An Adaptive Mechanism for Optimal Content Download in Wireless Networks

This paper presents an adaptive mechanism for improving the content download in wireless environments. The solution is based on the use of the file delivery over unidirectional transport (FLUTE) protocol in multicast networks, which reduce considerably the bandwidth when there are many users interested in the same contents. Specifically, the system proposed reduces the average download time of clients within the coverage area, thus improving the Quality of Experience. To that extent, clients send periodically feedback messages to the server reporting the losses they are experiencing. With this information, the server decides which is the optimum application layer forward error correction (AL-FEC) code rate that minimizes the average download time, taking into account the channel bandwidth, and starts sending data with that code rate. The system proposed is evaluated in various scenarios, considering different distributions of losses in the coverage area. Results show that the adaptive solution proposed is very suitable in wireless networks with limited bandwidth.This work is supported in part by the Ministerio de Economia y Competitividad of the Government of Spain under project COMINN (IPT-2012-0883-430000). The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Wenwu Zhu.De Fez Lava, I.; Guerri Cebollada, JC. (2014). An Adaptive Mechanism for Optimal Content Download in Wireless Networks. IEEE Transactions on Multimedia. 16(4):1140-1155. https://doi.org/10.1109/TMM.2014.2307155S1140115516

Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach

This paper proposes a novel energy-efficient multimedia delivery system called EStreamer. First, we study the relationship between buffer size at the client, burst-shaped TCP-based multimedia traffic, and energy consumption of wireless network interfaces in smartphones. Based on the study, we design and implement EStreamer for constant bit rate and rate-adaptive streaming. EStreamer can improve battery lifetime by 3x, 1.5x and 2x while streaming over Wi-Fi, 3G and 4G respectively.Comment: Accepted in ACM Transactions on Multimedia Computing, Communications and Applications (ACM TOMCCAP), November 201

Shrewd Selection Speeds Surfing: Use Smart EXP3!

In this paper, we explore the use of multi-armed bandit online learning techniques to solve distributed resource selection problems. As an example, we focus on the problem of network selection. Mobile devices often have several wireless networks at their disposal. While choosing the right network is vital for good performance, a decentralized solution remains a challenge. The impressive theoretical properties of multi-armed bandit algorithms, like EXP3, suggest that it should work well for this type of problem. Yet, its real-word performance lags far behind. The main reasons are the hidden cost of switching networks and its slow rate of convergence. We propose Smart EXP3, a novel bandit-style algorithm that (a) retains the good theoretical properties of EXP3, (b) bounds the number of switches, and (c) yields significantly better performance in practice. We evaluate Smart EXP3 using simulations, controlled experiments, and real-world experiments. Results show that it stabilizes at the optimal state, achieves fairness among devices and gracefully deals with transient behaviors. In real world experiments, it can achieve 18% faster download over alternate strategies. We conclude that multi-armed bandit algorithms can play an important role in distributed resource selection problems, when practical concerns, such as switching costs and convergence time, are addressed.Comment: Full pape