Multiple distributed controllers have been used in software-defined networks (SDNs) to improve scalability and reliability, where each controller manages one static partition of the network. In this paper, we show that dynamic mapping between switches and controllers can improve efficiency in managing traffic load variations. In particular, we propose balanced controller (BalCon) and BalConPlus, two SDN switch migration schemes to achieve load balance among SDN controllers with small migration cost. BalCon is suitable for the scenarios where the network does not require a serial processing of switch requests. For other scenarios, BalConPlus is more suitable, as it is immune to the switch migration blackout and does not cause any service disruption. Simulations demonstrate that BalCon and BalConPlus significantly reduce the load imbalance among SDN controllers by migrating only a small number of switches with low computation overhead. We also build a prototype testbed based on the open-source SDN framework RYU to verify the practicality and effectiveness of BalCon and BalConPlus. Experiment confirms the results of the simulations. It also shows that BalConPlus is immune to switch migration blackout, an adverse effect in the baseline BalCon.

Scalability and reliability are among the main concerns in large-scale Software Defined Networking (SDN) application scenarios. A common approach is to use multiple distributed controllers, each managing one static partition of the network. In this paper, we show that dynamic mapping can improve efficiency in managing traffic load variations. We then propose BalCon (Balanced Controller): an algorithmic solution designed to tackle and reduce the load imbalance among SDN controllers through proper SDN switch migrations. Simulations demonstrate that BalCon is lightweight from the computational point of view and reduces the load imbalance among SDN controllers (expressed as variance) by 40% by migrating only a small number of switches. We also built a realistic prototype of SDN controller, BalConController, based on the open-source SDN framework RYU.

Nanosatellites offer a solution to provide Internet access in areas where there is no ICT infrastructure, such as rural and remote areas, keeping low construction and maintenance costs. A nanosatellite constellation is composed of a certain number of nanosatellites distributed in one or more orbital planes. In most cases, this network cannot ensure an end-to-end connection between sources and destinations, because not all satellite links are up at the same time. The Delay and Disruption Tolerant Networking (DTN) paradigm is so necessary to deal with predictable disruptions and large delays, allowing nanosatellites, Internet gateways (also called hot spots), and rural gateways (also called cold spots) to keep data stored in their buffers also for tens of minutes waiting to be forwarded. We focused our attention on a possible selection strategy which indicates to all nanosatellites how many bundles (PDUs of the DTN protocol) they can upload from rural gateways during each contact. The decision is made by considering the maximum amount of data that nanosatellites and cold spots can exchange during each contact (quantity related to contact durations) and the possible presence of congestion situations in rural and remote areas or in nanosatellites. The proposed strategy is called ColdSel: it calculates the amount of bundles that each cold spot has to upload on the nanosatellite in contact with in order to mitigate congestion situations in rural areas and nanosatellites and to reduce the nanosatellite buffer occupancies so improving the performance in terms of data delivery time.

The design of High Throughput Satellite (HTS) systems builds on the concept of Smart Gateway Diversity (SGD) to exploit the spatial diversity of gateways in case of feeder link outage, occurring because of atmospheric impairments introduced in Extremely High Frequency (EHF) frequency bands. The gateway handover procedure requires precise prediction algorithms and coordination among different network elements. This paper presents novel outage prediction algorithms based on machine learning concepts, integrated in the framework of SDN architectures, to efficiently orchestrate the gateway handover operations. Simulation campaigns prove the validity of the proposed concept and shed light on the potentials of the SDN architecture in future HTS systems.

Nowadays, to benefit from Internet access is so easy in some areas of the world as difficult in others. There are some different projects whose purpose is to extend Internet access to areas which do not have it yet. Each of these projects has unique characteristics that distinguish it from others (different transmission channels, different devices used, \dots). One possible solution provides the use of a particular type of satellites called nanosatellites. Using these devices, we can have a solution to extend the network access in rural and remote areas which offers a good balance among performances, security and costs. In a network of this type ground stations (called hot spots) are deployed, which upload data destined to rural areas on nanosatellites and download data destined to Internet servers from nanosatellites. During a data connection, an Internet server that wants to reply to a request coming from a rural area has many hot spot alternatives to whom it can deliver data. The problem of choosing the ``optimal'' hot spot becomes important because a wrong choice could lead to a high delivery delay. We propose ``HotSel'': a hot spot selection algorithm able to minimize data delivery time. HotSel is simple and practical, and outperforms two other selection mechanisms used as comparison. All results have been collected by using Network Simulator 3 (NS3) and developing a module able to simulate a nanosatellite network.

Optimality conditions for Call Admission Control (CAC) problems with nonlinearly constrained feasibility regions and K classes of users are derived. The adopted model is a generalized stochastic knapsack, with exponentially distributed interarrival times of the objects. Call admission strategies are restricted to the family of Coordinate-Convex (CC) policies. For K = 2 classes of users, both general structural properties of the optimal CC policies and structural properties that depend on the revenue ratio are investigated. Then, the analysis is extended to the case K > 2. The theoretical results are exploited to narrow the set of admissible solutions to the associated knapsack problem, i.e., the set of CC policies to which an optimal one belongs. With respect to results available in the literature, less restrictive conditions on the optimality of the complete-sharing policy are obtained. To illustrate the role played by the theoretical results on the combinatorial CAC problem, simulation results are presented, which show how the number of candidate optimal CC policies dramatically decreases as the derived optimality conditions are imposed.

Necessary optimality conditions for Call Admission Control (CAC) problems with nonlinearly-constrained feasibility regions and two classes of users are derived. The policies are restricted to the class of coordinate-convex policies. Two kinds of structural properties of the optimal policies and their robustness with respect to changes of the feasibility region are investigated: 1) general properties not depending on the revenue ratio associated with the two classes of users and 2) more specific properties depending on such a ratio. The results allow one to narrow the search for the optimal policies to a suitable subset of the set of coordinate-convex policies.

In view of the dense and complex space network topologies envisioned for the future, the management of congestion control is a prominent issue that deserves a particular attention. Given the challenging peculiarities of interplanetary environments, this paper focuses on the advantages offered by storage-based routing and on potentials of implementing Random Early Detection (RED) and Explicit Congestion Notification (ECN) mechanisms within the Delay Tolerant Network (DTN) architecture. In this light, solutions relying upon the aforementioned concepts have been designed and tested. Preliminary results show that combination of RED and ECN schemes with network-selection strategies for storage-based routing is really promising and outperforms other solutions in terms of reliability, network resource utilisation and power consumption.