Distributed Optimal Lexicographic Max-Min Rate Allocation in Solar-Powered Wireless Sensor Networks

Abstract

Understanding the optimal usage of fluctuating renewable energy in Wireless Sensor Networks (WSNs) is complex. Lexicographic Max-min (LM) rate allocation is a good solution, but is non-trivial for multi-hop WSNs, as both fairness and sensing rates have to be optimized through the exploration of all possible forwarding routes in the network. All current optimal approaches to this problem are centralized and off-line, suffering from low scalability and large computational complexity; typically solving O(N 2 ) linear programming problems for N -node WSNs. This paper presents the first optimal distributed solution to this problem with much lower complexity. We apply it to Solar Powered WSNs (SP-WSNs) to achieve both LM optimality and sustainable operation. Based on realistic models of both time-varying solar power and photovoltaic-battery hardware, we propose an optimization framework that integrates a local power management algorithm with a global distributed LM rate allocation scheme. The optimality, convergence, and efficiency of our approaches are formally proven. We also evaluate our algorithms via experiments on both solar-powered MicaZ motes and extensive simulations using real solar energy data and practical power parameter settings. The results verify our theoretical analysis and demonstrate how our approach outperforms both the state-of-the-art centralized optimal and distributed heuristic solutions.

Practical Opportunistic Data Collection in Wireless Sensor Networks with Mobile Sinks

“…In addition, neither channel experienced interference by other external 2.4 GHz wireless transmissions during the experiment, as no WiFi signal was detectable around the deployment area. Fig.8 illustrates above experiment scenarios, where the diameter of each blue cycle in Fig.8(a) is linearly proportional to the percentage of time that the corresponding sensor node was in contact with a mobile sink; the width of each blue line is linearly proportional to the percentage of time that corresponding pair of sensors were connected as neighbors; and Fig.8(b) illustrates the time sequences of neighbor numbers of the two mobile sinks 4 . In this experiment, the packet size, node transmission power, and sensing rate, were set as 34 bytes, -25 dBm (results in around 2-3 meter transmission range), and one packet per five seconds for each sensor node respectively.…”

“…Fig. 9 shows the Cumulative distribution function (CDF) of the end-to-end 4. Since the collected illustration results are almost same for the two WSNMSs with orthogonal channels, we plot the CA-ETX experiment results in Fig.8 for brevity.…”

“…Traditional multi-hop Wireless Sensor Networks (WSNs) aims to support real-time data delivery (in hundreds of milliseconds) [4]- [7], which may fail in large-scale sensing applications. This is because that thousands of sensor nodes would be required to ensure both the sensing coverage and multihop network connectivity, resulting in expensive deployment cost and network congestions around the sink.…”

Distributed optimization in energy harvesting sensor networks with dynamic in-network data processing

“…There exist a large body of theoretical and practical research results in EH-WSNs [15], including power management schemes [1], [16], [17], routing [1], sensing [1], [18], [19], and path traveling optimization in WSNs using wireless power transfer [20]. Recent approaches that use Lyapunov optimization techniques [12] for joint power management and network optimization [4], [5], [21], are most relevant to our work.…”

Symbiot: Congestion-Driven Multi-resource Fairness for Multi-user Sensor Networks

“…Current max-min-based resource allocation schemes such as [6] do not deal well with both heterogeneous resources and user demands in multi-resource systems. Utilizing multi-resource fairness schemes [4], [5] such as Dominant Resource Fairness (DR-F) [4] have become a hot topic in both computation economics communities and cloud computing.…”