Optimal mobility-aware admission control in content delivery networks

This paper addresses the problem of mobility management in Content Delivery Networks (CDN). We introduce a CDN architecture where admission control is performed at mobility aware access routers. We formulate a Markov Modulated Poisson Decision Process for access control that captures the bursty nature of data and packetized traffic together with the heterogeneity of multimedia services. The optimization of performance parameters, like the blocking probabilities and the overall utilization, is conducted and the structural properties of the optimal solutions are also studied. Heuristics are proposed to encompass the computational difficulties of the optimal solution when several classes of multimedia traffic are considered

Energy-Efficient selective activation in Femtocell Networks

Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce GREENFEMTO, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that GREENFEMTO converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that GREENFEMTO requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution

Push & Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push&Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push&Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.Comment: Technical Report. This paper has been published on Wireless Networks, Springer. Animations and the complete code of the proposed algorithm are available for download at the address: http://www.dsi.uniroma1.it/~novella/mobile_sensors

Fast network configuration in Software Defined Networking

Software Defined Networking (SDN) provides a framework to dynamically adjust and re-program the data plane with the use of flow rules. The realization of highly adaptive SDNs with the ability to respond to changing demands or recover after a network failure in a short period of time, hinges on efficient updates of flow rules. We model the time to deploy a set of flow rules by the update time at the bottleneck switch, and formulate the problem of selecting paths to minimize the deployment time under feasibility constraints as a mixed integer linear program (MILP). To reduce the computation time of determining flow rules, we propose efficient heuristics designed to approximate the minimum-deployment-time solution by relaxing the MILP or selecting the paths sequentially. Through extensive simulations we show that our algorithms outperform current, shortest path based solutions by reducing the total network configuration time up to 55% while having similar packet loss, in the considered scenarios. We also demonstrate that in a networked environment with a certain fraction of failed links, our algorithms are able to reduce the average time to reestablish disrupted flows by 40%

Effect of nitrogen fertilization on sorghum for biomass production

ArticleTwo field experiments were carried out in 2005 and 2006 in central Italy in order to evaluate the effects of different nitrogen (N) application rates (0, 50 100 and 150 kg ha-1 ) on flowering date, plant height, biomass production and partitioning (leaves, panicles and stems) and biomass quality of a sorghum hybrid (H133). Sorghum showed a high potential in terms of biomass production without N fertilization (18.5 t ha-1 of d.m. in 2005 and 26.6 t ha-1 of d.m. in 2006). The rate that maximized the biomass production was 100 kg ha-1 of N, increasing the biomass dry weight by 23.8% in 2005 and 18.8% in 2006, with respect to unfertilized sorghum; higher N rates are not advisable in order to avoid increasing fertilization costs and environmental impact without benefit of greater biomass production. The two highest N rates when combined with low water availability appeared to increase the rate of plant development, causing earlier flowering and increasing the percentage of panicles in total biomass. Higher heating value (HHV), lower heating value (LHV) and ash concentration of biomass varied among N rates, with values of HHV and LHV lower for unfertilized sorghum (17.6 and 16.7 MJ kg-1 d.m., respectively) than when N was applied (from 19.0 to 19.7 and from 18.1 to 18.8 MJ kg-1 d.m., respectively); on the contrary, ash concentration was greater for unfertilized sorghum (7.5% d.m.) than for fertilized sorghum (from 5.8 to 6.7% d.m.). This research showed the high potential of sorghum in terms of biomass production also when cultivated with limited irrigation and fertilization inputs. The biomass dry yield obtained by one hectare of sorghum crop without N nitrogen fertilization (i.e. 22.6 t ha-1 of d.m., average of 2005 and 2006 values) produces the same energy, by thermal utilisation, of 9.3 toe, that is equivalent to energy produced by 10,385 L of diesel fuel or 11,097 m3 of methane fuel. This aspect increases the certainty of the energetic and environmental sustainability of sorghum crop

Network recovery from massive failures under uncertain knowledge of damages

This paper addresses progressive network recovery under uncertain knowledge of damages. We formulate the problem as a mixed integer linear programming (MILP), and show that it is NP-Hard. We propose an iterative stochastic recovery algorithm (ISR) to recover the network in a progressive manner to satisfy the critical services. At each optimization step, we make a decision to repair a part of the network and gather more information iteratively, until critical services are completely restored. Three different algorithms are used to find a feasible set and determine which node to repair, namely, 1) an iterative shortest path algorithm (ISR-SRT), 2) an approximate branch and bound (ISR-BB) and 3) an iterative multi-commodity LP relaxation (ISR-MULT). Further, we have modified the state-of-the-Art iterative split and prune (ISP) algorithm to incorporate the uncertain failures. Our results show that ISR-BB and ISR- MULT outperform the state-of-the-Art 'progressive ISP' algorithm while we can configure our choice of trade-off between the execution time, number of repairs (cost) and the demand loss. We show that our recovery algorithm, on average, can reduce the total number of repairs by a factor of about 3 with respect to ISP, while satisfying all critical deman

Multi-Pulse Laser Wakefield Acceleration: A New Route to Efficient, High-Repetition-Rate Plasma Accelerators and High Flux Radiation Sources

Laser-driven plasma accelerators can generate accelerating gradients three orders of magnitude larger than radio-frequency accelerators and have achieved beam energies above 1 GeV in centimetre long stages. However, the pulse repetition rate and wall-plug efficiency of plasma accelerators is limited by the driving laser to less than approximately 1 Hz and 0.1% respectively. Here we investigate the prospects for exciting the plasma wave with trains of low-energy laser pulses rather than a single high-energy pulse. Resonantly exciting the wakefield in this way would enable the use of different technologies, such as fibre or thin-disc lasers, which are able to operate at multi-kilohertz pulse repetition rates and with wall-plug efficiencies two orders of magnitude higher than current laser systems. We outline the parameters of efficient, GeV-scale, 10-kHz plasma accelerators and show that they could drive compact X-ray sources with average photon fluxes comparable to those of third-generation light source but with significantly improved temporal resolution. Likewise FEL operation could be driven with comparable peak power but with significantly larger repetition rates than extant FELs