnection network (RIN) is a custom-designed on-chip switching network yielding routing solutions for a pre-given set of applications. Like field programmable gate array (FPGA) routing networks, the RIN is used to make reconfigurable interconnections among functional blocks. Unlike FPGAs, the network topology of a RIN is irregular as it is designed for a given set of routing requirements and optimized for the area cost subject to given delay constraints. In this paper, we propose an automatic design scheme for RINs, including routing specification formulation, graph modelings, network topology designs, routing algorithms and multiplexer-based network circuit implementation. The choice of the design scheme is based on the existing routing network design practices and research, which give feasible solutions. Our scheme is to optimize the designs with the choice of design parameters. A computer-aided design (CAD) tool is developed based on the design scheme, which takes a set of routing requirements as input and produces the corresponding RIN network topology and network circuit in hardware description language format. We present the area costs of various RINs generated by the CAD tool subject to delay constraints, and illustrate the RIN design scheme with a reconfigurable multistream video system.

Fault tolerance, performance, and throughput have been major areas of research and development since the evolution of large-scale networks. Internet-based applications are rapidly growing, including large-scale computations, search engines, high-definition video streaming, e-commerce, and video on demand. In recent years, energy efficiency and fault tolerance have gained significant importance in data center networks and various studies directed the attention towards green computing. Data centers consume a huge amount of energy and various architectures and techniques have been proposed to improve the energy efficiency of data centers. However, there is a tradeoff between energy efficiency and fault tolerance. The objective of this study is to highlight a better tradeoff between the two extremes: (a) high energy efficiency and (b) ensuring high availability through fault tolerance and redundancy. The main objective of the proposed Energy-Aware Fault-Tolerant (EAFT) approach is to keep one level of redundancy for fault tolerance while scheduling resources for energy efficiency. The resultant energy-efficient data center network provides availability as well as fault tolerance at reduced operating cost. The main contributions of this article are: (a) we propose an Energy-Aware Fault-Tolerant (EAFT) data center network scheduler; (b) we compare EAFT with energy efficient resource scheduling techniques to provide analysis of parameters such as, workload distribution, average task per servers, and energy consumption; and (c) we highlight effects of energy efficiency techniques on the network performance of the data center.

Proactive deadlock prevention based on traffic classification sub-graphs for triplet-based NoC TriBA-cNoC

Multiprotocol label switching (MPLS) is a promising backbone technology for large and broadband IP networks. In an MPLS network, IP packets can be controlled more easily than is possible in best-effort IP forwarding. To clarify the network topologies and routing algorithms that are suitable for MPLS traffic engineering, we evaluate them from the viewpoint of network use efficiency and end-to-end quality. We characterize typical network topologies and practical routing algorithms. Using a network topology that has many alternative paths and a bandwidth priority algorithm can provide good end to-end quality and good network use efficiency.

All optical or hybrid electrical/optical switching data center network (DCN) architectures are capable of adapting the optical-layer topology to various network traffic demands based on the flexibility of optical switching technology. The topology reconfiguration strategies in previous research simply attempt to reconfigure optical circuit switching (OCS) links to offload heavier rack-to-rack traffic. However, due to the complex multi-layer interconnections and the various network traffic patterns in DCNs, the OCS links will not only offload the network traffic between its source and destination racks, but also forward the network traffic that belongs to the adjacent racks of the source and destinations racks. Previous strategies ignore the forwarding traffic and result in sub-optimal solutions. In order to overcome the shortcomings of previous methods and make full use of the OCS link resources in DCNs, an effective topology reconfiguration strategy named optical circuit bridge (OCBridge) has been proposed in our recent work. The main idea of our OCBridge is to take into account the traffic demands between the source and destination regions of each OCS link. In this paper, we first review our OCBridge, and then in simulation, we evaluate the performance of our OCBridge by testing it in two typical OCS-based DCNs, including OpenScale and Helios. Under our OCBridge, we analyze the outstanding network throughput performance of the DCNs and investigate the communication distance of traffic demands. Finally, in experiment, we deploy our OCBridge to a small prototype of OpenScale and verify that our OCBridge is capable of accelerating the distributed computing applications compared with previous topology reconfiguration strategies.

Present-day datacenter networks (DCNs) are designed to achieve full bisection bandwidth in order to provide high network throughput and server agility. However, the average utilization of typical DCN infrastructure is below 10% for significant time intervals. As a result, energy is wasted during these periods. In this thesis we analyze traffic behavior of datacenter networks using traces as well as simulated models. Based on the insight developed, we present techniques to reduce energy waste by making energy use scale linearly with load. The solutions developed are analyzed via simulations, formal analysis, and prototyping. The impact of our work is significant because the energy savings we obtain for networking infrastructure of DCNs are near optimal. A key finding of our traffic analysis is that network switch ports within the DCN are grossly under-utilized. Therefore, the first solution we study is to modify the routing within the network to force most traffic to the smallest of switches. This increases the hop count for the traffic but enables the powering off of many switch ports. The exact extent of energy savings is derived and validated using simulations. An alternative strategy we explore in this context is to replace about half the switches with fewer switches that have higher port density. This has the effect of enabling even greater traffic consolidation, thus enabling even more ports to sleep. Finally, we explore a third approach in which we begin with end-to-end traffic models and incrementally build a DCN topology that is optimized for that model. In other words, the network topology is optimized for the potential use of the datacenter. This approach makes sense because, as other researchers have observed, the traffic in a datacenter is heavily dependent on the primary use of the datacenter. A second line of research we undertake is to merge traffic in the analog domain prior to feeding it to switches. This is accomplished by use of a passive device we call a merge network. Using a merge network enables us to attain linear scaling of energy use with load regardless of datacenter traffic models. The challenge in using such a device is that layer 2 and layer 3 protocols require a one-to-one mapping of hardware addresses to IP (Internet Protocol) addresses. We overcome this problem by building a software shim layer that hides the fact that traffic is being merged. In order to validate the idea of a merge

Topology modeling is a challenging topic in the design and development of tools that simulate the behavior of interconnection networks. During the last years we have seen the birth of several simulation tools and frameworks modeling interconnects, some of them doing brilliant efforts to do the code re-usable and extensible. The main differences among these simulation tools and frameworks is the level of granularity and abstraction of their network models. Different network models may generate duplicated efforts in modeling certain aspects of them, such as the network topology or the routing algorithm. If the topology generation and routing algorithm modeling were separated from the modeling of other network aspects, then the simulator developers could focus on developing non-existing models and new functionality, without wasting time in doing a work previously done by other simulation tool developers. In this paper we describe TopGen, an external library that can be integrated with any tool that simulates interconnection networks. TopGen provides a compendious of well-known network topologies that can be used to interconnect the network components, such as end nodes, channels, switches and routers. It also provides the corresponding knowledge to apply a compendious of routing algorithms to the modeled network topologies. TopGen also supports the definition of customized topologies that are not the standard ones, thanks to a special interface used for this purpose. We also provide details on how to integrate TopGen with a network simulator, by means of a simple API. Finally, we describe several use cases of the TopGen library.