The incorporation of dynamic voltage scaling technology into computation offloading offers more flexibilities for mobile edge computing. In this paper, we investigate partial computation offloading ...by jointly optimizing the computational speed of smart mobile device (SMD), transmit power of SMD, and offloading ratio with two system design objectives: energy consumption of SMD minimization (ECM) and latency of application execution minimization (LM). Considering the case that the SMD is served by a single cloud server, we formulate both the ECM problem and the LM problem as nonconvex problems. To tackle the ECM problem, we recast it as a convex one with the variable substitution technique and obtain its optimal solution. To address the nonconvex and nonsmooth LM problem, we propose a locally optimal algorithm with the univariate search technique. Furthermore, we extend the scenario to a multiple cloud servers system, where the SMD could offload its computation to a set of cloud servers. In this scenario, we obtain the optimal computation distribution among cloud servers in closed form for the ECM and LM problems. Finally, extensive simulations demonstrate that our proposed algorithms can significantly reduce the energy consumption and shorten the latency with respect to the existing offloading schemes.
Extensive deployment of small cells in heterogenous cellular networks introduces both challenges and opportunities. Challenges come with reuse of limited frequency resources, which always introduce ...both intra- and inter-interference among small cells and macrocells. The opportunities refer to more potential inter- and intra-tier cooperation gains, in particular for ultra-dense heterogeneous and small cell networks. In addition to current spectral efficiency optimization, energy efficiency will also be a critical performance requirement for future green communications, especially when small cells are densely deployed to enhance the user's quality of experience. In this article, potential cooperation gains are explored via a cooperative bargaining game to counter challenges of mitigating interference and saving energy, thus improving both spectral and energy efficiency. We survey the current optimization and trade-offs of spectral and energy efficiency, and introduce the basics of cooperative game theory. Then a utility function is presented with spectral and energy efficiency coupled together. Furthermore, we present the bargaining cooperative game theoretic framework to explore potential cooperation gains. Moreover, two applications are investigated for the dedicated and co-channel deployment cases, including cooperative relay with spectrum leasing and cooperative capacity offload. Finally, we conclude the article with potential challenges of the presented cooperative framework and some thoughts for future research directions.
Ultra-dense networks can further improve the spectrum efficiency (SE) and the energy efficiency (EE). However, the interference avoidance and the green design are becoming more complex due to the ...intrinsic densification and scalability. It is known that the much denser small cells are deployed, the more cooperation opportunities exist among them. In this paper, we characterize the cooperative behaviors in the Nash bargaining cooperative game-theoretic framework, where we maximize the EE performance with a certain sacrifice of SE performance. We first analyze the relationship between the EE and the SE, based on which we formulate the Nash-product EE maximization problem. We achieve the closed-form sub-optimal SE equilibria to maximize the EE performance with and without the minimum SE constraints. We finally propose a CE2MG algorithm, and numerical results verify the improved EE and fairness of the presented CE2MG algorithm compared with the non-cooperative scheme.
Scientific issues relevant to interactions between aerosols and the Asian monsoon climate were discussed and evaluated at the 33rd ＂Forum of Science and Technology Frontiers＂ sponsored by the ...Department of Earth Sciences at the Chinese Academy of Sciences. Major results are summarized in this paper. The East Asian monsoon directly affects aerosol transport and provides a favorable background circulation for the occurrence and development of persistent fog-haze weather. Spatial features of aerosol transport and distribution are also influenced by the East Asian monsoon on seasonal, inter-annual, and decadal scales. High moisture levels in monsoon regions also affect aerosol optical and radiative properties. Observation analyses indicate that cloud physical properties and precipitation are significantly affected by aerosols in China with aerosols likely suppressing local light and moderate rainfall, and intensifying heavy rainfall in southeast coastal regions. However, the detailed mechanisms behind this pattern still need further exploration. The decadal variation in the East Asian monsoon strongly affects aerosol concentrations and their spatial patterns. The weakening monsoon circulation in recent decades has likely helped to increase regional aerosol concentrations. The substantial increase in Chinese air pollutants has likely decreased the temperature difference between land and sea, which favors intensification of the weakening monsoon circulation. Constructive suggestions regarding future studies on aerosols and monsoons were proposed in this forum and key uncertain issues were also discussed.
This paper investigates the problem of revealing the tradeoff between energy efficiency (EE) and delay in device-to-device (D2D) communications underlaying cellular networks. Considering both ...stochastic traffic arrivals and time-varying channel conditions, we formulate it as a stochastic optimization problem, which optimizes EE subject to the average power, interference-control, and network stability constraints. With the help of fractional programming and the Lyapunov optimization technique, we develop an algorithm, referred to as the TRADEOFF, to solve the problem. To deal with the nonconvex and NP-hard power allocation subproblem in the TRADEOFF, we adopt the prismatic branch and bound algorithm to find its globally optimal solution, where only a linear programming needs to be solved in each iteration. Thus, the TRADEOFF serves as an important benchmark to evaluate performance of other heuristic algorithms and is usually cost-efficient. The theoretical analysis and simulation results show that the TRADEOFF achieves an EE-delay tradeoff of O(1/V),O(V) with V being a control parameter and can strike a flexible balance between them by simply tuning V.
Unmanned aerial vehicles (UAVs) can be deployed as wireless relays or aerial base stations to improve network connectivity and coverage in cellular networks. UAVs can also be used to significantly ...enhance the performance of mobile ad-hoc networks and wireless sensor networks. In the future, UAVs are expected to become an integral part of the fifth generation wireless networks as well as key enablers of the coming massive Internet of Things. However, there are still many challenging issues in designing architectures and deployment of UAV-based networks. To address the issues, game theory has recently been adopted as an effective tool for modeling and analyzing problems in UAV-aided networks. In this paper, we survey the applications of game theory in solving various UAV-assisted networks challenges. We first provide a brief introduction to wireless communications with UAVs and then introduce basic game theory concepts and their relation to wireless networks. We further present the classification and brief introduction to the games applied to solve problems in UAV-aided networks. We then provide a comprehensive literature review on game-theoretic techniques utilized in dealing with challenges in the UAV-based wireless networks. Finally, we introduce advanced distributed schemes for interference management in large UAV-assisted communication networks. This paper aims to provide readers with an understanding of UAV-aided networks in terms of their architecture, benefits, challenges, and various game theoretical solutions applied to these communications networks.
Spectrum utilization, energy consumption, and cost efficiency are three key performance metrics that should be jointly investigated in developing a sustainable 5G system. Advanced spectrum sharing ...can enhance both the spectral efficiency and energy efficiency in a cost-effective manner, which is expected to perform much better than conventional networks. In this article, we survey cognitive and cooperative spectrum sharing, and classify a multi-level spectrum exploitation, coordination, and utilization framework from both technical and economic perspectives. We specifically concentrate on spectrum trading and leasing, spectrum mobility, relaying, routing, and harvesting. Finally, a spectrum flowing scheme is proposed for 5G cognitive heterogeneous cellular networks, which improves both spectral and energy efficiency.
Device-to-device (D2D) communications can enhance spectrum and energy efficiency due to direct proximity communication and frequency reuse. However, such performance enhancement is limited by mutual ...interference and energy availability, especially when the deployment of D2D links is ultra-dense. In this paper, we present a distributed power control method for ultra-dense D2D communications underlying cellular communications. In this power control method, in addition to the remaining battery energy of the D2D transmitter, we consider the effects of both the interference caused by the generic D2D transmitter to others and the interference from all others caused to the generic D2D receiver. We formulate a mean-field game (MFG) theoretic framework with the interference mean-field approximation. We design the cost function combining both the performance of the D2D communication and cost for transmit power at the D2D transmitter. Within the MFG framework, we derive the related Hamilton-Jacobi-Bellman and Fokker-Planck-Kolmogorov equations. Then, a novel energy and interference aware power control policy is proposed, which is based on the Lax-Friedrichs scheme and the Lagrange relaxation. The numerical results are presented to demonstrate the spectrum and energy efficiency performances of our proposed approach.
Space information network (SIN) is a promising networking architecture to significantly broaden the observation area and realize continuous information acquisition for earth observation. Over the ...dynamic and complex SIN environment, it is a key issue to coordinate multi-dimensional heterogeneous network resources (e.g., observation resource and transmission resource) in the presence of multi-resource variations and severe conflicts, such that diverse earth observation service requirements can be satisfied. To this end, this paper studies the multi-resource coordinate scheduling problem in SINs. Specifically, we first characterize the relationship among multi-resource using an event-driven time-expanded graph (EDTEG). Based on the EDTEG, observation resource and transmission resource are jointly considered, and an integer linear programming optimization problem is formulated to maximize the sum priorities of the successfully scheduled tasks. An iterative optimization technique is employed to decompose the problem into separate observation scheduling and transmission scheduling sub-problems, which can be efficiently solved by extended transmission time sharing graph and directed acyclic graph methods, respectively. Simulation results demonstrate the effectiveness of the proposed algorithm and performance impacts of different network parameters.
Traditional satellite networks are generally locked down to a specific space mission, with isolated substrate infrastructure as well as network resources. This forbids dynamic resource sharing among ...different networks, and thus leads to resource under utilization, poor service provisioning and unacceptable expenditure. In this regard, it is crucial to embrace emerging technologies such as software-defined networking and network virtualization to construct a FRBSN. Both the resource management architecture and enabling strategies are explicitly investigated to realize FRBSN. Specifically, we propose a novel TERG to precisely describe the evolution of multi-dimensional resources in BSN, and reveal the continuity and correlation relationships among various resources. Based on TERG, we further propose an optimal resource allocation strategy to facilitate efficient cooperation among various resources. The achievable performance limits are demonstrated by simulations under a realistic BSN setting.
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