Error Tolerant Address Configuration for Data Center Networks with Malfunctioning Devices

Special issue PRIMA 2013 The graph isomorphism (GI) problem asks whether two given graphs are isomorphic or not. The GI problem is quite basic and simple, however, it\textquoterights time complexity is a long standing open problem. The GI problem is clearly in NP, no polynomial time algorithm is known, and the GI problem is not NP-complete unless the polynomial hierarchy collapses. In this paper, we survey the computational complexity of the problem on some graph classes that have geometric characterizations. Sometimes the GI problem becomes polynomial time solvable when we add some restrictions on some graph classes. The properties of these graph classes on the boundary indicate us the essence of difficulty of the GI problem. We also show that the GI problem is as hard as the problem on general graphs even for grid unit intersection graphs on a torus, that partially solves an open problem.

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.

The number of data centers has been increased for various reasons such as cloud computing, big-data analysis, multimedia service, etc. With public interests on data center, many novel technologies for data center networks have been proposed and deployed to support data center operations more efficiently and effectively. However, the construction of data center network incurs significant costs. Moreover, various technologies interplay each other to achieve multiple objectives, and it makes difficult to validate and/or verify characteristics of data center network. In addition, it difficult to perform experiments with a number of hosts and switches. Therefore, it is necessary to observe the characteristics of target data center network before building it. A common approach to evaluate data center is to run simulations that should be similar with real-world data center environment. However, generating traffic with the characteristics of data center networks is not matured yet. People still employ a traffic generator based on the characteristics of Internet traffic. We design a traffic generator that shows more accurate characteristics of data center network traffic. Various traffic characteristics exploited explored by several studies are considered. The proposed method generates flow-level network traffic matrix based on Poisson Shot-Noise model. We implemented the traffic generator using Python programming language to create traffic matrix. To evaluate the proposed method, we compare the results with real data center network traffic. Our results show that the generated traffic owns similar characteristics with the real network traffic in terms of flow size, duration, and the mean and variance of total traffic rate.

Virtualization technologies have been widely deployed in data centers to improve the system utilization. However, they cause increased workload for operators to clarify the structure of virtual networks in data centers. To reduce the operation time, this paper provides the virtual-network management system which automates the integration of the configurations of the virtual networks. The proposed system collects the configurations from server virtualization platforms and VLAN-supported switches, and integrates these configurations according to the newly developed XML-based management information model for virtual-network configurations. The preliminary evaluations show that the proposed system helps to reduce the time to collect and update the configurations by about 40 percent. This result implies that the proposed system is effective for improving the configuration management process for virtual networks in data centers.

Data centers are integral part of cloud computing that support Web services, online social networking, data analysis, computation intensive applications and scientific computing. They require high performance components for their inter-process communication, storage and sub-communication systems. The performance bottleneck that used to be the processing power has now been shifted to communication speed within data centers. The performance of a data center, in terms of throughput and delay, is directly related to the performance of the underlying internal communication network. In this paper, we introduce an analytical model that can be used to evaluate the underlying network architecture in data centers. The model can further be used to develop simulation tools that extend the scope of performance evaluation beyond what it can be achieved by the theoretical model in terms of various network topologies, different traffic distributions, scalability, and load balancing. While the model is generic, we focus on its implementation for fat-tree networks that are widely used in data centers. The theoretical results are compared and validated with the simulation results for several network configurations. The results of this analysis provide a basis for data center network design and optimization.

In recent years, group communication has become more and more popular. In the current data center network, multicast plays an extremely important role in group communication. Traditional data center network is designed based on wires. Researchers have proposed Dcell, Bcube and other data center topologies successively. However, in the traditional data center network, the wired topology structure has the disadvantages of high overhead, complex deployment, high maintenance cost, slow heat dissipation and so on. Moreover, the existing wireless data center Flyways structure and Graphite structure have the problems of low connectivity and poor scalability. So this paper proposes and designs a new data center network topology Comb structure (Comb model is a multi-layer cellular structure model, which is a multi-layer structure composed of single-layer honeycomb-like structure interlaced with each other). The structure can effectively improve the connectivity of the data center, shorten the routing path, reduce the probability of node failure in the network, and ensure the smooth network.

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.

Graph isomorphism completeness for chordal bipartite graphs and strongly chordal graphs

Today, there is a generalized standard usage of internet for all.The devices via multiple technologies that facilitates to provide few communication methods to scholars to work with. By forming multiple paths in the data center network, latest generation data centers offer maximum bandwidth with robustness. To utilize this bandwidth, it is necessary that different data flows take separate paths. In brief, a single-path transport seems inappropriate for such networks. By using Multipath TCP, we must reconsider data center networks, with a diverse approach as to the association between topology, transport protocols, routing. Multipath TCP allows certain topologies that single path TCP cannot use. In newer generation data centers, Multipath TCP is already deployable using extensively deployed technologies such as Equal-cost multipath routing. But, major benefits will come when data centers are specifically designed for multipath transports. Due to manifold of technologies like Cloud computing, social networking, and information networks there is a need to deploy the number of large data centers. While Transport Control Protocol is the leading Layer-3 transport protocol in data center networks, the operating conditions like high bandwidth, small-buffered switches, and traffic patterns causes poor performance of TCP. Data Center TCP algorithm has newly been anticipated as a TCP option for data centers which address these limitations. It is worth noting that traditional TCP protocol.

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.

Today's data centers tend to have tens to hundreds of thousands of servers to provide massive and sophisticated services. Statistically, data center and data center networks (DCNs) remain highly underutilized which can be exploited for energy-saving. In this paper, we have studied energy-saving problem for network and server sides of the data center. The problem was formulated as a Mixed Integer Linear Program (MILP) that is solvable by an optimization software to jointly minimize the energy consumed by the servers and DCN. To overcome the optimization software high computational time, a heuristic algorithm to provide practical and efficient solution is introduced. The heuristic algorithm has two stages: first, it uses the virtual machines (VM) and the predicted servers resource utilization to provide VM consolidation algorithm and turn-off unused servers. The second stage uses an abstract performance-aware network flow consolidation that focused the traffic on subset of the network and turn-off the unused network devices. Simulation experiments using CloudsimSDN were conducted to validate the heuristic using real traces from Wikipedia in terms of energy consumption and average response time. The results show that the heuristic can save servers and network energy while maintaining performance.

In this contemporary world, technology is advancing at a rapid pace. In the recent decades, information technology has grown exponentially. Improving data center energy efficiency is an urgent issue with remarkable economic and environmental impacts. Enormous heat generation is fuelled by the data centers. Distribution of heat is a crucial parameter that affects data center cooling and energy consumption. Heat reduction is the crux of environmentally sustainable computing. Typically, data centres lack in effective sensing systems to monitor heat distribution at a large scale. In this chapter, I aim at using sensor networks as a dense instrumentation technology to comprehend and control cooling in data centers. This chapter presents the Aquasar project as the case study and explores the environmental challenges in developing sensor networks in data centers. I also explore the effective way of dealing with the excess heat from multiple servers in the data centers and the upper hand of water cooling over air cooling.

Data center networks, using a reliable, high speed communication network, is a core component of cloud computing. Recently, optical networks using Space Division Multiplexing has been proposed as a solution to the speed bottleneck anticipated in data center networks. To our knowledge the new challenges of designing such communication systems have not been addressed yet. In this paper we have proposed an optimal approach to the problem of developing a path-protection scheme to handle communication requests in data center (DC) networks using elastic optical networking and space division multiplexing. We have formulated our problem as an Integer Linear Program (ILP). We have also proposed a heuristic that can handle problems of practical size. Our simulations explore important features of our approach.

A survey on architectures and energy efficiency in Data Center Networks

The Visible Light Communication (VLC) has the potential to provide dense and fast connectivity at low cost. In this paper, we propose WSWDC, a novel VLC enabled wireless small-world data center. It employs VLC links to achieve a fully wireless data center network (DCN) across racks for the first time. The using of VLC links eliminates hierarchical switches and inter-rack cables, and thus reducing hardware investment, as well as maintenance cost. More precisely, to simplify the configuration and control operations, we propose three DCN design rationales: (1) fully-wireless, all inter-rack links are wireless; (2) easy-deployable, it is not necessary to change the existing infrastructure inside data center; (3) plug-and-play, no extra centralized control operations are required. Previous proposals, however, cannot achieve the three rationales simultaneously. To this end, we first use regular VLC links to interconnect racks as a regular grid DCN. To further exploiting the benefits of VLC links, a few random VLC links are carefully introduced to update the wireless grid DCN as a wireless small-world DCN. To avoid the potential interference among VLC links, we deploy VLC transceivers at different height on the top of each rack. In this way, VLC links would not interfere with others at each height level. Moreover, we design a greedy but efficient routing method for any pair of racks using their identifiers as inputs. Comprehensive evaluation results indicate that our WSWDC exhibits good network performance.