Abstract
For the large scale wireless networks, restricted access window (RAW) mechanism is a promising technique for realizing large-scale sensor access with the limited collision probability. In this paper, we are committed to designing the traffic distribution based sensor grouping scheme to balance the energy efficiency (EE) of different groups in the large scale access networks. Specifically, by adopting the Markov chain model, we formulate the optimization problem of max-min EE by taking into account traffic demands with even distribution of different all groups, but the formulated problem is an integer nonlinear programming (INLP) problem. In order to solve the INLP problem, we propose an optimal traffic grouping algorithm (OTGA) by utilizing the branch-and-bound method (BBM) to accommodate for the congestion level among groups. Though the traffic demands of each group can be obtained from the traffic grouping scheme, different combination of heterogeneous sensors can generate the same traffic demands, which make it difficult to find the optimal solution of sensor grouping from the proposed traffic grouping scheme. Furthermore, a heuristic traffic-sensor mapping algorithm (HTMA) is presented to make the traffic demands of each group appropriate. Thus, the proposed scheme can achieve a sub-optimal performance with the individual EE. The numerical results are provided to verify the effectiveness of the proposed schemes.
Highlights
INTRODUCTIONC. Kai et al.: Energy-Efficient Sensor Grouping for IEEE 802.11ah Networks uplink channel access but go dormant in other restricted access window (RAW) slots
OPTIMAL TRAFFIC GROUPING SCHEME ANALYSIS AND ALGORITHM DESIGN According to the performance analysis in terms of EE under different sensor grouping scheme in previous section, we prove that the EE max-min fairness among all groups will be achieved for the same traffic demands of each group and further propose a traffic grouping algorithm by using the classic branch-and-bound method (BBM) approach to solve P2 and realize the optimal traffic grouping
DESIGNING OF TRAFFIC-SENSOR MAPPING ALGORITHM In the previous section, we propose an optimal traffic grouping algorithm to maximize the EE of the worst group
Summary
C. Kai et al.: Energy-Efficient Sensor Grouping for IEEE 802.11ah Networks uplink channel access but go dormant in other RAW slots. Conventional random grouping strategy in IEEE 802.11 ah standard can improve uplink EE by optimizing the combination of the size of RAW and the number of nodes in each RAW [12], [13] Using this strategy, the part of RAWs will suffer from heavy traffic and spend more time and energy for contention, which may make the system outage. Since the AP affects the optimal size of RAW, a MAC enhancement algorithm was proposed to improve the successful probability for uplink access channel by using the Maximum Likelihood estimation methods to estimate the number of stations contending [14].
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