Multimedia sensor networks for real-time applications have strict constraints on delay, packet loss, and energy consumption requirements. For example, video streaming in a disaster-management scenario requires careful handling to ensure that the end-to-end delay is within the acceptable range and the video is received properly without any distortion. The failure to transmit a video stream effectively occurs for many reasons, including sensor function limitations, excessive power consumption, and a lack of routing reliability. We propose a novel mathematical model for quality of service (QoS) route determination that enables a sensor to determine the optimal path for minimising resource use while satisfying the required QoS constraints. The proposed mathematical model uses the Lagrangian relaxation mixed integer programming technique to define critical parameters and appropriate objective functions for controlling the adaptive QoS constrained route discovery process. Performance trade-offs between QoS requirements and energy efficiency were simulated using the LINGO mathematical programming language. The proposed approach significantly improves the network lifetime, while reducing energy consumption and decreasing average end-to-end delays within the sensor network via optimised resource sharing in intermediate nodes compared with existing routing algorithms.
Optimized Quality of Service for Real-Time Wireless Sensor Networks Using a Partitioning Multipath Routing Approach
