Following fast growth of cellular networks, more users have drawn attention to the contradiction between dynamic user data traffic and static data plans. To address this important but largely unexplored issue, in this paper, we design a new data plan sharing system named Prometheus, which is based on the scenario that some smartphone users have surplus data traffic and are willing to help others download data. To realize this system, we first propose a mechanism that incorporates LT codes into UDP. It is robust to transmission errors and encourages more concurrent transmissions and forwardings. It also can be implemented easily with low implementation complexity. Then we design an incentive mechanism using a Stackelberg game to choose assistant users ( @math ), all participants will gain credits in return, which can be used to ask for future help when they need to download something. Finally real environment experiments are conducted and the results show that users in our Prometheus not only can manage their surplus data plan more efficiently, but also achieve a higher speed download rate.
Cooperative transmission has been studied for many years. Most VANET protocols are designed based on the assumption of node cooperativeness @cite_0 . Wireless sensor networks (WSNs) are another areas where cooperative transmission often occurs @cite_6 @cite_15 @cite_10 .
@cite_0 @cite_15 @cite_10 @cite_6
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In this paper, we investigate the use of cooperative communications for high performance data dissemination in dense wireless sensor networks. We first identify the limitations of existing cooperative schemes. While we previously proposed a multi-hop cooperative data dissemination scheme, REER, to address these limitations, the construction of such structure relies on a pre-established reference path. The partially centralized approach makes REER unscalable when encountering network dynamics. To address this issue, this paper proposes a novel distributed multi-hop cooperative communication scheme (DMC), which is fully distributed and consists of two operation phases: (1) cooperative mesh structure (CMS) construction, and (2) CMS-based data dissemination, which includes random value-based scheme and distance-based scheme for forwarding node selection. Simulation results show that DMC performs well in terms of a number of QoS metrics, and fits well in large-scale networks and highly dynamic environments. In this paper, a novel idea of user cooperation in wireless networks has been exploited to improve the performance of the IEEE 802.11 medium access control (MAC) protocol. The new MAC protocol leverages the multi-rate capability of IEEE 802.11b and allows the mobile stations (STA) far away from the access point (AP) to transmit at a higher rate by using an intermediate station as a relay. Two specific variations of the new MAC protocol, namely CoopMAC I and CoopMAC II, are introduced in the paper. Both are able to increase the throughput of the whole network and reduce the average packet delay. Moreover, CoopMAC II also maintains backward compatibility with the legacy 802.11 protocol. The performance improvement is further evaluated by analysis and extensive simulations. The gains of cooperative communications in wireless networks have been explored recently under the ideal assumption of negligible receiving and processing power. In sensor networks, the power spent for listening and computing can constitute a significant portion of the total consumed power, and such an overhead can reduce the gains promised by cooperation. In this paper, cooperation gains are investigated by taking into consideration such overheads in the analytical framework. The performance metric considered is the energy efficiency of the system measured by the total power required to achieve a certain quality of service requirement. The analytical and numerical results reveal very interesting threshold behavior below which direct transmission is more energy efficient, and above which cooperation provides more gains. Such a tradeoff is shown to depend on many parameters such as the relative locations of the source and destination, the values of the receive and processing powers, the application, and many other factors. Moreover, there are experimental results conducted to verify the channel model assumed in the paper