An Intelligent delay efficient data aggregation scheduling for distributed sensor networks

Abstract

Data aggregation is the most prominent task in many wireless sensor network (WSN) applications, that enables all data from the network to be collected at the sink node. The most critical issue in data aggregation is data aggregation scheduling. This problem becomes even cumbersome when considered to obtain minimum latency and collision in the networks where fixed amount of data can be aggregated. Many researches have been conducted to resolve the issue of data delivery with low latency and collision. Though, some methods nearly achieved this objective but at the cost of increased complexity. Also, many works assume the system to be centralized having knowledge of every related device in the network. Practically, WSNs are likely to be distributed where each device’s information is dissociated from the other. In this context, a data aggregation scheduling algorithm is proposed to aggregate the data from a tree-based distributed sensor network. An effective aggregation tree construction based on Dijkstra’s algorithm is adopted which avoids the chance of re-transmission of data. Furthermore, a new collision prevention scheduling (CPS) algorithm is designed which ensures the data aggregation through non-collision schedules using minimum time slots. The proposed method shows 54.74% less aggregation latency compared to its competitor data aggregation scheduling approach. The outcome of extensive simulations confirms the efficiency and good performance of the proposed algorithm over previous works.