ADAPT: Adaptive distributed optimization approach for uploading data with redundancy in cooperative mobile cloud

Abstract

With the development of information technology and the ubiquity of mobile devices, increasing amounts of data are generated, processed, and transmitted by mobile devices. To alleviate the tension between the energy poverty of mobile devices and the increasing demand for transmitting data, the energy-efficient data transmission problem attracts considerable interests. Nonetheless, how to upload data with redundancy efficiently lacks a thorough study despite the wide existence of this problem in many situations like data storage among mobile devices and mobile crowd sensing. Since uploading redundant data brings little value while still consuming precious energy, it is important to design an efficient approach for mobile devices to upload data with redundancy cooperatively. In this work, we formulate the uploading data with redundancy in cooperative mobile cloud as an energy-constrained utility maximization problem. To solve this problem, we propose an adaptive distributed optimization approach consisting of the correlated upload decision and the online distributed scheduling algorithm. By the correlated upload decision, each mobile device can make adaptive decisions on how much data to upload and which data to upload according to its own observations independently. The online distributed scheduling algorithm enables mobile devices to optimally upload data. A series of simulation experiments are conducted to demonstrate the effectiveness of our approach. Finally, we test our approach on a real demo system to verify its practicability in reality. KEYWORDS data transmission, energy constraints, data with redundancy, mobile cloud, online distributed optimization 1 INTRODUCTION Recent years have witnessed a rapid growth of mobile devices. It is reported by Cisco that mobile users will reach 5.6 billion, accounting for 21% of all networked devices in 2020. 1 With the development of information technology and the ubiquity of mobile devices, more and more data are generated, processed, and transmitted by mobile devices. 2 However, the miniature nature of mobile devices imposes the intrinsic battery-capacity bottleneck that makes energy-hungry applications still remain off bounds, especially for the data transmission tasks. To relieve the tension between the inherent limited battery capacity of mobile devices and the increasing need for transmitting data, large numbers of researchers have studied the energy-efficient data transmission problems. 3-7 Unfortunately, how to transmit data with redundancy has not been studied thoroughly despite the wide existence of this problem in many situations such as the following two examples. Data Storage and Uploading in Dynamic Wireless Network. It is a common practice to apply mobile devices to the emergency managements, 8 eg, disaster response 9,10 and military operation. 11,12 Differing from the network in normal environments, the network in emergent environments is highly dynamic. Frequent connection and data transmission to remote cloud datacenters is infeasible in such network bec...