Given the complexity and heterogeneity in Cloud computing scenarios, the modeling approach has widely been employed to investigate and analyze the energy consumption of Cloud applications, by abstracting real-world objects and processes that are difficult to observe or understand directly. It is clear that the abstraction sacrifices, and usually does not need, the complete reflection of the reality to be modeled. Consequently, current energy consumption models vary in terms of purposes, assumptions, application characteristics and environmental conditions, with possible overlaps between different research works. There- fore, it would be necessary and valuable to reveal the state-of-the-art of the existing modeling efforts, so as to weave different models together to facilitate comprehending and further investigating application energy consumption in the Cloud domain. By systematically selecting, assessing and synthesizing 76 relevant studies, we rationalized and organized over 30 energy consumption models with unified notations. To help investigate the existing models and facilitate future modeling work, we deconstructed the runtime execution and deployment environment of Cloud applications, and identified 18 environmental factors and 12 workload factors that would be influential on the energy consumption. In particular, there are complicated trade-offs and even debates when dealing with the combinational impacts of multiple factors.

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Recently, IEEE 802.11ax Task Group has adapted OFDMA as a new technique for enabling multi-user transmission. It has been also decided that the scheduling duration should be same for all the users in a multi-user OFDMA so that the transmission of the users should end at the same time. In order to realize that condition, the users with insufficient data should transmit null data (i.e. padding) to fill the duration. While this scheme offers strong features such as resilience to Overlapping Basic Service Set (OBSS) interference and ease of synchronization, it also poses major side issues of degraded throughput performance and waste of devices' energy. In this work, for OFDMA based 802.11 WLANs we first propose practical algorithm in which the scheduling duration is fixed and does not change from time to time. In the second algorithm the scheduling duration is dynamically determined in a resource allocation framework by taking into account the padding overhead, airtime fairness and energy consumption of the users. We analytically investigate our resource allocation problems through Lyapunov optimization techniques and show that our algorithms are arbitrarily close to the optimal performance at the price of reduced convergence rate. We also calculate the overhead of our algorithms in a realistic set-up and propose solutions for the implementation issues.

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Road safety is one of the most important emerging applications envisioned for Vehicular Ad hoc Networks (VANETs). Generally, such applications involve the broadcast of safety messages, consisting of beacons transmitting vehicles' state (e.g. position and velocity) with a regular period, as well as emergency messages warning about unexpected critical events. From the perspective of safety, the application performance depends foremost on two metrics: for the event-driven warning messages, the probability of message reception; and for periodic messages, the variability of the inter-reception time (IRT), which ultimately determines the freshness of the information received by the driver. In this paper, we develop an analytical model to compute the above metrics in an urban traffic scenario. Focusing on a road segment linked to a signalized junction as a basic building block of urban traffic systems, we apply a novel road traffic density model to investigate the dynamics of the reliability metrics and characterize the region(s) on the road segment according to the achieved safety level. Our numerical study shows that in broadcast mode, the hidden terminal effect is the driving factor determining the reliability of transmissions. Furthermore, the impact of hidden terminals has the greatest effect in road sections where vehicles have high velocity, leading to the poorest performance in regions where reliable reception is needed the most in order to minimize the risk of accidents.