The innovative information-based Named-Data Networking (NDN) architecture provides a good opportunity to rethink many of the design decisions that are taken for granted in the Internet today. For example, active queue management (AQM) tasks have been traditionally implemented in the routers to alleviate network congestion before their buffers fill up. However, AQM operations could be performed on an end-to-end basis by taking advantage of NDN features. In this paper, we provide an implementation of an AQM algorithm for the NDN architecture that we use to drive a classical AIMD-based congestion control protocol at the receivers. To accomplish this, we take advantage of the 64-bit Congestion Mark field present in the link layer of NDN packets to encode both rate and delay information about each transmission queue along a network path. In order to make the solution scalable, this information is delivered stochastically, guaranteeing that receivers get accurate and updated information about every pertinent queue. This information is enough to implement the well-known controlled delay (CoDel) AQM algorithm. Simulation results show that our client-located CoDel implementation is able to react to congestion when the bottleneck queuing delay surpasses the 5ms target set by the usual in-network CoDel implementation and, at the same time, get a fair and efficient share of the available transmission capacity.

The efforts to replace the successful, albeit aging, TCP/IP Internet architecture with a better suited one have driving research interest to information-centric alternatives. The Named Data Networking (NDN) architecture is probably one of the main contenders to become the network layer of the future Internet thanks to its inbuilt support for mobility, in-network caching, security and, in general, for being better adapted to the needs of current network applications. At the same time, massive satellite constellations are currently being deployed in low Earth orbits (LEO) to provide a backend for network connectivity. It is expected that, very soon, these constellations will function as proper networks thanks to inter-satellite communication links. These new satellite networks will be able to benefit from their greenfield status and the new network architectures. In this paper we analyze how to deploy the network caches of an NDN-based LEO satellite network. In particular, we show how we can jointly select the most appropriate caching nodes for each piece of content and how to forward data across the constellation in two simple alternative ways. Performance results show that the caching and forwarding strategies proposed reduce path lengths up to a third with just a few caching nodes while, simultaneously, helping to spread the load along the network.

Low Earth orbit (LEO) satellite constellations are increasingly gaining attention as future global Internet providers. At the same time, named data networking (NDN) is a new data-centric architecture that has been recently proposed to replace the classic TCP/IP architecture since it is particularly well suited to the most common usage of the Internet nowadays as a content delivery network. Certainly, the use of NDN is especially convenient in highly dynamic network environments, such as those of next LEO constellations incorporating inter-satellite links (ISL). Among other native facilities, such as inbuilt security, NDN readily supports the mobility of clients, thus helping to overcome one of the main problems raised in LEO satellite networks. Moreover, thanks to a stateful forwarding plane with support for multicast transmission and inbuilt data caches, NDN is also able to provide a more efficient usage of the installed transmission capacity. In this paper, we propose a new location-based forwarding strategy for LEO satellite networks that takes advantage of the knowledge of the relative position of the satellites and the grid structure formed by the ISLs to perform the forwarding of NDN packets. So, forwarding at each node is done using only local information (node and destination locations), without the need of interchanging information between nodes, as is the case with conventional routing protocols. Using simulation, we show that the proposed forwarding strategy is a good candidate to promote the efficient and effective future use of the NDN architecture in LEO satellite networks.

This paper addresses the optimization of the energy efficiency of underlay multicast device-to-device communications on cellular networks. In particular, the energy efficiency of both the global network and the individual users is maximized considering various fairness factors such as maximum power and minimum rate constraints. For this, a canonical mixed-integer non-linear formulation of the joint power control and resource allocation problem is used.

Non-orthogonal multiple access (NOMA) techniques have emerged in the past years as a solution to approximate the throughput performance of wireless communications systems to their theoretical capacity region. We consider in this paper an optimization-based model for multicast device-to-device (MD2D) communications where the channels are not orthogonal and maybe (partially or fully) shared among the transmitters in each cluster. This setting leads naturally to the introduction of NOMA transmitters and receivers who use successive interference cancellation(SIC) to separate the superposed signals. To analyze the role of NOMA in MD2D, its performance impact, potential performance gains and possible shortcomings, we formulate a model that includesSIC operations in the decoders, so that higher rates can be attained when several sources transmit on the same channel(s). We also investigate the energy efficiency of the network (global and max-min)through a dynamic power control algorithm and present a centralized and a semi-distributed solution to these optimization problems. Through numerical simulations, we show that NOMA is able to improve both the sum-rate and the max-min rate of a MD2D network even from a small degree of resource sharing. Furthermore, these gains also improve the global energy efficiency on the network,but not always the max-min energy efficiency of the devices.

This paper presents a new efficient ARIMA-based forecasting model for predicting wind speed at short-term horizons. Performance results show that the proposed ARIMA model can be an excellent choice for wind-powered sensor nodes due to its potential for achieving accurate enough predictions with very low computational burden and memory overhead. In addition, it is very simple to setup, since it can dynamically adapt to varying wind conditions and locations without requiring any particular reconfiguration or previous data training phase for each different scenario.

The low power idle mode implemented by Energy Efficient Ethernet (EEE) allows network interfaces to save up to 90% of their nominal energy consumption when idling. However, EEE capable hardware from several manufactures delays the entrance to the low power mode for a considerable amount of time (hysteresis). In this paper we augment existing EEE energy models to account for this hysteresis delay and show that, using the configuration ranges provided by manufacturers, most existing EEE networking devices are unable to obtain significant energy savings. To improve their energy efficiency, we propose to implement frame coalescing directly at traffic sources, before reaching the network interface.

This paper presents a novel energy prediction model that makes use of the altitude angle of the sun at different times of day to predict future solar energy availability with very low computational load and memory overhead. Unlike most of the state-of-the-art predictors that use past energy observations to make predictions, our model does not require maintaining local energy harvesting patterns of past days. Moreover, our proposal is extremely simple to set up since it does not require any particular tuning for each different scenario or location.

In this paper, we optimize the energy efficiency of device-to-multi-device (D2MD) communications. While point-to-point scenarios have been extensively studied to improve the spectral efficiency in cellular networks, the introduction of multicast communications brings, in addition, the possibility of reusing the spectrum resources also inside the groups. We formulate the energy efficiency problem in this context, and show that a decomposition approach which first uses matching theory to allocate the channels to each group, and then optimizes to find the unique transmission power vectors in each group, gives good performance results for the optimization of both the system’s energy efficiency and the max-min individual energy efficiency for a desired minimum transmission rate. Numerical results confirm the usefulness of the proposed framework for optimizing the planning and deployment of D2MD networks with energy efficiency as a primary performance goal.

This paper provides new insights on the practical efficiency limits of most common coalescing techniques (time-based and size-based coalescing). In particular, we derive the fundamental limits on the maximum energy savings considering a target average frame delay. Additionally, we present new open-loop adaptive variants of both coalescing techniques. These proposals dynamically adjust the length of the sleeping periods in accordance with actual traffic conditions to reduce energy consumption while keeping the average delay near a predefined value simultaneously.

This paper presents a promising power saving algorithm that can be implemented using standard SDN capabilities of current switches to reduce operation costs on both data centers and wired access networks. In particular, we focus on minimizing the energy consumption in bundles of Energy Efficient Ethernet links leveraging SDN. For this, we design, build and analyze three energy-efficient SDN-compatible flow allocation algorithms from the point of view of energy consumption, packet loss rate and transmission latency.

This paper presents a new dynamic scheme to manage the sleep mode of energy-aware base stations (BSs) that can be autonomously governed. This kind of BSs can be put to sleep without causing undesired coverage holes, thus preserving the cellular service over the whole coverage area. With the proposed mechanism, energy-aware BSs enter the sleep mode as soon as they have no traffic to send and then apply a coalescing algorithm that dynamically adjusts the length of the sleeping periods to maximize the energy savings while maintaining the average service delay around a target value at the same time.

In this paper, we focus on the energy demands of link aggregates that are commonly used to increase the capacity of a network connection. We build on known energy models of single Energy Efficient Ethernet (EEE) links to derive the energy demands of the whole aggregate as a function on how the traffic load is spread among its powered links. We then provide a practical method to share the load that minimizes overall energy consumption with controlled packet delay and prove that it is valid for a wide range of EEE links.

Networking operational costs and environmental concerns have lately driven the quest for energy efficient equipment. In wired networks, energy efficient Ethernet (EEE) interfaces can greatly reduce power demands when compared to regular Ethernet interfaces. Their power saving capabilities have been studied and modeled in many research articles in the last few years, together with their effects on traffic delay. However, to this date, all articles have considered them in isolation instead of as part of a network of EEE interfaces. In this paper we develop a model for the traffic delay on a network of EEE interfaces. We prove that, whatever the network topology, the per interface delay increment due to the power savings capabilities is bounded and, in most scenarios, negligible. This confirms that EEE interfaces can be used in all but the most delay constrained scenarios to save considerable amounts of power.

This paper presents a new frame coalescing mechanism that dynamically adjusts the coalescing queue threshold in order to minimize the energy consumption of dual-mode EEE interfaces and maintains, at the same time, the average frame delay close to a target value.

This paper presents a promising mechanism that reduces energy consumption of user equipments using the DRX mechanism while simultaneously maintaining average packet delay around a desired target. In addition, our proposal is able to achieve significant power savings without either increasing signaling overhead or requiring any changes to deployed wireless protocols.

Rising energy consumption of IT infrastructure concerns have spurred the development of more power efficient networking equipment and algorithms. When old equipment just drew an almost constant amount of power regardless of the traffic load, there were some efforts to minimize the total energy usage by modifying routing decisions to aggregate traffic in a minimal set of links, creating the opportunity to power off some unused equipment during low traffic periods. New equipment, with power profile functions depending on the offered load, presents new challenges for optimal routing. The goal now is not just to power some links down, but to aggregate and/or spread the traffic so that devices operate in their sweet spot in regards to network usage. In this paper we present an algorithm that, making use of the ant colonization algorithm, computes, in a decentralized manner, the routing tables so as to minimize global energy consumption. Moreover, the resulting algorithm is also able to track changes in the offered loadand react to them in real time.

This paper evaluates through simulation the potential power savings that can be obtained in ONUs using the low power mode known as doze mode. In particular, the impact of the DBA algorithm and the doze mode governor on both energy efficiency and frame delay are analyzed.

This paper provides a general GI/G/1 model for the energy consumption and the traffic delay obtained with a 10 Gb/s EEE interface using both frame and burst transmission algorithms. Specializations of the general model for Poisson and deterministic traffic are also provided.

This paper provides mathematical models for the expected energy savings and the average packet delay obtained in EEE interfaces using the most well known sleeping algorithms. These models are then used to derive the optimum configuration parameters for the sleeping algorithms given some efficiency constraints.

This paper provides an accurate analytical model for the power savings achievable in EEE devices using the burst transmission algorithm to govern the low power mode.

Traditional TCP-Reno like congestion control protocols exhibit poor performance when deployed in fast or very large network paths. Delay based congestion avoidance mechanisms (DCA), like FAST-TCP, get much higher performance, in the same circumstances. However, when mixed with TCP-Reno or alike traffic they are unable to attain their fair share of bandwidth. In this paper we present a new mechanism that can indirectly detect the present of non DCA-friendly traffic that can be used by new DCA algorithms to auto-tune themselves with more aggressive parameters to achieve their fair share.

Delay-based congestion control algorithms provide higher throughput and stability than traditional loss-based AIMD algorithms, but they are inherently unfair against older connections when the queuing and the propagation delay cannot be measured accurately and independently. This paper presents a novel measurement algorithm whereby fairness between old and new connections is preserved. The algorithm does not modify the dynamics of congestion control, and runs entirely in the server host using locally available information.