Search

Millimeter-wave (mm-wave) technologies are the main driver to deliver the multiple-Gbps promise in next-generation wireless access networks. However, the GHz-bandwidth potential must coexist with a harsh propagation environment. While strong attenuations can be compensated by directional antenna arrays, the severe impact of obstacle blockages can only be mitigated by smart resource allocation techniques. Multi-connectivity, as multiple mm-wave links from a mobile device to different base stations, is one of them. However, the higher reliability provided by several access alternatives can be fully exploited only if uncorrelated link statuses are guaranteed. Therefore, spatial diversity must be enforced. Moreover, since interposing obstacles can block a link, short access links allow reducing the link unavailability probability. Smart base-station selections can be made once the network is deployed, however, our results show that much better results are achievable if spatial diversity and link-length aspects are directly included in the network planning phase. In this article, we propose an mm-wave access network planning framework that considers base-station spatial diversity, link lengths, and achievable user throughput, according to channel conditions and network congestion. The comparison against traditional k-coverage approaches shows that our approach can obtain much better access reliability, thus providing higher robustness to random obstacles and self-blockage phenomena.

Data-center topologies interconnect an ever larger number of servers using a high number of alternative paths to provide high bandwidth and a high degree of resiliency. The state-of-the-art routing strategy is based on Equal-cost multipath (ECMP) which employs static hashing mechanism over packet header fields to spread the traffic over multiple paths. Routing the traffic without considering the size of the flows and the utilization of the paths might cause congestion due to the collision of multiple large flows on a same downstream path. We present CEDRO, an in-switch mechanism to detect and reschedule colliding large flows. By exploiting the latest advances in SDN programmable network devices, we offload to the network the detection of both the elephant flows and the path congestion conditions and the rescheduling mechanism. CEDRO is able to promptly cope with path congestion and failures directly from the dataplane, regardless of the availability of the external controller. We implemented CEDRO in an emulated SDN network and tested it against realistic traffic scenarios. Numerical evaluation shows CEDRO is able to improve the average and 95-th percentile of the Flow Completion Time compared to ECMP.

Every time an Internet user downloads a video, shares a picture, or sends an email, his/her device addresses a data center and often several of them. These complex systems feed the web and all Internet applications with their computing power and information storage, but they are very energy hungry. The energy consumed by Information and Communication Technology (ICT) infrastructures is currently more than 4% of the worldwide consumption and it is expected to double in the next few years. Data centers and communication networks are responsible for a large portion of the ICT energy consumption and this has stimulated in the last years a research effort to reduce or mitigate their environmental impact. Most of the approaches proposed tackle the problem by separately optimizing the power consumption of the servers in data centers and of the network. However, the Cloud computing infrastructure of most providers, which includes traditional telcos that are extending their offer, is rapidly evolving toward geographically distributed data centers strongly integrated with the network interconnecting them. Distributed data centers do not only bring services closer to users with better quality, but also provide opportunities to improve energy efficiency exploiting the variation of prices in different time zones, the locally generated green energy, and the storage systems that are becoming popular in energy networks. In this paper, we propose an energy aware joint management framework for geo-distributed data centers and their interconnection network. The model is based on virtual machine migration and formulated using mixed integer linear programming. It can be solved using state-of-the art solvers such as CPLEX in reasonable time. The proposed approach covers various aspects of Cloud computing systems. Alongside, it jointly manages the use of green and brown energies using energy storage technologies. The obtained results show that significant energy cost savings can be achieved compared to a baseline strategy, in which data centers do not collaborate to reduce energy and do not use the power coming from renewable resources.

Software-Defined Networking (SDN) brought an unprecedented flexibility and programmability into computer networks. In order to simplify the management of an SDN network, several high-level languages have been proposed. The Intent Framework provided by Open Network Operating System (ONOS), for example, allows programmers to specify high-level policies without worrying about low-level device details, which are inferred by the controller. In addition, the Intent Framework ensures that the objective is met by transparently re-compiling the intents as a consequence of environment changes (e.g. link failures). In this work we extend the Intent Framework to make it able to both compile multiple intents together and to re-optimize their paths according to the network state based on flow statistics. We present Intent Monitor and Reroute service, a new ONOS module to optimize traffic forwarding of any ONOS applications based on intents, via an external plug&play routing logic with no modifications to ONOS applications at all. Finally we evaluate the benefits by enhancing the ONOS SDN-IP application with an adaptive Robust Traffic Engineering algorithm.

SDN intent-based networking allows programmers to specify high-level policies without worrying about the low-level configurations which are compiled by the controller. Our Intent Monitor and Reroute service (IMR) extends the capabilities of ONOS Intent Framework by allowing to both compile multiple intents together and to re-optimize their paths, according to the network state and their flow statistics, via off-platform applications (OPA). In this demo we show two examples of intent-based ONOS application whose network performance can be improved, with no modifications to their code, exploiting the IMR service.

The attractive features of millimeter-wave (mm-wave) technologies in the forthcoming 5G networks entail a rich set of network access challenges. These technologies are characterized by high-gain array antennas to overcome the huge attenuations, this requires to resort to directional transmissions during every network operation. The initial access phase is one of the most critical, because, if not properly managed, it can introduce a non-negligible access delay caused by multiple transmission attempts along several directions. We believe that contextual information about user and network conditions can boost this discovery phase. In this paper, we investigate how differently-rich context information can impact on the duration of the initial cell access. We propose several initial access procedures that can exploit different available information and cope with the presence of obstacles within the service area. Finally, relying on the contextual information on past access attempts, we develop a recommendation system based on machine-learning techniques, which, by processing this information, can derive the best directions to explore to connect incoming users.

Nowadays, the maintenance costs of wireless devices represent one of the main limitations to the deployment of wireless mesh networks (WMNs) as a means to provide Internet access in urban and rural areas. A promising solution to this issue is to let the WMN operator lease its available bandwidth to a subset of customers, forming a wireless mesh community network, in order to increase network coverage and the number of residential users it can serve. In this paper, we propose and analyze an innovative marketplace to allocate the available bandwidth of a WMN operator to those customers who are willing to pay the higher price for the requested bandwidth, which in turn can be subleased to other residential users. We formulate the allocation mechanism as a combinatorial truthful auction considering the key features of wireless multihop networks and further present a greedy algorithm that finds efficient and fair allocations even for large-scale, real scenarios while maintaining the truthfulness property. Numerical results show that the greedy algorithm represents an efficient, fair, and practical alternative to the combinatorial auction mechanism.

The exponential growth of mobile traffic is forcing operators to quickly increase the capacity of their networks by means of new technologies and advanced architectures. This capacity expansion not only brings increasing fixed costs for additional network infrastructures, but also inflates operational costs, which are becoming critical, mainly in terms of energy bills. In this perspective, monitoring the energy consumption of network devices and defining their energy profile models are valuable approaches for estimating energy costs and identifying the most efficient configurations. In this article, we propose an energy profiling approach that simplifies the characterization of different base station components and allows the estimation of the network energy efficiency relying only on traffic statistics. We have validated the approach over the extensive dataset of real measurements provided by a probe network for monitoring live energy consumption of Vodafone sites in three different countries.

Cognitive radio networks (CRNs) are composed of frequency-agile radio devices that allow licensed (primary) and unlicensed (secondary) users to coexist, where secondary users opportunistically access channels without interfering with the operation of primary ones. From the perspective of secondary users, spectrum availability is a time-varying network resource over which multihop end-to-end connections must be maintained. In this paper, a theoretical outlook on the problem of routing secondary user flows in a CRN is provided. The investigation aims to characterize optimal sequences of routes over which a secondary flow is maintained. The optimality is defined according to a novel metric that considers the maintenance cost of a route as channels, and/or links must be switched due to the primary user activity. Different from the traditional notion of route stability, the proposed approach considers subsequent path selections, as well. The problem is formulated as an integer programming optimization model. Properties of the problem are also formally introduced and leveraged to design a heuristic algorithm when information on primary user activity is not complete. Numerical results are presented to assess the optimality gap of the heuristic routing algorithm in realistic CRN scenarios.

The introduction of millimeter-wave (mm-wave) technologies in the future 5G networks poses a rich set of network access challenges. We need new ways of dealing with legacy network functionalities to fully unleash their great potential, among them the cell discovery procedure is one of the most critical. In this paper, we propose novel cell discovery algorithms enhanced by the context information available through a C-/U-plane-split heterogeneous network architecture. They rely on a geo-located context database to overcome the severe effects of obstacle blockages. Moreover, we investigate the coordination problem of multiple mm-wave base stations that jointly process user access requests. We show that optimizing the resource allocated to the discovery has a great importance in defining perceived latency and supported user request rate. We have performed complete and accurate numerical simulations to provide a clear overview of the main challenging aspects. The results show that the proposed solutions have an outstanding performance with respect to basic discovery approaches and can fully enable mm-wave cell discovery in 5G networks.

Hybrid Wireless-Optical Broadband Access Networks (WOBANs) are gauging momentum as flexible, bandwidth-effective, and cost-effective solutions for providing connectivity to residential users in metropolitan areas. In this work, we address the issue of designing the topology of deployed WOBANs. Namely, we consider the case where the coverage of a Ethernet-based Passive Optical Network (EPON) is extended by an additional wireless segment which features multi-hop wireless links operated either according to the IEEE 802.11 standard, or to the IEEE 802.16 one. We propose a mathematical programming model which optimizes the overall WOBAN topology in terms of deployment cost, while accounting for the specific traffic requirements of the residential users, and the specific features of the technological components. The potentials of the proposed model are showcased by deriving and commenting numerical results obtained when planning realistic WOBAN scenarios.

International audience; The opportunistic utilization of third party WiFi access devices to offload customer traffic from the mobile network has recently gained momentum as a promising approach to increase the network capacity and simultaneously reduce the energy consumption of the Radio Access Network (RAN) infrastructure. To foster the opportunistic utilization of unexploited Internet connections, we propose a new and open market where a mobile operator can lease the bandwidth made available by third parties (residential users or private companies) through their access points to increase dynamically (and adaptively) the network capacity. We formulate the offloading problem as a reverse auction considering the most general case of partial covering of the traffic to be offloaded. We discuss the conditions (i) to offload the maximum amount of data traffic according to the capacity made available by third party access devices, (ii) to foster the participation of access point owners (individual rationality), and (iii) to prevent market manipulation (incentive compatibility). Finally, we propose three alternative greedy algorithms that efficiently solve the offloading problem, even for large-size network scenarios.

Inter-Cell Interference Coordination (ICIC) has been identified for LTE as the main instrument for interference control. With ICIC, quality requirements can be guaranteed while avoiding the complexity of coordinated baseband processing approaches. However, most ICIC schemes proposed so far rely on centralized multi-cell scheduling algorithms that involve very heavy signaling overhead and, as a result, cannot be used for dense cellular layouts. In this paper, we propose H 2 (IC) 2 , a novel ICIC scheme that, in contrast to previous approaches, incurs very low overhead and is practical for dense deployments. H 2 (IC) 2 is based on the Almost Blank SubFrame (ABSF) approach specified by 3GPP, which controls interference by avoiding data transmission in some subframes. Our scheme follows a two-tier approach, consisting of (i) the local schedulers, which perform the scheduling decisions locally and compute ABSF patterns, and (ii) a central coordinator, which supervises ABSF decisions. As a result of such a two-tier design, the scheme requires very light signaling to drive the local schedulers to globally efficient operating points. We analyze the convergence of distributed ABSF/scheduling decisions by using game theoretical tools and show that H 2 (IC) 2 performs fairly close to the benchmark provided by a centralized omniscient scheduler.

With the advent of next-generation mobile devices, wireless networks must be upgraded to fill the gap between huge user data demands and scarce channel capacity. Mm-waves technologies appear as the key-enabler for the future 5G networks design, exhibiting large bandwidth availability and high data rate. As counterpart, the small wave-length incurs in a harsh signal propagation that limits the transmission range. To overcome this limitation, array of antennas with a relatively high number of small elements are used to exploit beamforming techniques that greatly increase antenna directionality both at base station and user terminal. These very narrow beams are used during data transfer and tracking techniques dynamically adapt the direction according to terminal mobility. During cell discovery when initial synchronization must be acquired, however, directionality can delay the process since the best direction to point the beam is unknown. All space must be scanned using the tradeoff between beam width and transmission range. Some support to speed up the cell search process can come from the new architectures for 5G currently being investigated, where conventional wireless network and mm-waves technologies coexist. In these architecture a functional split between C-plane and U-plane allows to guarantee the continuous availability of a signaling channel through conventional wireless technologies with the opportunity to convey context information from users to network. In this paper, we investigate the use of position information provided by user terminals in order to improve the performance of the cell search process. We analyze mm-wave propagation environment and show how it is possible to take into account of position inaccuracy and reflected rays in presence of obstacles. TRUE pub

This paper presents the approach of extending cellular networks with millimeter-wave backhaul and access links. Introducing a logical split between control and user plane will permit full coverage while seamlessly achieving very high data rates in the vicinity of mm-wave small cells.

Base stations have been identified to be the most power consuming part in current mobile networks. Since their power profile only depends to a small fraction on the actual traffic load, putting some base stations in sleep mode has been identified as a solution to scale the network power consumption with the actual load. This paper presents a new system architecture based on the paradigm of “cell on-demand”, which is currently studied in the Beyond Cellular Green Generation (BCG2) project of the GreenTouch consortium. We first outline the key characteristics of the new system architecture, then, we present a framework for position information processing in order to predict the channel quality between a user and a set of switched-off base stations that can potentially be activated by the system to serve the user. Experimental evaluation on a small scale testbed shows the viability of the proposed framework by achieving estimation errors of 20%.

We consider cognitive radio networks where primary licensed users coexist with unlicensed users, which are allowed to opportunistically access licensed spectrum upon performing spectrum sensing functionality. An analytical framework based on queuing theory and game theory is introduced to assess the performance of the spectrum sharing process. Queuing theory is used to model the achievable throughput of secondary users, whereas game theoretic tools are introduced to capture the competitive dynamics of the spectrum sharing process among multiple secondary users. The proposed framework is used to derive performance measures of spectrum sharing when spectrum access is/is not regulated by a central spectrum management authority.

The Radio Access Network (RAN) infrastructure represents the most critical part for capacity planning, which usually accounts for peak traffic conditions. A promising approach to increase the RAN capacity and simultaneously reduce its energy consumption is represented by the opportunistic utilization of third party Wi-Fi access devices. In order to foster the utilization of unexploited Internet connections, we propose a new and open market, where a mobile operator can lease the bandwidth made available by third parties (residential users or private companies) through their access points to increase the network capacity and save large amounts of energy. We formulate the offloading problem as a reverse auction considering the most general case of partial covering of the traffic to be offloaded. We discuss the conditions (i) to offload the maximum amount of data traffic according to the capacity of third party access devices, (ii) to foster the participation of access point owners (individual rationality), and (iii) to prevent market manipulation (incentive compatibility). Finally, we propose a greedy algorithm that solves the offloading problem in polynomial time, even for large-size network scenarios.

In recent years, with the evolution of new and content-rich Internet services, mobile network operators face the challenging task to guarantee ubiquitous access to their customers, while minimizing network deployment costs. In order to foster the opportunistic utilization of unexploited Internet connections of residential users, we propose a new marketplace where mobile network operators can rent the unused capacity of residential users' access devices (e.g., wireless access points or femtocells) when the traffic demand of their mobile customers exceeds the operator's network capacity. We formulate the allocation problem as a combinatorial reverse auction, which prevents market manipulation, and we further propose a greedy algorithm that finds efficient allocations in polynomial time, even for large-size network scenarios. Numerical results demonstrate that our proposed schemes well capture the economical and networking essence of the allocation problem, thus representing a promising approach to enhance the performance of next-generation wireless access networks.

This work considers the issue of distributing contents to vehicles through roadside communication infrastructure. Within this scenario, this work studies the dynamics of infrastructure deployment by using game theoretic tools. A strategic game is used to model the case in which the operators perform their deployment decisions concurrently, whereas an extensive game is used to study the dynamics in case one operator is the deployment leader and moves first. The equilibria of the aforementioned games are then assessed as a function of several parameters (nominal infrastructure capacity, interference, vehicle flows). Simulations are used to validate the analytical findings. © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20120427

With the proliferation of mobile devices and vehicular onboard-units mobility is becoming a key factor in determining the performance of networked systems: both the performance of the infrastructure (e.g., the amount of control traffic) and the performance perceived by the end-users (e.g., access latency, throughput) are influenced by mobility. Mobility, as a manifestation of the physical world, transforms content distribution systems into cyber-physical systems. The efficient design and operation of cyber-physical systems, in general, requires an understanding of the characteristics and of the interactions between the components of the system.

Data collected by sensors often have to be remotely delivered through multi-hop wireless paths to data sinks connected to application servers for information processing. The position of these sinks has a huge impact on the quality of the specific Wireless Sensor Network (WSN). Indeed, it may create artificial traffic bottlenecks which affect the energy efficiency and the WSN lifetime. This paper considers a heterogeneous network scenario where wireless sensors deliver data to intermediate gateways geared with a diverse wireless technology and interconnected together and to the sink. An optimization framework based on Integer Linear Programming (ILP) is developed to locate wireless gateways minimizing the overall installation cost and the energy consumption in the WSN, while accounting for multi-hop coverage between sensors and gateways, and connectivity among wireless gateways. A traffic-variable scenario is also considered, where the network can go through high and low traffic operation points, and the topology is optimized accordingly. The proposed ILP formulations are solved to optimality for medium-size instances to analyze the quality of the designed networks, and heuristic algorithms are also proposed to tackle large-scale heterogeneous scenarios.

Cognitive Radio Networks (CRNs) are composed of frequency-agile radio devices that allow licensed (primary) and unlicensed (secondary) users to coexist, where secondary users opportunistically access channels without interfering with the operation of primary ones. From the perspective of secondary users, spectrum availability is a time varying network resource over which multi-hop end-to-end connections must be maintained. In this work, a theoretical outlook on the problem of routing secondary user flows in a CRN is provided. The investigation aims to characterize optimal sequences of routes over which a secondary flow is maintained. The optimality is defined according to a novel metric that considers the maintenance cost of a route as channels and/or links must be switched due to the primary user activity. Different from the traditional notion of route stability, the proposed approach considers subsequent path selections, as well. The problem is formulated as an integer programming optimization model and shown to be of polynomial time complexity in case of full knowledge of primary user activity. Properties of the problem are also formally introduced and leveraged to design a heuristic algorithm to solve the minimum maintenance cost routing problem when information on primary user activity is not complete. Numerical results are presented to assess the optimality gap of the heuristic routing algorithm.

Data collected by sensors often have to be remotely delivered through multi-hop wireless paths to data sinks connected to application servers for information processing. The position of these sinks has a huge impact on the quality of the specific Wireless Sensor Network (WSN). Indeed, it may create artificial traffic bottlenecks which affect the energy efficiency and the WSN lifetime. This paper considers a heterogeneous network scenario where wireless sensors deliver data to intermediate gateways geared with a diverse wireless technology and interconnected together and to the sink. An optimization framework based on Integer Linear Programming (ILP) is developed to locate wireless gateways minimizing the overall installation cost and the energy consumption in the WSN, while accounting for multi-hop coverage between sensors and gateways, and connectivity among wireless gateways. The proposed ILP formulations are solved to optimality for medium-size instances to analyze the quality of the designed networks, and heuristic algorithms are also proposed to tackle large-scale heterogeneous scenarios.

In this paper novel optimization models are proposed for planning Wireless Mesh Networks (WMNs), where the objective is to minimize the network installation cost while providing full coverage to wireless mesh clients. Our mixed integer linear programming models allow to select the number and positions of mesh routers and access points, while accurately taking into account traffic routing, interference, rate adaptation, and channel assignment. We provide the optimal solutions of three problem formulations for a set of realistic-size instances (with up to 60 mesh devices) and discuss the effect of different parameters on the characteristics of the planned networks. Moreover, we propose and evaluate a relaxation-based heuristic for large-sized network instances which jointly solves the topology/coverage planning and channel assignment problems. Finally, the quality of the planned networks is evaluated under different traffic conditions through detailed system level simulations.

Wireless Mesh Networks (WMNs) have recently emerged as a technology for next-generation wireless networking. WMNs partially replace wired backbone networks, and it is therefore reasonable to plan carefully radio resource assignment to provide quality guarantees to traffic flows. Directional transmissions allow to reduce radio interference, thus exploiting spatial reuse. Therefore, as a main contribution, in this paper we study the joint routing and scheduling optimization problem in Wireless Mesh Networks where nodes are equipped with directional antennas. To this aim, we assume a Spatial reuse Time Division Multiple Access (STDMA) scheme, a dynamic power control able to vary the emitted power slot-by-slot, and a rate adaptation mechanism that sets transmission rates according to the Signal- to-Interference-and-Noise Ratio (SINR). We provide column generation-based heuristic approaches for the proposed models in a set of realistic-size instances and discuss the impact of different parameters on the network performance. The results show that our schemes increase considerably the total traffic accepted by the network, providing bounds to the achievable performance.

Trajectory Based Forwarding (TBF) is a new approach to routing in ad hoc wireless networks. It exploits node position information and, similarly to source routing, requires the source node to encode a trajectory into the packet header. The routing process does not require to specify forwarding nodes. As a matter of fact, forwarding nodes are dynamically selected while packets cross the network according to their position with respect to the trajectory. Therefore, this new approach is particularly suitable for application scenarios where network topology is fast varying, due to node mobility (e.g. inter-vehicular networks) or to energy management schemes (e.g. sensor networks), whereas the stability of the trajectories is guaranteed by the physical characteristics of the service area (roads, building aisles, etc.). This paper describes a new TBF scheme that shifts forwarding decision from transmitter to receiver exploiting broadcast transmissions. We thoroughly analyze the behavior and the properties of the proposed scheme considering the impact of the medium access control mechanism and the effect of limited transmission ranges. We consider piecewise lines connecting source node to destination area and we extend the approach to the multicast case by defining trajectory-trees. Moreover, we propose a forwarding mechanism able to walk around obstacles along the trajectory.

Trajectory based forwarding (TBF) is a new approach for routing in ad hoc wireless networks. It assumes that nodes know their position and, similarly to source routing, requires the source node to encode a trajectory into the packet header. However, trajectories are just geometrical lines and the routing process does not require specifying forwarding nodes. As a matter of fact, forwarding nodes are dynamically selected while packets cross the network according to their position with respect to the trajectory. Therefore, this new approach is particularly suitable for application scenarios where network topology is fast varying, due to node mobility (e.g. inter-vehicular networks) or to energy management schemes (e.g. sensor networks), whereas the stability of the trajectories is guaranteed by the physical characteristics of the service area (roads, building aisles etc.). In this paper we propose a new TBF scheme that exploits broadcast transmissions at MAC layer and does not require maintaining a list of active neighbours positions in every node. We consider piecewise lines connecting source node to destination area and we extend the approach to the multicast case defining trajectory-trees.

Future metropolitan and access networks are expected to comprise heterogeneous optical and broadband wireless technologies. The growing demand of users for transparent, ubiquitous access to diverse communication services poses several challenges. We envision a future metro-access architecture that comprises Optical Burst Switching networks that feed Ethernet Passive Optical Networks (PON) or upcoming Wavelength-Division Multiplexing PON, which in turn feed IEEE 802.16 and IEEE 802.11 nodes. Nodes in the wireless realm may communicate in a multihop fashion, forming mesh networks. To maintain cost and resource efficiency, we propose the introduction of Quality of Service (QoS) proxies at the border between different link technologies. These entities handle QoS requirements and aid to the support of mobility. The architecture requires no modification of the Medium Access Control mechanisms of the different technologies.