Switching with Adaptive Interval Labels for Wireless Networks

摘要

The initial design of the Internet and its protocols did not impose limitations to performance as its purpose intended to use and share expensive computing resources. Modern networks consists of different communication models that expand the capabilities of how resources are exchanged with one another. Wireless sensor networks (WSN) and the Internet of Things (IoT) are examples that have become dominant network platforms for data acquisition, allowing service providers and consumers to collect and exchange data with sensors and devices embedded throughout the physical world. However, these types of networks suffer from the limitations of lossy communication media and low-powered devices. Additional drawbacks that these networks still face are that conventional design methods intended for traditional networks are still being used in protocol design and implementation. An area of such design concern includes routing. RPL has been proposed as a routing-protocol solution for WSN's by catering to the specific needs of low-power and lossy networks. Although RPL is emerging as a standard for routing in WSN's, it still faces many challenges concerning scalability with increases to network size, point-to-point traffic, and underspecification of handling node failures. In this thesis we propose Switching with Adaptive Interval Labels (SAIL), which takes a clean-slate approach from traditional routing. SAIL utilizes compact routing rather than destination-based routing, and caters to the issues RPL faces by replacing destination-based identifiers with interval labels. We implement SAIL using the ns-3 simulator and compare its performance to RPL in a wireless-network deployment. Our results show that SAIL outperforms RPL in energy conservation and forms shorter forwarding paths in small to medium-sized networks. For larger deployments we show that SAIL provides tremendously lower storage overhead where routing table sizes remain constant, while RPL routing tables grow linearly at O(n), where n equals the number of nodes in the network.