Abstract

Many applications in wireless sensor networks (WSNs) require energy consumption to be minimized and the data delivered to the sink within a specific delay. A usual solution for reducing energy consumption is duty cycling, in which nodes periodically switch between sleep and active states. By increasing the duty cycle interval, consumed energy can be reduced more. However, a large duty cycle interval causes a long end-to-end (E2E) packet delay. As a result, the requirement of a specific delay bound for packet delivery may not be satisfied. In this paper, we aim at maximizing the duty cycle while still guaranteeing that the packets arrive at the sink with the required probability, i.e., the required delay-constrained success ratio (DCSR) is achieved. In order to meet this objective, we propose a novel scheduling and forwarding scheme, namely the deadline-aware scheduling and forwarding (DASF) algorithm. In DASF, the E2E delay distribution with the given network model and parameters is estimated in order to determine the maximum duty cycle interval, with which the required DCSR is satisfied. Each node independently selects a wake-up time using the selected interval, and packets are forwarded to a node in the potential forwarding set, which is determined based on the distance between nodes and the sink. DASF does not require time synchronization between nodes, and a node does not need to maintain neighboring node information in advance. Simulation results show that the proposed scheme can satisfy a required delay-constrained success ratio and outperforms existing algorithms in terms of E2E delay and DCSR.

Highlights

  • Wireless sensor networks (WSNs) have been widely used in many applications [1,2], such as military surveillance, agriculture and environment monitoring

  • In order to address the limitations of existing algorithms, we propose a delay-constrained forwarding algorithm, namely deadline-aware scheduling and forwarding (DASF), which guarantees that packets arrive at the sink with the required probability, or delay-constrained success ratio (DCSR), while maximizing the duty cycle interval

  • When event rate is set to 1.5 packets per second, packets are forwarded to the sink, on average, in 9.8 s under DASF compared to 12.2 s and 27.4 s in cases of lukewarm potato forwarding (LPF) and random asynchronous wakeup (RAW) algorithms, respectively

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Summary

Introduction

Wireless sensor networks (WSNs) have been widely used in many applications [1,2], such as military surveillance, agriculture and environment monitoring. There have been several studies on both routing and scheduling protocols in order to deal with end-to-end (E2E) delay problems [4,5,6,7,8,9] Those existing algorithms require global information [7] (e.g., all one-hop delays and communication links in the network), a high message complexity [6,9] or costly time synchronization between nodes [4,5,8]. In order to address the limitations of existing algorithms, we propose a delay-constrained forwarding algorithm, namely deadline-aware scheduling and forwarding (DASF), which guarantees that packets arrive at the sink with the required probability, or delay-constrained success ratio (DCSR), while maximizing the duty cycle interval.

Related Work
Problem Definition
Network Model
A Deadline-Aware Scheduling and Forwarding Scheme
Group-Based Forwarding
The Distribution of M
One-Hop Delay Distribution
E2E Delay Distribution
Performance Study
Effects of Required DCSR Changes
Effects of Delay Bound
Performance Comparison with Other Algorithms
Effects of Node Density
Effects of Event Rate
Effects of the Number of Sources
Findings
Conclusion and Future Work
Full Text
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