We propose an analytical framework to tightly characterize the scaling laws for the additional bandwidth that servers must supply to guarantee perfect service in peer-assisted Video-on-Demand systems, taking into account essential aspects such as peer churn, bandwidth heterogeneity, and Zipf-like video popularity. Our results reveal that the catalog size and the content popularity distribution have a huge effect on the system performance. We show that users' cooperation can effectively reduce the servers' burden for a wide range of system parameters, confirming to be an attractive solution to limit the costs incurred by content providers as the system scales to large populations of users.

We propose a unified methodology to analyse the performance of caches (both isolated and interconnected), by extending and generalizing a decoupling technique originally known as Che's approximation, which provides very accurate results at low computational cost. We consider several caching policies, taking into account the effects of temporal locality. In the case of interconnected caches, our approach allows us to do better than the Poisson approximation commonly adopted in prior work. Our results, validated against simulations and trace-driven experiments, provide interesting insights into the performance of caching systems.

We analyze a peer-assisted Video-on-Demand (VoD) system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case, as well as in controlled nonsequential swarms. Our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, and nonstationary traffic conditions, which have not been documented or analyzed before. Finally, we provide important hints for the design of efficient peer-assisted VoD systems under server capacity constraints.

We propose an analytical framework to tightly characterize the scaling laws for the additional bandwidth that servers must supply to guarantee perfect service in peer-assisted Video-on-Demand systems, taking into account essential aspects such as peer churn, bandwidth heterogeneity, and Zipf-like video popularity. Our results reveal that the catalog size and the content popularity distribution have a huge effect on the system performance. We show that users' cooperation can effectively reduce the servers' burden for a wide range of system parameters, confirming to be an attractive solution to limit the costs incurred by content providers as the system scales to large populations of users.

We consider a communication system in which a given digital content has to be delivered sequentially at constant rate to a set of users who asynchronously request it according to a Poisson process. Users can retrieve data: 1) from one or more sources that statically store the entire content; and 2) from users who have previously requested the content, and contribute (for limited time) a random amount of upload bandwidth to the system. We propose a stochastic fluid framework that allows characterizing the aggregate streaming rate necessary at the sources to satisfy all active requests. In particular, we establish the conditions under which the system becomes asymptotically scalable as the number of users grows. Our theoretical results apply to increasingly popular video-on-demand systems exploiting users' cooperation.

We consider a peer-assisted Video-on-demand system, in which video distribution is supported both by peers caching the whole video and by peers concurrently downloading it. We propose a stochastic fluid framework that allows to characterize the additional bandwidth requested from the servers to satisfy all users watching a given video. We obtain analytical upper bounds to the server bandwidth needed in the case in which users download the video content sequentially. We also present a methodology to obtain exact solutions for special cases of peer upload bandwidth distribution. Our bounds permit to tightly characterize the performance of peer-assisted VoD systems as the number of users increases, for both sequential and non-sequential delivery schemes. In particular, we rigorously prove that the simple sequential scheme is asymptotically optimal both in the bandwidth surplus and in the bandwidth deficit mode, and that peer-assisted systems become totally self-sustaining in the surplus mode as the number of users grows large.

We analyze a peer-assisted Video-on-Demand system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case. Our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, non-stationary traffic conditions, which have not been documented or analyzed before. We provide an analytical methodology to design efficient peer-assisted VoD systems and optimal resource allocation strategies.

Optical switching fabrics (OSF) are gaining interest because they promise to satisfy the higher information densities demanded by each successive generation of high-end routers and switches. Silicon microring resonators (MRR) can be employed to perform switching operations directly in the optical domain. However, similarly to other devices used to build all-optical switching fabrics, such as Arrayed Waveguide Gratings (AWG), MRR-based switching fabrics might show a limited scalability in terms of port count due to the crosstalk accumulation caused by the spatial wavelengths reuse. We consider an OSF built on a Wavelength-Routing-Matrix (WRM) based on MRRs, we highlight its scalability issues and we propose a new design as well as two different strategies to limit the wavelength spatial reuse.

We extend the analysis of the scaling laws of wireless ad hoc networks to the case of correlated nodes movements, which are commonly found in real mobility processes. We consider a simple version of the Reference Point Group Mobility model, in which nodes belonging to the same group are constrained to lie in a disc area, whose center moves uniformly across the network according to the i.i.d. model. We assume fast mobility conditions and take as a primary goal the maximization of per-node throughput. We discover that correlated node movements have a huge impact on asymptotic throughput and delay and can sometimes lead to better performance than the one achievable under independent nodes movements.

We extend the analysis of the scaling laws of wireless ad hoc networks to the case of correlated nodes movements, which are commonly found in real mobility processes. We consider a simple version of the Reference Point Group Mobility model, in which nodes belonging to the same group are constrained to lie in a disc area, whose center moves uniformly across the network according to the i.i.d. model. We assume fast mobility conditions, and take as primary goal the maximization of per-node throughput. We discover that correlated node movements have huge impact on asymptotic throughput and delay, and can sometimes lead to better performance than the one achievable under independent nodes movements.

We consider static ad hoc wireless networks comprising significant inhomogeneities in the node spatial distribution over the area and analyze the scaling laws of their transport capacity as the number of nodes increases. In particular, we consider nodes placed according to a shot-noise Cox process (SNCP), which allows to model the clustering behavior usually recognized in large-scale systems. For this class of networks, we propose novel scheduling and routing schemes that approach previously computed upper bounds to the per-flow throughput as the number of nodes tends to infinity.

In this paper, we analyze asymptotic delay-throughput performance of mobile ad-hoc networks comprising heterogeneous nodes with restricted mobility. In particular, we consider a scenario in which each node moves around one or more home-points (in a finite number) randomly placed over the area. For such restricted mobility model, we propose a new class of scheduling and routing schemes, which significantly outperforms all delay-throughput results previously obtained.