Open Access Dissertation
Date of Award
As wireless cyber-physical systems (WCPS) are increasingly being deployed in mission-critical applications, it becomes imperative that we consider application QoS requirements in in-network processing (INP). In this dissertation, we explore the potentials of two INP methods, packet packing and network coding, on improving network performance while satisfying application QoS requirements. We find that not only can these two techniques increase the
energy efficiency, reliability, and throughput of WCPS while satisfying QoS requirements of applications in a relatively static environment, but also they can provide low cost proactive protection against transient node failures in a more dynamic wireless environment.
We first study the problem of jointly optimizing packet packing and the timeliness of data delivery. We identify the conditions under which the problem is strong NP-hard, and we find that the problem complexity heavily depends on aggregation constraints instead of network and traffic properties. For cases when the problem is NP-hard, we show that there is no polynomial-time approximation scheme (PTAS); for cases when the problem can be solved in polynomial time, we design polynomial time, offline algorithms for finding the optimal packet packing schemes. We design a distributed, online protocol tPack that schedules packet transmissions to maximize the local utility of packet packing at each node. We evaluate the properties of tPack in NetEye testbed. We find that jointly optimizing data delivery timeliness and packet packing and considering real-world aggregation constraints significantly improve network performance.
We then work on the problem of minimizing the transmission cost of network coding based routing in sensor networks. We propose the first mathematical framework so far as we know on how to theoretically compute the expected transmission cost of NC-based routing in terms of expected number of transmission. Based on this framework, we design a polynomial-time greedy algorithm for forwarder set selection and prove its optimality on transmission cost minimization. We designed EENCR, an energy-efficient NC-based routing protocol that implement our forwarder set selection algorithm to minimize the overall transmission cost. Through comparative study on EENCR and other state-of-the-art routing protocols, we show that EENCR significantly outperforms CTP, MORE and CodeOR in delivery reliability, delivery cost and network goodput.
Furthermore, we study the 1+1 proactive protection problem using network coding. We show that even under a simplified setting, finding two node-disjoint routing braids with minimal total cost is NP-hard. We then design a heuristic algorithm to construct two node-disjoint braids with a transmission cost upper bounded by two shortest node-disjoint paths. And we design ProNCP, a proactive NC-based protection protocol using similar design philosophy as in EENCR. We evaluate the performance of ProNCP under various transient network failure scenarios. Experiment results show that ProNCP is resilient to various network failure scenarios and provides a state performance in terms of reliability, delivery cost and goodput.
Our findings in this dissertation explore the challenges, benefits and solutions in designing real-time, efficient, resilient and QoS-guaranteed wireless cyber-physical systems, and our solutions shed lights for future research on related topics.
Xiang, Qiao, "In-Network Processing For Mission-Criticalwireless Networked Sensing And Control: A Real-Time, Efficiency, And Resiliency Perspective" (2014). Wayne State University Dissertations. 942.