Valentino Pacifici

Convergence in Player-Specific Graphical Resource Allocation Games

As a model of distributed resource allocation in networked systems, we consider resource allocation games played over a influence graph. The influence graph models limited interaction between the players due to, e.g., the network topology: the payoff that an allocated resource yields to a player depends only on the resources allocated by her neighbors on the graph. We prove that pure strategy Nash equilibria (NE) always exist in graphical resource allocation games and we provide a linear time algorithm to compute equilibria. We show that these games do not admit a potential function: if there are closed paths in the influence graph then there can be best reply cycles. Nevertheless, we show that from any initial allocation of a resource allocation game it is possible to reach a NE by playing best replies and we provide a bound on the maximal number of update steps required. Furthermore we give sufficient conditions in terms of the influence graph topology and the utility structure under which best reply cycles do not exist. Finally we propose an efficient distributed algorithm to reach an equilibrium over an arbitrary graph and we illustrate its performance on different random graph topologies.

Cache capacity allocation for BitTorrent-like systems to minimize inter-ISP traffic

Many Internet service providers (ISPs) have deployed peer-to-peer (P2P) caches in their networks in order to decrease costly inter-ISP traffic. A P2P cache stores parts of the most popular contents locally, and if possible serves the requests of local peers to decrease the inter-ISP traffic. Traditionally, P2P cache resource management focuses on managing the storage resource of the cache so as to maximize the inter-ISP traffic savings. In this paper we show that when there are many overlays competing for the upload bandwidth of a P2P cache then in order to maximize the inter-ISP traffic savings the caches upload bandwidth should be actively allocated among the overlays. We formulate the problem of P2P cache bandwidth allocation as a Markov decision process, and describe two approximations to the optimal cache bandwidth allocation policy. Based on the insights obtained from the approximate policies we propose SRP, a priority-based allocation policy for BitTorrent-like P2P systems. We use extensive simulations to evaluate the performance of the proposed policies, and show that cache bandwidth allocation can improve the inter-ISP traffic savings by up to 30 to 60 percent. We validate the results via BitTorrent experiments on Planet-lab.

Cache bandwidth allocation for P2P file-sharing systems to minimize inter-ISP traffic

Many Internet service providers (ISPs) have deployed peer-to-peer (P2P) caches in their networks in order to decrease costly inter-ISP traffic. A P2P cache stores parts of the most popular contents locally, and if possible serves the requests of local peers to decrease the inter-ISP traffic. Traditionally, P2P cache resource management focuses on managing the storage resource of the cache so as to maximize the inter-ISP traffic savings. In this paper, we show that when there are many overlays competing for the upload bandwidth of a P2P cache, then in order to maximize the inter-ISP traffic savings, the caches upload bandwidth should be actively allocated among the overlays. We formulate the problem of P2P cache bandwidth allocation as a Markov decision process and propose three approximations to the optimal cache bandwidth allocation policy. We use extensive simulations and experiments to evaluate the performance of the proposed policies, and show that the bandwidth allocation policy that prioritizes swarms with a small ratio of local peers to all peers in the swarm can improve the inter-ISP traffic savings in BitTorrent-like P2P systems by up to 30%-60%.

Efficient Distribution of Visual Processing Tasks in Multi-camera Visual Sensor Networks

Multi-camera visual sensor networks (VSNs) require large computational resources in order to perform visual analysis in real-time. One way to match the computational needs is to augment the VSN with dedicated processing nodes that do in-network processing, but this requires careful allocation of loads from the sensor nodes in order to ensure low processing times. In this paper we formulate the problem of load allocation and completion time minimization in a VSN as an optimization problem. We propose a distributed algorithm for load allocation, and evaluate its performance in terms of completion time and convergence compared to a Greedy algorithm. Simulations show that the proposed algorithm converges faster, but at the cost of increased completion times. Nonetheless, combined with appropriate coordination, the proposed algorithm achieves low completion times at low complexity.

Distributed Algorithms for Content Caching in Mobile Backhaul Networks

The growing popularity of mobile multimedia content and the increase of wireless access bitrates are straining backhaul capacity in mobile networks. A cost-effective solution to reduce the strain, enabled by emerging all-IP 4G and 5G mobile backhaul architectures, could be in-network caching of popular content during times of peak demand. In this paper we formulate the problem of content caching in a mobile backhaul as a binary integer programming problem, and we propose a 2- approximation algorithm for the problem. The 2-approximation requires full information about the network topology and the link costs, as well as about the content demands at the different caches, we thus propose two distributed algorithms that are based on limited information on the content demands. We show that the distributed algorithms terminate in a finite number of steps, and we provide analytical results on their approximation ratios. We use simulations to evaluate the proposed algorithms in terms of the achieved approximation ratio and computational complexity on realistic mobile backhaul topologies.

Distributed Caching Algorithms for Interconnected Operator CDNs

Fixed and mobile network operators increasingly deploy managed content distribution networks (CDNs) with the objective of reducing the traffic on their transit links and to improve their customers’ quality of experience. As network operator managed CDNs (nCDNs) become commonplace, operators will likely provide common interfaces to interconnect their nCDNs for mutual benefit, as they do with peering today. In this paper, we consider the problem of using distributed algorithms for computing a cache allocation for nCDNs. We show that if every network operator aims to minimize its cost and bilateral payments are not allowed, then it may be impossible to compute a cache allocation. For the case when bilateral payments are possible, we propose two distributed algorithms, the aggregate value compensation and the object value compensation algorithms, which differ in terms of the level of parallelism they allow and in terms of the amount of information exchanged between nCDNs. We prove that the algorithms converge, and we propose a scheme to ensure ex-post individual rationality. Simulations performed on a real autonomous system-level network topology and synthetic topologies show that the algorithms have geometric rate of convergence, and scale well with the graphs’ density and the nCDN capacity.

Distributed algorithms for content placement in hierarchical cache networks

Abstract The growing popularity of mobile multimedia content and the increase of wireless access bitrates are straining backhaul capacity in mobile networks. A cost-effective solution to reduce the strain, enabled by emerging all-IP 4G and 5G mobile backhaul architectures, could be in-network caching of popular content during times of peak demand. Motivated by the potential benefits of caching in mobile backhaul networks, in this paper we formulate the problem of content placement in a hierarchical cache network as a binary integer programming problem. We provide a polynomial time solution when the link costs are induced by a potential and we propose a 2-approximation algorithm for the general case. The 2-approximation requires full information about the network topology and the link costs, as well as about the content demands at the different caches, we thus propose two distributed algorithms that are based on limited information on the content demands. We show that the distributed algorithms terminate in a finite number of steps, and we provide analytical results on their approximation ratios. We use simulations to evaluate the proposed algorithms in terms of the achieved approximation ratio and computational complexity on hierarchical cache network topologies as a model of mobile backhaul networks.