Hindawi Publishing Corporation Journal of Computer Networks and Communications Volume 2013, Article ID 497157, 18 pages http://dx.doi.org/10.1155/2013/497157 Research Article Optimized Quality of Service for Real-Time Wireless Sensor Networks Using a Partitioning Multipath Routing Approach Mohammed Zaki Hasan 1,2 and Tat-Chee Wan 1,3 1 School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia 2 College of Computer Sciences and Mathematics, University of Mosul, Mosul 41002, Iraq 3 National Advanced IPv6 Centre (NAV6), Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia Correspondence should be addressed to Mohammed Zaki Hasan; mz.cod08@student.usm.my Received 20 December 2012; Revised 26 March 2013; Accepted 3 April 2013 Academic Editor: Lixin Gao Copyright © 2013 M. Z. Hasan and T.-C. Wan. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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. Te failure to transmit a video stream efectively 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. Te proposed mathematical model uses the Lagrangian relaxation mixed integer programming technique to defne critical parameters and appropriate objective functions for controlling the adaptive QoS constrained route discovery process. Performance trade-ofs between QoS requirements and energy efciency were simulated using the LINGO mathematical programming language. Te proposed approach signifcantly 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. 1. Introduction A typical sensor network comprises a large number of multi- functional, low-cost, and low-power nodes that are deployed densely and randomly in an environment for monitored sensing to control the environment, perform local processing, and communicate results with a base station that performs most of the complex processing. One of the many challenges concerning wireless sensor networks (WSNs) is how to provide Quality of Service (QoS) parameter guarantees in real-time applications. Several approaches and protocols have been proposed in the literature for QoS parameter support in these types of networks [1, 2]. Energy consumption is considered to be the most important constraint in WSNs because of the low power and the processing factors. Tese factors reduce the QoS and the lifetime of the network. Te primary concern is how to properly use resources (for deriving multimedia content) to provide appropriately shared data among all of the transmission radios while maintaining a proper level of imaging and video data transmission. Te main goal is the appropriate use of multimedia resources by properly maintaining a level of optimized QoS, which further depends on the performance of the radio. Tis goal requires careful processing to achieve optimal end-to-end delay, jitter, and energy consumption, as well as acceptable throughput. Diferent applications of real-time WSNs have diferent QoS priorities based on the performance of the transmission radio. For example, some applications, such as event detection (Figure 1), might require higher data rates, minimal end-to-end delay, and a long battery lifetime. Te requirements depend on the situation for which the application uses the radio service. It is important for each sensor node in the network domain to consider resource allocation as an optimization problem with diferent potential goals. First, a sensor should attempt to optimize source-based capabilities to maximize its use of resources. Second, a sensor