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

Timely Data Delivery in a Realistic Bus Network

Abstract—WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the problem of how to route data from its source to its destination in order to maximize the delivery probability by a given deadline. We assume to know the bus schedule, but we take into account that randomness, due to road traffic conditions or passengers boarding and alighting, affects bus mobility. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, minimizing the number of hops a packet can travel, and a recently-proposed heuristic based on bus frequencies. Our optimal algorithm outperforms all of them, but most of the times it essentially reduces to minimizing the expected traversal time. For values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to reach almost the performance of the costly flooding approach. I

Complex Network Analysis and the Applications in Vehicle Delay-Tolerant Networks

Vehicle Delay Tolerant Networks (VDTNs) is a particular kind of Delay Tolerant Networks (DTNs), where vehicles equipped with transmission capabilities are interconnected to form Vehicle NETworks (VNETs). Some applications and services on the top of VDTNs have raised a lot of attention, especially by providing information about weather conditions, road safety, traffic jams, speed limit, and even video streamings without the need of infrastructures. However, due to features such as high vehicle mobility, dynamic scenarios, sparsity of vehicles, short contact durations, disruption and intermittent connectivity and strict requirements for latency, many VDTNs do not present satisfactory performance, because no path exists between a source and its target. In this dissertation, we propose three routing methods to solve the problem as follows. Our first VDTN system focuses on the multi-copy routing in Vehicle Delay Tolerant Networks (VDTNs). Multi-copy routing can balance the network congestion caused by broadcasting and the efficiency limitation in single-copy routing. However, the different copies of each packet search the destination node independently in current multi-copy routing algorithms, which leads to a low utilization of copies since they may search through the same path repeatedly without cooperation. To solve this problem, we propose a fractal Social community based efficient multi-coPy routing in VDTNs, namely SPread. First, we measure social network features in Vehicle NETworks (VNETs). Then, by taking advantage of weak ties and fractal structure feature of the community in VNETs, SPread carefully scatters different copies of each packet to different communities that are close to the destination community, thus ensuring that different copies search the destination community through different weak ties. For the routing of each copy, current routing algorithms either fail to exploit reachability information of nodes to different nodes (centrality based methods) or only use single-hop reachability information (community based methods), e.g., similarity and probability. Here, the reachability of node $i$ to a destination $j$ (a community or a node) means the possibility that a packet can reach $j$ through $i$. In order to overcome above drawbacks, inspired by the personalized PageRank algorithm, we design new algorithms for calculating multi-hop reachability of vehicles to different communities and vehicles dynamically. Therefore, the routing efficiency of each copy can be enhanced. Finally, extensive trace-driven simulation demonstrates the high efficiency of SPread in comparison with state-of-the-art routing algorithms in DTNs. However, in SPread, we only consider the VNETs as complex networks and fail to use the unique location information to improve the routing performance. We believe that the complex network knowledge should be combined with special features of various networks themselves in order to benefit the real application better. Therefore, we further explore the possibility to improve the performance of VDTN system by taking advantage of the special features of VNETs. We first analyze vehicle network traces and observe that i) each vehicle has only a few active sub-areas that it frequently visits, and ii) two frequently encountered vehicles usually encounter each other in their active sub-areas. We then propose Active Area based Routing method (AAR) which consists of two steps based on the two observations correspondingly. AAR first distributes a packet copy to each active sub-area of the target vehicle using a traffic-considered shortest path spreading algorithm, and then in each sub-area, each packet carrier tries to forward the packet to a vehicle that has high encounter frequency with the target vehicle. Furthermore, we propose a Distributed AAR (DAAR) to improve the performance of AAR. Extensive trace-driven simulation demonstrates that AAR produces higher success rates and shorter delay in comparison with the state-of-the-art routing algorithms in VDTNs. Also, DAAR has a higher success rate and a lower average delay compared with AAR since information of dynamic active sub-areas tends to be updated from time to time, while the information of static active sub-areas may be outdated due to the change of vehicles\u27 behaviors. Finally, we try to combine different routing algorithms together and propose a DIstributed Adaptive-Learning routing method for VDTNs, namely DIAL, by taking advantages of the human beings communication feature that most interactions are generated by pairs of people who interacted often previously. DIAL consists of two components: the information fusion based routing method and the adaptive-learning framework. The information fusion based routing method enables DIAL to improve the routing performance by sharing and fusing multiple information without centralized infrastructures. Furthermore, based on the information shared by information fusion based routing method, the adaptive-learning framework enables DIAL to design personalized routing strategies for different vehicle pairs without centralized infrastructures. Therefore, DIAL can not only share and fuse multiple information of each vehicle without centralized infrastructures, but also design each vehicle pair with personalized routing strategy. Extensive trace-driven simulation demonstrates that DIAL has better routing success rate, shorter average delays and the load balance function in comparison with state-of-the-art routing methods which need the help of centralized infrastructures in VDTNs

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed