24,973 research outputs found
Robust Energy Management for Green and Survivable IP Networks
Despite the growing necessity to make Internet greener, it is worth pointing
out that energy-aware strategies to minimize network energy consumption must
not undermine the normal network operation. In particular, two very important
issues that may limit the application of green networking techniques concern,
respectively, network survivability, i.e. the network capability to react to
device failures, and robustness to traffic variations. We propose novel
modelling techniques to minimize the daily energy consumption of IP networks,
while explicitly guaranteeing, in addition to typical QoS requirements, both
network survivability and robustness to traffic variations. The impact of such
limitations on final network consumption is exhaustively investigated. Daily
traffic variations are modelled by dividing a single day into multiple time
intervals (multi-period problem), and network consumption is reduced by putting
to sleep idle line cards and chassis. To preserve network resiliency we
consider two different protection schemes, i.e. dedicated and shared
protection, according to which a backup path is assigned to each demand and a
certain amount of spare capacity has to be available on each link. Robustness
to traffic variations is provided by means of a specific modelling framework
that allows to tune the conservatism degree of the solutions and to take into
account load variations of different magnitude. Furthermore, we impose some
inter-period constraints necessary to guarantee network stability and preserve
the device lifetime. Both exact and heuristic methods are proposed.
Experimentations carried out with realistic networks operated with flow-based
routing protocols (i.e. MPLS) show that significant savings, up to 30%, can be
achieved also when both survivability and robustness are fully guaranteed
A Novel Network Coded Parallel Transmission Framework for High-Speed Ethernet
Parallel transmission, as defined in high-speed Ethernet standards, enables
to use less expensive optoelectronics and offers backwards compatibility with
legacy Optical Transport Network (OTN) infrastructure. However, optimal
parallel transmission does not scale to large networks, as it requires
computationally expensive multipath routing algorithms to minimize differential
delay, and thus the required buffer size, optimize traffic splitting ratio, and
ensure frame synchronization. In this paper, we propose a novel framework for
high-speed Ethernet, which we refer to as network coded parallel transmission,
capable of effective buffer management and frame synchronization without the
need for complex multipath algorithms in the OTN layer. We show that using
network coding can reduce the delay caused by packet reordering at the
receiver, thus requiring a smaller overall buffer size, while improving the
network throughput. We design the framework in full compliance with high-speed
Ethernet standards specified in IEEE802.3ba and present solutions for network
encoding, data structure of coded parallel transmission, buffer management and
decoding at the receiver side. The proposed network coded parallel transmission
framework is simple to implement and represents a potential major breakthrough
in the system design of future high-speed Ethernet.Comment: 6 pages, 8 figures, Submitted to Globecom201
Optimizing Emergency Transportation through Multicommodity Quickest Paths
In transportation networks with limited capacities and travel times on the arcs, a class of problems attracting a growing scientific interest is represented by the optimal routing and scheduling of given amounts of flow to be transshipped from the origin points to the specific destinations in minimum time. Such problems are of particular concern to emergency transportation where evacuation plans seek to minimize the time evacuees need to clear the affected area and reach the safe zones. Flows over time approaches are among the most suitable mathematical tools to provide a modelling representation of these problems from a macroscopic point of view. Among them, the Quickest Path Problem (QPP), requires an origin-destination flow to be routed on a single path while taking into account inflow limits on the arcs and minimizing the makespan, namely, the time instant when the last unit of flow reaches its destination. In the context of emergency transport, the QPP represents a relevant modelling tool, since its solutions are based on unsplittable dynamic flows that can support the development of evacuation plans which are very easy to be correctly implemented, assigning one single evacuation path to a whole population. This way it is possible to prevent interferences, turbulence, and congestions that may affect the transportation process, worsening the overall clearing time. Nevertheless, the current state-of-the-art presents a lack of studies on multicommodity generalizations of the QPP, where network flows refer to various populations, possibly with different origins and destinations. In this paper we provide a contribution to fill this gap, by considering the Multicommodity Quickest Path Problem (MCQPP), where multiple commodities, each with its own origin, destination and demand, must be routed on a capacitated network with travel times on the arcs, while minimizing the overall makespan and allowing the flow associated to each commodity to be routed on a single path. For this optimization problem, we provide the first mathematical formulation in the scientific literature, based on mixed integer programming and encompassing specific features aimed at empowering the suitability of the arising solutions in real emergency transportation plans. A computational experience performed on a set of benchmark instances is then presented to provide a proof-of-concept for our original model and to evaluate the quality and suitability of the provided solutions together with the required computational effort. Most of the instances are solved at the optimum by a commercial MIP solver, fed with a lower bound deriving from the optimal makespan of a splittable-flow relaxation of the MCQPP
Know Your Enemy: Stealth Configuration-Information Gathering in SDN
Software Defined Networking (SDN) is a network architecture that aims at
providing high flexibility through the separation of the network logic from the
forwarding functions. The industry has already widely adopted SDN and
researchers thoroughly analyzed its vulnerabilities, proposing solutions to
improve its security. However, we believe important security aspects of SDN are
still left uninvestigated. In this paper, we raise the concern of the
possibility for an attacker to obtain knowledge about an SDN network. In
particular, we introduce a novel attack, named Know Your Enemy (KYE), by means
of which an attacker can gather vital information about the configuration of
the network. This information ranges from the configuration of security tools,
such as attack detection thresholds for network scanning, to general network
policies like QoS and network virtualization. Additionally, we show that an
attacker can perform a KYE attack in a stealthy fashion, i.e., without the risk
of being detected. We underline that the vulnerability exploited by the KYE
attack is proper of SDN and is not present in legacy networks. To address the
KYE attack, we also propose an active defense countermeasure based on network
flows obfuscation, which considerably increases the complexity for a successful
attack. Our solution offers provable security guarantees that can be tailored
to the needs of the specific network under consideratio
Energy management in communication networks: a journey through modelling and optimization glasses
The widespread proliferation of Internet and wireless applications has
produced a significant increase of ICT energy footprint. As a response, in the
last five years, significant efforts have been undertaken to include
energy-awareness into network management. Several green networking frameworks
have been proposed by carefully managing the network routing and the power
state of network devices.
Even though approaches proposed differ based on network technologies and
sleep modes of nodes and interfaces, they all aim at tailoring the active
network resources to the varying traffic needs in order to minimize energy
consumption. From a modeling point of view, this has several commonalities with
classical network design and routing problems, even if with different
objectives and in a dynamic context.
With most researchers focused on addressing the complex and crucial
technological aspects of green networking schemes, there has been so far little
attention on understanding the modeling similarities and differences of
proposed solutions. This paper fills the gap surveying the literature with
optimization modeling glasses, following a tutorial approach that guides
through the different components of the models with a unified symbolism. A
detailed classification of the previous work based on the modeling issues
included is also proposed
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