Wireless Mesh Networks to Support Video Surveillance: Architecture, Protocol, and Implementation Issues

Current video-surveillance systems typically consist of many video sources distributed over a wide area, transmitting live video streams to a central location for processing and monitoring. The target of this paper is to present an experience of implementation of a large-scale video-surveillance system based on a wireless mesh network infrastructure, discussing architecture, protocol, and implementation issues. More specifically, the paper proposes an architecture for a video-surveillance system, and mainly centers its focus on the routing protocol to be used in the wireless mesh network, evaluating its impact on performance at the receiver side. A wireless mesh network was chosen to support a video-surveillance application in order to reduce the overall system costs and increase scalability and performance. The paper analyzes the performance of the network in order to choose design parameters that will achieve the best trade-off between video encoding quality and the network traffic generated

orchestrating softwarized networks with a marketplace approach

Abstract In the last years, network softwarization is gaining increasing popularity since it allows to achieve dinamicity and flexibility in network management, stimulating a lot of interest by both academia and industry. Cloud computing paradigm together with the new networking paradigms of Software Defined Networking (SDN) and Network Function Virtualization (NFV) are supporting this evolution, by providing network services as single Virtual Network Functions (VNFs) or chains of them. The main problem is scalability of both infrastructure and management. In fact, in order to support the SDN/NFV paradigm, the Telco Operator should deploy huge data centers, which have to be geographically distributed to guarantee low latencies to time-constrained flows, and implement complex orchestration policies. To this purpose, this paper proposes to extend the SDN/NFV framework with a marketplace where Telco Operator customers behave as third-party sellers with their hardware and software resources providing VNF as a service (VNFaaS), so helping the Telco Operator in providing network services in an efficient and scalable way

A processor-sharing scheduling strategy for NFV nodes

The introduction of the two paradigms SDN and NFV to "softwarize" the current Internet is making management and resource allocation two key challenges in the evolution towards the Future Internet. In this context, this paper proposes Network-Aware Round Robin (NARR), a processor-sharing strategy, to reduce delays in traversing SDN/NFV nodes. The application of NARR alleviates the job of the Orchestrator by automatically working at the intranode level, dynamically assigning the processor slices to the virtual network functions (VNFs) according to the state of the queues associated with the output links of the network interface cards (NICs). An extensive simulation set is presented to show the improvements achieved with respect to two more processor-sharing strategies chosen as reference

Design of a Traffic-Aware Governor for Green Routers

Today the reduction of energy consumption in telecommunications networks is one of the main goals to be pursued by manufacturers and researchers. In this context, the paper focuses on routers that achieve energy saving by applying the frequency scaling approach. The target is to propose an analytical model to support designers in choosing the main configuration parameters of the Router Governor in order to meet Quality of Service (QoS) requirements while maximizing energy saving gain. More specifically, the model is used to evaluate the input traffic impacts on the choice of the active router clock frequencies and on the overall green router performance. A case study based on the open NetFPGA reference router is considered to show how the proposed model can be easily applied to a real case scenario

On the intertwining between capacity scaling and TCP congestion control

Recent works advocate the possibility of improving energy efficiency of network devices by modulating switching and transmission capacity according to traffic load. However, addressing the trade-off between energy saving and Quality of Service (QoS) under these approaches is not a trivial task, specially because most of the traffic in the Internet of today is carried by TCP, and is hence adaptive to the available resources. In this paper we present a preliminary investigation of the possible intertwining between capacity scaling approaches and TCP congestion control, and we show how this interaction can affect performance in terms of both energy saving and QoS

Network interface power management and TCP congestion control: a troubled marriage

Optimizing the trade-off between power saving and Quality of Service in the current Internet is a challenging research objective, whose difficulty stems also from the dominant presence of Transmission Control Protocol (TCP) traffic, and its elastic nature. More specifically, recent works support the possibility of improving energy efficiency of network devices by modulating switching and transmission capacity according to traffic load, whereas TCP traffic is in turn adaptive to the available resources. In a previous work, we have shown that an intertwining exists between capacity scaling approaches and TCP congestion control. In this paper, we investigate the reasons of such intertwining, and we evaluate how and how much the dynamics of the two algorithms affect each other’s performance. More specifically, we will show that such an interaction is essentially due to the relative speed of the two algorithms, which determines the conditions for the successful or unsuccessful coexistence of the two mechanisms

Effect of Islanding and Telecontrolled Switches on Distribution System Reliability Considering Load and Green-Energy Fluctuations

To improve electrical distribution network reliability, some portions of the network could operate in autonomous mode, provided that the related technical issues are addressed. More specifically, when there is not a path from those portions to the primary substation due to a fault in the network, such portions could be disconnected from the main network and supplied by local generation only. Such a mode of operation is known as "intentional islanding" and its effectiveness, in terms of adequacy, depends on the ability of the local generation to meet the island's load. In fact, the ratio between the available local generation and load demand can frequently change during islanding due to load variations and, especially, due to the strongly irregular behavior of the primary energy sources of renewable generators. This paper proposes an analytical formulation to assess local generation adequacy during intentional islanding, accounting for the aforementioned variations. More specifically, the fluctuations of load and green-energy generators during islanding are modeled by means of Markov chains, whose output quantities are encompassed in the proposed analytical formulation. Such a formulation is used by the analytical equations of load points' outage rate and duration. The evaluation of the reliability indices accounts for a protection scheme based on an appropriate communication infrastructure. Therefore, a brief overview on the telecommunications technologies has been presented with reference to their suitability for the specific application. In particular, distribution network safety issues have been considered as the main concern. The results show that neglecting load and generation fluctuations leads to a strong overestimation of the ability of distributed generators to meet the island load. Through a case study it is observed that the error on the load point outage rate is greater than the one affecting the outage duration

Battery Management in a Green Fog-Computing Node: a Reinforcement-Learning Approach

In the last years, Internet is evolving towards the cloud-computing paradigm complemented by fog-computing in order to distribute computing, storage, control, networking resources, and services close to end-user devices as much as possible, while sending heavy jobs to the remote cloud. When fog-computing nodes cannot be powered by the main electric grid, some environmental-friendly solutions, such as the use of solar- or wind-based generators could be adopted. Their relatively unpredictable power output makes it necessary to include an energy storage system in order to provide power, when a peak of work occurs during periods of low-power generation. An optimized management of such an energy storage system in a green fog-computing node is necessary in order to improve the system performance, allowing the system to cope with high job arrival peaks even during low-power generation periods. In this perspective, this paper adopts reinforcement learning to choose a server activation policy that ensures the minimum job loss probability. A case study is presented to show how the proposed system works, and an extensive performance analysis of a fog-computing node highlights the importance of optimizing battery management according to the size of the Renewable-Energy Generator system and the number of available servers

Modelli per la gestione di servizi multimediali su reti a larga banda

Dottorato di ricerca in ingegneria elettronica, informatica e delle telecomunicazioni. 8. ciclo. Coordinatore C. Tamburello. Tutore S. PalazzoConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro,7, Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal