DaGCM : A Concurrent Data Uploading Framework for Mobile Data Gathering in Wireless Sensor Networks

Abstract

DaGCM: A Concurrent Data Uploading Framework for Mobile Data Gathering in Wireless Sensor Networks

Data uploading time is a large portion of mobile data gathering time in wireless sensor networks. By equipping the mobile collector with multiple antennas, data uploading time can be greatly shortened.

In this DaGCM A Concurrent Data Uploading Framework for Mobile Data Gathering in Wireless Sensor Networks paper, we propose a new data gathering cost minimization framework for mobile data gathering in wireless sensor networks by jointly considering dynamic wireless connectivity capacity and power control.

We study the problem under constraints of flow conservation, energy consumption, elastic connection capacity, transmission compatibility, and sojourn time. We use the subgradient iteration algorithm to solve the problem of minimization.

Finally, to demonstrate the convergence and robustness of the proposed algorithms, we provide extensive simulation results. The results reveal 20% shorter data collection latency on average with lower energy consumption compared to previous works, as well as lower data collection costs and robustness in case of node failures.

During the operation, sensors organize themselves into a network and periodically report sensing data to the sink(s). How to aggregate sensor data largely determines the network’s energy consumption. In recent years, extensive research has been devoted to collecting data in WSNs.

The literature has studied the feasibility of using multiple-input multiple-output (MIMO) in WSNs to reduce data transmission time and improve spatial diversity. These works considered the gathering of static data.

To this end, Zhao et al. introduced a two-antenna mobile collector. The mobile collector can thus enjoy more freedom on the receiving side to move to preferred locations (anchor points) to form a virtual MIMO system.

Conclusion

In this paper, we have designed a cross-layer optimization framework for mobile data collection in WSNs, considering elastic connection capacity and sensor power control. To solve the problem, we use subgradient iterative approach and present several distributed subalgorithms with explicit passing of the message. Extensive numerical results demonstrate convergence within 50 iterations of the proposed algorithm.