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Fang W.,Beijing Jiaotong University | Fang W.,State Key Laboratory of Astronautical Dynamics of China | Yin X.,Northwest University, China | An Y.,State Key Laboratory of Astronautical Dynamics of China | And 3 more authors.
Information Sciences | Year: 2015

Mobile cloud computing has emerged as a new computing paradigm promising to extend the capabilities of resource-constrained mobile devices. In this new paradigm, mobile devices are enabled to offload computing tasks, report sensing records, and store large files on the cloud through wireless networks. Therefore, efficient data transmission has become an important issue affecting user experiences on mobile cloud. Considering the limited battery energy of mobile devices and different application requirements on transmission delay, this study presents an online control algorithm (OPERA) based on the Lyapunov optimization theory for optimally scheduling data transmission between mobile devices and cloud. The OPERA algorithm is able to make control decisions on application scheduling, interface selection and packet dropping to minimize a joint utility of network energy cost and packet dropping penalty, without requiring any statistical information of traffic arrivals and link throughputs. Rigorous analysis and extensive simulations have demonstrated its distinguished performance in terms of utility optimality, system stability and service delay. © 2015 Elsevier Inc. Source


Liu W.,State Key Laboratory of Astronautical Dynamics of China | Liu W.,Beijing University of Posts and Telecommunications | Zhao X.,Beijing Jiaotong University | An Y.,State Key Laboratory of Astronautical Dynamics of China | And 3 more authors.
Mathematical Problems in Engineering | Year: 2016

Wireless sensing devices have been widely used in civilian and military applications over the past decade. In some application scenarios, the sensors are sparsely deployed in the field and are costly or infeasible to have stable communication links for delivering the collected data to the destined server. A possible solution is to utilize the motion of entities that are already present in the environment to provide opportunistic relaying services for sensory data. In this paper, we design and propose a new scheduling scheme that opportunistically schedules data transmissions based on the optimal stopping theory, with a view of minimizing the energy consumption on network probes for data delivery. In fact, by exploiting the stochastic characteristics of the relay motion, we can postpone the communication up to an acceptable time deadline until the best relay is found. Simulation results validate the effectiveness of the derived optimal strategy. © 2016 Wei Liu et al. Source


Fang W.,Beijing Jiaotong University | Fang W.,State Key Laboratory of Astronautical Dynamics of China | An Z.,CAS Institute of Computing Technology | Shu L.,Guangdong University of Petrochemical Technology | And 3 more authors.
Journal of Network and Computer Applications | Year: 2014

This paper considers optimization of time average admission rate in an energy-constrained network system with multiple classes of data flows. The system operates regularly over time intervals called frames, while each frame begins with a fixed-length active period and ends with a variable-length idle period. At the beginning of the frame, the system chooses a service mode from a collection of options that affect the class and the amount of data flow served as well as the energy incurred in the active period. After service, the system chooses an amount of time to remain idle. The optimization goal is to make decisions over time that maximizes a weighted sum of admitted data rates subject to constraints on queue stability and energy expenditure. However, conventional solutions suffer from a curse of dimensionality for systems with large state space. Therefore, using a generalized Lyapunov optimization technique, we design a new online control algorithm that solves the problem. The algorithm can push time average admission rate close to optimal, with a corresponding tradeoff in average queue backlog. Remarkably, it does not require any knowledge of the data arrival rates and is provably optimal. © 2014 Elsevier Ltd. Source


Fang W.,Beijing Jiaotong University | Fang W.,State Key Laboratory of Astronautical Dynamics of China | Zhao X.,Beijing Jiaotong University | An Y.,State Key Laboratory of Astronautical Dynamics of China | And 3 more authors.
Computer Communications | Year: 2016

The rapid advances in mobile devices and their embedded sensors have enabled a compelling paradigm for collecting ubiquitous data to share with each other or the general public. In this paper, we study how to achieve the close-to-optimal transmission utility performance for sensor-enhanced mobile devices that are capable of harvesting energy from the environment. This is a very challenging task due to the stochastic and unpredictable nature of data arrival, channel condition, and energy replenishment. By taking advantage of the Lyapunov optimization framework, we propose an online scheduling algorithm called OSCAR (Optimal SCheduling AlgoRithm), which jointly make control decisions on system state, energy harvesting, and data transmission for achieving optimal utility on mobile sensing devices. Different from traditional techniques, OSCAR does not require any knowledge of system statistics, including the energy state process. Rigorous analysis and extensive experiments have demonstrated both the system stability and the utility optimality achieved by the OSCAR algorithm. © 2015 Elsevier B.V. All rights reserved. Source

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