In this paper, we review recent advances in mobile media communication, processing, and analysis. To identify the opportunities and challenges in fast growing mobile media computing, we discuss several emerging topics including mobile visual search, retargeting, mobile video streaming, and cloud based mobile media computing. According to the infrastructure of mobile devices vs. servers, we come up with essential concerns in mobile media computing such as wireless bandwidth consumption, mobile energy saving, media adaptation for better quality of services, the computational load shift from mobiles to servers, etc. With booming mobile Apps on diverse media consumption, it is envisioned that mobile media research and development is bringing about significant achievements in traditional topics of communication, processing, and analytics.

With the emergence of the adaptive bit rate (ABR) streaming technology, the video/content streaming technology is shifting toward a file-based content distribution. That is, video content is encoded into a set of smaller media files containing video of 2–10 seconds before transmission. This file-based content distribution, coupled with increasingly rapid adoption of smartphones, requires an efficient file-based distribution algorithm to satisfy the QoS demand in wireless networks. In this paper, we study the transmission of a finite-sized file over wireless networks using multipath routing, with the objective to minimize file transmission delay instead of average packet delay. The file transmission delay is defined as the time interval from the instant that a file is first transmitted to the time at which the file can be reconstructed in the destination node. We observe that file transmission delay depends not only on the mean of the packet delay but also on its distribution, especially the tail. This observation leads to a better understanding of the file transfer delay in wireless networks and a minimum delay file transmission strategy. In a wireless multipath communication scenario, we propose to use packet level erasure code (e.g., digital fountain code) to transmit data file with redundancy. Given that a file with k packets is encoded into n packets for transmission, the use of digital fountain code allows the file to be received when only k out of n packets are received. By adding redundant packets, the destination node does not have to wait for the packet to arrive late, hence reducing the delay of the file transmission. We characterize the tradeoff between the code rate (i.e., the ratio of the number of transmitted packets to the number of the original packets) and the file delay reduction. As a rule of thumb, we provide practical guidelines in determining an appropriate code rate for a fixed file to achieve a reasonable transmission delay. We show that only a few redundant packets are needed to achieve a significant reduction in file transmission delay.

In this paper we investigate the problem of sending data blocks containing finite number of packets over two independent routing paths in mesh networks. The objective is to minimize the average block delay by allocating packets into the two routing paths optimally. Previous researchers have shown that using more paths can reduce packet delay and the rate-based allocation policy is optimal, based on the delay metric solely depending on delay mean of each path. In our research, generalizing the multi-path routing scheme to accommodate data block transport, we first establish an upper bound for the average block delay, depending on both delay mean and variance of each path, and then solve a non-linear optimization problem to obtain the optimal packet allocation policy, which either allocates all the packets to the faster path for blocks of small size or allocate all the packets to both paths in proportion to their service rates for blocks of large size. Contrary to conventional results, our analysis suggests that using additional slower routing path could increase the average block delay in some cases. We further characterize the whole spectrum of optimal packet allocation policies as a function of block sizes, and conclude that the existing rate-based allocation policy is a special case for large data block.

We develop a novel auction-based algorithm to allow users to fairly compete for a wireless fading channel. We use the second-price auction mechanism whereby user bids for the channel, during each time slot, based on the fade state of the channel, and the user that makes the highest bid wins use of the channel by paying the second highest bid. Under the assumption that each user has a limited budget for bidding, we show the existence of a Nash equilibrium strategy, and the Nash equilibrium leads to a unique allocation for certain channel state distribution, such as the exponential distribution and the uniform distribution over [0, 1]. For uniformly distributed channel state, we establish that the aggregate throughput received by the users using the Nash equilibrium strategy is at least 3/4 of what can be obtained using an optimal centralized allocation that does not take fairness into account. We also show that the Nash equilibrium strategy leads to an allocation that is Pareto optimal (i.e., it is impossible to make some users better off without making some other users worse off). Based on the Nash equilibrium strategies of the second-price auction with money constraint, we further propose a centralized opportunistic scheduler that does not suffer the shortcomings associated with the proportional fair scheduler.

We present a game-theoretical model of a wireless communication system with multiple competing users sharing a multi-access fading channel. With a specified capture rule and a limited amount of energy available, a user opportunistically adjusts its transmission power based on its own channel state to maximize the user's own individual throughput. We derive an explicit form of the Nash equilibrium power allocation strategy. Furthermore, this Nash equilibrium power allocation strategy is unique under certain capture rule. We also quantify the loss of efficiency in throughput due to user's selfish behavior. Moreover, as the number of users in the system increases, the total system throughput obtained by using a Nash equilibrium strategy approaches the maximum attainable throughput.

We consider the problem of transmission scheduling of data over a wireless fading channel with hard deadline constraints. Our system consists of N users, each with a fixed amount of data that must be served by a common deadline. Given that, for each user, the channel fade state determines the throughput per unit of energy expended, our objective is to minimize the overall expected energy consumption while satisfying the deadline constraint. We consider both a linear and a strictly convex rate-power curve and obtain optimal solutions, based on dynamic programming (DP), and tractable approximate heuristics in both cases. For the special non-fading channel case with convex rate-power curve, an optimal solution is obtained based on the shortest path formulation. In the case of a linear rate-power curve, our DP solution has a nice "threshold" form; while for the convex rate-power curve we are able to obtain a heuristic algorithm with comparable performance with that of the optimal scheduling scheme.

This paper develops routing and scheduling algorithms for packet transmission in a low Earth orbit satellite network with a limited number of transmitters and buffer space. We consider a packet switching satellite network, where time is slotted and the transmission time of each packet is fixed and equal to one time slot. Packets arrive at each satellite independently with a some probability during each time slot; their destination satellite is uniformly distributed. With a limited number of transmitters and buffer space on-board each satellite, contention for transmission inevitably occurs as multiple packets arrive at a satellite. First, we establish the stability region of the system in terms of the maximum admissible packet arrival rate that can possibly be supported. We then consider three transmission scheduling schemes for resolving these contentions: random packet win, where the winning packet is chosen at random; oldest packet win, where the packet that has traveled the longest distance wins the contention; and shortest hops win (SHW), where the packet closest to its destination wins the contention. We evaluate the performance of each of the schemes in terms of throughput. For a system without a buffer, the SHW scheme attains the highest throughput. However, when even limited buffer space is available, all three schemes achieve about the same throughput performance. Moreover, even with a buffer size of just a few packets the achieved throughput is close to that of the infinite buffer case.

This paper considers the link capacity requirement for a N/spl times/N mesh-torus network under a uniform all-to-all traffic model. Both primary capacity and spare capacity for recovering from link failures are examined. In both cases, we use a novel method of "cuts on a graph" to obtain lower bounds on capacity requirements and subsequently find algorithms for routing and failure recovery that meet these bounds. Finally, we quantify the benefits of path based restoration over that of link based restoration; specifically, we find that the spare capacity requirement for a link based restoration scheme is nearly N times that for a path based scheme.