With the emergence of online platforms for (social) sharing, collaboration and backing up, mobile users generate ever-increasing amounts of digital data, such as documents, photos, and videos, which they upload while on the go. Cellular Internet connectivity (e.g., 3G/4G) enables mobile users to upload their data but drains the battery of their devices and overloads mobile service providers. Wi-Fi data offloading overcomes the aforementioned issues for delay-tolerant data. However, it comes at the cost of constrained mobility for users, as they are required to stay within a given area while the data is uploaded. The up-link of the broadband connection of the access point often constitutes a bottleneck and incurs waiting times of up to tens of minutes. In this paper, we advocate the exploitation of the storage capabilities of common devices located on the Wi-Fi access point's LAN, typically residential gateways, NAS units or set-top boxes, to decrease the waiting time. We propose Hoop, a system for offloading upload tasks onto such devices. Hoop operates seamlessly on http(s) post , which makes it highly generic and widely applicable; it also requires limited changes on the gateways and on the web servers and none to existing protocols or browsers. Hoop is secure and, in a typical setting, reduces the waiting time by up to a factor of 46. We analyze the security of Hoop and evaluate its performance by correlating mobility traces of users with the position of the Wi-Fi access points of a leading community network (i.e., FON) that relies on major national ISPs. We show that, in practice, Hoop drastically decreases the delay between the time the photo is taken and the time it is uploaded, compared to regular Wi-Fi data offloading. We also demonstrate the practicality of Hoop by implementing it on a wireless router.

In this paper, we study cache policies for cloud-based caching. Cloud-based caching uses cloud storage services such as Amazon S3 as a cache for data items that would have been recomputed otherwise. Cloud-based caching departs from classical caching: cloud resources are potentially infinite and only paid when used, while classical caching relies on a fixed storage capacity and its main monetary cost comes from the initial investment. To deal with this new context, we design and evaluate a new caching policy that minimizes the cost of a cloud-based system. The policy takes into account the frequency of consumption of an item and the cloud cost model. We show that this policy is easier to operate, that it scales with the demand and that it outperforms classical policies managing a fixed capacity.

Modern storage systems now typically combine plain replication and erasure codes to reliably store large amount of data in datacenters. Plain replication allows a fast access to popular data, while erasure codes, e.g., Reed-Solomon codes, provide a storage-efficient alternative for archiving less popular data. Although erasure codes are now increasingly employed in real systems, they experience high overhead during maintenance, i.e., upon failures, typically requiring files to be decoded before being encoded again to repair the encoded blocks stored at the faulty node.

Mobile users generate ever-increasing amounts of digital data, such as photos, which they upload, while on the go, to online services. 3G connectivity enables mobile users to upload their data while on the go but drains the battery of their devices and overloads mobile service providers. Wi-Fi data offloading overcomes the aforementioned issues for delay-tolerant data, at the cost of constrained mobility for users as they are required to stay within a given area while the data is uploaded. The up-link of the broadband connection of the access point is a bottleneck and incurs significant waiting times. In this paper, we advocate the exploitation of the storage capabilities of common devices located on the Wi-Fi access point LAN, typically residential gateways, to decrease the waiting time. We propose Hoop, a system for offloading upload tasks onto such devices. Hoop operates seamlessly on HTTP(S) POSTs, making it highly generic, it also requires limited changes on the gateways and on the web server and none to existing protocols or browsers. Hoop is secure and, in a typical setting, reduces the waiting time by up to a factor of 46. By correlating mobility traces with the positions of the Wi-Fi access points of a major community network, we show that Hoop drastically decreases the delay between the time a photo is taken and the time it is uploaded, compared to regular Wi-Fi offloading.

The explosion of the amount of data stored in cloud systems calls for more efficient paradigms for redundancy. While replication is widely used to ensure data availability, erasure correcting codes provide a much better trade-off between storage and availability. Regenerating codes are good candidates for they also offer low repair costs in term of network bandwidth. While they have been proven optimal, they are difficult to understand and parameterize. In this paper we provide an analysis of regenerating codes for practitioners to grasp the various trade-offs. More specifically we make two contributions: (i) we study the impact of the parameters by conducting an analysis at the level of the system, rather than at the level of a single device, (ii) we compare the computational costs of various implementations of codes and highlight the most efficient ones. Our goal is to provide system designers with concrete information to help them choose the best parameters and design for regenerating codes.

Distributed storage systems rely heavily on redundancy to ensure data availability as well as durability. In networked systems subject to intermittent node unavailability, the level of redundancy introduced in the system should be minimized and maintained upon failures. Repairs are well-known to be extremely bandwidth-consuming and it has been shown that, without care, they may significantly congest the system. In this paper, we propose an approach to redundancy management accounting for nodes heterogeneity with respect to availability. We show that by using the availability history of nodes, the performance of two important faces of distributed storage (replica placement and repair) can be significantly improved. Replica placement is achieved based on complementary nodes with respect to nodes availability, improving the overall data availability. Repairs can be scheduled thanks to an adaptive per-node timeout according to node availability, so as to decrease the number of repairs while reaching comparable availability. We propose practical heuristics for those two issues. We evaluate our approach through extensive simulations based on real and well-known availability traces. Results clearly show the benefits of our approach with regards to the critical trade-off between data availability, load-balancing and bandwidth consumption.

The availability of end devices of peer-to-peer storage and backup systems has been shown critical for usability and for system reliability in practice. This has led to the adoption of hybrid architectures composed of both peers and servers. Such architectures mask the instability of peers thus approaching the performances of client-server systems while providing scalability at a low cost. In this paper, we advocate the replacement of such servers by a cloud of residential gateways, as they are already present in users' homes, thus pushing the required stable components at the edge of the network. In our gateway-assisted system, gateways act as buffers between peers, compensating for their intrinsic instability. This enables to offload backup tasks quickly from the user's machine to the gateway, while significantly lowering the retrieval time of backed up data. We evaluate our proposal using real world traces including existing traces from Skype and Jabber as well as a trace of residential gateways for availability, and a residential broadband trace for bandwidth. Results show that the time required to backup data in the network is comparable to a server-assisted approach, while substantially improving the time to restore data, which drops from a few days to a few hours. As gateways are becoming increasingly powerful in order to enable new services, we expect such a proposal to be leveraged on a short term basis.

The match between a peer-to-peer overlay and the physical Internet infrastructure is a constant issue. Time-constrained peer-to-peer applications such as live streaming systems are even more challenging because participating peers have to discover their closest neighbors as quickly as possible. We propose in this paper an approach based on landmarks and a management server. Despite its centralized architecture, this method can scale to a large population of peers. We focus in this paper on challenging this basic idea through intensive simulations, using a large-scale map of the Internet router (IR) layer in a simulator dedicated to peer-to-peer systems. We compare the results obtained by the new method with a random selection and an optimal selection and we show that this proposal makes sense.

In this paper, we address QoS (Quality of Service) issues of video transmission over WiFi-WMM based triple play home networks. Based on NS2 (Network Simulator version2) tool, a simulation study was conducted using triple traffic patterns (video, voice and data) under various home network scenarios. The results basically illustrate that WMM (Wi-Fi Multimedia) cannot provide sufficient QoS mechanisms to guarantee quasi error free video delivery in a home network when video is competing with voice and data.