We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate the problem of optimally choosing the mobile devices that will serve as gateways from the cellular to the ad hoc network, the ad hoc routes from the gateways to individual devices, and the layers to deliver on these ad hoc routes.
We develop a Mixed Integer Linear Program (MILP)-based algorithm, called POPT, to solve this optimization problem. Pocket delivers the highest possible video quality and optimization problem that determines:
1) The mobile devices that will serve as gateways and relay video data from the cellular network to the ad hoc network,
2) The multihop ad hoc routes for disseminating video data
3) The subsets of video data each mobile device relays to the next hops under capacity constraints. We formulate the optimization problem into a Mixed Integer Linear Program (MILP), and propose an MILP-based algorithm, called POPT, to optimally solve the problem.
We recommend the THS algorithm for video streaming over hybrid cellular and ad hoc networks. Last, we also build a real video dissemination system among multiple Android smart phones over a live cellular network. Via actual experiments, we demonstrate the practicality and efficiency of the proposed THS algorithm.
We call it Tree-Based Heuristic Scheduling (THS) algorithm, and it works as follows: We first sort all the transmission units in the W-segment scheduling window in descending order of importance, by layer, segment, and video. We then go through these WL units, and sequentially schedule the transmissions to all mobile devices. Video Dissemination over Hybrid Cellular and Ad Hoc Networks
Linear Program (LP)-based algorithm called MTS, for lower time complexity generic ad hoc protocols do not work well in hybrid cellular and WiFi ad hoc networks, and may lead to:
1) degraded overall throughput, 2) unfair resource allocation, and 3) low resilience to mobility. They propose two approaches to improve the efficiency of ad hoc protocols. First, the base station can run optimization algorithms for the WiFi ad hoc network, for example, to build optimized routes. Second, mobile devices connected to other access networks can offload traffic from the cellular network to those access networks, so as to avoid network congestion around the base station.
We propose a hybrid network, in which each multicast group is either in the cellular in the ad hoc mode. Initially, all multicast groups are in ad hoc mode, and when the bandwidth requirement of a group exceeds the ad hoc network capacity, the base station picks up that group and switches it into the cellular mode.
In the ad hoc network, a flooding routing protocol is used to discover neighbors and a heuristic is employed to forward video data. Our work differs from in several aspects: 1) we propose a unified optimization problem that jointly finds the optimal gateway mobile devices, ad hoc routes, and video adaptation, 2) we consider existing cellular base stations that may not natively support multicast, and 3) we employ Variable-Bit-Rate (VBR) streams.
More specifically, we empirically measure the mapping between the node location and link capacity several times, and use the resulting values for capacity estimation. We adopt the video traces of H.264/MPEG4 layered videos from an online video library. The mean bit rate and average video quality for each layer of the considered videos are given in Table 2. In this paper, we report sample simulation results of distributing Crew. However, the proposed formulation and solutions are general and also work for the scenarios where mobile devices watch different videos.