QoS-Aware Power-Optimized Path Selection for Data Center Networks (Q-PoPS)

Reducing the power consumption and maintaining the Flow Completion Time (FCT) for the Quality of Service (QoS) of applications in Data Center Networks (DCNs) are two major concerns for data center operators. However, existing works either fail in guaranteeing the QoS due to the neglect of the FCT constraints or achieve a less satisfying power efficiency. In this paper, we propose SmartFCT, which employs Software-Defined Networking (SDN) coupled with the Deep Reinforcement Learning (DRL) to improve the power efficiency of DCNs and guarantee the FCT. The DRL agent can generate a dynamic policy to consolidate traffic flows into fewer active switches in the DCN for power efficiency, and the policy also leaves different margins in different active links and switches to avoid FCT violation of unexpected short bursts of flows. Simulation results show that with similar FCT guarantee, SmartFCT can save 8% more of the power consumption compared to the state-of-the-art solutions.

The exponential increase of Internet traffic due to cloud computing and other emerging web applications has created the need for more powerful data centres. These warehouse-scale data centres consist of thousands of racks interconnected with commodity switches and consume vast amount of energy. To face the requirements of the future data centres, new interconnection schemes have to be adopted to provide high throughput and reduced power consumption. Several optical interconnects for future data centre networks have recently appeared that provide high throughput, low latency and reduced power consumption. This paper discusses the need for a shift of the data centres networks to the optical domain to reduce the power consumption and meet the bandwidth requirements. Additionally, this paper presents some indicative optical interconnects for high performance data centres that have appeared recently in the research literature. Finally, it presents a qualitative categorization and comparison of these schemes based on their main features such as performance, connectivity and scalability.

Data center networks (DCNs) are at the forefront of a radical transformation, fueled by the rapid rise of artificial intelligence (AI), cloud-native adoption, and enterprise digitalization, which together place unprecedented demands on their design and performance. From healthcare AI and intelligent transportation to business analytics, modern DCNs are expected to support a diverse and evolving mix of bandwidth-demanding applications, each with distinct quality of service (QoS) requirements. Yet, most state-of-the-art DCN solutions rely on oversimplified DCN data traffic models, failing to address the required application-level differentiation in terms of end-to-end (E2E) latency demands. In response, we propose ALAS-DCN, a novel, to our knowledge, application-aware, low-latency, scalable DCN architecture, based on optical packet switching in the intra-rack and inter-rack domains that is both designed and rigorously evaluated using commercial QoS specifications and realistic traffic patterns of different applications coexisting within the same DCN. ALAS-DCN integrates three hierarchical optical sub-networks: intra-rack, inter-rack, and bridge, each governed by a custom wavelength division multiplexing (WDM) medium access control (MAC) protocol that dynamically prioritizes critical traffic packets, according to the specific application E2E latency demands. Unlike prior approaches, our evaluation leverages realistic workload traces generated by established traffic generators, capturing the application diversity within modern data center (DC) environments. Extensive experimental simulations across five representative DC categories, each hosting a different mix of modern applications, demonstrate that ALAS-DCN consistently achieves up to 95% throughput efficiency and sub-µs latency for high priority traffic across a variety of applications, consistently meeting their differentiated latency constraints. Scalable up to 20,000 servers, ALAS-DCN redefines the DCN as not just a transport layer but an intelligent enabler of next-generation application performance.

A survey on architectures and energy efficiency in Data Center Networks

In the era of cloud computing, data center network (DCN) can consume a significant amount of power (e.g., 10 to 20 percent) in large-scale data centers. To reduce the power consumption of DCN, traffic consolidation has been recently proposed as an effective approach to reduce the number of DCN devices in use. However, existing consolidation approaches do not sufficiently consider the flow completion time (FCT) requirement. On one hand, missing the FCT deadlines can cause serious violation of service-level agreement, especially for delay-sensitive networking services, such as web search and E-commerce. On the other hand, keeping all the devices on to make FCTs much shorter than the desired requirements is unnecessary because 1) users may not be able to perceive the difference, and 2) such a greedy strategy can lead to unnecessarily high DCN power consumption and thus more electricity costs. In this paper, we propose FCTcon, a dynamic FCT control strategy for DCN power optimization. FCTcon is designed rigorously based on control theory to dynamically control the FCT of delay-sensitive traffic flows exactly to the requirements, such that the desired FCT performance is guaranteed while the maximum amount of DCN power savings can be achieved. Results from both hardware experiments and simulation evaluation demonstrate that, compared to the state-of-the-art DCN power optimization schemes, FCTcon can improve the DCN FCT performance, while achieving nearly the same or even more power savings. Consequently, FCTcon can result in more than 22.0 to 62.2 percent extra net profits for a data center with 50K servers. In addition, we further propose two extended designs of FCTcon to handle the coflow abstraction recently proposed for DCN, which successfully reduce the coflow deadline miss ratio by 12 to 15 percent.

Maintaining high-performance operation under dynamic and nonuniform network traffic has been a technical challenge in current data center networks (DCNs). With the aim to provide better quality of service (QoS) for diverse applications, this work presents a dynamic and adaptive DCN reconfiguration framework based on deep reinforcement learning (DCR2L). The proposed framework is integrated into the SDN control plane of the DCN, implementing real-time and automatic DCN reconfiguration. Performance of the DCR2L framework is experimentally demonstrated in our DCN lab, including 4 racks and 16 servers. Experimental results show a network latency improvement of 6.9% based on the DCR2L at an average network bandwidth of 2.3 Gb/s. Based on measured traffic and physical parameters in the experiment, performance of the DCR2L framework is numerically assessed with the realistic traffic of diverse QoS requirements for both electrical and optical DCNs and for different data center scales. Leaf–spine electrical and OPSquare optical networks are set up in an OMNeT++ simulator. For a data plane network consisting of 16 racks and 320 servers, results indicate that the DCR2L framework improves the network latency of up to 16.4% under leaf–spine and up to 24.6% under OPSquare for the overall traffic with respect to the classical heuristic method. For a DCN scale of 10,240 servers, the DCR2L framework provides up to 12.5% lower latency for the leaf–spine electrical network and up to 17.8% latency improvement for the OPSquare optical network.

Software-Defined Networking (SDN) is a networking design approach, which separates the data plane from the control plane, providing the network with certain benefits due to centralized programmatic control. SDN provides a centralized view and enables management of the entire network. It offers flexibility in configuration, reduces time to deploy, provides automation and facilitates building a network without requiring the knowledge of any vendor-specific software/hardware. SDN offers the datacenter network benefits such as improving traffic and security management as well as providing a scalable infrastructure. Load balancing enhances the performance of the network by distributing traffic among servers and therefore preventing congestion and server underutilization. This paper aims to explore SDN and test its implementation and demonstrate how to implement its concepts within a datacenter network. The experiment considers the datacenter network implemented in Sudan University of Science and Technology as a case study. The edited network topology is made up of a Demilitarize Zone (DMZ) having three servers, a Local Area Network (LAN) and a main switch. The Hub, Switch and Load balancer scenarios are implemented using Mininet emulator. In addition, the three scenarios are tested using external devices and analyzed using Wireshark. Moreover, the connectivity of HTTP and FTP is verified.

Data center network (DCN) can consume a significant amount of power (e.g., 10% to 20%) in large-scale data centers. To reduce the power consumption of DCN, traffic consolidation has been recently proposed as an effective approach to reduce the number of DCN devices in use. However, existing consolidation approaches do not sufficiently consider the flow completion time (FCT) requirement. On one hand, missing the FCT deadlines can cause serious violation of service-level agreement, especially for delay-sensitive networking services, such as web search and E-commerce. On the other hand, keeping all the devices on to make FCTs much shorter than the desired requirements is unnecessary because 1) users may not be able to perceive the difference, and 2) such a greedy strategy can lead to unnecessarily high DCN power consumption and thus more electricity costs. In this paper, we propose FCTcon, a dynamic FCT control strategy for DCN power optimization. FCTcon is designed rigorously based on control theory to dynamically control the FCT of delay-sensitive traffic flows exactly to requirements, such that the desired FCT performance is guaranteed while the maximum amount of DCN power savings can be achieved. Results from both hardware experiments and simulation evaluations demonstrate that, compared to the state-of-the-art DCN power optimization schemes, FCTcon can improve the DCN FCT performance, while achieving nearly the same or even more power savings. Consequently, FCTcon can result in more than 22.0% to 62.2% extra net profits for a data center with 50K servers.

The key infrastructure of Cloud Computing is data center which is shared by many tenants. Each tenant's application competes for acquiring more network bandwidth in order to maximize its utility. However, this may cause interference among these diverse applications. Malicious competition not only degrades its performance, but also makes the overall performance of the data center poor and ineffective. To ensure the Quality of Services (QoS) and achieve high network utilization, in this paper, we propose a bandwidth allocation scheme for data center networks (DCNs), which is based on an application utility-based model. In our scheme, multi-path feature of DCN is leveraged to improve the network utilization, and utility functions are constructed to differentiate the throughput and delay sensibilities of different applications. Moreover, our scheme is suitable for arbitrary DCN topologies and without modification on current hardware. The numerical simulation shows that our scheme can provide bandwidth guarantee, fine-grained service differentiation and achieve high network utilization.

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.

As the infrastructure of cloud computing and big data, data centers have been deployed widely. Then, how to make full use of the computing and storage resources in data centers will be the focus. Data center networks are considered important solution for the problem above, which include intra-data center and inter-data center networks. Both of them will depend on the optical networking due to its advantages, such as high bandwidth, low latency, and low energy consumption. Data center interconnected by flexi-grid optical networks is a promising scenario to allocate spectral resources for applications in a dynamic, tunable and efficient control manner. Compared with inter-data center, optical interconnect in intra-data center networks is a more pressing need and promising scenario to accommodate these applications in a dynamic, flexible and efficient manner. OpenFlow based Software Defined Networking (SDN) is considered as a good technology, which is very suitable for data center networks. This paper mainly focuses on the data center optical networks based on software defined networking (SDN), which can control the heterogeneous networks with unified resource interface. Architecture and experimental demonstration of OpenFlow-based optical interconnects in intra-data center Networks and OpenFlow-based flexi-grid optical networks for inter-data center are presented in the paper respectively. Some future works are listed finally.

The proposed Internet paradigm The Flying Ad Hoc Network (FANET), Named Data Network (NDN), and Software Defined Network (SDN) have attracted the interest of the scientific community. The TCP/IP protocol is the present Internet standard, while NDN is the future internet architecture that builds on it. Data availability is improved via NDN, which substitutes named data for the nodes' addresses. SDN is a good option for communicating effectively, utilizing resources effectively, and supporting developing technologies. The SDN has attracted interest because of its high-level programmability and flexibility. Numerous applications in the military, business, and civil sectors make extensive use of FANE T. The broadcast characteristic of NDN causes an issue known as a broadcast storm in dense FANET environments. The issue is caused by duplicate packets, which raises the overall amount of traffic and retransmissions. FANET has a problem with the timely and quick transmission of essential packets. In this paper, we suggested a new scheme named "Novel Adaptive Broadcast Storm Avoidance (NABA)" for SDN and NDN-enabled FANET, which uses a controller to lessen the broadcast issue. Our scheme made use of the SDN controller's effective flow management to regulate the broadcast storm and facilitate packet transfers. Additionally, we divided up the packet into categories based on priority. The priority of the packet is determined by the naming criterion. In terms of the overall number of Interests and content retrieval time, the findings show that NAB A performs better than native NDN floods.

Data centre networks are intended to meet the data transmission needs of the data centre’s highly networked hosts. The network architecture and routing technique can have a major impact on performance parameters such as latency. The fat-tree network is now one of the most popular data centre network architectures. In recent times, data centre network traffic has been steadily expanding. Because of the high volume of traffic, it is nearly impossible for a single server to satisfy all the client’s requests. In this paper, a bio-inspired Territorial Predator Scent Marking Algorithm (TPSMA) is proposed for load balancing in a fat-tree software-defined data centre. The bio-inspired algorithm was developed to increase network Quality of Service (QoS). The proposed technique is validated using the network emulator Mininet, with the Open Network Operating System ONOS controller. The performance study conducted showed that the throughput and network utilization were improved, hence improving the QoS.

An energy-efficient virtual machine placement and route scheduling scheme in data center networks

One of the main control tasks in a computer network is to organize an effective system of information delivery; this task is of particular relevance in the software defined network. Conventional routing tools do not meet the requirements to service quality and the requirements for equitable distribution of congestion along communication channels. Routing in conventional networks is performed by the shortest path search based on a specified parameter, but these tools do not provide sufficient agility when changing routes in the network. Another drawback is the need to transmit regular updates of routing information by passing the service traffic, thereby dramatically increasing the congestion and reducing the throughput. At present, the most effective way to ensure the assigned quality of service parameters, as well as a promising solution to organize efficient routing under conditions of uncertainty, is a software defined network. This new networking paradigm makes it possible to simplify the process of managing the network, to significantly enhance the use of network resources, and to reduce operating costs. One of the main advantages of such a network is control at the upper levels of the reference model, which makes it possible to simplify both the process of network management and the process to manage traffic in corporate networks and data center networks. A new approach to traffic design in a software defined network has been proposed that employs the making-decision theory oriented towards routing exactly in such networks. If there is a «problematic area» and there is the need to overcome it, the decision-making theory under conditions of uncertainty is used, since the probability of selecting the best way to circumvent it accounts for the patterns in transmitted traffic. Such a method makes it possible to reduce the loss of inelastic traffic that is an important component of the overall amount of transmitted information. From a practical point of view, the algorithm constructed in this work, when compared to known algorithms for traffic engineering, improves the quality of service in software defined networks