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

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

Incentive based Routing Protocol for Mobile Peer to Peer Networks

Incentive models are becoming increasingly popular in Mobile Peer to Peer Networks (M-P2P) as these models entice node participation in return for a virtual currency to combat free riding and to effectively manage constraint resources in the network. Many routing protocols proposed are based on best effort data traffic policy, such as the shortest route selection (hop minimization). Using virtual currency to find a cost effective optimal route from the source to the destination, while considering Quality of Service (QoS) aspects such as bandwidth and service capacity constraints for data delivery, remains a challenging task due to the presence of multiple paths and service providers. Modeling the network as a directed weighted graph and using the cost acquired from the price function as an incentive to pay the intermediate nodes in M-P2P networks to forward data, we develop a Game theoretic approach based on stochastic games to find an optimal route considering QoS aspect. The performance of our routing protocol is evaluated and compared with some existing routing protocols and the result shows that our protocol proves to be efficient compared to shortest-path DSR and multiple paths SMR in terms of average response time, energy and bandwidth utilization in the network

An economic incentive based routing protocol incorporating quality of service for mobile peer-to-peer networks

Economic incentive models are becoming increasingly popular in Mobile Peer to Peer Networks (M-P2P). These models entice node participation to combat free riding and to effectively manage constraint resources in the network. Due to the dynamic topology of the M-P2P network, the connections between the peers become unpredictable and therefore, reliable routing becomes important. Many routing protocols proposed earlier (such as DSR, AODV) are based on best effort data traffic policy, such as the shortest route selection (hop minimization). Using economic models to find a cost effective optimal route from the source to the destination, while considering Quality of Service (QoS) aspects such as bandwidth and Service Capacity constraints for data delivery, remains a challenging task due to the presence of multiple paths and service providers. In this paper, we propose a Game theory based economic approach for routing with QoS support in M-P2P networks to forward data. Modeling the network as a directed weighted graph and using the cost acquired from the price function as an incentive to pay the intermediate nodes, we develop a Game theoretic approach based on stochastic games to find an optimal route. We formulate a capacity function, which provides the available bandwidth to support the QoS aspect. The performance of our routing protocol is also evaluated and compared with some existing routing protocols and the result shows that our protocol proves to be efficient compared to shortest-path DSR and multiple paths SMR in terms of average response time, energy utilization and bandwidth availability in the network --Abstract, page iv