افزایش طول عمر شبکه در شبکه های حسگر
Abstract
1. Introduction
2. Proposed work
3. Algorithm SDLHO: Scheduling DATs using Local Heuristics with Ordering
4. Algorithm SDLHT: Scheduling DATs using Local Heuristics with Tree factor
5. Performance evaluation
6. Conclusion
Declaration of competing interest
References
Abstract
Data gathering is a basic requirement in many applications of Wireless Sensor Networks (WSNs). In tree based data gathering, Data Aggregation Tree (DAT) is constructed by the sink or by the nodes in a distributed manner. In this paper, we study the problem of enhancing Network Lifetime (NL) using hybrid DAT construction methods. In hybrid methods of DAT construction, the sink and the nodes collaboratively construct the DAT. We propose three algorithms for Scheduling DATs using Local Heuristics with Ordering (SDLHO), with Randomization (SDLHR) and with Tree factor (SDLHT) techniques.These techniques avoid disparity in energy levels of the nodes and increase the survivability of the network. In addition, to address imperfect link quality, we propose an algorithm for Scheduling DATs using Local Heuristics with Ordering based on Link Quality (SDLHO-LQ). Rigorous simulation results demonstrate the efficacy of the proposed algorithms; and their ability to scaleup to suit deployment of applications in harsh regions. Further, their performances evaluated to quantify the amount of enhancements of NL with the existing state of art is propitious to suit the distributed environments.
Introduction
In WSNs, the sensors gather and send data to the sink. In applications like environmental monitoring, battlefield surveillance, structural health monitoring, pipeline monitoring and precision agriculture, the sensor nodes are typically randomly deployed and left unattended. Transmission of packets between sensors consumes energy. In terms of power consumption, transmitting a single bit of data is equivalent to 800 instructions [1]. In such situations, employing data gathering mechanisms that judiciously utilize battery power of sensor nodes is essential. By combining data packets from different sensor nodes, the number of packet transmissions is reduced. This technique of combining data so that crucial data is made available at the sink is termed as in-network data aggregation DA. In-network DA using tree based routing structure saves the cost of maintaining a routing table at each node and is suitable in energy constrained WSNs. Tree based DA reduces the number of packet transmissions, decreases energy consumption and improves NL. However, reducing packet transmissions is a challenging problem as it depends on the amount of data generated at each node and the structure of the DAT.In tree based DA, the DAT can be constructed in two ways. (1) In centralized DAT construction, the sink gathers information of the entire network and then constructs a DAT using a suitable tree construction algorithm [2–7]. (2) In distributed method of DAT construction, the nodes communicate with their neighboring nodes and select appropriate parent and child nodes to construct a DAT [1,5,8–10]. In this case, the sink does not require information about the entire network however this method adds communication overhead.